Repository: mwouts/jupytext Branch: main Commit: e939bf5359be Files: 805 Total size: 8.1 MB Directory structure: gitextract_26hsbj6f/ ├── .git-blame-ignore-revs ├── .git_archival.txt ├── .gitattributes ├── .github/ │ ├── codecov.yml │ ├── dependabot.yml │ └── workflows/ │ ├── ci.yml │ ├── comment-pr.yml │ ├── publish.yml │ ├── step_build.yml │ ├── step_coverage.yml │ ├── step_pre-commit.yml │ ├── step_static-analysis.yml │ ├── step_tests-conda.yml │ ├── step_tests-pip.yml │ ├── step_tests-ui.yml │ └── update-playwright-snapshots.yml ├── .gitignore ├── .pre-commit-config.yaml ├── .pre-commit-hooks.yaml ├── .readthedocs.yml ├── CHANGELOG.md ├── LICENSE ├── README.md ├── binder/ │ ├── labconfig/ │ │ └── default_setting_overrides.json │ ├── postBuild │ └── requirements.txt ├── demo/ │ ├── Benchmarking Jupytext.py │ ├── Jupytext's word cloud.py │ ├── Tests in a notebook.md │ ├── World population.Rmd │ ├── World population.ipynb │ ├── World population.lgt.py │ ├── World population.md │ ├── World population.myst.md │ ├── World population.pandoc.md │ ├── World population.pct.py │ ├── World population.spx.py │ ├── get_started.md │ └── vscode/ │ ├── notebook.ipynb │ └── notebook.py ├── docs/ │ ├── Makefile │ ├── advanced-options.md │ ├── changelog.md │ ├── conf.py │ ├── config.md │ ├── contributing.md │ ├── developing.md │ ├── doc-requirements.txt │ ├── faq.md │ ├── formats-markdown.md │ ├── formats-scripts.md │ ├── index.md │ ├── install.md │ ├── jupyter-collaboration.md │ ├── jupyterlab-extension.md │ ├── languages.md │ ├── make.bat │ ├── paired-notebooks.md │ ├── text-notebooks.md │ ├── tutorials.md │ ├── using-cli.md │ ├── using-pre-commit.md │ └── vs-code.md ├── jupyterlab/ │ ├── .gitignore │ ├── .prettierignore │ ├── .yarnrc.yml │ ├── install.json │ ├── jupyter-config/ │ │ ├── jupyter_notebook_config.d/ │ │ │ └── jupytext.json │ │ └── jupyter_server_config.d/ │ │ └── jupytext.json │ ├── jupyterlab_jupytext/ │ │ └── __init__.py │ ├── lerna.json │ ├── package.json │ ├── packages/ │ │ └── jupyterlab-jupytext-extension/ │ │ ├── .gitignore │ │ ├── CHANGELOG.md │ │ ├── README.md │ │ ├── package.json │ │ ├── schema/ │ │ │ └── plugin.json │ │ ├── src/ │ │ │ ├── commands.ts │ │ │ ├── factory.ts │ │ │ ├── index.ts │ │ │ ├── registry.ts │ │ │ ├── svg.d.ts │ │ │ ├── tokens.ts │ │ │ └── utils.ts │ │ ├── style/ │ │ │ ├── base.css │ │ │ ├── index.css │ │ │ └── index.js │ │ ├── tsconfig.json │ │ └── ui-tests/ │ │ ├── README.md │ │ ├── jupyter_server_test_config.py │ │ ├── package.json │ │ ├── playwright.config.js │ │ └── tests/ │ │ ├── jupytext-launcher.spec.ts │ │ ├── jupytext-menu.spec.ts │ │ ├── jupytext-notebook.spec.ts │ │ └── jupytext-settings.spec.ts │ ├── scripts/ │ │ └── install_extension.py │ └── tsconfig.eslint.json ├── pyproject.toml ├── src/ │ ├── jupytext/ │ │ ├── __init__.py │ │ ├── __main__.py │ │ ├── async_contentsmanager.py │ │ ├── async_pairs.py │ │ ├── cell_metadata.py │ │ ├── cell_reader.py │ │ ├── cell_to_text.py │ │ ├── cli.py │ │ ├── combine.py │ │ ├── compare.py │ │ ├── config.py │ │ ├── doxygen.py │ │ ├── formats.py │ │ ├── header.py │ │ ├── jupytext.py │ │ ├── kernels.py │ │ ├── languages.py │ │ ├── magics.py │ │ ├── marimo.py │ │ ├── metadata_filter.py │ │ ├── myst.py │ │ ├── paired_paths.py │ │ ├── pairs.py │ │ ├── pandoc.py │ │ ├── pep8.py │ │ ├── quarto.py │ │ ├── reraise.py │ │ ├── stringparser.py │ │ ├── sync_contentsmanager.py │ │ ├── sync_pairs.py │ │ └── version.py │ └── jupytext_config/ │ ├── __init__.py │ ├── __main__.py │ ├── jupytext_config.py │ └── labconfig.py ├── tests/ │ ├── conftest.py │ ├── data/ │ │ └── notebooks/ │ │ ├── inputs/ │ │ │ ├── R/ │ │ │ │ └── simple_r_script.R │ │ │ ├── R_spin/ │ │ │ │ └── knitr-spin.R │ │ │ ├── Rmd/ │ │ │ │ ├── R_sample.Rmd │ │ │ │ ├── chunk_options.Rmd │ │ │ │ ├── ioslides.Rmd │ │ │ │ ├── knitr-spin.Rmd │ │ │ │ └── markdown.Rmd │ │ │ ├── hydrogen/ │ │ │ │ └── hydrogen_latex_html_R_magics.py │ │ │ ├── ipynb_R/ │ │ │ │ ├── R notebook with invalid cell keys.ipynb │ │ │ │ └── ir_notebook.ipynb │ │ │ ├── ipynb_bash/ │ │ │ │ └── sample_bash_notebook.ipynb │ │ │ ├── ipynb_clojure/ │ │ │ │ └── html-demo.ipynb │ │ │ ├── ipynb_coconut/ │ │ │ │ └── coconut_homepage_demo.ipynb │ │ │ ├── ipynb_cpp/ │ │ │ │ ├── root_cpp.ipynb │ │ │ │ └── xcpp_by_quantstack.ipynb │ │ │ ├── ipynb_cs/ │ │ │ │ └── csharp.ipynb │ │ │ ├── ipynb_fs/ │ │ │ │ └── fsharp.ipynb │ │ │ ├── ipynb_gnuplot/ │ │ │ │ └── gnuplot_notebook.ipynb │ │ │ ├── ipynb_go/ │ │ │ │ └── hello_world_gonb.ipynb │ │ │ ├── ipynb_groovy/ │ │ │ │ └── tailrecursive-factorial.ipynb │ │ │ ├── ipynb_haskell/ │ │ │ │ └── haskell_notebook.ipynb │ │ │ ├── ipynb_idl/ │ │ │ │ └── demo_gdl_fbp.ipynb │ │ │ ├── ipynb_java/ │ │ │ │ └── simple-helloworld.ipynb │ │ │ ├── ipynb_js/ │ │ │ │ └── ijavascript.ipynb │ │ │ ├── ipynb_julia/ │ │ │ │ ├── julia_benchmark_plotly_barchart.ipynb │ │ │ │ └── julia_functional_geometry.ipynb │ │ │ ├── ipynb_logtalk/ │ │ │ │ └── logtalk_notebook.ipynb │ │ │ ├── ipynb_lua/ │ │ │ │ └── lua_example.ipynb │ │ │ ├── ipynb_m/ │ │ │ │ └── octave_notebook.ipynb │ │ │ ├── ipynb_maxima/ │ │ │ │ └── maxima_example.ipynb │ │ │ ├── ipynb_ocaml/ │ │ │ │ └── ocaml_notebook.ipynb │ │ │ ├── ipynb_ps1/ │ │ │ │ └── powershell.ipynb │ │ │ ├── ipynb_py/ │ │ │ │ ├── Line_breaks_in_LateX_305.ipynb │ │ │ │ ├── Notebook with function and cell metadata 164.ipynb │ │ │ │ ├── Notebook with html and latex cells.ipynb │ │ │ │ ├── Notebook with many hash signs.ipynb │ │ │ │ ├── Notebook with metadata and long cells.ipynb │ │ │ │ ├── Notebook_with_R_magic.ipynb │ │ │ │ ├── Notebook_with_more_R_magic_111.ipynb │ │ │ │ ├── The flavors of raw cells.ipynb │ │ │ │ ├── cat_variable.ipynb │ │ │ │ ├── convert_to_py_then_test_with_update83.ipynb │ │ │ │ ├── frozen_cell.ipynb │ │ │ │ ├── jupyter.ipynb │ │ │ │ ├── jupyter_again.ipynb │ │ │ │ ├── jupyter_with_raw_cell_in_body.ipynb │ │ │ │ ├── jupyter_with_raw_cell_on_top.ipynb │ │ │ │ ├── jupyter_with_raw_cell_with_invalid_yaml.ipynb │ │ │ │ ├── jupyterlab-slideshow_1441.ipynb │ │ │ │ ├── notebook_with_complex_metadata.ipynb │ │ │ │ ├── nteract_with_parameter.ipynb │ │ │ │ ├── plotly_graphs.ipynb │ │ │ │ ├── raw_cell_with_complex_yaml_like_content.ipynb │ │ │ │ ├── raw_cell_with_non_dict_yaml_content.ipynb │ │ │ │ ├── sample_rise_notebook_66.ipynb │ │ │ │ └── text_outputs_and_images.ipynb │ │ │ ├── ipynb_q/ │ │ │ │ └── kalman_filter_and_visualization.ipynb │ │ │ ├── ipynb_robot/ │ │ │ │ └── simple_robot_notebook.ipynb │ │ │ ├── ipynb_rust/ │ │ │ │ └── evcxr_jupyter_tour.ipynb │ │ │ ├── ipynb_sage/ │ │ │ │ └── sage_print_hello.ipynb │ │ │ ├── ipynb_sas/ │ │ │ │ └── sas.ipynb │ │ │ ├── ipynb_scala/ │ │ │ │ └── simple_scala_notebook.ipynb │ │ │ ├── ipynb_scheme/ │ │ │ │ └── Reference Guide for Calysto Scheme.ipynb │ │ │ ├── ipynb_sos/ │ │ │ │ └── jupytext_replication.ipynb │ │ │ ├── ipynb_stata/ │ │ │ │ └── stata_notebook.ipynb │ │ │ ├── ipynb_tcl/ │ │ │ │ └── tcl_test.ipynb │ │ │ ├── ipynb_ts/ │ │ │ │ └── itypescript.ipynb │ │ │ ├── ipynb_wolfram/ │ │ │ │ └── wolfram.ipynb │ │ │ ├── ipynb_xonsh/ │ │ │ │ └── xonsh_example.ipynb │ │ │ ├── julia/ │ │ │ │ └── julia_sample_script.jl │ │ │ ├── marimo/ │ │ │ │ └── basic_marimo_example.py │ │ │ ├── md/ │ │ │ │ ├── jupytext_markdown.md │ │ │ │ └── plain_markdown.md │ │ │ ├── myst/ │ │ │ │ ├── fenced_code_vs_code_cells.md │ │ │ │ └── reference_link.md │ │ │ ├── percent/ │ │ │ │ └── hydrogen.py │ │ │ ├── ps1/ │ │ │ │ └── build.ps1 │ │ │ ├── python/ │ │ │ │ ├── light_sample.py │ │ │ │ └── python_notebook_sample.py │ │ │ └── sphinx/ │ │ │ └── plot_notebook.py │ │ └── outputs/ │ │ ├── Rmd_to_ipynb/ │ │ │ ├── R_sample.ipynb │ │ │ ├── chunk_options.ipynb │ │ │ ├── ioslides.ipynb │ │ │ ├── knitr-spin.ipynb │ │ │ └── markdown.ipynb │ │ ├── ipynb_to_Rmd/ │ │ │ ├── Line_breaks_in_LateX_305.Rmd │ │ │ ├── Notebook with function and cell metadata 164.Rmd │ │ │ ├── Notebook with html and latex cells.Rmd │ │ │ ├── Notebook with many hash signs.Rmd │ │ │ ├── Notebook with metadata and long cells.Rmd │ │ │ ├── Notebook_with_R_magic.Rmd │ │ │ ├── Notebook_with_more_R_magic_111.Rmd │ │ │ ├── R notebook with invalid cell keys.Rmd │ │ │ ├── Reference Guide for Calysto Scheme.Rmd │ │ │ ├── The flavors of raw cells.Rmd │ │ │ ├── cat_variable.Rmd │ │ │ ├── coconut_homepage_demo.Rmd │ │ │ ├── convert_to_py_then_test_with_update83.Rmd │ │ │ ├── csharp.Rmd │ │ │ ├── demo_gdl_fbp.Rmd │ │ │ ├── evcxr_jupyter_tour.Rmd │ │ │ ├── frozen_cell.Rmd │ │ │ ├── fsharp.Rmd │ │ │ ├── gnuplot_notebook.Rmd │ │ │ ├── haskell_notebook.Rmd │ │ │ ├── hello_world_gonb.Rmd │ │ │ ├── html-demo.Rmd │ │ │ ├── ijavascript.Rmd │ │ │ ├── ir_notebook.Rmd │ │ │ ├── itypescript.Rmd │ │ │ ├── julia_benchmark_plotly_barchart.Rmd │ │ │ ├── julia_functional_geometry.Rmd │ │ │ ├── jupyter.Rmd │ │ │ ├── jupyter_again.Rmd │ │ │ ├── jupyter_with_raw_cell_in_body.Rmd │ │ │ ├── jupyter_with_raw_cell_on_top.Rmd │ │ │ ├── jupyter_with_raw_cell_with_invalid_yaml.Rmd │ │ │ ├── jupyterlab-slideshow_1441.Rmd │ │ │ ├── jupytext_replication.Rmd │ │ │ ├── kalman_filter_and_visualization.Rmd │ │ │ ├── logtalk_notebook.Rmd │ │ │ ├── lua_example.Rmd │ │ │ ├── maxima_example.Rmd │ │ │ ├── notebook_with_complex_metadata.Rmd │ │ │ ├── nteract_with_parameter.Rmd │ │ │ ├── ocaml_notebook.Rmd │ │ │ ├── octave_notebook.Rmd │ │ │ ├── plotly_graphs.Rmd │ │ │ ├── powershell.Rmd │ │ │ ├── raw_cell_with_complex_yaml_like_content.Rmd │ │ │ ├── raw_cell_with_non_dict_yaml_content.Rmd │ │ │ ├── root_cpp.Rmd │ │ │ ├── sage_print_hello.Rmd │ │ │ ├── sample_bash_notebook.Rmd │ │ │ ├── sample_rise_notebook_66.Rmd │ │ │ ├── sas.Rmd │ │ │ ├── simple-helloworld.Rmd │ │ │ ├── simple_robot_notebook.Rmd │ │ │ ├── simple_scala_notebook.Rmd │ │ │ ├── stata_notebook.Rmd │ │ │ ├── tailrecursive-factorial.Rmd │ │ │ ├── tcl_test.Rmd │ │ │ ├── text_outputs_and_images.Rmd │ │ │ ├── wolfram.Rmd │ │ │ ├── xcpp_by_quantstack.Rmd │ │ │ └── xonsh_example.Rmd │ │ ├── ipynb_to_hydrogen/ │ │ │ ├── Line_breaks_in_LateX_305.py │ │ │ ├── Notebook with function and cell metadata 164.py │ │ │ ├── Notebook with html and latex cells.py │ │ │ ├── Notebook with many hash signs.py │ │ │ ├── Notebook with metadata and long cells.py │ │ │ ├── Notebook_with_R_magic.py │ │ │ ├── Notebook_with_more_R_magic_111.py │ │ │ ├── R notebook with invalid cell keys.R │ │ │ ├── Reference Guide for Calysto Scheme.ss │ │ │ ├── The flavors of raw cells.py │ │ │ ├── cat_variable.py │ │ │ ├── coconut_homepage_demo.coco │ │ │ ├── convert_to_py_then_test_with_update83.py │ │ │ ├── csharp.cs │ │ │ ├── demo_gdl_fbp.pro │ │ │ ├── evcxr_jupyter_tour.rs │ │ │ ├── frozen_cell.py │ │ │ ├── fsharp.fsx │ │ │ ├── gnuplot_notebook.gp │ │ │ ├── haskell_notebook.hs │ │ │ ├── hello_world_gonb.go │ │ │ ├── html-demo.clj │ │ │ ├── ijavascript.js │ │ │ ├── ir_notebook.R │ │ │ ├── itypescript.ts │ │ │ ├── julia_benchmark_plotly_barchart.jl │ │ │ ├── julia_functional_geometry.jl │ │ │ ├── jupyter.py │ │ │ ├── jupyter_again.py │ │ │ ├── jupyter_with_raw_cell_in_body.py │ │ │ ├── jupyter_with_raw_cell_on_top.py │ │ │ ├── jupyter_with_raw_cell_with_invalid_yaml.py │ │ │ ├── jupyterlab-slideshow_1441.py │ │ │ ├── jupytext_replication.sos │ │ │ ├── kalman_filter_and_visualization.q │ │ │ ├── logtalk_notebook.lgt │ │ │ ├── lua_example.lua │ │ │ ├── maxima_example.mac │ │ │ ├── notebook_with_complex_metadata.py │ │ │ ├── nteract_with_parameter.py │ │ │ ├── ocaml_notebook.ml │ │ │ ├── octave_notebook.m │ │ │ ├── plotly_graphs.py │ │ │ ├── powershell.ps1 │ │ │ ├── raw_cell_with_complex_yaml_like_content.py │ │ │ ├── raw_cell_with_non_dict_yaml_content.py │ │ │ ├── root_cpp.cpp │ │ │ ├── sage_print_hello.sage │ │ │ ├── sample_bash_notebook.sh │ │ │ ├── sample_rise_notebook_66.py │ │ │ ├── sas.sas │ │ │ ├── simple-helloworld.java │ │ │ ├── simple_robot_notebook.robot │ │ │ ├── simple_scala_notebook.scala │ │ │ ├── stata_notebook.do │ │ │ ├── tailrecursive-factorial.groovy │ │ │ ├── tcl_test.tcl │ │ │ ├── text_outputs_and_images.py │ │ │ ├── wolfram.wolfram │ │ │ ├── xcpp_by_quantstack.cpp │ │ │ └── xonsh_example.xsh │ │ ├── ipynb_to_marimo/ │ │ │ ├── Line_breaks_in_LateX_305.py │ │ │ ├── Notebook with function and cell metadata 164.py │ │ │ ├── Notebook with many hash signs.py │ │ │ ├── cat_variable.py │ │ │ ├── frozen_cell.py │ │ │ ├── jupyter.py │ │ │ ├── notebook_with_complex_metadata.py │ │ │ ├── plotly_graphs.py │ │ │ ├── sample_rise_notebook_66.py │ │ │ └── text_outputs_and_images.py │ │ ├── ipynb_to_md/ │ │ │ ├── Line_breaks_in_LateX_305.md │ │ │ ├── Notebook with function and cell metadata 164.md │ │ │ ├── Notebook with html and latex cells.md │ │ │ ├── Notebook with many hash signs.md │ │ │ ├── Notebook with metadata and long cells.md │ │ │ ├── Notebook_with_R_magic.md │ │ │ ├── Notebook_with_more_R_magic_111.md │ │ │ ├── R notebook with invalid cell keys.md │ │ │ ├── Reference Guide for Calysto Scheme.md │ │ │ ├── The flavors of raw cells.md │ │ │ ├── cat_variable.md │ │ │ ├── coconut_homepage_demo.md │ │ │ ├── convert_to_py_then_test_with_update83.md │ │ │ ├── csharp.md │ │ │ ├── demo_gdl_fbp.md │ │ │ ├── evcxr_jupyter_tour.md │ │ │ ├── frozen_cell.md │ │ │ ├── fsharp.md │ │ │ ├── gnuplot_notebook.md │ │ │ ├── haskell_notebook.md │ │ │ ├── hello_world_gonb.md │ │ │ ├── html-demo.md │ │ │ ├── ijavascript.md │ │ │ ├── ir_notebook.md │ │ │ ├── itypescript.md │ │ │ ├── julia_benchmark_plotly_barchart.md │ │ │ ├── julia_functional_geometry.md │ │ │ ├── jupyter.md │ │ │ ├── jupyter_again.md │ │ │ ├── jupyter_with_raw_cell_in_body.md │ │ │ ├── jupyter_with_raw_cell_on_top.md │ │ │ ├── jupyter_with_raw_cell_with_invalid_yaml.md │ │ │ ├── jupyterlab-slideshow_1441.md │ │ │ ├── jupytext_replication.md │ │ │ ├── kalman_filter_and_visualization.md │ │ │ ├── logtalk_notebook.md │ │ │ ├── lua_example.md │ │ │ ├── maxima_example.md │ │ │ ├── notebook_with_complex_metadata.md │ │ │ ├── nteract_with_parameter.md │ │ │ ├── ocaml_notebook.md │ │ │ ├── octave_notebook.md │ │ │ ├── plotly_graphs.md │ │ │ ├── powershell.md │ │ │ ├── raw_cell_with_complex_yaml_like_content.md │ │ │ ├── raw_cell_with_non_dict_yaml_content.md │ │ │ ├── root_cpp.md │ │ │ ├── sage_print_hello.md │ │ │ ├── sample_bash_notebook.md │ │ │ ├── sample_rise_notebook_66.md │ │ │ ├── sas.md │ │ │ ├── simple-helloworld.md │ │ │ ├── simple_robot_notebook.md │ │ │ ├── simple_scala_notebook.md │ │ │ ├── stata_notebook.md │ │ │ ├── tailrecursive-factorial.md │ │ │ ├── tcl_test.md │ │ │ ├── text_outputs_and_images.md │ │ │ ├── wolfram.md │ │ │ ├── xcpp_by_quantstack.md │ │ │ └── xonsh_example.md │ │ ├── ipynb_to_myst/ │ │ │ ├── Line_breaks_in_LateX_305.md │ │ │ ├── Notebook with function and cell metadata 164.md │ │ │ ├── Notebook with html and latex cells.md │ │ │ ├── Notebook with many hash signs.md │ │ │ ├── Notebook with metadata and long cells.md │ │ │ ├── Notebook_with_R_magic.md │ │ │ ├── Notebook_with_more_R_magic_111.md │ │ │ ├── R notebook with invalid cell keys.md │ │ │ ├── Reference Guide for Calysto Scheme.md │ │ │ ├── The flavors of raw cells.md │ │ │ ├── cat_variable.md │ │ │ ├── coconut_homepage_demo.md │ │ │ ├── convert_to_py_then_test_with_update83.md │ │ │ ├── csharp.md │ │ │ ├── demo_gdl_fbp.md │ │ │ ├── evcxr_jupyter_tour.md │ │ │ ├── frozen_cell.md │ │ │ ├── fsharp.md │ │ │ ├── gnuplot_notebook.md │ │ │ ├── haskell_notebook.md │ │ │ ├── hello_world_gonb.md │ │ │ ├── ijavascript.md │ │ │ ├── ir_notebook.md │ │ │ ├── itypescript.md │ │ │ ├── julia_benchmark_plotly_barchart.md │ │ │ ├── jupyter.md │ │ │ ├── jupyter_again.md │ │ │ ├── jupyter_with_raw_cell_in_body.md │ │ │ ├── jupyter_with_raw_cell_on_top.md │ │ │ ├── jupyter_with_raw_cell_with_invalid_yaml.md │ │ │ ├── jupyterlab-slideshow_1441.md │ │ │ ├── jupytext_replication.md │ │ │ ├── kalman_filter_and_visualization.md │ │ │ ├── logtalk_notebook.md │ │ │ ├── lua_example.md │ │ │ ├── maxima_example.md │ │ │ ├── notebook_with_complex_metadata.md │ │ │ ├── nteract_with_parameter.md │ │ │ ├── ocaml_notebook.md │ │ │ ├── octave_notebook.md │ │ │ ├── plotly_graphs.md │ │ │ ├── powershell.md │ │ │ ├── raw_cell_with_complex_yaml_like_content.md │ │ │ ├── raw_cell_with_non_dict_yaml_content.md │ │ │ ├── root_cpp.md │ │ │ ├── sage_print_hello.md │ │ │ ├── sample_bash_notebook.md │ │ │ ├── sample_rise_notebook_66.md │ │ │ ├── sas.md │ │ │ ├── simple-helloworld.md │ │ │ ├── simple_robot_notebook.md │ │ │ ├── simple_scala_notebook.md │ │ │ ├── stata_notebook.md │ │ │ ├── tailrecursive-factorial.md │ │ │ ├── tcl_test.md │ │ │ ├── text_outputs_and_images.md │ │ │ ├── wolfram.md │ │ │ └── xonsh_example.md │ │ ├── ipynb_to_pandoc/ │ │ │ ├── Notebook_with_R_magic.md │ │ │ ├── Notebook_with_more_R_magic_111.md │ │ │ ├── cat_variable.md │ │ │ ├── convert_to_py_then_test_with_update83.md │ │ │ ├── frozen_cell.md │ │ │ ├── ir_notebook.md │ │ │ ├── julia_benchmark_plotly_barchart.md │ │ │ ├── jupyter.md │ │ │ ├── jupyter_again.md │ │ │ ├── jupyter_with_raw_cell_in_body.md │ │ │ ├── jupyter_with_raw_cell_on_top.md │ │ │ ├── notebook_with_complex_metadata.md │ │ │ ├── nteract_with_parameter.md │ │ │ ├── plotly_graphs.md │ │ │ ├── raw_cell_with_complex_yaml_like_content.md │ │ │ ├── raw_cell_with_non_dict_yaml_content.md │ │ │ ├── sample_rise_notebook_66.md │ │ │ └── text_outputs_and_images.md │ │ ├── ipynb_to_percent/ │ │ │ ├── Line_breaks_in_LateX_305.py │ │ │ ├── Notebook with function and cell metadata 164.py │ │ │ ├── Notebook with html and latex cells.py │ │ │ ├── Notebook with many hash signs.py │ │ │ ├── Notebook with metadata and long cells.py │ │ │ ├── Notebook_with_R_magic.py │ │ │ ├── Notebook_with_more_R_magic_111.py │ │ │ ├── R notebook with invalid cell keys.R │ │ │ ├── R notebook with invalid cell keys.low.r │ │ │ ├── Reference Guide for Calysto Scheme.scm │ │ │ ├── Reference Guide for Calysto Scheme.ss │ │ │ ├── The flavors of raw cells.py │ │ │ ├── cat_variable.py │ │ │ ├── coconut_homepage_demo.coco │ │ │ ├── convert_to_py_then_test_with_update83.py │ │ │ ├── csharp.cs │ │ │ ├── demo_gdl_fbp.pro │ │ │ ├── evcxr_jupyter_tour.rs │ │ │ ├── frozen_cell.py │ │ │ ├── fsharp.fsx │ │ │ ├── gnuplot_notebook.gp │ │ │ ├── haskell_notebook.hs │ │ │ ├── hello_world_gonb.go │ │ │ ├── html-demo.clj │ │ │ ├── ijavascript.js │ │ │ ├── ir_notebook.R │ │ │ ├── ir_notebook.low.r │ │ │ ├── itypescript.ts │ │ │ ├── julia_benchmark_plotly_barchart.jl │ │ │ ├── julia_functional_geometry.jl │ │ │ ├── jupyter.py │ │ │ ├── jupyter_again.py │ │ │ ├── jupyter_with_raw_cell_in_body.py │ │ │ ├── jupyter_with_raw_cell_on_top.py │ │ │ ├── jupyter_with_raw_cell_with_invalid_yaml.py │ │ │ ├── jupyterlab-slideshow_1441.py │ │ │ ├── jupytext_replication.sos │ │ │ ├── kalman_filter_and_visualization.q │ │ │ ├── logtalk_notebook.lgt │ │ │ ├── lua_example.lua │ │ │ ├── maxima_example.mac │ │ │ ├── notebook_with_complex_metadata.py │ │ │ ├── nteract_with_parameter.py │ │ │ ├── ocaml_notebook.ml │ │ │ ├── octave_notebook.m │ │ │ ├── plotly_graphs.py │ │ │ ├── powershell.ps1 │ │ │ ├── raw_cell_with_complex_yaml_like_content.py │ │ │ ├── raw_cell_with_non_dict_yaml_content.py │ │ │ ├── root_cpp.cpp │ │ │ ├── sage_print_hello.sage │ │ │ ├── sample_bash_notebook.sh │ │ │ ├── sample_rise_notebook_66.py │ │ │ ├── sas.sas │ │ │ ├── simple-helloworld.java │ │ │ ├── simple_robot_notebook.robot │ │ │ ├── simple_scala_notebook.scala │ │ │ ├── stata_notebook.do │ │ │ ├── tailrecursive-factorial.groovy │ │ │ ├── tcl_test.tcl │ │ │ ├── text_outputs_and_images.py │ │ │ ├── wolfram.wolfram │ │ │ ├── xcpp_by_quantstack.cpp │ │ │ └── xonsh_example.xsh │ │ ├── ipynb_to_quarto/ │ │ │ ├── Notebook_with_more_R_magic_111.qmd │ │ │ ├── cat_variable.qmd │ │ │ ├── frozen_cell.qmd │ │ │ └── julia_benchmark_plotly_barchart.qmd │ │ ├── ipynb_to_script/ │ │ │ ├── Line_breaks_in_LateX_305.py │ │ │ ├── Notebook with function and cell metadata 164.py │ │ │ ├── Notebook with html and latex cells.py │ │ │ ├── Notebook with metadata and long cells.py │ │ │ ├── Notebook_with_R_magic.py │ │ │ ├── Notebook_with_more_R_magic_111.py │ │ │ ├── R notebook with invalid cell keys.R │ │ │ ├── R notebook with invalid cell keys.low.r │ │ │ ├── Reference Guide for Calysto Scheme.scm │ │ │ ├── Reference Guide for Calysto Scheme.ss │ │ │ ├── The flavors of raw cells.py │ │ │ ├── cat_variable.py │ │ │ ├── coconut_homepage_demo.coco │ │ │ ├── convert_to_py_then_test_with_update83.py │ │ │ ├── csharp.cs │ │ │ ├── demo_gdl_fbp.pro │ │ │ ├── evcxr_jupyter_tour.rs │ │ │ ├── frozen_cell.py │ │ │ ├── fsharp.fsx │ │ │ ├── gnuplot_notebook.gp │ │ │ ├── haskell_notebook.hs │ │ │ ├── hello_world_gonb.go │ │ │ ├── html-demo.clj │ │ │ ├── ijavascript.js │ │ │ ├── ir_notebook.R │ │ │ ├── ir_notebook.low.r │ │ │ ├── itypescript.ts │ │ │ ├── julia_benchmark_plotly_barchart.jl │ │ │ ├── julia_functional_geometry.jl │ │ │ ├── jupyter.py │ │ │ ├── jupyter_again.py │ │ │ ├── jupyter_with_raw_cell_in_body.py │ │ │ ├── jupyter_with_raw_cell_on_top.py │ │ │ ├── jupyter_with_raw_cell_with_invalid_yaml.py │ │ │ ├── jupyterlab-slideshow_1441.py │ │ │ ├── jupytext_replication.sos │ │ │ ├── kalman_filter_and_visualization.q │ │ │ ├── logtalk_notebook.lgt │ │ │ ├── lua_example.lua │ │ │ ├── maxima_example.mac │ │ │ ├── notebook_with_complex_metadata.py │ │ │ ├── nteract_with_parameter.py │ │ │ ├── ocaml_notebook.ml │ │ │ ├── octave_notebook.m │ │ │ ├── plotly_graphs.py │ │ │ ├── powershell.ps1 │ │ │ ├── raw_cell_with_complex_yaml_like_content.py │ │ │ ├── raw_cell_with_non_dict_yaml_content.py │ │ │ ├── root_cpp.cpp │ │ │ ├── sage_print_hello.sage │ │ │ ├── sample_bash_notebook.sh │ │ │ ├── sample_rise_notebook_66.py │ │ │ ├── sas.sas │ │ │ ├── simple-helloworld.java │ │ │ ├── simple_robot_notebook.robot │ │ │ ├── simple_scala_notebook.scala │ │ │ ├── stata_notebook.do │ │ │ ├── tailrecursive-factorial.groovy │ │ │ ├── tcl_test.tcl │ │ │ ├── text_outputs_and_images.py │ │ │ ├── wolfram.wolfram │ │ │ ├── xcpp_by_quantstack.cpp │ │ │ └── xonsh_example.xsh │ │ ├── ipynb_to_script_vim_folding_markers/ │ │ │ ├── Line_breaks_in_LateX_305.py │ │ │ ├── Notebook with function and cell metadata 164.py │ │ │ ├── Notebook with html and latex cells.py │ │ │ ├── Notebook with many hash signs.py │ │ │ ├── Notebook with metadata and long cells.py │ │ │ ├── Notebook_with_R_magic.py │ │ │ ├── Notebook_with_more_R_magic_111.py │ │ │ ├── The flavors of raw cells.py │ │ │ ├── cat_variable.py │ │ │ ├── convert_to_py_then_test_with_update83.py │ │ │ ├── frozen_cell.py │ │ │ ├── jupyter.py │ │ │ ├── jupyter_again.py │ │ │ ├── jupyter_with_raw_cell_in_body.py │ │ │ ├── jupyter_with_raw_cell_on_top.py │ │ │ ├── jupyter_with_raw_cell_with_invalid_yaml.py │ │ │ ├── jupyterlab-slideshow_1441.py │ │ │ ├── notebook_with_complex_metadata.py │ │ │ ├── nteract_with_parameter.py │ │ │ ├── plotly_graphs.py │ │ │ ├── raw_cell_with_complex_yaml_like_content.py │ │ │ ├── raw_cell_with_non_dict_yaml_content.py │ │ │ ├── sample_rise_notebook_66.py │ │ │ └── text_outputs_and_images.py │ │ ├── ipynb_to_script_vscode_folding_markers/ │ │ │ ├── Line_breaks_in_LateX_305.py │ │ │ ├── Notebook with function and cell metadata 164.py │ │ │ ├── Notebook with html and latex cells.py │ │ │ ├── Notebook with many hash signs.py │ │ │ ├── Notebook with metadata and long cells.py │ │ │ ├── Notebook_with_R_magic.py │ │ │ ├── Notebook_with_more_R_magic_111.py │ │ │ ├── The flavors of raw cells.py │ │ │ ├── cat_variable.py │ │ │ ├── convert_to_py_then_test_with_update83.py │ │ │ ├── frozen_cell.py │ │ │ ├── jupyter.py │ │ │ ├── jupyter_again.py │ │ │ ├── jupyter_with_raw_cell_in_body.py │ │ │ ├── jupyter_with_raw_cell_on_top.py │ │ │ ├── jupyter_with_raw_cell_with_invalid_yaml.py │ │ │ ├── jupyterlab-slideshow_1441.py │ │ │ ├── notebook_with_complex_metadata.py │ │ │ ├── nteract_with_parameter.py │ │ │ ├── plotly_graphs.py │ │ │ ├── raw_cell_with_complex_yaml_like_content.py │ │ │ ├── raw_cell_with_non_dict_yaml_content.py │ │ │ ├── sample_rise_notebook_66.py │ │ │ └── text_outputs_and_images.py │ │ ├── ipynb_to_sphinx/ │ │ │ ├── Line_breaks_in_LateX_305.py │ │ │ ├── cat_variable.py │ │ │ ├── convert_to_py_then_test_with_update83.py │ │ │ ├── jupyter.py │ │ │ ├── jupyter_again.py │ │ │ ├── jupyterlab-slideshow_1441.py │ │ │ ├── notebook_with_complex_metadata.py │ │ │ ├── nteract_with_parameter.py │ │ │ ├── plotly_graphs.py │ │ │ ├── sample_rise_notebook_66.py │ │ │ └── text_outputs_and_images.py │ │ ├── ipynb_to_spin/ │ │ │ ├── R notebook with invalid cell keys.R │ │ │ ├── R notebook with invalid cell keys.low.r │ │ │ ├── ir_notebook.R │ │ │ └── ir_notebook.low.r │ │ ├── md_to_ipynb/ │ │ │ ├── jupytext_markdown.ipynb │ │ │ └── plain_markdown.ipynb │ │ ├── myst_to_ipynb/ │ │ │ ├── fenced_code_vs_code_cells.ipynb │ │ │ └── reference_link.ipynb │ │ ├── script_to_ipynb/ │ │ │ ├── basic_marimo_example.ipynb │ │ │ ├── build.ipynb │ │ │ ├── hydrogen.ipynb │ │ │ ├── hydrogen_latex_html_R_magics.ipynb │ │ │ ├── julia_sample_script.ipynb │ │ │ ├── knitr-spin.ipynb │ │ │ ├── light_sample.ipynb │ │ │ ├── python_notebook_sample.ipynb │ │ │ └── simple_r_script.ipynb │ │ ├── sphinx-rst2md_to_ipynb/ │ │ │ └── plot_notebook.ipynb │ │ └── sphinx_to_ipynb/ │ │ └── plot_notebook.ipynb │ ├── external/ │ │ ├── cli/ │ │ │ ├── test_black.py │ │ │ ├── test_cli_check.py │ │ │ └── test_isort.py │ │ ├── conftest.py │ │ ├── contents_manager/ │ │ │ └── test_contentsmanager_external.py │ │ ├── docs/ │ │ │ └── test_using_cli.py │ │ ├── jupyter_fs/ │ │ │ └── test_jupyter_fs.py │ │ ├── pre_commit/ │ │ │ ├── test_pre_commit_0_ipynb_to_py.py │ │ │ ├── test_pre_commit_1_sync.py │ │ │ ├── test_pre_commit_1_sync_with_config.py │ │ │ ├── test_pre_commit_1_sync_with_no_config.py │ │ │ ├── test_pre_commit_2_sync_nbstripout.py │ │ │ ├── test_pre_commit_3_sync_black_nbstripout.py │ │ │ ├── test_pre_commit_4_sync_execute.py │ │ │ ├── test_pre_commit_5_reformat_markdown.py │ │ │ ├── test_pre_commit_mode.py │ │ │ └── test_pre_commit_scripts.py │ │ ├── round_trip/ │ │ │ └── test_mirror_external.py │ │ ├── rst2md/ │ │ │ └── test_rst2md.py │ │ ├── simple_external_notebooks/ │ │ │ ├── test_read_simple_pandoc.py │ │ │ └── test_read_simple_quarto.py │ │ └── test_marimo.py │ ├── functional/ │ │ ├── cli/ │ │ │ ├── test_cli.py │ │ │ ├── test_cli_config.py │ │ │ ├── test_source_is_newer.py │ │ │ └── test_synchronous_changes.py │ │ ├── config/ │ │ │ └── test_config.py │ │ ├── contents_manager/ │ │ │ └── test_async_and_sync_contents_manager_are_in_sync.py │ │ ├── docs/ │ │ │ ├── test_changelog.py │ │ │ └── test_doc_files_are_notebooks.py │ │ ├── metadata/ │ │ │ ├── test_metadata_filter.py │ │ │ └── test_metadata_filters_from_config.py │ │ ├── others/ │ │ │ ├── invalid_file_896.md │ │ │ ├── test_active_cells.py │ │ │ ├── test_auto_ext.py │ │ │ ├── test_cell_markers.py │ │ │ ├── test_cell_metadata.py │ │ │ ├── test_cell_tags_are_preserved.py │ │ │ ├── test_cells.py │ │ │ ├── test_combine.py │ │ │ ├── test_custom_cell_magics.py │ │ │ ├── test_doxygen.py │ │ │ ├── test_hide_remove_input_outputs_rmarkdown.py │ │ │ ├── test_invalid_file.py │ │ │ ├── test_jupytext_errors.py │ │ │ ├── test_jupytext_read.py │ │ │ ├── test_nbformat_version.py │ │ │ ├── test_preserve_empty_cells.py │ │ │ ├── test_pytest.py │ │ │ ├── test_raw_strings.py │ │ │ ├── test_read_write_functions.py │ │ │ ├── test_remove_encoding.py │ │ │ ├── test_sample_notebooks_are_normalized.py │ │ │ ├── test_save_multiple.py │ │ │ ├── test_trust_notebook.py │ │ │ ├── test_unicode.py │ │ │ └── test_write_does_not_modify_notebook.py │ │ ├── round_trip/ │ │ │ ├── test_jupytext_nbconvert_round_trip.py │ │ │ ├── test_mirror.py │ │ │ ├── test_myst_header.py │ │ │ ├── test_read_all_py.py │ │ │ └── test_rmd_to_ipynb.py │ │ └── simple_notebooks/ │ │ ├── test_ipynb_to_R.py │ │ ├── test_ipynb_to_myst.py │ │ ├── test_ipynb_to_py.py │ │ ├── test_ipynb_to_rmd.py │ │ ├── test_knitr_spin.py │ │ ├── test_read_dotnet_try_markdown.py │ │ ├── test_read_empty_text_notebook.py │ │ ├── test_read_folding_markers.py │ │ ├── test_read_incomplete_rmd.py │ │ ├── test_read_simple_R.py │ │ ├── test_read_simple_clojure.py │ │ ├── test_read_simple_csharp.py │ │ ├── test_read_simple_go.py │ │ ├── test_read_simple_groovy.py │ │ ├── test_read_simple_hydrogen.py │ │ ├── test_read_simple_ipynb.py │ │ ├── test_read_simple_java.py │ │ ├── test_read_simple_julia.py │ │ ├── test_read_simple_markdown.py │ │ ├── test_read_simple_matlab.py │ │ ├── test_read_simple_nomarker.py │ │ ├── test_read_simple_ocaml.py │ │ ├── test_read_simple_percent.py │ │ ├── test_read_simple_python.py │ │ ├── test_read_simple_rmd.py │ │ ├── test_read_simple_rust.py │ │ ├── test_read_simple_scheme.py │ │ └── test_read_simple_sphinx.py │ ├── integration/ │ │ ├── cli/ │ │ │ ├── test_cli_pipe.py │ │ │ └── test_execute.py │ │ ├── contents_manager/ │ │ │ ├── test_cm_config.py │ │ │ ├── test_contentsmanager.py │ │ │ └── test_load_multiple.py │ │ └── jupytext_config/ │ │ └── test_jupytext_config.py │ └── unit/ │ ├── test_cell_id.py │ ├── test_compare.py │ ├── test_escape_magics.py │ ├── test_formats.py │ ├── test_header.py │ ├── test_labconfig.py │ ├── test_markdown_in_code_cells.py │ ├── test_paired_paths.py │ ├── test_pep8.py │ └── test_stringparser.py └── tools/ └── absolute_links_in_readme.py ================================================ FILE CONTENTS ================================================ ================================================ FILE: .git-blame-ignore-revs ================================================ # git config blame.ignoreRevsFile .git-blame-ignore-revs 961ce04d240560ea5d54b5d1ab40e6b5d76b4474 ================================================ FILE: .git_archival.txt ================================================ node: $Format:%H$ node-date: $Format:%cI$ describe-name: $Format:%(describe:tags=true,match=*[0-9]*)$ ref-names: $Format:%D$ ================================================ FILE: .gitattributes ================================================ World\ population.ipynb linguist-documentation .git_archival.txt export-subst # SCM syntax highlighting & preventing 3-way merges pixi.lock merge=binary linguist-language=TOML linguist-generated=true ================================================ FILE: .github/codecov.yml ================================================ codecov: token: 8bdc5016-2a81-4a43-bdd5-7b3b9adc37e7 notify: wait_for_ci: true coverage: status: project: source: paths: - "src/jupytext/" target: 96% threshold: 0.2% tests: paths: - "tests/" target: 100% unit-tests: threshold: 0.2% flags: - unit functional-tests: threshold: 0.2% flags: - functional integration-tests: threshold: 0.2% flags: - integration external-tests: threshold: 0.2% flags: - external patch: default: target: 80% ================================================ FILE: .github/dependabot.yml ================================================ # To get started with Dependabot version updates, you'll need to specify which # package ecosystems to update and where the package manifests are located. # Please see the documentation for all configuration options: # https://docs.github.com/code-security/dependabot/dependabot-version-updates/configuration-options-for-the-dependabot.yml-file version: 2 updates: # Let's not bother about bumping top level dependencies as they are mostly # developmental packages like linters. We can bump them manually # when we make changes to extension packages to be consistent with JupyterLab. # Importantly, these packages will not and should not effect the working of the # extension, so lets try to keep maintenance low by ignoring this. # - package-ecosystem: "npm" # See documentation for possible values # directory: "jupyterlab" # Location of package manifests # schedule: # interval: "weekly" # groups: # top-level-dependencies: # patterns: # - "*" - package-ecosystem: "npm" # See documentation for possible values directory: "jupyterlab/packages/jupyterlab-jupytext-extension" # Location of package manifests schedule: interval: "weekly" groups: jupytext-extension-dependencies: patterns: - "*" - package-ecosystem: "npm" # See documentation for possible values directory: "jupyterlab/packages/jupyterlab-jupytext-extension/ui-tests" # Location of package manifests schedule: interval: "weekly" groups: jupytext-extension-ui-tests-dependencies: patterns: - "*" ================================================ FILE: .github/workflows/ci.yml ================================================ name: CI on: workflow_dispatch: inputs: upload-build-artifacts: type: boolean required: false default: false description: Upload build artifacts push: paths-ignore: - "CHANGELOG.md" branches: [ main ] pull_request: branches: [ main ] schedule: - cron: "0 11 * * 4" permissions: # All nested workflows will inherit these permissions and so no need to declare # in each step file contents: read concurrency: group: ${{ github.workflow }}-${{ github.ref }} cancel-in-progress: true jobs: pre-commit: uses: ./.github/workflows/step_pre-commit.yml static-analysis: needs: [ pre-commit ] uses: ./.github/workflows/step_static-analysis.yml permissions: contents: read security-events: write test-pip: needs: [ pre-commit ] uses: ./.github/workflows/step_tests-pip.yml with: coverage: ${{ github.event_name != 'schedule' }} coverage: needs: [ test-pip ] uses: ./.github/workflows/step_coverage.yml if: github.event_name != 'schedule' test-conda: needs: [ pre-commit ] uses: ./.github/workflows/step_tests-conda.yml with: coverage: ${{ github.event_name != 'schedule' }} test-ui: needs: [ test-pip ] uses: ./.github/workflows/step_tests-ui.yml build: needs: [ test-pip, test-conda, test-ui ] uses: ./.github/workflows/step_build.yml with: upload: ${{ inputs.upload-build-artifacts || false }} pass: name: Pass needs: [ pre-commit, static-analysis, test-pip, coverage, test-conda, test-ui, build ] runs-on: ubuntu-latest steps: - uses: re-actors/alls-green@release/v1 with: jobs: ${{ toJSON(needs) }} allowed-skips: coverage if: always() ================================================ FILE: .github/workflows/comment-pr.yml ================================================ name: Comment PR on: pull_request_target: permissions: pull-requests: write jobs: comment-pr: runs-on: ubuntu-latest name: Comment PR steps: - name: Checkout uses: actions/checkout@v4 - name: Comment PR uses: thollander/actions-comment-pull-request@v2 with: message: | Thank you for making this pull request. Did you know? You can try it on Binder: [![Binder:lab](https://img.shields.io/badge/binder-jupyterlab-0172B2.svg)](https://mybinder.org/v2/gh/${{ github.event.pull_request.head.repo.full_name }}/${{ github.event.pull_request.head.ref }}?urlpath=lab/tree/demo/get_started.ipynb) or [![Binder:notebook](https://img.shields.io/badge/binder-notebook-0172B2.svg)](https://mybinder.org/v2/gh/${{ github.event.pull_request.head.repo.full_name }}/${{ github.event.pull_request.head.ref }}?filepath=demo). Also, the version of Jupytext developed in this PR can be installed with `pip`: ``` HATCH_BUILD_HOOKS_ENABLE=true pip install git+${{ github.event.pull_request.head.repo.clone_url }}@${{ github.event.pull_request.head.ref }} ``` (this requires `nodejs`, see more at [Developing Jupytext](https://jupytext.readthedocs.io/en/latest/developing.html)) comment_tag: binder_link ================================================ FILE: .github/workflows/publish.yml ================================================ name: Publish on: push: tags: - "v[0-9]+.[0-9]+.[0-9]+*" permissions: contents: read jobs: build: uses: ./.github/workflows/step_build.yml publish: needs: [ build ] runs-on: ubuntu-latest environment: name: pypi url: https://pypi.org/p/jupytext permissions: contents: read id-token: write steps: - name: Checkout source uses: actions/checkout@v3 - name: Install pixi uses: prefix-dev/setup-pixi@v0.9.1 with: pixi-version: v0.59.0 cache: true - name: Build package run: | eval "$(pixi shell-hook)" HATCH_BUILD_HOOKS_ENABLE=true hatch build - name: Publish uses: pypa/gh-action-pypi-publish@release/v1 ================================================ FILE: .github/workflows/step_build.yml ================================================ name: build run-name: Build package on: workflow_call: inputs: upload: type: boolean required: false default: false description: Upload build artifacts ref: type: string description: Tag to build permissions: contents: read jobs: build: runs-on: ubuntu-latest steps: - name: Checkout source uses: actions/checkout@v4 - name: Install pixi uses: prefix-dev/setup-pixi@v0.9.1 with: pixi-version: v0.59.0 cache: true - name: Build package run: | eval "$(pixi shell-hook)" HATCH_BUILD_HOOKS_ENABLE=true hatch build - name: Archive build artifacts uses: actions/upload-artifact@v4 with: name: dist path: dist if: ${{ inputs.upload }} ================================================ FILE: .github/workflows/step_coverage.yml ================================================ name: coverage run-name: Check coverage on: workflow_call: permissions: contents: read jobs: coverage: name: > ${{ matrix.coverage }} runs-on: ubuntu-latest strategy: fail-fast: false matrix: coverage: [unit, functional, integration, external] steps: - name: Checkout uses: actions/checkout@v4 - name: Base Setup uses: jupyterlab/maintainer-tools/.github/actions/base-setup@v1 with: python_version: 3.x - name: Install from source run: python -m pip install -e '.[test-cov,test-${{ matrix.coverage }}]' - name: Install a Jupyter Kernel run: python -m ipykernel install --name python_kernel --user - name: Run the tests run: pytest tests/${{ matrix.coverage }} -n logical --cov --cov-report=xml - name: Upload the coverage uses: codecov/codecov-action@v5 with: flags: ${{ matrix.coverage }} fail_ci_if_error: true verbose: true ================================================ FILE: .github/workflows/step_pre-commit.yml ================================================ name: pre-commit run-name: Run pre-commit tests on: workflow_call: permissions: contents: read jobs: pre-commit: runs-on: ubuntu-latest steps: - name: Checkout source uses: actions/checkout@v4 - name: Set up Python uses: actions/setup-python@v5 with: python-version: "3.x" - name: Install pixi uses: prefix-dev/setup-pixi@v0.9.1 with: pixi-version: v0.55.0 cache: true - uses: pre-commit/action@v3.0.0 lint-extension: runs-on: ubuntu-latest steps: - name: Checkout source uses: actions/checkout@v4 - name: Base Setup uses: jupyterlab/maintainer-tools/.github/actions/base-setup@v1 with: python_version: "3.x" # Current repo organization will not permit to set up pre-commit config for # TS lint related packages due to absence of package.json in the top level # repo. So we run lint step separately here - name: Lint the extension run: | # Install JupyterLab in an isolated env to get jlpm pip install jupyterlab>=4 # Install lint deps and lint extension cd jupyterlab/ jlpm jlpm run lint:check ================================================ FILE: .github/workflows/step_static-analysis.yml ================================================ name: static-analysis run-name: Run CodeQL analysis on: workflow_call: permissions: contents: read security-events: write jobs: codeql: runs-on: ubuntu-latest continue-on-error: true steps: - name: Checkout repository uses: actions/checkout@v4 - name: Initialize CodeQL uses: github/codeql-action/init@v3 with: languages: python, javascript - name: Perform CodeQL Analysis uses: github/codeql-action/analyze@v3 ================================================ FILE: .github/workflows/step_tests-conda.yml ================================================ name: test-conda run-name: Run Conda tests for different OS on: workflow_call: inputs: coverage: type: boolean description: Upload coverage to CodeCov default: true permissions: contents: read jobs: test-conda: name: > ${{ matrix.os }} (${{ matrix.dependency-mode }} dependencies) strategy: fail-fast: false matrix: os: [ 'ubuntu-latest', 'macos-latest', 'windows-latest' ] dependency-mode: [ 'locked', 'latest' ] runs-on: ${{ matrix.os }} defaults: run: shell: bash -el {0} steps: - name: Checkout uses: actions/checkout@v4 - name: Install pixi uses: prefix-dev/setup-pixi@v0.9.1 with: pixi-version: v0.59.0 cache: true - name: Update pixi environment if: matrix.dependency-mode == 'latest' run: | eval "$(pixi shell-hook)" pixi update - name: Run tests run: | eval "$(pixi shell-hook)" # Install from source HATCH_BUILD_HOOKS_ENABLE=true python -m pip install -e . # Install a Jupyter Kernel python -m ipykernel install --name jupytext-ci --user # Test with pytest pytest -n logical --cov --cov-report=xml # Uninstall jupyter-fs as it overrides the original browser-test.js to # check its own functionality (https://github.com/jpmorganchase/jupyter-fs/blob/main/jupyterfs/browser-test.js) # So uninstall jupyter-fs before running browser check pip uninstall jupyter-fs -y # Check extension jupyter labextension list jupyter labextension list 2>&1 | grep -ie "jupyterlab-jupytext.*OK" # Test lab extension python -m jupyterlab.browser_check - name: Upload coverage uses: codecov/codecov-action@v5 with: fail_ci_if_error: true verbose: true if: inputs.coverage ================================================ FILE: .github/workflows/step_tests-pip.yml ================================================ name: test-pip run-name: Run main tests using Pip on: workflow_call: inputs: coverage: type: boolean description: Upload coverage to CodeCov default: true permissions: contents: read jobs: test-pip: name: > 🐍 ${{ matrix.python-version }} ${{ matrix.dependency_type && format('({0})', matrix.dependency_type) }} ${{ matrix.quarto && '(Quarto)' }} ${{ matrix.no_kernel && '(No kernel)' }} ${{ matrix.markdown-it-py && format('(markdown-it-py {0})', matrix.markdown-it-py) }} ${{ matrix.no_markdown-it-py && '(No markdown-it-py)'}} ${{ matrix.jupyter_server && format('(Jupyter-server {0})', matrix.jupyter_server) }} runs-on: ubuntu-latest strategy: fail-fast: false matrix: python-version: [ "3.9", "3.10", "3.11", "3.12", "3.13", "3.14"] experimental: [false] include: # Test with jupyter-server=2.10 that does not have the 'require_hash' argument - python-version: "3.x" jupyter_server: "2.10.0" # Test minimum markdown-it-py supported (otherwise the most recent version is used) - python-version: "3.x" markdown-it-py: "~=2.0" - python-version: "3.x" no_markdown-it-py: true - python-version: "3.x" no_kernel: true - python-version: "3.x" quarto: true steps: - name: Checkout uses: actions/checkout@v4 - name: Base Setup uses: jupyterlab/maintainer-tools/.github/actions/base-setup@v1 with: python_version: ${{ matrix.python-version }} dependency_type: ${{ matrix.dependency_type }} - name: Install from source run: > HATCH_BUILD_HOOKS_ENABLE=true python -m pip install -e '.[test-cov,test-external]' jupyterlab ${{ format('markdown-it-py{0}', matrix.markdown-it-py) }} - name: Install Jupyter Server if: ${{ matrix.jupyter_server }} run: python -m pip install 'jupyter_server~=${{ matrix.jupyter_server }}' - name: List the versions of the Jupyter components run: jupyter --version - name: Install a Jupyter Kernel if: ${{ !matrix.no_kernel }} run: python -m ipykernel install --name python_kernel --user - name: Uninstall markdown-it-py # Markdown-it-py is a dependency of Jupytext, # but Jupytext should still work if it is not installed if: ${{ matrix.no_markdown-it-py }} run: python -m pip uninstall markdown-it-py --yes - name: Install Quarto if: ${{ matrix.quarto }} env: GITHUB_TOKEN: ${{secrets.GITHUB_TOKEN}} run: | # download the latest release gh release download --repo quarto-dev/quarto-cli --pattern 'quarto-*-linux-amd64.deb' # install it sudo apt install ./*.deb - name: Test with pytest continue-on-error: ${{ matrix.experimental }} run: pytest -n logical --cov --cov-report=xml - name: Test lab extension run: | # Uninstall jupyter-fs as it overrides the original browser-test.js to # check its own functionality (https://github.com/jpmorganchase/jupyter-fs/blob/main/jupyterfs/browser-test.js) # So uninstall jupyter-fs before running browser check # pip uninstall jupyter-fs -y # Check extension jupyter labextension list jupyter labextension list 2>&1 | grep -ie "jupyterlab-jupytext.*OK" python -m jupyterlab.browser_check - name: Upload coverage uses: codecov/codecov-action@v5 with: fail_ci_if_error: true verbose: true if: inputs.coverage ================================================ FILE: .github/workflows/step_tests-ui.yml ================================================ name: test-ui run-name: Run UI tests with Galata on: workflow_call: permissions: contents: read jobs: test-ui: continue-on-error: false runs-on: ubuntu-latest steps: - name: Checkout uses: actions/checkout@v4 - name: Install pixi uses: prefix-dev/setup-pixi@v0.9.1 with: pixi-version: v0.59.0 cache: true - name: Install from source run: | eval "$(pixi shell-hook)" HATCH_BUILD_HOOKS_ENABLE=true python -m pip install -e '.[test-ui]' - name: Uninstall jupyter-fs run: | eval "$(pixi shell-hook)" # Uninstall jupyter-fs as it overrides the original browser-test.js to # check its own functionality (https://github.com/jpmorganchase/jupyter-fs/blob/main/jupyterfs/browser-test.js) pip uninstall jupyter-fs -y - name: Install galata working-directory: jupyterlab/packages/jupyterlab-jupytext-extension/ui-tests env: PLAYWRIGHT_SKIP_BROWSER_DOWNLOAD: 1 run: | eval "$(pixi shell-hook)" jlpm install - name: Install browser working-directory: jupyterlab/packages/jupyterlab-jupytext-extension/ui-tests run: | eval "$(pixi shell-hook)" jlpm playwright install chromium - name: Integration tests working-directory: jupyterlab/packages/jupyterlab-jupytext-extension/ui-tests run: | eval "$(pixi shell-hook)" jlpm playwright test - name: Upload UI Test artifacts if: failure() uses: actions/upload-artifact@v4 with: name: ui-test-output path: | jupyterlab/packages/jupyterlab-jupytext-extension/ui-tests/test-results ================================================ FILE: .github/workflows/update-playwright-snapshots.yml ================================================ name: Update Playwright Snapshots on: issue_comment: types: [created, edited] permissions: contents: write pull-requests: write jobs: update-snapshots: if: ${{ github.event.issue.pull_request && contains(github.event.comment.body, 'update playwright snapshots') }} runs-on: ubuntu-latest steps: - name: React to the triggering comment run: | gh api repos/${{ github.repository }}/issues/comments/${{ github.event.comment.id }}/reactions --raw-field 'content=+1' env: GITHUB_TOKEN: ${{ secrets.GITHUB_TOKEN }} - name: Checkout uses: actions/checkout@v4 - name: Checkout the branch from the PR that triggered the job run: | gh pr checkout ${{ github.event.issue.number }} env: GITHUB_TOKEN: ${{ secrets.GITHUB_TOKEN }} - name: Install jupytext run: | HATCH_BUILD_HOOKS_ENABLE=true python -m pip install -e '.[test-ui]' jupyterlab # Uninstall jupyter-fs as it overrides the original browser-test.js to # check its own functionality (https://github.com/jpmorganchase/jupyter-fs/blob/main/jupyterfs/browser-test.js) pip uninstall jupyter-fs -y - name: Update snapshots uses: jupyterlab/maintainer-tools/.github/actions/update-snapshots@v1 with: github_token: ${{ secrets.GITHUB_TOKEN }} # Test folder within your repository test_folder: jupyterlab/packages/jupyterlab-jupytext-extension/ui-tests/tests # Playwright knows how to start JupyterLab server start_server_script: 'null' npm_client: jlpm ================================================ FILE: .gitignore ================================================ .build .cache .eggs .tox build /dist docs/_build # Will be created by postBuild demo/get_started.ipynb # jetbrains ide stuff *.iml .idea/ # vscode ide stuff *.code-workspace .history .vscode/* !.vscode/*.template # Notebooks *.pyc .ipynb_checkpoints .jupyter_ystore.db* # Test related files .coverage .pytest_cache *.coverage* *.xml .ruff_cache # Ignore node_modules and yarn cache node_modules .yarn # Ignore jupyter-releaser related stuff .jupyter_releaser_checkout # pixi environments .pixi *.egg-info ================================================ FILE: .pre-commit-config.yaml ================================================ # Install the pre-commit hooks below with # 'pre-commit install' # Auto-update the version of the hooks with # 'pre-commit autoupdate' # Run the hooks on all files with # 'pre-commit run --all' # NB: In this config we exclude the example and tests notebooks # from the code hooks (black, flake8, etc) as we want to keep # the text representation of the test notebooks unchanged, plus # the (sync) contentsmanager.py which is generated from the async one. exclude: > (?x)^( demo/.*| tests/data/notebooks/.*| src/jupytext/sync_pairs.py| src/jupytext/sync_contentsmanager.py| )$ repos: - repo: https://github.com/pre-commit/pre-commit-hooks rev: v6.0.0 hooks: - id: check-json - id: check-yaml - id: end-of-file-fixer - id: trailing-whitespace - repo: https://github.com/astral-sh/ruff-pre-commit rev: v0.14.13 hooks: - id: ruff-check args: ["--fix", "--show-fixes"] - id: ruff-format - repo: https://github.com/asottile/pyupgrade rev: v3.21.2 hooks: - id: pyupgrade args: [--py39-plus] - repo: local hooks: - id: pixi-lock name: Update pixi.lock file entry: pixi install language: system pass_filenames: false files: ^(pyproject\.toml|pixi\.toml|pixi\.lock|src/jupytext/version\.py)$ ================================================ FILE: .pre-commit-hooks.yaml ================================================ - id: jupytext name: jupytext description: Runs jupytext on all notebooks and paired files. language: python entry: jupytext --pre-commit-mode require_serial: true # We have only added the most frequent text notebook types, but # many more types are actually supported (r, matlab, js, bash, powershell, robot, ...) # If you need support for one of these other extensions, please override this default value types_or: [jupyter, markdown, python] ================================================ FILE: .readthedocs.yml ================================================ # Read the Docs configuration file # See https://docs.readthedocs.io/en/stable/config-file/v2.html for details # Required version: 2 # Build the documentation using Pixi build: os: "ubuntu-24.04" tools: python: "3.12" commands: - asdf plugin add pixi - asdf install pixi latest - asdf global pixi latest - pixi run -e docs sphinx-build -b html docs ${READTHEDOCS_OUTPUT:-docs/_build}/html ================================================ FILE: CHANGELOG.md ================================================ Jupytext ChangeLog ================== 1.19.1 (2026-01-25) ------------------- **Changed** - Jupytext does not change the file icons anymore! Thanks to [Michał Krassowski](https://github.com/krassowski) for finally solving this long standing issue! ([#398](https://github.com/mwouts/jupytext/issues/398)) - We have bumped lodash from 4.17.21 to 4.17.23 in JupyterLab extension ([#1483](https://github.com/mwouts/jupytext/pull/1483)) - We require `marimo<=0.19.4` in tests following a change in the location of the `marimo` import ([#1485](https://github.com/mwouts/jupytext/issues/1485)) 1.19.0 (2026-01-18) ------------------- **Changed** - The environment used to develop Jupytext is now maintained using Pixi ([#1459](https://github.com/mwouts/jupytext/pull/1459)) **Fixed** - We have restored the support for `.qmd` documents in Jupyter ([#1435](https://github.com/mwouts/jupytext/issues/1435)) - We have fixed warnings about the cell ids like either `Cell is missing an id field` or `Additional properties are not allowed ('id' was unexpected)` when converting to some formats, including Pandoc ([#1464](https://github.com/mwouts/jupytext/pull/1464)) - We have updated the dependencies of the Jupytext extension for JupyterLab. Many thanks to [Mahendra Paipuri](https://github.com/mahendrapaipuri) for his PR ([#1477](https://github.com/mwouts/jupytext/pull/1477))! **Added** - We have added a new `py:marimo` format, which uses the `marimo` command line interface to convert notebooks to and from the Marimo format ([#1431](https://github.com/mwouts/jupytext/pull/1431)) 1.18.1 (2025-10-19) ------------------- **Fixed** - Fixed test `test_check_source_is_newer_when_using_jupytext_sync` to work reliably on systems with low filesystem timestamp resolution ([#1460](https://github.com/mwouts/jupytext/issues/1460)) **Changed** - We now use `pixi` to maintain the local Python environments used for developing and testing Jupytext. 1.18.0 (2025-10-18) ------------------- **Added** - The documentation has a chapter on the [Jupytext Sync](https://jupytext.readthedocs.io/en/latest/vs-code.html) extension for VS Code ([#1395](https://github.com/mwouts/jupytext/issues/1395)) - We have added a new option `--check-source-is-newer` to the Jupytext CLI. Use this option if you want to make sure that the file passed as argument to Jupytext is the newest of all paired files, and/or newer than the destination file. - We have added a section on [Jupyter Collaboration](https://jupytext.readthedocs.io/en/latest/jupyter-collaboration.html) which also provides a very useful autoreload functionality ([#406](https://github.com/mwouts/jupytext/issues/406), [#1401](https://github.com/mwouts/jupytext/issues/1401)) - Pairing groups allow you to define different pairing configurations for specific subsets of notebooks. The `formats` configuration option now supports a list of format dictionaries for first-match pairing. Use `[[formats]]` sections in your TOML configuration to define multiple format specifications, where the first matching format is used. This allows applying different pairing rules to notebooks in different locations, such as generating documentation markdown files only for tutorial notebooks ([#1383](https://github.com/mwouts/jupytext/issues/1383)) - We have added more tests to document the complex pairing formats, which also work on Windows ([#1028](https://github.com/mwouts/jupytext/issues/1028)) - Pairing into nested folders was fixed on Windows ([#1028](https://github.com/mwouts/jupytext/issues/1028)) - Jupytext is now tested with Python 3.14 ([#1456](https://github.com/mwouts/jupytext/issues/1456)) **Fixed** - The Jupytext CLI now detects if a file it has read or consulted has been modified while it was processing it. That can happen in the context of the [Jupytext Sync](https://marketplace.visualstudio.com/items?itemName=caenrigen.jupytext-sync) extension for VS Code ([#1411](https://github.com/mwouts/jupytext/issues/1411), [vscode-jupytext-sync-#12](https://github.com/caenrigen/vscode-jupytext-sync/issues/12)). When such a synchronous modification is detected, Jupytext now raises an error. Many thanks to [Anne Archibald](https://github.com/aarchiba) for reporting the issue and preparing an inspiring PR ([#1417](https://github.com/mwouts/jupytext/pull/1417)). - We don't import `notebook` when `jupyter_server` is available ([#1436](https://github.com/mwouts/jupytext/issues/1436)) - Jupytext now supports more characters in the cell metadata keys, to improve compatibility with `jupyterlab-slideshow` ([#1441](https://github.com/mwouts/jupytext/issues/1441)). Thanks to [Nicolas Thierry](https://github.com/nthiery) for this fix. - The function `find_jupytext_configuration_file` now works with relative directories ([#1440](https://github.com/mwouts/jupytext/issues/1440)). This fix was contributed by [Thierry Parmentelat](https://github.com/parmentelat). - We have fixed a parsing error for R Markdown files ([#1429](https://github.com/mwouts/jupytext/issues/1429)) - We have fixed a parsing error when the first cell of the notebook contains a YAML header that is not a dict ([#1444](https://github.com/mwouts/jupytext/issues/1444)) **Changed** - We have updated the pre-commit hooks. The code is now formatted using `ruff format`, and updated for Python 3.9+ using https://github.com/asottile/pyupgrade ([#1423](https://github.com/mwouts/jupytext/issues/1423)) 1.17.3 (2025-08-28) ------------------- **Added** - All the extensions supported by Jupytext now appear in the `--to` paragraph of `jupytext --help` ([#433](https://github.com/mwouts/jupytext/issues/433)) - We have added a new function `get_formats_from_notebook_path` that returns the list of paired formats for a given notebook ([#1419](https://github.com/mwouts/jupytext/issues/1419)) **Fixed** - We have fixed `jupytext --sync`, and the contents manager, to make sure that a simple `.py` file (not in the percent format) will not be treated as a paired file when the Jupytext configuration file has `formats="ipynb,py:percent"` ([#1418](https://github.com/mwouts/jupytext/issues/1418)) - A notebook can be moved in Jupyter even if that makes it unpaired ([#1414](https://github.com/mwouts/jupytext/issues/1414)) - The test against `jupyter-fs` now installs its `fs` extra dependency ([#1398](https://github.com/mwouts/jupytext/issues/1398)) - The `jupytext --sync` command now works correctly with symbolic links. Thanks to [mccullerlp](https://github.com/mccullerlp) for reporting ([#1407](https://github.com/mwouts/jupytext/issues/1407)) and addressing ([#1408](https://github.com/mwouts/jupytext/pull/1408)) the problem! - Jupytext will look for `quarto.cmd` on Windows. Thanks to [mccullerlp](https://github.com/mccullerlp) for documenting the issue ([#1406](https://github.com/mwouts/jupytext/issues/1406), [#1409](https://github.com/mwouts/jupytext/pull/1409)). - We have corrected the `jupytext --paired-paths` command: it will now take the Jupytext configuration file, if any, into account ([#1419](https://github.com/mwouts/jupytext/issues/1419)) 1.17.2 (2025-06-01) ------------------- **Fixed** - The `--set-formats` argument takes precedence over pre-existing pairing information in the notebook ([#1386](https://github.com/mwouts/jupytext/issues/1386)) **Changed** - We have removed Python 3.8 from the list of supported Python version, and from the CI, as it has reached its EOL **Added** - ROOT-flavored C++ notebooks can be paired to `.cpp` files - thanks to [Steven Gardiner](https://github.com/sjgardiner) for this contribution ([#1384](https://github.com/mwouts/jupytext/pull/1384)) 1.17.1 (2025-04-26) ------------------- **Fixed** - Renaming files other than notebooks will not load their content ([#1376](https://github.com/mwouts/jupytext/issues/1376)) 1.17.0 (2025-04-05) ------------------- **Added** - The MyST frontmatter found in MyST Markdown notebooks can be mapped to a YAML header at the top of the Jupyter notebook. This way MyST notebooks in either the `md:myst` or `ipynb` format can be used with MyST. Thanks to [Ian Carroll](https://github.com/itcarroll) for proposing and implementing this change ([#1314](https://github.com/mwouts/jupytext/issues/1314)) - The context menu has a "New Text Notebook" entry. Thanks to [Mahendra Paipuri](https://github.com/mahendrapaipuri) for this PR ([#1365](https://github.com/mwouts/jupytext/pull/1365))! **Changed** - Jupytext's default contents manager is now derived from the asynchronous AsyncLargeFileManager. Thanks to [Darshan Poudel](https://github.com/Darshan808) for making this finally happen ([#1328](https://github.com/mwouts/jupytext/pull/1328))! - The [percent format](https://jupytext.readthedocs.io/en/latest/formats-scripts.html#the-percent-format) is now the default format for scripts. If you run `jupytext --to py notebook.ipynb` you now get a `py:percent` script (use `--to py:light` for the light format) [#1201](https://github.com/mwouts/jupytext/pull/1201) - The `rst2md` conversion now works with `sphinx-gallery>=0.8`. Thanks to [Thomas J. Fan](https://github.com/thomasjpfan) for fixing this! ([#1334](https://github.com/mwouts/jupytext/pull/1334)) - We have updated the JupyterLab extension dependencies ([#1300](https://github.com/mwouts/jupytext/pull/1300), [#1355](https://github.com/mwouts/jupytext/pull/1355), [#1360](https://github.com/mwouts/jupytext/pull/1360)). Thanks to [Mahendra Paipuri](https://github.com/mahendrapaipuri) for these PRs! **Fixed** - We have added and fixed round trip tests on MyST Markdown notebooks ([#759](https://github.com/mwouts/jupytext/issues/759), [#789](https://github.com/mwouts/jupytext/issues/789), [#1267](https://github.com/mwouts/jupytext/issues/1267), [#1317](https://github.com/mwouts/jupytext/issues/1317)) - The `--quiet` option now works with the `--pipe` mode of Jupytext CLI ([#1305](https://github.com/mwouts/jupytext/issues/1305)) - Jupytext is now compatible with the cell toolbar extension - thanks to [Nicolas Brichet](https://github.com/brichet) for the fix! ([#1358](https://github.com/mwouts/jupytext/pull/1358)) - The project description on PyPI now uses absolute links ([#1287](https://github.com/mwouts/jupytext/issues/1287)) 1.16.7 (2025-02-09) ------------------- **Added** - Logtalk notebooks are now supported ([#1308](https://github.com/mwouts/jupytext/pull/1308)) - thanks to [Paulo Moura](https://github.com/pmoura) for this contribution **Fixed** We have updated the dependencies of the JupyterLab extension to address [security issues](https://github.com/mwouts/jupytext/security/dependabot). 1.16.6 (2024-12-16) ------------------- **Fixed** - We fixed a "File Changed" warning when saving notebooks ([#1301](https://github.com/mwouts/jupytext/issues/1301)) **Changed** - The original file name is easier to infer from the tmp file name in pre-commit hooks ([#1289](https://github.com/mwouts/jupytext/issues/1289)) - thanks to [Lunin Leonid](https://github.com/lrlunin) for making this change. 1.16.5 (2024-12-15) ------------------- **Fixed** - We have fixed a notebook corruption issue when using Jupytext with Jupyter-Collaboration ([#1124](https://github.com/mwouts/jupytext/issues/1124), [jupyter-collaboration 214](https://github.com/jupyterlab/jupyter-collaboration/issues/214)). - We have added the `require_hash` argument on the Jupytext contents manager. The hash of a paired file is the concatenation of the hash of the text file and the hash for the `.ipynb` file ([#1165](https://github.com/mwouts/jupytext/issues/1165)) - The `rst2md` tests have been fixed by requiring `sphinx<8` ([#1266](https://github.com/mwouts/jupytext/issues/1266)) - Some dependencies of the JupyterLab extensions were updated ([#1272](https://github.com/mwouts/jupytext/issues/1272), [#1273](https://github.com/mwouts/jupytext/issues/1273), [#1280](https://github.com/mwouts/jupytext/issues/1280), [#1285](https://github.com/mwouts/jupytext/issues/1285), [#1290](https://github.com/mwouts/jupytext/issues/1290)) - The pre-commit hook is now compatible with log.showsignature=True ([#1281](https://github.com/mwouts/jupytext/issues/1281)). Thanks to [Justin Lecher](https://github.com/jlec) for this fix. **Added** - Jupytext is now tested with Python 3.13 ([#1242](https://github.com/mwouts/jupytext/issues/1242)). Thanks to [Jerry James](https://github.com/jamesjer) for the suggested fixes! - The extension of a notebook piped into stdin will be taken in the notebook metadata ([#1282](https://github.com/mwouts/jupytext/issues/1282)) 1.16.4 (2024-07-12) ------------------- **Fixed** - We use `asyncio.iscoroutinefunction` to determine whether the current contents manager is sync or async ([#1260](https://github.com/mwouts/jupytext/issues/1260)) 1.16.3 (2024-07-09) ------------------- **Fixed** - We use `inspect` to determine whether the current contents manager derives from `AsyncContentsManager` (which is not supported by Jupytext at the moment). This fixes a compatibility issue with `jupyter-fs==1.0.0` ([#1239](https://github.com/mwouts/jupytext/issues/1239)). Thanks to [Mahendra Paipuri](https://github.com/mahendrapaipuri) for this PR! - We have fixed a typo when `build_jupytext_contents_manager_class` can't be imported ([#1162](https://github.com/mwouts/jupytext/issues/1162)) - A Python 3.13 deprecation warning was fixed [#1241](https://github.com/mwouts/jupytext/pull/1241) - thanks to [Jerry James](https://github.com/jamesjer) - We have fixed a typo when `build_jupytext_contents_manager_class` can't be imported ([#1162](https://github.com/mwouts/jupytext/issues/1162)) - Some dependencies of the JupyterLab extensions were updated ([#1243](https://github.com/mwouts/jupytext/issues/1243), [#1245](https://github.com/mwouts/jupytext/issues/1245)) **Added** - Lua notebooks are now supported ([#1252](https://github.com/mwouts/jupytext/pull/1252)) - thanks to [erentar](https://github.com/erentar) for this contribution - Go notebooks are supported too ([#1244](https://github.com/mwouts/jupytext/issues/1244))! Many thanks to [Jan Pfeifer](https://github.com/janpfeifer), author of [GoNB](https://github.com/janpfeifer/gonb), and to [HaveF](https://github.com/HaveF) for their help on this topic. - Empty prefixes are now allowed in Jupytext format when specified as a dictionary ([#1144](https://github.com/mwouts/jupytext/issues/1144)) **Changed** - We've had to deactivate the tests on the Quarto format in the CI as the Quarto round trip might now add a Markdown cell to the notebook ([#1255](https://github.com/mwouts/jupytext/issues/1255)) 1.16.2 (2024-05-05) ------------------- **Added** - Added support for Xonsh notebooks ([#1213](https://github.com/mwouts/jupytext/pull/1213)) - thanks to [Jeffrey Odongo](https://github.com/jsquaredosquared) for this contribution **Changed** - By default, the JupyterLab extension for Jupytext is not included in the build (set `HATCH_BUILD_HOOKS_ENABLE=true` to include it). This simplifies the installation of Jupytext in pre-commit hooks ([#1210](https://github.com/mwouts/jupytext/issues/1210)) - Temporary text notebooks for the `--pipe` or `--check` commands are now created in the notebook directory ([#1206](https://github.com/mwouts/jupytext/issues/1206)) - Jupytext uses the standard library `tomllib` in Python 3.11, or `tomli` in Python 3.10 or older, to match JupyterLab's dependencies ([#1195](https://github.com/mwouts/jupytext/issues/1195)) - The dependencies of the JupyterLab extension were updated ([#1216](https://github.com/mwouts/jupytext/issues/1216), [#1218](https://github.com/mwouts/jupytext/issues/1218), [#1231](https://github.com/mwouts/jupytext/issues/1231)) - `jupytext --sync` will not update the timestamp of text notebooks if their content is unchanged ([#1215](https://github.com/mwouts/jupytext/issues/1215)) **Fixed** - Jupytext is now tested with `pandoc>=3.0`. Please note that switching to `pandoc>=3.0` will add cell ids to your `pandoc:md` notebooks ([#1006](https://github.com/mwouts/jupytext/issues/1006)) 1.16.1 (2024-01-13) ------------------- **Changed** - The CI has been updated. Thanks to [Christian Le](https://github.com/LecrisUT) for taking care of this! ([#1190](https://github.com/mwouts/jupytext/issues/1190), [#1204](https://github.com/mwouts/jupytext/issues/1204)) **Fixed** - Fixed an issue about unpairing notebooks from the Jupytext Menu ([#1197](https://github.com/mwouts/jupytext/issues/1197)) - JupyterLab's dependency `follow-redirects` was updated from 1.15.3 to 1.15.4 ([#1203](https://github.com/mwouts/jupytext/issues/1203)) 1.16.0 (2023-12-03) ------------------- **Added** - The Jupytext Menu is back! And text notebooks can be created directly from the launcher. This is an outstanding contribution by [Mahendra Paipuri](https://github.com/mahendrapaipuri) ([#1154](https://github.com/mwouts/jupytext/issues/1154), [#1163](https://github.com/mwouts/jupytext/issues/1163)). This requires JupyterLab 4.x or Jupyter Notebook 7.x. **Changed** - Jupytext is now configured with `pyproject.toml` and built with `hatch`. The layout has been reorganised to follow `src-layout` ([#1140](https://github.com/mwouts/jupytext/issues/1140)). This is another outstanding contribution by [Mahendra Paipuri](https://github.com/mahendrapaipuri). - The tests are now part of the `sdist`. They have been reorganized into unit/functional/integration/external ([#1167](https://github.com/mwouts/jupytext/issues/1167), [#1173](https://github.com/mwouts/jupytext/issues/1173)). - The legacy extension for Jupyter Notebook <=6 (the Jupytext Menu) has been removed. **Fixed** - The bibliography section in Rmd files does not become a code cell anymore ([#1161](https://github.com/mwouts/jupytext/issues/1161)) - Commented code in `active-py` cells is not uncommented anymore ([#1131](https://github.com/mwouts/jupytext/issues/1131)) - The test coverage has been restored ([#1167](https://github.com/mwouts/jupytext/issues/1167), [#1173](https://github.com/mwouts/jupytext/issues/1173)) - We test Jupytext against the pre-release version of JupyterLab, and other dependencies ([#1168](https://github.com/mwouts/jupytext/issues/1168)) 1.15.2 (2023-09-16) ------------------- **Added** - The JupyterLab extension is now compatible with the [JupyterLab RISE](https://github.com/jupyterlab-contrib/rise) extension. Many thanks to [Frédéric Collonval](https://github.com/fcollonval) for his PR ([#1126](https://github.com/mwouts/jupytext/pull/1126))! 1.15.1 (2023-08-26) ------------------- **Added** - We have added a new command line interface `jupytext-config` that you can use to set Jupytext as the default viewer for text notebooks in JupyterLab and Jupyter Notebook 7. Thanks to [Thierry Parmentelat](https://github.com/parmentelat) for this contribution! ([#1094](https://github.com/mwouts/jupytext/pull/1094)) 1.15.0 (2023-07-30) ------------------- **Changed** - This version comes with a version of the JupyterLab extension that is compatible with JupyterLab 4.x. Many thanks to [Thierry Parmentelat](https://github.com/parmentelat) for his PRs! ([#1092](https://github.com/mwouts/jupytext/pull/1092), [#1109](https://github.com/mwouts/jupytext/pull/1109)) - Pandoc 3.0 is now supported, thanks to [Raniere Silva](https://github.com/rgaiacs) for his PR ([#1099](https://github.com/mwouts/jupytext/pull/1099)) - We have reorganized the documentation and the README.md ([#1031](https://github.com/mwouts/jupytext/issues/1031), [#1073](https://github.com/mwouts/jupytext/issues/1073)) - Invalid `pyproject.toml` files will be ignored by Jupytext in Jupyter ([#1103](https://github.com/mwouts/jupytext/issues/1103)) - We have updated the pre-commit tools 1.14.7 (2023-06-29) ------------------- **Changed** - We have updated the GitHub workflows - thanks to Matthew Feickert and to Cristian Le for their help on this subject ([#1037](https://github.com/mwouts/jupytext/issues/1037)) - We have removed the upper bound on `markdown-it-py<3`. Now we test Jupytext with `markdown-it-py` in versions `2.x` and `3.x` on the CI ([#1075](https://github.com/mwouts/jupytext/issues/1075)) **Fixed** - Notebooks with an empty YAML header work ([#1070](https://github.com/mwouts/jupytext/issues/1070)) - Double quote strings in R Markdown options can contain single quotes ([#1079](https://github.com/mwouts/jupytext/issues/1079)) - The necessary directories are created when paired notebooks are moved to a sub-folder ([#1059](https://github.com/mwouts/jupytext/issues/1059)) - Commented quotes are recognized as such ([#1060](https://github.com/mwouts/jupytext/issues/1060)) - Jupytext can use either `pkg_resources` or `packaging` to parse version numbers ([#1085](https://github.com/mwouts/jupytext/issues/1085)) 1.14.6 (2023-06-04) ------------------- **Changed** - This version comes with a build requirement `jupyterlab>=3,<4`, as the Jupyterlab extension for Jupytext is not compatible with JupyterLab 4 yet ([#1054](https://github.com/mwouts/jupytext/issues/1054)) - The JupyterLab extension was released to `npm` in version 1.3.9. 1.14.5 (2023-02-25) ------------------- **Added** - Added Stata as a supported language ([#1027](https://github.com/mwouts/jupytext/pull/1027)) - thanks to [Raffaele Mancuso](https://github.com/raffaem) for this contribution - Added SAS as a supported language ([#1047](https://github.com/mwouts/jupytext/pull/1047)) - thanks to [lawrencet149](https://github.com/lawrencet149) for this contribution - We have added a series of test to make sure that the main formats support cell tags ([#1024](https://github.com/mwouts/jupytext/issues/1024)) **Fixed** - When a metadata key is not a valid identifier, a warning is emitted and the metadata is not saved to the text representation ([#1042](https://github.com/mwouts/jupytext/issues/1042)) - The CI was fixed by [Matthew Feickert](https://github.com/matthewfeickert) ([#1035](https://github.com/mwouts/jupytext/pull/1035)) - We now use `concurrency` to cancel previous runs on the same branch/PR ([#1037](https://github.com/mwouts/jupytext/issues/1037)) - We use both `codecov.notify.after_n_builds` and `comment.after_n_builds` to get only the final codecov comment **Changed** - Empty tags are not exported to the text notebook anymore ([#960](https://github.com/mwouts/jupytext/issues/960)) - We updated the `yarn.lock` file for the jupyter lab extension to address security vulnerabilities ([#1030](https://github.com/mwouts/jupytext/issues/1030), [#1036](https://github.com/mwouts/jupytext/issues/1036)) - In the pre-commit tests we now use `main` for the main branch 1.14.4 (2022-12-11) ------------------- **Added** - Added Wolfram Language as a supported language ([#1014](https://github.com/mwouts/jupytext/issues/1014)) - thanks to [Etienne Dechamps](https://github.com/dechamps) for this contribution 1.14.3 (2022-12-11) ------------------- **Fixed** - When the default contents manager is _async_ (i.e. `jupyter_server>=2.0.0`), the Jupyter server extension for Jupytext derives a contents manager from `LargeFileManager` instead, as async contents managers are not supported by Jupytext at the moment ([#1020](https://github.com/mwouts/jupytext/issues/1020)) - We have made adjustments on the CI as flake8 was moved to GitHub, and Python 3.6 is not available anymore on `ubuntu-latest` 1.14.2 (2022-11-12) ------------------- **Fixed** - The sample notebooks have been normalized with `nbformat.validator.normalize` ([#1002](https://github.com/mwouts/jupytext/issues/1002)). - The warnings in the test suite that we cannot fix are filtered using a new `pytest.ini` file - We updated the `yarn.lock` file for the jupyter lab extension to address security vulnerabilities ([#984](https://github.com/mwouts/jupytext/issues/984), [#1005](https://github.com/mwouts/jupytext/issues/1005), [#1011](https://github.com/mwouts/jupytext/issues/1011)) **Changed** - The CI uses Python 3.9 rather than 3.7 when testing conda environments **Added** - Gnuplot is now supported ([#998](https://github.com/mwouts/jupytext/issues/998)) - thanks to [razimantv](https://github.com/razimantv) for this contribution - We now test Jupytext against Python 3.6 to 3.11 on the CI - We have added a test to document how to use the folder and prefix matching when pairing notebooks ([#974](https://github.com/mwouts/jupytext/issues/974)) 1.14.1 (2022-07-29) ------------------- **Fixed** - The timestamp of a paired notebook is the timestamp of the most recent paired file. This fixes the warning "File Changed" after reloading the notebook in Jupyter ([#978](https://github.com/mwouts/jupytext/issues/978)). 1.14.0 (2022-07-03) ------------------- **Changed** - The Jupytext configuration file has a new option `cm_config_log_level` that defaults to `info_if_changed`. With that value, the contents manager will log a line regarding the configuration file used only when the config file is not the same as the one previously used ([#959](https://github.com/mwouts/jupytext/issues/959)) - many thanks to R.C. Thomas for suggesting this and thoughtfully testing the patch. - Hidden configuration files like `.jupytext.toml` or `.jupytext.py` are now ignored by Jupytext's contents manager when `allow_hidden=False` (that option was introduced in `jupyter_server==2.0.0a1`) ([#964](https://github.com/mwouts/jupytext/issues/964)). - We have changed `jupytext --set-formats` to make it more similar to `jupytext --sync`. Now `--set-formats` will not override existing paired files anymore ([#969](https://github.com/mwouts/jupytext/issues/969)). **Added** - We have added a test `test_pre_commit_hook_sync_with_no_config` that documents how to use the pre-commit hook without a configuration file ([#967](https://github.com/mwouts/jupytext/issues/967)) 1.13.8 (2022-04-04) ------------------- **Fixed** - Text-only notebooks are always trusted (as they don't include any output cells) ([#941](https://github.com/mwouts/jupytext/issues/941)) - We made sure that our tests also work in absence of a Python kernel ([#906](https://github.com/mwouts/jupytext/issues/906)) - The coverage of the `tests` folder has been restored at 100% - Bash commands like `!{cmd}` are now correctly escaped in the `py:percent` format ([#938](https://github.com/mwouts/jupytext/issues/938)) **Added** - Added Tcl as a supported language ([#930](https://github.com/mwouts/jupytext/issues/930)) - thanks to [shishitao](https://github.com/shishitao) for this contribution - Added Maxima as a supported language ([#927](https://github.com/mwouts/jupytext/issues/927)) - thanks to [Alberto Lusiani](https://github.com/alusiani) for contributing a sample Maxima notebook. **Changed** - The Jupytext contents manager is derived from the `LargeFileManager` imported from `jupyter_server` rather than `notebook` ([#933](https://github.com/mwouts/jupytext/issues/933)) - Allow for markdown-it-py v2 ([#924](https://github.com/mwouts/jupytext/issues/924)) - We have updated the hooks used in the test pre-commits, to fix an issue on the CI ([#940](https://github.com/mwouts/jupytext/issues/940), [#942](https://github.com/mwouts/jupytext/issues/942)) - We updated the `yarn.lock` file for the jupyter lab extension to address security vulnerabilities ([#904](https://github.com/mwouts/jupytext/issues/904), [#925](https://github.com/mwouts/jupytext/issues/925), [#935](https://github.com/mwouts/jupytext/issues/935), [#939](https://github.com/mwouts/jupytext/issues/939)) 1.13.7 (2022-02-09) ------------------- **Fixed** - The Jupytext CLI only suggest `--update` when the target is an .ipynb file ([#905](https://github.com/mwouts/jupytext/issues/905)) - thanks to [st--](https://github.com/st--) for this contribution - We made sure that commands like `cat notebook.md | jupytext --execute` work ([#908](https://github.com/mwouts/jupytext/issues/908)) **Added** - Added Haskell as supported language ([#909](https://github.com/mwouts/jupytext/issues/909)) - thanks to [codeweber](https://github.com/codeweber) for this contribution **Changed** - We have updated the pre-commit hooks and in particular we switched to the first stable version of `black==22.1.0`. - We require `pandoc==2.16.2` for testing. The representation for code cells changed from ` ``` {.python}` to ` ``` python` in that version of Pandoc ([#906](https://github.com/mwouts/jupytext/issues/906)). We don't use `pandoc>=2.17` in tests at the moment because of the introduction of cell ids that cannot be filtered. - Jupytext will not add anymore a UTF-8 encoding on Python scripts when the notebook contains non-ascii characters ([#907](https://github.com/mwouts/jupytext/issues/907)) - We have added `pyupgrade` to the pre-commit hooks used for developing Jupytext ([#907](https://github.com/mwouts/jupytext/issues/907)) 1.13.6 (2022-01-11) ------------------- **Fixed** - The `text_representation` metadata of text notebooks is filtered from `.ipynb` files both in `jupytext.write` and in the contents manager for Jupyter ([#900](https://github.com/mwouts/jupytext/issues/900)) **Changed** - Jupytext will not issue a warning when a format suffix starting with '.', '-' or '_' is passed to the `--to` option ([#901](https://github.com/mwouts/jupytext/issues/901)) 1.13.5 (2021-12-27) ------------------- **Fixed** - Jupytext will not open a text notebook that is not UTF-8 ([#896](https://github.com/mwouts/jupytext/issues/896)) 1.13.4 (2021-12-12) ------------------- **Changed** - The test suite filters the warnings that don't belong to Jupytext ([#823](https://github.com/mwouts/jupytext/issues/823)) **Fixed** - The parsing of notebooks that don't have a YAML header (like `docs/formats.md`) was improved. - The test suite works with `pytest-randomly` ([#838](https://github.com/mwouts/jupytext/issues/838)) 1.13.3 (2021-12-04) ------------------- **Changed** - The "Jupytext Notebook" factory that lets the user configure the Notebook viewer as the default for text notebooks accepts more filetypes: "myst", "r-markdown" and "quarto" ([#803](https://github.com/mwouts/jupytext/issues/803)) - Empty MyST Markdown files are valid notebooks ([#883](https://github.com/mwouts/jupytext/issues/883)) - Jupytext also works with `markdown-it-py` v2.0 ([#885](https://github.com/mwouts/jupytext/issues/885)) 1.13.2 (2021-11-30) ------------------- **Changed** - The extension for JupyterLab benefited from a series of improvements contributed by [Frédéric Collonval](https://github.com/fcollonval): - A new "Jupytext Notebook" factory offers the option to open text notebooks directly with the notebook view ([#803](https://github.com/mwouts/jupytext/issues/803)). To use it, follow the instructions in the [documentation](https://github.com/mwouts/jupytext/blob/main/docs/index.md#Install). - The ICommandPalette is optional, for compatibility with RISE within JupyterLab [RISE[#605](https://github.com/mwouts/jupytext/issues/605)](https://github.com/damianavila/RISE/pull/605) - Added support for translation - Branch `master` was renamed to `main` (links in the documentation were updated) 1.13.1 (2021-10-07) ------------------- **Fixed** - The magic commands in `py:percent` scripts with no explicit format information remain commented over a round trip ([#848](https://github.com/mwouts/jupytext/issues/848)) 1.13.0 (2021-09-25) ------------------- **Added** - The Jupytext CLI has a new `--diff` command to show the differences between two notebooks (and if you want to see the changes in a file being updated by Jupytext, use `--show-changes`) ([#799](https://github.com/mwouts/jupytext/issues/799)) - Jupyter will show the diff between text and `ipynb` paired notebooks when it cannot open a paired notebook because the `ipynb` version is more recent. Also, if the inputs in the two files are identical then the notebook will open with no error ([#799](https://github.com/mwouts/jupytext/issues/799)) - The `py:percent` format will use raw strings when encoding Markdown cells as string, if they contain backslash characters ([#836](https://github.com/mwouts/jupytext/issues/836)) **Fixed** - We have upgraded the jupyterlab extension dependencies and especially `ansi-regex` to fix a security vulnerability ([#857](https://github.com/mwouts/jupytext/issues/857)) **Changed** - The Jupytext configuration file is reloaded only when a notebook is opened, saved, or when a different folder is explored ([#797](https://github.com/mwouts/jupytext/issues/797)) 1.12.0 (2021-09-09) ------------------- **Added** - Jupytext supports Quarto notebooks (with `.qmd` extension) ([#837](https://github.com/mwouts/jupytext/issues/837)) - Jupytext can be configured through the `pyproject.toml` file. Thanks to Robin Brown for this contribution! ([#828](https://github.com/mwouts/jupytext/issues/828)) - Jupytext now supports OCaml files with `.ml` extension. Thanks to Quentin Fortier for getting this started ([#832](https://github.com/mwouts/jupytext/issues/832)) **Fixed** - Added more test to make sure that notebooks can be trusted. In practice, notebooks could not be trusted in JupyterLab<3.0.13 because of the absence of cell ids ([#826](https://github.com/mwouts/jupytext/issues/826)) 1.11.5 (2021-08-31) ------------------- **Fixed** - Fixed typos revealed by `codespell` - thanks to @hectormz for this contribution ([#829](https://github.com/mwouts/jupytext/issues/829)) - We updated the dependencies of the `jupyterlab-jupytext` extension to address several security issues ([#842](https://github.com/mwouts/jupytext/issues/842)) ([#843](https://github.com/mwouts/jupytext/issues/843)) - The Jupytext dev environment (`requirements-dev.txt`) now uses `jupyterlab==3.0.17` rather than `3.0.0` because of another security issue ([#839](https://github.com/mwouts/jupytext/issues/839)) 1.11.4 (2021-07-14) ------------------- **Changed** - The documentation illustrates how the `cell_markers` option (and the other ones) can be set directly in the `jupytext.toml` config file ([#809](https://github.com/mwouts/jupytext/issues/809)). - The dependency on `mdit-py-plugins` through `markdown-it-py[plugins]` was made explicit ([#814](https://github.com/mwouts/jupytext/issues/814)) **Fixed** - System assigns of the form `var = !cmd` are commented out ([#816](https://github.com/mwouts/jupytext/issues/816)) - Fixed an `InconsistentPath` issue with notebooks paired with scripts in a folder. The prefix in the Jupytext formats always use /, while paths might use either / or \ ([#806](https://github.com/mwouts/jupytext/issues/806)) - Tests that cannot succeed are skipped when either the Jupytext folder is not a git repository, when `sphinx-gallery` is too recent, or when `pandoc` is not up-to-date ([#814](https://github.com/mwouts/jupytext/issues/814)) - Removed the mention of '--update' in 'jupytext --pipe' since outputs are preserved already 1.11.3 (2021-06-10) ------------------- **Changed** - Jupytext CLI has a new option `--use-source-timestamp` that sets the last modification time of the output file equal to that of the source file (this avoids having to change the timestamp of the source file) ([#784](https://github.com/mwouts/jupytext/issues/784)) - In the pre-commit mode, Jupytext now uses the commit timestamp to determine which file in the pair is the most recent ([#780](https://github.com/mwouts/jupytext/issues/780)) **Fixed** - Dependencies of the JupyterLab extension have been upgraded to fix a security vulnerability ([#798](https://github.com/mwouts/jupytext/pull/798)) - The `--warn-only` option also applies to pipes. Use this if the pipe may fail, e.g. if you apply `black` on a possibly invalid script ([#781](https://github.com/mwouts/jupytext/issues/781)) - Variables assigned from a magic command are commented out in `py` scripts ([#781](https://github.com/mwouts/jupytext/issues/781)) - Fixed a round-trip issue on notebooks that have None/null in their metadata ([#792](https://github.com/mwouts/jupytext/issues/792)) 1.11.2 (2021-05-02) ------------------- **Changed** - Jupytext's dependency markdown-it-py is now in v1 ([#769](https://github.com/mwouts/jupytext/issues/769)) - The optional argument `fmt` in `jupytext.reads` now has the default value `None` - thanks to Yuvi Panda ([#763](https://github.com/mwouts/jupytext/issues/763)) **Fixed** - All text files are opened with an explicit `utf-8` encoding ([#770](https://github.com/mwouts/jupytext/issues/770)) - Previously `--pipe black` was not always putting two blank lines between functions. To fix that we load the internal Jupytext cell metadata like `lines_to_next_cell` from the text file rather than ipynb ([#761](https://github.com/mwouts/jupytext/issues/761)) - The timestamp of the source file is not updated any more when the destination file is not in the pair ([#765](https://github.com/mwouts/jupytext/issues/765), [#767](https://github.com/mwouts/jupytext/issues/767)) **Added** - A new test documents when the `ipython3` pygment lexer appears in MyST Markdown files ([#759](https://github.com/mwouts/jupytext/issues/759)) 1.11.1 (2021-03-26) ------------------- **Fixed** - Format options stored in the notebook itself are now taken into account (Fixes [#757](https://github.com/mwouts/jupytext/issues/757)) 1.11.0 (2021-03-18) ------------------- **Fixed** - The `jupytext.toml` config file can now be used together with the `jupytext` pre-commit hook ([#752](https://github.com/mwouts/jupytext/issues/752)) - The `notebook_extensions` option of the `jupytext.toml` file now works ([#746](https://github.com/mwouts/jupytext/issues/746)) **Changed** - The options in `jupytext.toml` where renamed to match the `jupytext` metadata in the text notebooks. One should now use `formats` rather than `default_jupytext_formats` and `notebook_metadata_filter` rather than `default_notebook_metadata_filter` ([#753](https://github.com/mwouts/jupytext/issues/753)) 1.10.3 (2021-03-07) ------------------- **Fixed** - We have updated `marked`, an indirect dependency of the `jupyterlab-jupytext` extension, to fix a moderate vulnerability ([#750](https://github.com/mwouts/jupytext/issues/750)). - We use non-random cell ids in the tests to avoid test failures due to duplicate cell ids ([#747](https://github.com/mwouts/jupytext/issues/747)) 1.10.2 (2021-02-17) ------------------- **Fixed** - We have adjusted the `MANIFEST.in` file to exclude the `node_modules` but still include the JupyterLab extension that was missing in the `.tar.gz` (and conda) package in v1.10.1. Many thanks to Martin Renou for providing the fix at ([#741](https://github.com/mwouts/jupytext/issues/741)) 1.10.1 (2021-02-11) ------------------- **Added** - The recursive glob pattern `**/*.ipynb` is now supported by Jupytext - Thanks to Banst for this contribution ([#731](https://github.com/mwouts/jupytext/issues/731)) - Sage notebooks are supported. They can be converted to `.sage` and `.md` files and back. Thanks to Lars Franke for suggesting this! ([#727](https://github.com/mwouts/jupytext/issues/727)) - Jupytext is also accessible with `python -m jupytext`. Thanks to Matthew Brett for his PR! ([#739](https://github.com/mwouts/jupytext/issues/739)) **Changed** - We have tested Jupytext with the new cell ids introduced in `nbformat>=5.1.0`. Cell ids are preserved by the `--sync` and `--update` command. So we removed the constraint on the version of `nbformat` ([#735](https://github.com/mwouts/jupytext/issues/735)). **Fixed** - We filtered out the `node_modules` folder from the `.tar.gz` package for Jupytext ([#730](https://github.com/mwouts/jupytext/issues/730)) 1.10.0 (2021-02-04) ------------------- **Added** - Jupytext has a pre-commit hook! Many thanks to John Paton and Aaron Gokaslan for making this happen ([#698](https://github.com/mwouts/jupytext/issues/698)) - Jupytext CLI will not rewrite files that don't change ([#698](https://github.com/mwouts/jupytext/issues/698)). - If you want to see the diff for changed files, use the new `--diff` option ([#722](https://github.com/mwouts/jupytext/issues/722)) - We have added `isort` and `autoflake8` to the `pre-commit` configuration file used for developing the Jupytext project ([#709](https://github.com/mwouts/jupytext/issues/709)) - We made sure that `py:percent` scripts end with exactly one blank line ([#682](https://github.com/mwouts/jupytext/issues/682)) - We checked that Jupytext works well with symbolic links to folders (not files!) ([#696](https://github.com/mwouts/jupytext/issues/696)) **Changed** - Jupytext does not work properly with the new cell ids of the version 4.5 of `nbformat>=5.1.0` yet, so we added the requirement `nbformat<=5.0.8` ([#715](https://github.com/mwouts/jupytext/issues/715)) - Jupytext will issue an informative error or warning on notebooks in a version of nbformat that is not known to be supported ([#681](https://github.com/mwouts/jupytext/issues/681), [#715](https://github.com/mwouts/jupytext/issues/715)) **Fixed** - Code cells that contain triple backticks (or more) are now encapsulated with four backticks (or more) in the Markdown and MyST Markdown formats. The version number for the Markdown format was increased to 1.3, and the version number for the MyST Markdown format was increased to 0.13 ([#712](https://github.com/mwouts/jupytext/issues/712)) - Indented magic commands are supported ([#694](https://github.com/mwouts/jupytext/issues/694)) 1.9.1 (2021-01-06) ------------------ **Fixed** - Include the lab extension that was missing in the conda package ([#703](https://github.com/mwouts/jupytext/pull/703)). 1.9.0 (2021-01-05) ------------------ **Changed** - The Jupytext extension for JupyterLab is compatible with JupyterLab 3.0, thanks to Martin Renou's awesome contribution ([#683](https://github.com/mwouts/jupytext/pull/683)). 1.8.2 (2021-01-04) ------------------ **Changed** - Jupytext 1.8.2 depends on `python>=3.6`. The last version of Jupytext explicitly tested with Python 2.7 and 3.5 was Jupytext 1.7.1 ([#697](https://github.com/mwouts/jupytext/issues/697)). 1.8.1 (2021-01-03) ------------------ **Changed** - The dependency on `markdown-it-py` is conditional on `python>=3.6` ([#697](https://github.com/mwouts/jupytext/issues/697)) 1.8.0 (2020-12-22) ------------------ **Changed** - Removed support for Python 2.7 and 3.5, a preliminary step towards a JupyterLab 3.0-compatible extension ([#683](https://github.com/mwouts/jupytext/issues/683)) - The MyST Markdown format uses `markdown-it-py~=0.6.0` ([#692](https://github.com/mwouts/jupytext/issues/692)) 1.7.1 (2020-11-16) ------------------ **Fixed** - Text notebooks have the same format and mimetype as ipynb notebooks. This fixes the _File Load Error - content.indexOf is not a function_ error on text notebooks ([#659](https://github.com/mwouts/jupytext/issues/659)) 1.7.0 (2020-11-14) ------------------ **Changed** - Jupytext's contents manager uses the parent CM's `get` and `save` methods to read and save text files, and explicitly calls `jupytext.reads` and `jupytext.writes` to do the conversion. We don't use `mock` nor internal parent methods any more. Thanks to Max Klein for helping making this work! ([#634](https://github.com/mwouts/jupytext/issues/634), [#635](https://github.com/mwouts/jupytext/issues/635)) - Thanks to the above, Jupytext can work on top of contents manager that don't derive from `FileContentsManager`, and in particular it works with `jupyterfs` ([#618](https://github.com/mwouts/jupytext/issues/618)) - The documentation was reorganized. `README.md` was simplified and now includes many links to the documentation. - The documentation now uses `myst_parser` rather than `recommonmark`. And we use `conda` on RTD ([#650](https://github.com/mwouts/jupytext/issues/650), [#652](https://github.com/mwouts/jupytext/issues/652)) - The `readf` and `writef` functions were dropped (they had been deprecated in favor of `read` and `write` in June 2019, v1.2.0) - The description & dependencies of the JupyterLab extension were updated ([#654](https://github.com/mwouts/jupytext/issues/654)) - The `--set-kernel -` command, on a Python notebook, gives an explicit error when no kernel is not found that matches the current Python executable. - All the GitHub workflow files were concatenated into a unique file, and we have added an `pypi-publish` step to automatically publish the package on PyPi when new releases are created. - The `CHANGELOG.md` file was moved under `docs` to better expose the history of changes. **Added** - Configuration errors are reported in the console and/or in Jupyter ([#613](https://github.com/mwouts/jupytext/issues/613)) - Jupytext's Contents Manager internal errors are logged on the console, and trigger an HTTP Error 500 ([#638](https://github.com/mwouts/jupytext/issues/638)) - The GitHub actions run on both push events and pull requests, and duplicate jobs are skipped ([#605](https://github.com/mwouts/jupytext/issues/605)) - Jupytext has a `tox.ini` file, thanks to Chris Sewell ([#605](https://github.com/mwouts/jupytext/issues/605)) - Jupytext is tested against Python 3.9 - The `execution` cell metadata is now filtered by default ([#656](https://github.com/mwouts/jupytext/issues/656)) **Fixed** - Optional dependency on `sphinx-gallery` frozen to version `~=0.7.0` ([#614](https://github.com/mwouts/jupytext/issues/614)) - Codecov/patch reports should be OK now ([#639](https://github.com/mwouts/jupytext/issues/639)) - Jupytext tests work on non-English locales ([#636](https://github.com/mwouts/jupytext/issues/636)) - Cell metadata that are already present in text notebook can be filtered out using a config file ([#656](https://github.com/mwouts/jupytext/issues/656)) - Optional cell attributes like attachments are preserved ([#671](https://github.com/mwouts/jupytext/issues/671)) 1.6.0 (2020-09-01) ------------------ **Added** - New option `hide_notebook_metadata` to encapsulate the notebook metadata in an HTML comment ([#527](https://github.com/mwouts/jupytext/issues/527)) - New option `root_level_metadata_as_raw_cell`. Set it to `False` if you don't want to see root level metadata of R Markdown notebooks as a raw cell in Jupyter ([#415](https://github.com/mwouts/jupytext/issues/415)) - New option `doxygen_equation_markers` to translate Markdown equations into Doxygen equations ([#517](https://github.com/mwouts/jupytext/issues/517)) - New option `custom_cell_magics` to comment out cells starting with user-specific cell magics ([#513](https://github.com/mwouts/jupytext/issues/513)) - Documented how to use `isort` on notebooks ([#553](https://github.com/mwouts/jupytext/issues/553)) - `jupytext notebook.ipynb --to filename.py` will warn that `--to` is used in place of `--output`. - `jupytext --set-formats filename.py` will suggest to use `--sync` instead of `--set-formats` ([#544](https://github.com/mwouts/jupytext/issues/544)) - Warn if 'Include Metadata' is off when saving text files in Jupyter ([#561](https://github.com/mwouts/jupytext/issues/561)) - Test that notebooks paired through a configuration file are left unmodified ([#598](https://github.com/mwouts/jupytext/issues/598)) - Test that metadata filters in the configuration files are taken into account when using `jupytext --to` ([#543](https://github.com/mwouts/jupytext/issues/543)) - New argument `--run-path` to execute the notebooks at the desired location ([#595](https://github.com/mwouts/jupytext/issues/595)) - Activated GitHub code scanning alerts **Changed** - Jupytext now depends on `markdown-it-py` (Python 3.6 and above) and always features the MyST-Markdown format, thanks to Chris Sewell ([#591](https://github.com/mwouts/jupytext/issues/591)) - The `md:myst` and `md:pandoc` are always included in the Jupytext formats, and an informative runtime error will occur if the required dependencies, resp. `markdown-it-py` and `pandoc`, are not installed. ([#556](https://github.com/mwouts/jupytext/issues/556)) - The `# %%` cell marker has the same indentation as the first line in the cell ([#562](https://github.com/mwouts/jupytext/issues/562)) - Jupytext is now installed from source on MyBinder to avoid cache issues ([#567](https://github.com/mwouts/jupytext/issues/567)) - The tests that execute a notebook are now skipped on Windows to avoid timeout issues ([#489](https://github.com/mwouts/jupytext/issues/489)) **Fixed** - Only scripts can have an encoding comment, not Markdown or R Markdown files ([#576](https://github.com/mwouts/jupytext/issues/576)) - Spaces in `--pipe` commands are supported ([#562](https://github.com/mwouts/jupytext/issues/562)) - Bash commands starting with special characters are now correctly detected, thanks to Aaron Gokaslan ([#587](https://github.com/mwouts/jupytext/issues/587)) - MyST Markdown files are recognized as such even if MyST-Markdown is not available ([#556](https://github.com/mwouts/jupytext/issues/556)) - Build JupyterLab with `dev-build=False` and `minimize=False` on mybinder to avoid build errors - Configured coverage targets in `codecov.yml` 1.5.2 (2020-07-21) ------------------ **Changed** - The documentation uses the Alabaster theme **Fixed** - Preserve indentation when commenting out magic commands ([#437](https://github.com/mwouts/jupytext/issues/437)) - Fixed MyBinder - `jupytext.py` is not a configuration file ([#559](https://github.com/mwouts/jupytext/issues/559), [#567](https://github.com/mwouts/jupytext/issues/567)) 1.5.1 (2020-07-05) ------------------ **Fixed** - Added `toml` as a dependency ([#552](https://github.com/mwouts/jupytext/issues/552)). - Filtered out `__pycache__` and `.pyc` files from the pip package. - Fixed coverage upload by adding `coverage` as a dependency to the conda CI workflow. - Fixed the conda CI / Python 2.7 job by explicitly installing `backports.functools_lru_cache` ([#554](https://github.com/mwouts/jupytext/issues/554)). 1.5.0 (2020-06-07) ------------------ **Added** - Jupytext can use a local or global [configuration file](https://github.com/mwouts/jupytext/blob/main/docs/config.md) ([#508](https://github.com/mwouts/jupytext/issues/508)) - Jupytext can pair notebooks in trees. Use e.g. `notebooks///ipynb,scripts///py:percent` if you want to replicate the tree of notebooks under `notebooks` in a folder named `scripts` ([#424](https://github.com/mwouts/jupytext/issues/424)) - The extension for Jupyter Notebook has a _New Text Notebook_ menu that creates text-only notebooks ([#443](https://github.com/mwouts/jupytext/issues/443)) - Groovy and Java are now supported, thanks to Przemek Wesołek ([#500](https://github.com/mwouts/jupytext/issues/500)) - The Coconut language is also supported, thanks to Thurston Sexton ([#532](https://github.com/mwouts/jupytext/issues/532)) - Resource files with `.resource` extension from the Robot Framework are supported, thanks to Hiski Valli ([#535](https://github.com/mwouts/jupytext/issues/535)) - Jupytext is tested in `pip` and `conda` environments, on Linux, Mac OS and Windows, using Github actions ([#487](https://github.com/mwouts/jupytext/issues/487)) - Jupytext uses pre-commit checks and automatic reformatting with `pre-commit`, `black` and `flake8` ([#483](https://github.com/mwouts/jupytext/issues/483)) - Documentation improvements: - Mention that the YAML header can be created with either `--set-kernel`, `--set-formats`, or both ([#485](https://github.com/mwouts/jupytext/issues/485)) - Mention that one should use double quotes, not single quotes, around `jupytext --check` commands like `"pytest {}"` on Windows ([#475](https://github.com/mwouts/jupytext/issues/475)) - Improved error message when a file is in a version that can't be read by Jupytext ([#531](https://github.com/mwouts/jupytext/issues/531)) **Fixed** - Skip the `jupytext --execute` tests when the warning _Timeout waiting for IOPub output_ occurs, which is the case intermittently on Windows ([#489](https://github.com/mwouts/jupytext/issues/489)) - Fixed wrong paired paths when syncing with the --pre-commit flag ([#506](https://github.com/mwouts/jupytext/issues/506)) 1.4.2 (2020-04-05) ------------------ **Added** - Added an example with custom notebook metadata ([#469](https://github.com/mwouts/jupytext/issues/469)) - Added an example with custom cell tags ([#478](https://github.com/mwouts/jupytext/issues/478)) **Changed** - The outputs from the `.ipynb` file are matched with the input cells from the text file with less strict rules. In this version, a search and replace on the text file will not remove the outputs any more ([#464](https://github.com/mwouts/jupytext/issues/464)). - Update parsing of myst notebooks to new (markdown-it based) parser (please upgrade to `myst-parser` to version `~0.8`) ([#473](https://github.com/mwouts/jupytext/issues/473)) - Use `os.path.samefile` when searching for the kernel that corresponds to the current environment (`--set-kernel -`) **Fixed** - Fixed the CLI example for not commenting out magic commands: `--opt comment_magics=false`. In addition, most of the `jupytext` commands in `using-cli.md` are now tested! ([#465](https://github.com/mwouts/jupytext/issues/465)) - `jupytext.read` and `jupytext.write` now give more meaningful errors when the format information is incorrect ([#462](https://github.com/mwouts/jupytext/issues/462)) - Multiline comments starting or ending with quadruple quotes should not cause issues anymore ([#460](https://github.com/mwouts/jupytext/issues/460)) - Fixed active cells in the py:percent format ([#477](https://github.com/mwouts/jupytext/issues/477)) 1.4.1 (2020-03-19) ------------------ **Added** - Script of script (SoS) notebooks are now supported. Thanks to Thomas Pernet-coudrier for contributing the sample notebook ([#453](https://github.com/mwouts/jupytext/issues/453)). - New MyST Markdown format (`md:myst`), developed by the [ExecutableBookProject](https://github.com/ExecutableBookProject) team. Read more about the MyST Markdown format in the [documentation](https://jupytext.readthedocs.io/en/latest/formats.html#myst-markdown). And many thanks to Chris Sewell for contributing the actual implementation! ([#447](https://github.com/mwouts/jupytext/issues/447) [#456](https://github.com/mwouts/jupytext/issues/456) [#458](https://github.com/mwouts/jupytext/issues/458)) **Fixed** - When using `jupytext --pipe cmd`, the output of `cmd` should not appear in the terminal ([#432](https://github.com/mwouts/jupytext/issues/432)) 1.4.0 (2020-03-09) ------------------ **Changed** - The new jupyterlab extension (in version 1.2.0) is compatible with JupyterLab 2.0. Many thanks to Jean Helie! ([#449](https://github.com/mwouts/jupytext/issues/449)) - It is not compatible with JupyterLab 1.x anymore. If you wish, you can install manually the previous version of the extension with `jupyter labextension install jupyterlab-jupytext@1.1.1`. **Fixed** - Display the output/errors of command executed with `jupytext --pipe` or `jupytext --check` ([#432](https://github.com/mwouts/jupytext/issues/432)) 1.3.5 (2020-03-08) ------------------ **Fixed** - Removed leading slash in notebook paths ([#444](https://github.com/mwouts/jupytext/issues/444)) - Fixed `jupytext --set-formats` when using formats with prefix and/or suffix ([#450](https://github.com/mwouts/jupytext/issues/450)) 1.3.4 (2020-02-18) ------------------ **Added** - C# and F# Jupyter notebooks are now supported ([#427](https://github.com/mwouts/jupytext/issues/427), [#429](https://github.com/mwouts/jupytext/issues/429)) **Fixed** - `jupytext --to script *.ipynb` now computes the script extension for each notebook ([#428](https://github.com/mwouts/jupytext/issues/428)) - Fix shebang handling for languages with non-# comments, by Jonas Bushart ([#434](https://github.com/mwouts/jupytext/issues/434)) - Indented bash commands are now commented out ([#437](https://github.com/mwouts/jupytext/issues/437)) - The main formats are documented in `jupytext --help` ([#426](https://github.com/mwouts/jupytext/issues/426), [#433](https://github.com/mwouts/jupytext/issues/433)) 1.3.3 (2020-01-27) ------------------ **Added** - Jupytext has a logo! Many thanks to Kyle Kelley for contributing the actual logo ([#423](https://github.com/mwouts/jupytext/issues/423)), and to Chris Holdgraf for suggesting this ([#260](https://github.com/mwouts/jupytext/issues/260)). - Nested metadata filtering is now supported! You can use this to rid of `jupytext_version` if you wish ([#416](https://github.com/mwouts/jupytext/issues/416)). **Fixed** - Code cells in the Markdown format can contain triple backticks inside multiline strings ([#419](https://github.com/mwouts/jupytext/issues/419)). - Changes in the YAML header when running `jupytext --test` on text files are ignored ([#414](https://github.com/mwouts/jupytext/issues/414)). 1.3.2 (2020-01-08) ------------------ **Fixed** - The `--pre-commit` mode now ignores non-notebook files in the index ([#338](https://github.com/mwouts/jupytext/issues/338)). - `nbformat_minor` is taken from the notebook with outputs When inputs and outputs are merged. 1.3.1 (2019-12-26) ------------------ **Added** - New `nomarker` format in the Jupyter Notebook and JupyterLab extensions ([#397](https://github.com/mwouts/jupytext/issues/397)) **Changed** - The `normarker` format replaces the one previously named `bare`. **Fixed** - Multiline strings are now accepted in the YAML header ([#404](https://github.com/mwouts/jupytext/issues/404)). Fix contributed by ZHUO Qiang ([#405](https://github.com/mwouts/jupytext/issues/405)). - Fixed the instructions on how to use multiline comments for all Markdown cells in the py:percent format, by ZHUO Qiang ([#403](https://github.com/mwouts/jupytext/issues/403)). - Added `cd` to the list of magic commands. - Do not read paired files when `--set-formats` is being used (fixes [#399](https://github.com/mwouts/jupytext/issues/399)). 1.3.0 (2019-11-23) ------------------ See also [What's new in Jupytext 1.3?](https://gist.github.com/mwouts/724efe5e00654fc2145a4c916796e071) **Added** - Pairing a notebook to both `.md` and `.py` is now supported. Input cells are loaded from the most recent text representation ([#290](https://github.com/mwouts/jupytext/issues/290)) - Both the Jupyter Notebook and the JupyterLab extension for Jupytext were updated ([#290](https://github.com/mwouts/jupytext/issues/290)) - Raw cells are now encoded using HTML comments (`` and ``) in Markdown files ([#321](https://github.com/mwouts/jupytext/issues/321)) - Markdown cells can be delimited with any of ``, `` or `` ([#344](https://github.com/mwouts/jupytext/issues/344)) - Code blocks from Markdown files, when they don't have an explicit language, appear in Markdown cells in Jupyter ([#321](https://github.com/mwouts/jupytext/issues/321)) - Code blocks with an explicit language and a `.noeval` attribute are inactive in Jupyter ([#347](https://github.com/mwouts/jupytext/issues/347)) - Markdown and raw cells can be quoted with triple quotes in the `py:percent` format. And Markdown cells can start with just `# %% [md]` ([#305](https://github.com/mwouts/jupytext/issues/305)) - The light format uses `# + [markdown]` rather than the previous `cell_type` metadata to identify markdown cells with metadata ([#356](https://github.com/mwouts/jupytext/issues/356)) - Explicit Markdown cells in the light format `# + [markdown]` can use triple quotes ([#356](https://github.com/mwouts/jupytext/issues/356)) - IPython magic help commands like `float?` are classified as magics, and thus commented in Python scripts ([#297](https://github.com/mwouts/jupytext/issues/297)) - Cell metadata can be encoded as either `key=value` (the new default) or in JSON. An automatic option `cell_metadata_json` should help minimize the impact on existing files ([#344](https://github.com/mwouts/jupytext/issues/344)) - R Markdown hidden inputs, outputs, or cells are now mapped to the corresponding Jupyter Book tags by default ([#337](https://github.com/mwouts/jupytext/issues/337)) - The notebook metadata filter is automatically updated when extra keys are added to the YAML header ([#376](https://github.com/mwouts/jupytext/issues/376)) - The Jupyter Notebook extension for Jupytext is compatible with Jupyter Notebook 6.0 ([#346](https://github.com/mwouts/jupytext/issues/346)) - `jupytext notebook.py --to ipynb` updates the timestamp of `notebook.py` so that the paired notebook still works in Jupyter ([#335](https://github.com/mwouts/jupytext/issues/335), [#254](https://github.com/mwouts/jupytext/issues/254)) - `jupytext --check pytest notebook.ipynb` can be used to run test functions in a notebook ([#286](https://github.com/mwouts/jupytext/issues/286)) - `jupytext --check` and `jupytext --pipe` can run commands that only operate on files: when `{}` is found in the text of the command, `jupytext` saves the text representation of the notebook in a temp file, and replaces `{}` with the name of that file before executing the command. ([#286](https://github.com/mwouts/jupytext/issues/286)) - Documented how to sync notebooks in a pre-commit hook ([#338](https://github.com/mwouts/jupytext/issues/338)) - Added support for Rust/Evxcr, by Jonas Bushart ([#351](https://github.com/mwouts/jupytext/issues/351)) - Added support for [Robot Framework](https://robots-from-jupyter.github.io/), by Asko Soukka ([#378](https://github.com/mwouts/jupytext/issues/378)) - Added support for PowerShell ([#349](https://github.com/mwouts/jupytext/issues/349)) **Changed** - Use `CHANGELOG.md` rather than `HISTORY.rst` **Fixed** - Commands like `cat = x` are not magic commands, so they are not commented any more ([#339](https://github.com/mwouts/jupytext/issues/339)) - Fixed an inconsistent round trip (code cell with `"cat"` being converted to a markdown cell) in the `py:light` format ([#339](https://github.com/mwouts/jupytext/issues/339)) - `jupytext --test textfile.ext` now really compares the text file to its round trip (rather than the corresponding notebook) ([#339](https://github.com/mwouts/jupytext/issues/339)) - Markdown cells that contain code are now preserved in a round trip through the Markdown and R Markdown formats ([#361](https://github.com/mwouts/jupytext/issues/361)) - Code cells with a `%%python3` cell magic are now preserved in a round trip through the Markdown format ([#365](https://github.com/mwouts/jupytext/issues/365)) - `jupytext --execute` runs the notebook in its folder ([#382](https://github.com/mwouts/jupytext/issues/382)) - Strings in the metadata of code cells are quoted in the Rmd representation. And we escape R code in chunk options with `#R_CODE#` ([#383](https://github.com/mwouts/jupytext/issues/383)) 1.2.4 (2019-09-19) ------------------ **Added** - The documentation includes a mention on how to set metadata filters at the command line ([#330](https://github.com/mwouts/jupytext/issues/330)) - Jupytext will not catch any error when the flag `--warn-only` is not set ([#327](https://github.com/mwouts/jupytext/issues/327)) **Fixed** - Now the flag `--warn-only` catches every possible error ([#263](https://github.com/mwouts/jupytext/issues/263)) - `.md` and `.markdown` files are treated identically ([#325](https://github.com/mwouts/jupytext/issues/325)) - Fixed `--set-kernel` when using pipes ([#326](https://github.com/mwouts/jupytext/issues/326)) - Fixed utf-8 encoding on stdout on Python 2 ([#331](https://github.com/mwouts/jupytext/issues/331)) 1.2.3 (2019-09-02) ------------------ **Fixed** - Dependency on `setuptools` in `pandoc.py` made optional to fix the build of the conda package ([#310](https://github.com/mwouts/jupytext/issues/310), [#323](https://github.com/mwouts/jupytext/issues/323)) 1.2.2 (2019-09-01) ------------------ **Added** - Documentation includes a section on how to use Jupytext as a Python library ([#317](https://github.com/mwouts/jupytext/issues/317)) - Mention of the server extension in the documentation ([#304](https://github.com/mwouts/jupytext/issues/304)) - Text notebooks can be tested with `jupytext --execute notebook.md` ([#303](https://github.com/mwouts/jupytext/issues/303)) - The default value of `as_version` in `jupytext.read` is `nbformat.NO_CONVERT`, as for `nbformat.read` - Jupytext tests are now included in sdist ([#310](https://github.com/mwouts/jupytext/issues/310)) **Fixed** - Fixed the usability of the `fmt` argument in `jupytext.read` ([#312](https://github.com/mwouts/jupytext/issues/312)) - Fixed the download notebook error when `c.notebook_extensions` has a custom value ([#318](https://github.com/mwouts/jupytext/issues/318)) - String delimiters in commented text are now ignored ([#307](https://github.com/mwouts/jupytext/issues/307)) 1.2.1 (2019-07-20) ------------------ **Added** - Added documentation on how to use Jupytext with JupyterLab 0.35 ([#299](https://github.com/mwouts/jupytext/issues/299)) - and on using Jupytext with the pre-commit package manager ([#292](https://github.com/mwouts/jupytext/issues/292)) - The `read` and `write` functions are easier to use ([#292](https://github.com/mwouts/jupytext/issues/292)) **Fixed** - Jupytext now ships the `jupyterlab-jupytext` extension in version 1.0.2. The version 1.0.1 erroneously introduces a `target_formats` metadata in the jupytext section, instead of `formats`, and works only after two clicks. 1.2.0 (2019-07-18) ------------------ **Added** - New `--execute` option in Jupytext CLI ([#231](https://github.com/mwouts/jupytext/issues/231)) - The `--set-formats` option in Jupytext CLI also triggers `--sync`, allowing shorter commands. - `jupytext`'s `read` and `write` functions can be used as drop-in replacements for `nbformat`'s ones ([#262](https://github.com/mwouts/jupytext/issues/262)). - `jupytext --sync` will now skip unpaired notebooks ([#281](https://github.com/mwouts/jupytext/issues/281)). - The JupyterLab extension was updated. It now works on text files ([#213](https://github.com/mwouts/jupytext/issues/213)) and has a new option to include (or not) the metadata in the text representation of the notebook. - Jupytext's contents manager class is derived dynamically from the default CM class for compatibility with `jupyter_server` ([#270](https://github.com/mwouts/jupytext/issues/270)) - Removed dependency on `mock` and `testfixtures`, thanks to Jean-Sebastien Dieu ([#279](https://github.com/mwouts/jupytext/issues/279)) - Added support for `.markdown` extension ([#288](https://github.com/mwouts/jupytext/issues/288)) **Fixed** - The `jupyterlab-jupytext` extension shipped with the python package is in version 1.0.1, and is compatible only with JupyterLab >= 1.0. If you use an earlier version of JupyterLab, please install the version 0.19 of the extension with `jupyter labextension install jupyterlab-jupytext@0.19` ([#276](https://github.com/mwouts/jupytext/issues/276), [#278](https://github.com/mwouts/jupytext/issues/278)) - Text files can be unpaired ([#289](https://github.com/mwouts/jupytext/issues/289)) 1.1.7 (2019-06-23) ------------------ **Added** - Added support for Scala notebook, by Tobias Frischholz ([#253](https://github.com/mwouts/jupytext/issues/253)) - Added a getting started notebook for jupytext (and Binder), by Chris Holdgraf ([#257](https://github.com/mwouts/jupytext/issues/257)) - The Markdown and R Markdown representations are now tested for all the languages - The Jupytext notebook extension also works when the notebook is a text file ([#213](https://github.com/mwouts/jupytext/issues/213)) **Fixed** - The Jupytext Menu in Jupyter Notebook is now compatible with `jupyter_nbextensions_configurator` ([#178](https://github.com/mwouts/jupytext/issues/178)) - Entries in the Jupytext menu are updated when the menu is hovered on ([#248](https://github.com/mwouts/jupytext/issues/248)) - Fixed link to `.md` files in the documentation ([#255](https://github.com/mwouts/jupytext/issues/255)) 1.1.6 (2019-06-11) ------------------ **Added** - Jupytext now supports Javascript and Typescript, thanks to Hatem Hosny ([#250](https://github.com/mwouts/jupytext/issues/250)) - Jupytext works with Python 3.8 as well **Fixed** - Fix global `auto` pairing ([#249](https://github.com/mwouts/jupytext/issues/249)) 1.1.5 (2019-06-06) ------------------ **Fixed** - Fixed implicit dependency on `jupyter_client` ([#245](https://github.com/mwouts/jupytext/issues/245)) 1.1.4 (2019-06-05) ------------------ **Added** - New argument `--set-kernel` in Jupytext command line ([#230](https://github.com/mwouts/jupytext/issues/230)) - Jupytext now accepts `--to script` or `--to auto` ([#240](https://github.com/mwouts/jupytext/issues/240)) - Jupytext now has a real Sphinx documentation on [readthedocs](https://jupytext.readthedocs.io/en/latest), thanks to Chris Holdgraf ([#237](https://github.com/mwouts/jupytext/issues/237)) **Fixed** - Invalid notebooks may cause a warning, but not a fatal error ([#234](https://github.com/mwouts/jupytext/issues/234)) - Jupyter server extension leaves the contents manager unchanged if it is a sub-class of Jupytext's CM ([#236](https://github.com/mwouts/jupytext/issues/236)) - Fixed format inference when metadata is present but not format information ([#239](https://github.com/mwouts/jupytext/issues/239)) - Preserve executable and encoding information in scripts with metadata ([#241](https://github.com/mwouts/jupytext/issues/241)) 1.1.3 (2019-05-22) ------------------ **Added** - Support for IDL notebooks and .pro scripts ([#232](https://github.com/mwouts/jupytext/issues/232)) 1.1.2 (2019-05-16) ------------------ **Added** - Jupytext's content manager has a new `notebook_extensions` option ([#224](https://github.com/mwouts/jupytext/issues/224), [#183](https://github.com/mwouts/jupytext/issues/183)) - Cells can be made inactive in scripts with the `active-ipynb` cell tag ([#226](https://github.com/mwouts/jupytext/issues/226)) **Fixed** - Directories ending in .jl (or .ipynb) are not notebooks ([#228](https://github.com/mwouts/jupytext/issues/228)) - Empty notebooks have no language ([#227](https://github.com/mwouts/jupytext/issues/227)) 1.1.1 (2019-04-16) ------------------ **Added** - Jupytext server extension leaves the contents manager unchanged when it is already a subclass of TextFileContentsManager ([#218](https://github.com/mwouts/jupytext/issues/218)) - The base class for TextFileContentsManager defaults to FileContentsManager when LargeFileManager is not available ([#217](https://github.com/mwouts/jupytext/issues/217)) 1.1.0 (2019-04-14) ------------------ **Added** - Markdown and R Markdown formats now support metadata ([#66](https://github.com/mwouts/jupytext/issues/66), [#111](https://github.com/mwouts/jupytext/issues/111), [#188](https://github.com/mwouts/jupytext/issues/188)) - The `light` format for Scripts can use custom cell markers, e.g. Vim or VScode/PyCharm folding markers ([#199](https://github.com/mwouts/jupytext/issues/199)) - Pandoc's Markdown format for Jupyter notebooks is available in Jupytext as `md:pandoc` ([#208](https://github.com/mwouts/jupytext/issues/208)) **Fixed** - Jupytext's contents manager is now based on `LargeFileManager` to allow large file uploads ([#210](https://github.com/mwouts/jupytext/issues/210)) - YAML header parsed with yaml.safe_load rather than yaml.load ([#215](https://github.com/mwouts/jupytext/issues/215)) - IPython line magic can be split across lines ([#209](https://github.com/mwouts/jupytext/issues/209)) - `jupytext --to py` rather than `--to python` in the README ([#216](https://github.com/mwouts/jupytext/issues/216)) 1.0.5 (2019-03-26) ------------------ **Fixed** - Fix the error 'notebook file has changed on disk' when saving large notebooks ([#207](https://github.com/mwouts/jupytext/issues/207)) 1.0.4 (2019-03-20) ------------------ **Added** - Wildcard are now supported on Windows ([#202](https://github.com/mwouts/jupytext/issues/202)) - Trusted notebooks remain trusted when inputs cells are modified ([#203](https://github.com/mwouts/jupytext/issues/203)) **Fixed** - Pre-commit mode adds the result of conversion to the commit ([#200](https://github.com/mwouts/jupytext/issues/200)) 1.0.3 (2019-03-13) ------------------ **Added** - Matlab and Octave notebooks and scripts are now supported ([#197](https://github.com/mwouts/jupytext/issues/197)) **Fixed** - `notebook_metadata_filter = "all"` now works ([#196](https://github.com/mwouts/jupytext/issues/196)) - Default pairing in subfolders fixed in JupyterLab ([#180](https://github.com/mwouts/jupytext/issues/180)) 1.0.2 (2019-02-27) ------------------ **Added** - Rename notebooks in pairs in the tree view ([#190](https://github.com/mwouts/jupytext/issues/190)) - Associate `.scm` file extension with Scheme scripts ([#192](https://github.com/mwouts/jupytext/issues/192)) - Added support for Clojure, by bzinberg ([#193](https://github.com/mwouts/jupytext/issues/193)) **Fixed** - Allow spaces between `?` or `!` and python or bash command ([#189](https://github.com/mwouts/jupytext/issues/189)) 1.0.1 (2019-02-23) ------------------ **Fixed** - Exclude tests in package deployment ([#184](https://github.com/mwouts/jupytext/issues/184)) - Jupytext's serverextension only runs selected init steps ([#185](https://github.com/mwouts/jupytext/issues/185)) - Added an additional test for magic arguments ([#111](https://github.com/mwouts/jupytext/issues/111)) 1.0.0 (2019-02-19) ------------------ **Added** - Jupytext now includes a Jupyter Notebook extension and a JupyterLab extension ([#86](https://github.com/mwouts/jupytext/issues/86)). - Jupytext command line has more arguments: `--paired-paths` to list the paths for the paired representations of the notebook, and `--sync` to synchronise the content of all paired paths based on the most recent file ([#146](https://github.com/mwouts/jupytext/issues/146)). In addition, the `--from` argument is optional even when the notebook is read from stdin ([#148](https://github.com/mwouts/jupytext/issues/148)). - The pairing information, and more generally the notebook metadata can be edited with the CLL, see the `--set-formats` and the `--update-metadata` arguments ([#141](https://github.com/mwouts/jupytext/issues/141)). - Jupytext can `--pipe` the text representation of a notebook to external programs like `black` or `flake8` ([#154](https://github.com/mwouts/jupytext/issues/154), [#142](https://github.com/mwouts/jupytext/issues/142)) - The Python representation of notebooks containing PEP8 cells is now expected to be PEP8 compliant ([#154](https://github.com/mwouts/jupytext/issues/154)). - Format specification allow prefix and suffix for path and file name ([#138](https://github.com/mwouts/jupytext/issues/138), [#142](https://github.com/mwouts/jupytext/issues/142)). Use `ipynb,prefix/suffix.py:percent` to pair the current notebook named `notebook.ipynb` to a script named `prefixnotebooksuffix.py`. Suffix and prefix can also be configured on the `ipynb` file, with the same syntax. - Introducing a new `hydrogen` format for scripts, which derives from `percent`. In that format Jupyter magic commands are not commented ([#59](https://github.com/mwouts/jupytext/issues/59), [#126](https://github.com/mwouts/jupytext/issues/126), [#132](https://github.com/mwouts/jupytext/issues/132)). - Introducing a new `bare` format for scripts, which derives from `light`. That format has no cell marker. Use a notebook metadata filter `{"jupytext": {"notebook_metadata_filter":"-all"}}` if you want no YAML header ([#152](https://github.com/mwouts/jupytext/issues/152)). - The default format for R script is now `light`, as for the other languages. - Added support for q/kdb+ notebooks ([#161](https://github.com/mwouts/jupytext/issues/161)). - Python scripts or Markdown documents that have no Jupyter metadata receive a metadata filter that ensures that metadata is not exported back to the text representation ([#124](https://github.com/mwouts/jupytext/issues/124)). - Metadata filters are represented as strings rather than dictionaries to make YAML headers shorter. Previous syntax from [#105](https://github.com/mwouts/jupytext/issues/105) is still supported. They were also renamed to `notebook_metadata_filter` and `cell_metadata_filter`. - Markdown and RMarkdown formats have a new option `split_at_heading` to split Markdown cells at heading ([#130](https://github.com/mwouts/jupytext/issues/130)) **Fixed** - Main language of scripts is inferred from script extension. Fixes a round trip conversion issue for Python notebooks with a Javascript cell. - Non-Python scripts opened as notebooks in Jupyter are now correctly saved even when no matching kernel is found. - Jupyter magic commands like `ls` are commented in the light and R markdown format ([#149](https://github.com/mwouts/jupytext/issues/149)). - Cell starting with `%%html`, `%%latex` are now commented out in the `light`, `percent` and `Rmd` formats ([#179](https://github.com/mwouts/jupytext/issues/179)). 0.8.6 (2018-11-29) ------------------ **Added** - The `language_info` section is not part of the default header any more. Language information is now taken from metadata `kernelspec.language`. ([#105](https://github.com/mwouts/jupytext/issues/105)). - When opening a paired notebook, the active file is now the file that was originally opened ([#118](https://github.com/mwouts/jupytext/issues/118)). When saving a notebook, timestamps of all the alternative representations are tested to ensure that Jupyter's autosave does not override manual modifications. - Jupyter magic commands are now commented per default in the `percent` format ([#126](https://github.com/mwouts/jupytext/issues/126), [#132](https://github.com/mwouts/jupytext/issues/132)). Version for the `percent` format increases from '1.1' to '1.2'. Set an option `comment_magics` to `false` either per notebook, or globally on Jupytext's contents manager, or on `jupytext`'s command line, if you prefer not to comment Jupyter magics. - Jupytext command line has a pre-commit mode ([#121](https://github.com/mwouts/jupytext/issues/121)). 0.8.5 (2018-11-13) ------------------ **Added** - `bash` scripts as notebooks ([#127](https://github.com/mwouts/jupytext/issues/127)) - R scripts with `.r` extension are supported ([#122](https://github.com/mwouts/jupytext/issues/122)) - Jupytext selects the first kernel that matches the language ([#120](https://github.com/mwouts/jupytext/issues/120)) 0.8.4 (2018-10-29) ------------------ **Added** - Notebook metadata is filtered - only the most common metadata are stored in the text representation ([#105](https://github.com/mwouts/jupytext/issues/105)) - New config option `freeze_metadata` on the content manager and on the command line interface (defaults to `False`). Use this option to avoid creating a YAML header or cell metadata if there was none initially. ([#110](https://github.com/mwouts/jupytext/issues/110)) - Language magic arguments are preserved in R Markdown, and also supported in `light` and `percent` scripts ([#111](https://github.com/mwouts/jupytext/issues/111), [#114](https://github.com/mwouts/jupytext/issues/114), [#115](https://github.com/mwouts/jupytext/issues/115)) - First markdown cell exported as a docstring when using the Sphinx format ([#107](https://github.com/mwouts/jupytext/issues/107)) 0.8.3 (2018-10-19) ------------------ **Added** - Frozen cells are supported in R Markdown, light and percent scripts ([#101](https://github.com/mwouts/jupytext/issues/101)) - Inactive cells extended to percent scripts ([#108](https://github.com/mwouts/jupytext/issues/108)) - `jupytext` gains a `--version` argument ([#103](https://github.com/mwouts/jupytext/issues/103)) - "ExecuteTime" cell metadata is not included in the text representation anymore ([#106](https://github.com/mwouts/jupytext/issues/106)) 0.8.2 (2018-10-15) ------------------ **Added** - Round trip conversion testing with `jupytext --test` was improved ([#99](https://github.com/mwouts/jupytext/issues/99)) - Round trip conversion tested on Jake Vanderplas' Python for Data Science Handbook. **Fixed** - Nested lists and dictionaries are now supported in notebook metadata - Final empty code cell supported in Sphinx representation 0.8.1 (2018-10-11) ------------------ **Fixed** - Sphinx format tested on `World population` notebook ([#97](https://github.com/mwouts/jupytext/issues/97)) - Mirror test made stronger on this occasion! - Markdown representation recognize Julia, Scheme and C++ code cells as such - Light representation of Scheme and C++ notebooks fixed ([#61](https://github.com/mwouts/jupytext/issues/61)) 0.8.0 (2018-10-10) ------------------ **Added** - All `jupytext` related metadata goes to a `jupytext` section ([#91](https://github.com/mwouts/jupytext/issues/91)). Please make sure your collaborators use the same version of Jupytext, as the new version can read previous metadata, but not the opposite. - Notebooks extensions can be prefixed with any prefix of at most three chars ([#87](https://github.com/mwouts/jupytext/issues/87)). - Export of the same notebook to multiple formats is now supported. To export to all python formats, plus `.ipynb` and `.md`, use `"jupytext": {"formats": "ipynb,pct.py:percent,lgt.py:light,spx.py:sphinx,md"},`. - README includes a short section on how to extend `light` and `percent` formats to more languages ([#61](https://github.com/mwouts/jupytext/issues/61)). - Jupytext's contents manager accepts the `auto` extension in `default_jupytext_formats` ([#93](https://github.com/mwouts/jupytext/issues/93)). - All Jupyter magics are escaped in `light` scripts and R markdown documents. Escape magics in other formats with a `comment_magics` metadata (true or false), or with the contents manager `comment_magics` global flag ([#94](https://github.com/mwouts/jupytext/issues/94)). **Fixed** - Trusting notebooks made functional again. - Command line `jupytext` returns a meaningful error when no argument is given. - Fixed global pairing configuration ([#95](https://github.com/mwouts/jupytext/issues/95)). 0.7.2 (2018-10-01) ------------------ **Added** - `light` and `percent` formats made available for scheme and cpp notebooks. Adding more formats is straightforward - just add a new entry to _SCRIPT_EXTENSIONS in languages.py, a sample notebook and a mirror test ([#61](https://github.com/mwouts/jupytext/issues/61)) - Format name is automatically appended to extension in `jupytext_formats` when notebook is loaded/saved. **Fixed** - Notebooks extensions can only be prefixed with `.nb` ([#87](https://github.com/mwouts/jupytext/issues/87)) 0.7.1 (2018-09-24) ------------------ **Fixed** - Markdown cells header in sphinx gallery format may have a space between first # and following. 0.7.0 (2018-09-23) ------------------ **Added** - Header for cells in `percent` format is more robust: use `[markdown]` and `[raw]` to identify cell types. Cell type comes after the cell title. ([#59](https://github.com/mwouts/jupytext/issues/59)) - Jupytext can read and write notebooks as Hydrogen/VScode/Spyder/PyCharm compatible scripts (cells starting with `# %%`) ([#59](https://github.com/mwouts/jupytext/issues/59)) - Jupytext can read and write notebooks as Sphinx-gallery compatible scripts ([#80](https://github.com/mwouts/jupytext/issues/80)) - Metadata are supported for all cell types in light python and percent formats ([#66](https://github.com/mwouts/jupytext/issues/66)). Due to this, light python format version is now 1.3. Light python notebooks in versions 1.1 and 1.2 are still readable. - Command line `jupytext` has a `from` argument, and now accepts notebook from the standard input. **Fixed** - Fix merging of input and output notebooks ([#83](https://github.com/mwouts/jupytext/issues/83)) - Removed extra new line on stdout in command line `jupytext` ([#84](https://github.com/mwouts/jupytext/issues/84)) 0.6.5 (2018-09-13) ------------------ **Added** - Code lines that start with a quotation mark in Jupyter are commented in the corresponding Python and Julia scripts ([#73](https://github.com/mwouts/jupytext/issues/73)) - Update pypy, add flake8 tests on Travis CI ([#74](https://github.com/mwouts/jupytext/issues/74)) **Fixed** - Import notebook.transutils before notebook.services.contents.filemanager ([#75](https://github.com/mwouts/jupytext/issues/75)) 0.6.4 (2018-09-12) ------------------ **Added** - Jupytext will not load paired notebook when text representation is out of date ([#63](https://github.com/mwouts/jupytext/issues/63)) - Package tested against Python 3.7 ([#68](https://github.com/mwouts/jupytext/issues/68)) **Fixed** - Allow unicode characters in notebook path ([#70](https://github.com/mwouts/jupytext/issues/70)) - Read README.md as unicode in `setup.py` ([#71](https://github.com/mwouts/jupytext/issues/71)) 0.6.3 (2018-09-07) ------------------ **Added** - Lighter cell markers for Python and Julia scripts ([#57](https://github.com/mwouts/jupytext/issues/57)). Corresponding file format version at 1.2. Scripts in previous version 1.1 can still be opened. - New screenshots for the README. **Fixed** - Command line conversion tool `jupytext` fixed on Python 2.7 ([#46](https://github.com/mwouts/jupytext/issues/46)) 0.6.2 (2018-09-05) ------------------ **Added** - Initial support for Jupyter notebooks as Julia scripts ([#56](https://github.com/mwouts/jupytext/issues/56)) - Command line conversion tool `jupytext` has explicit `to` and `output` options ([#46](https://github.com/mwouts/jupytext/issues/46)) - Round trip test with `jupytext --test` improved ([#54](https://github.com/mwouts/jupytext/issues/54)) - Improved README ([#51](https://github.com/mwouts/jupytext/issues/51)) **Fixed** - testfixtures now in requirements ([#55](https://github.com/mwouts/jupytext/issues/55)) - Empty code cells are now preserved ([#53](https://github.com/mwouts/jupytext/issues/53)) 0.6.1 (2018-08-31) ------------------ **Added** - Package and conversion script renamed from `nbrmd` to `jupytext`. 0.6.0 (2018-08-31) ------------------ **Added** - Cell parsing and exporting done in two specialized classes. This is way easier to read. Pylint score at 9.9 ! - Python file format updated to 1.1: default end of cell for python scripts is one blank space. Two blank spaces are allowed as well. Now you can reformat code in Python IDE without breaking notebook cells ([#38](https://github.com/mwouts/jupytext/issues/38)). - Added support for plain markdown files ([#40](https://github.com/mwouts/jupytext/issues/40), [#44](https://github.com/mwouts/jupytext/issues/44)). - Demonstration notebooks more user friendly ([#45](https://github.com/mwouts/jupytext/issues/45)). - Command line tool simpler to use ([#46](https://github.com/mwouts/jupytext/issues/46)). - Start code patterns present in Jupyter cells are escaped. - Default `nbrmd_format` is empty (mwouts/nbsrc/[#5](https://github.com/mwouts/jupytext/issues/5)): no Jupyter notebook is created on disk when the user opens a Python or R file and saves it from Jupyter, unless the users asks for it by setting `nbrmd_format`. **Fixed** - Fixed message in the `nbsrc` script ([#43](https://github.com/mwouts/jupytext/issues/43)) - Technical metadata don't appear any more in scripts unless required ([#42](https://github.com/mwouts/jupytext/issues/42)) - Code cells that are fully commented remain code cells after round trip ([#41](https://github.com/mwouts/jupytext/issues/41)) 0.5.4 (2018-08-24) ------------------ **Added** - R to Rmd conversion compares well to knitr::spin ([#26](https://github.com/mwouts/jupytext/issues/26)) - Increased coverage to 98% 0.5.3 (2018-08-22) ------------------ **Fixed** - Read and write version to the same metadata ([#36](https://github.com/mwouts/jupytext/issues/36)) 0.5.2 (2018-08-22) ------------------ **Added** - Classical jupyter extensions (autoreload, rmagics) are also escaped ([#35](https://github.com/mwouts/jupytext/issues/35)) - Explicit file format version, set at 1.0, to avoid overriding ipynb files by accident ([#36](https://github.com/mwouts/jupytext/issues/36)) 0.5.1 (2018-08-21) ------------------ **Fixed** - Source only notebooks can be trusted. 0.5.0 (2018-08-21) ------------------ **Added** - Jupyter magic commands escaped when exported ([#29](https://github.com/mwouts/jupytext/issues/29)) - 'endofcell' option for explicit (optional) end-of-cell marker ([#31](https://github.com/mwouts/jupytext/issues/31)) - 'active' cell option now supported for .py and .R export ([#30](https://github.com/mwouts/jupytext/issues/30)) - Raw cells now preserved when exported to .py or .R ([#32](https://github.com/mwouts/jupytext/issues/32)) - Extensions can be prefixed, like `.nb.py`, (mwouts/nbsrc[#5](https://github.com/mwouts/jupytext/issues/5)) - When a file with an extension not associated to 'ipynb' is opened and saved, no 'ipynb' file is created (mwouts/nbsrc[#5](https://github.com/mwouts/jupytext/issues/5)) - Extensions can now be a sequence of groups. For instance, `nbrmd_formats="ipynb,nb.py;script.ipynb,py"` will create an `ipynb` file when a `nb.py` is opened (and conversely), and a `script.ipynb` file when a `py` file is opened (mwouts/nbsrc[#5](https://github.com/mwouts/jupytext/issues/5)) - `nbsrc` script was moved to the `nbrmd` package. The `nbsrc` package now only contains the documentation (mwouts/nbsrc[#3](https://github.com/mwouts/jupytext/issues/3)) 0.4.6 (2018-07-26) ------------------ - Ping pypi - previous version still not available 0.4.5 (2018-07-26) ------------------ **Fixed** - Removed dependency of `setup.py` on `yaml` 0.4.4 (2018-07-26) ------------------- **Fixed** - Package republished with `python setup.py sdist bdist_wheel` to fix missing dependencies 0.4.3 (2018-07-26) ------------------ **Added** - Multiline comments now supported [#25](https://github.com/mwouts/jupytext/issues/25) - Readme refactored, notebook demos available on binder [#23](https://github.com/mwouts/jupytext/issues/23) **Fixed** - ContentsManager can be imported even if `notebook.transutils` is not available, for compatibility with older python distributions. - Fixed missing cell metadata [#27](https://github.com/mwouts/jupytext/issues/27) - Documentation tells how to avoid creating `.ipynb` files [#16](https://github.com/mwouts/jupytext/issues/16) 0.4.2 (2018-07-23) ------------------ **Added** - Added test for R notebooks - Added pylint badge, imports now in correct order - New `active` cell metadata that allows cell activation only for desired extensions (currently available for Rmd and ipynb extensions only) 0.4.1 (2018-07-20) ------------------ **Fixed** - Indented python code will not start a new cell [#20](https://github.com/mwouts/jupytext/issues/20) - Fixed parsing of Rmd cell metadata [#21](https://github.com/mwouts/jupytext/issues/21) 0.4.0 (2018-07-18) ------------------ **Added** - `.py` format for notebooks is lighter and pep8 compliant **Fixed** - Default nbrmd config not added to notebooks ([#17](https://github.com/mwouts/jupytext/issues/17)) - `nbrmd_formats` becomes a configurable traits ([#16](https://github.com/mwouts/jupytext/issues/16)) - Removed `nbrmd_sourceonly_format` metadata. Source notebook is current notebook when not `.ipynb`, otherwise the first notebook format in `nbrmd_formats` (not `.ipynb`) that is found on disk 0.3.0 (2018-07-17) ------------------ **Added** - Introducing support for notebooks as python `.py` or R scripts `.R` 0.2.6 (2018-07-13) ------------------ **Added** - Introduced `nbrmd_sourceonly_format` metadata - Inputs are loaded from `.Rmd` file when a matching `.ipynb` file is opened. **Fixed** - Trusted notebooks remain trusted ([#12](https://github.com/mwouts/jupytext/issues/12)) 0.2.5 (2018-07-11) ------------------ **Added** - Outputs of existing `.ipynb` versions are combined with matching inputs of R markdown version, as suggested by @grst ([#12](https://github.com/mwouts/jupytext/issues/12)) **Fixed** - Support for unicode text in python 2.7 ([#11](https://github.com/mwouts/jupytext/issues/11)) 0.2.4 (2018-07-05) ------------------ **Added** - nbrmd will always open notebooks, even if header of code cells are not terminated. Merge conflicts can thus be solved in Jupyter directly. - New metadata 'main language' that preserves the notebook language. **Fixed** - dependencies included in `setup.py` - pre_save_hook work with non-empty `notebook_dir` ([#9](https://github.com/mwouts/jupytext/issues/9)) 0.2.3 (2018-06-28) ------------------ **Added** - Screenshots in README **Fixed** - RMarkdown exporter for nbconvert fixed on non-recent python - Tests compatible with other revisions of nbformat >= 4.0 - Tests compatible with older pytest versions 0.2.2 (2018-06-28) ------------------- **Added** - RMarkdown exporter for nbconvert - Parsing of R options robust to parenthesis - Jupyter cell tags are preserved **Fixed** - requirements.txt now included in pypi packages 0.2.1 (2018-06-24) ------------------ **Added** - Support for editing markdown files in Jupyter - New pre-save hook `update_selected_formats` that saves to formats in metadata 'nbrmd_formats' - Rmd cell options directly mapped to cell metadata **Fixed** - ContentManager compatible with Python 2.7 0.2.0 (2018-06-21) ------------------ **Added** - The package provides a `RmdFileContentsManager` for direct edit of R markdown files in Jupyter - Notebook metadata and cell options are preserved 0.1.1 (2018-06-19) ------------------ **Added** - `nbrmd` prints the result of conversion to stdout, unless flag `-i` is provided - Notebooks with R code chunks are supported 0.1 (2018-06-18) ---------------- - Initial version with the `nbrmd` converter and Jupyter `pre_save_hook` ================================================ FILE: LICENSE ================================================ MIT License Copyright (c) 2018-2026 Marc Wouts Permission is hereby granted, free of charge, to any person obtaining a copy of this software and associated documentation files (the "Software"), to deal in the Software without restriction, including without limitation the rights to use, copy, modify, merge, publish, distribute, sublicense, and/or sell copies of the Software, and to permit persons to whom the Software is furnished to do so, subject to the following conditions: The above copyright notice and this permission notice shall be included in all copies or substantial portions of the Software. THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE SOFTWARE. ================================================ FILE: README.md ================================================ ![](https://github.com/mwouts/jupytext/blob/17aea37c612f33a4e27eeee4b81966f1506920fd/docs/images/logo_large.png?raw=true) [![CI](https://github.com/mwouts/jupytext/actions/workflows/ci.yml/badge.svg?branch=main)](https://github.com/mwouts/jupytext/actions) [![Documentation Status](https://readthedocs.org/projects/jupytext/badge/?version=latest)](https://jupytext.readthedocs.io/en/latest/?badge=latest) [![codecov.io](https://codecov.io/github/mwouts/jupytext/coverage.svg?branch=main)](https://codecov.io/gh/mwouts/jupytext/branch/main) [![MIT License](https://img.shields.io/github/license/mwouts/jupytext)](https://github.com/mwouts/jupytext/blob/main/LICENSE) [![Code style: black](https://img.shields.io/badge/code%20style-black-000000.svg)](https://github.com/psf/black) [![GitHub language count](https://img.shields.io/github/languages/count/mwouts/jupytext)](docs/languages.md) [![Conda Version](https://anaconda.org/conda-forge/jupytext/badges/version.svg)](https://anaconda.org/conda-forge/jupytext/) [![Pypi](https://img.shields.io/pypi/v/jupytext.svg)](https://pypi.python.org/pypi/jupytext) [![pyversions](https://img.shields.io/pypi/pyversions/jupytext.svg)](https://pypi.python.org/pypi/jupytext) [![Binder:lab](https://img.shields.io/badge/binder-jupyterlab-0172B2.svg)](https://mybinder.org/v2/gh/mwouts/jupytext/main?urlpath=lab/tree/demo/get_started.ipynb) [![Binder:notebook](https://img.shields.io/badge/binder-notebook-0172B2.svg)](https://mybinder.org/v2/gh/mwouts/jupytext/main?filepath=demo) [![launch - renku](https://renkulab.io/renku-badge.svg)](https://renkulab.io/projects/best-practices/jupytext/sessions/new?autostart=1) [![Jupyter Con 2020](https://img.shields.io/badge/YouTube-JupyterCon%202020-red.svg)](https://www.youtube.com/watch?v=SDYdeVfMh48) # Jupytext Have you always wished Jupyter notebooks were plain text documents? Wished you could edit them in your favorite IDE? And get clear and meaningful diffs when doing version control? Then, Jupytext may well be the tool you're looking for! ## Text Notebooks A Python notebook encoded in the `py:percent` [format](docs/formats-scripts.md#the-percent-format) has a `.py` extension and looks like this: ``` # %% [markdown] # This is a markdown cell # %% def f(x): return 3*x+1 ``` Only the notebook inputs (and optionally, the metadata) are included. Text notebooks are well suited for version control. You can also edit or refactor them in an IDE - the `.py` notebook above is a regular Python file. We recommend the `percent` format for notebooks that mostly contain code. The `percent` format is available for Julia, Python, R and many other [languages](docs/languages.md). If your notebook is documentation-oriented, a [Markdown-based format](docs/formats-markdown.md) (text notebooks with a `.md` extension) might be more appropriate. Depending on what you plan to do with your notebook, you might prefer the Myst Markdown format, which interoperates very well with Jupyter Book, or Quarto Markdown, or even Pandoc Markdown. ## Installation Install Jupytext in the Python environment that you use for Jupyter. Use either pip install jupytext or conda install jupytext -c conda-forge Then, restart your JupyterLab server, and make sure Jupytext is activated in Jupyter: `.py` and `.md` files have a Notebook icon, and you can open them as Notebooks with a right click in JupyterLab. ![Notebook icon on text notebooks](https://github.com/mwouts/jupytext/blob/64b4be818508760116f91bf156342cb4cf724d93/docs/images/jupyterlab_right_click.png?raw=true) ## Paired Notebooks Text notebooks with a `.py` or `.md` extension are well suited for version control. They can be edited or authored conveniently in an IDE. You can open and run them as notebooks in JupyterLab with a right click. However, the notebook outputs are lost when the notebook is closed, as only the notebook inputs are saved in text notebooks. A convenient alternative to text notebooks are [paired notebooks](docs/paired-notebooks.md). These are a set of two files, say `.ipynb` and `.py`, that contain the same notebook, but in different formats. You can edit the `.py` version of the paired notebook, and get the edits back in Jupyter by selecting _reload notebook from disk_. The outputs will be reloaded from the `.ipynb` file, if it exists. The `.ipynb` version will be updated or recreated the next time you save the notebook in Jupyter. 💡 **Tip:** You can automate the notebook reloading by installing the [Jupyter Collaboration](docs/jupyter-collaboration.md) extension. To pair a notebook in JupyterLab, use the command `Pair Notebook with percent Script` from the Command Palette: ![](https://github.com/mwouts/jupytext/blob/64b4be818508760116f91bf156342cb4cf724d93/docs/images/pair_commands.png?raw=true) To pair all the notebooks in a certain directory, create a [configuration file](docs/config.md) with this content: ``` # jupytext.toml at the root of your notebook directory formats = "ipynb,py:percent" ``` ## Command line Jupytext is also available at the [command line](docs/using-cli.md). You can - pair a notebook with `jupytext --set-formats ipynb,py:percent notebook.ipynb` - synchronize the paired files with `jupytext --sync notebook.py` (the inputs are loaded from the most recent paired file) - convert a notebook in one format to another with `jupytext --to ipynb notebook.py` (use `-o` if you want a specific output file) - pipe a notebook to a linter with e.g. `jupytext --pipe black notebook.ipynb` ## Sample use cases ### Notebooks under version control This is a quick how-to: - Open your `.ipynb` notebook in Jupyter and [pair](docs/paired-notebooks.md) it to a `.py` notebook, using either the _pair_ command in JupyterLab, or a global [configuration file](docs/config.md) - Save the notebook - this creates a `.py` notebook - Add this `.py` notebook to version control You might exclude `.ipynb` files from version control (unless you want to see the outputs versioned!). Jupytext will recreate the `.ipynb` files locally when the users open and save the `.py` notebooks. ### Collaborating on notebooks with Git Collaborating on Jupyter notebooks through Git becomes as easy as collaborating on text files. Assume that you have your `.py` notebooks under version control (see above). Then, - Your collaborator pulls the `.py` notebook - They open it _as a notebook_ in Jupyter (right-click in JupyterLab) - At that stage the notebook has no outputs. They run the notebook and save it. Outputs are regenerated, and a local `.ipynb` file is created - They edit the notebook, and push the updated `notebook.py` file. The diff is nothing else than a standard diff on a Python script. - You pull the updated `notebook.py` script, and refresh your browser. The input cells are updated based on the new content of `notebook.py`. The outputs are reloaded from your local `.ipynb` file. Finally, the kernel variables are untouched, so you have the option to run only the modified cells to get the new outputs. ### Editing or refactoring a notebook in an IDE Once your notebook is [paired](docs/paired-notebooks.md) with a `.py` file, you can easily edit or refactor the `.py` representation of the notebook in an IDE. Once you are done editing the `.py` notebook, you will just have to _reload_ the notebook in Jupyter to get the latest edits there. Note: It is simpler to close the `.ipynb` notebook in Jupyter when you edit the paired `.py` file. There is no obligation to do so; however, if you don't, you should be prepared to read carefully the pop-up messages. If Jupyter tries to save the notebook while the paired `.py` file has also been edited on disk since the last reload, a conflict will be detected and you will be asked to decide which version of the notebook (in memory or on disk) is the appropriate one. Alternatively, the [Jupyter Collaboration](docs/jupyter-collaboration.md) extension provides an autoreload feature which simplifies this. ## More resources Read more about Jupytext in the [documentation](https://jupytext.readthedocs.io). If you're new to Jupytext, you may want to start with the [FAQ](docs/faq.md) or with the [Tutorials](docs/tutorials.md). There is also this short introduction to Jupytext: [![](https://img.shields.io/badge/YouTube-JupyterCon%202020-red.svg)](https://www.youtube.com/watch?v=SDYdeVfMh48). ================================================ FILE: binder/labconfig/default_setting_overrides.json ================================================ { "@jupyterlab/docmanager-extension:plugin": { "defaultViewers": { "markdown": "Jupytext Notebook", "myst": "Jupytext Notebook", "r-markdown": "Jupytext Notebook", "quarto": "Jupytext Notebook", "julia": "Jupytext Notebook", "python": "Jupytext Notebook", "r": "Jupytext Notebook" } } } ================================================ FILE: binder/postBuild ================================================ # Stop everything if one command fails set -e # Install from sources # NB: If you want to use Jupytext on your binder, don't install it from source, # just add "jupytext" to your "binder/requirements.txt" instead. HATCH_BUILD_HOOKS_ENABLE=true pip install . mkdir -p ${HOME}/.jupyter/labconfig cp binder/labconfig/* ${HOME}/.jupyter/labconfig # Create the notebook for our jupytext demo jupytext demo/get_started.md --to ipynb --update-metadata '{"jupytext":null}' # Remove the markdown representation # (the demo starts with just the ipynb file) rm demo/get_started.md # Trust our World Population notebook jupyter trust demo/World\ population.ipynb # Install the bash kernel python -m bash_kernel.install ================================================ FILE: binder/requirements.txt ================================================ jupyterlab>=4 notebook>=7 plotly matplotlib wordcloud pandas wbdata bash_kernel ================================================ FILE: demo/Benchmarking Jupytext.py ================================================ # In this notebook, we benchmark the Jupytext formats for Jupyter notebooks against the base format # Open this script as a notebook in Jupyter to run it and see the plots import time import copy import pandas as pd import plotly.graph_objects as go from plotly.colors import DEFAULT_PLOTLY_COLORS import nbformat import jupytext # The notebook to be tested notebook = jupytext.read('World population.ipynb') # Same notebook, with no outputs, for a fair comparison notebook_no_outputs = copy.deepcopy(notebook) for cell in notebook_no_outputs.cells: cell.outputs = [] cell.execution_count = None # + JUPYTEXT_FORMATS = ['ipynb', 'md', 'py:light', 'py:percent', 'py:sphinx'] # Let's see if we have pandoc here try: jupytext.writes(notebook, fmt='md:pandoc') JUPYTEXT_FORMATS.append('md:pandoc') except jupytext.formats.JupytextFormatError as err: print(str(err)) # Let's see if we have myst-parser installed here try: jupytext.writes(notebook, fmt='myst') JUPYTEXT_FORMATS.append('myst') except jupytext.formats.JupytextFormatError as err: print(str(err)) # - def sample_perf(nb, n=30): samples = pd.DataFrame( pd.np.NaN, index=pd.MultiIndex.from_product( (range(n), ['nbformat'] + JUPYTEXT_FORMATS), names=['sample', 'implementation']), columns=pd.Index(['size', 'read', 'write'], name='measure')) for i, fmt in samples.index: t0 = time.time() if fmt == 'nbformat': text = nbformat.writes(nb) else: text = jupytext.writes(nb, fmt) t1 = time.time() samples.loc[(i, fmt), 'write'] = t1 - t0 samples.loc[(i, fmt), 'size'] = len(text) t0 = time.time() if fmt == 'nbformat': nbformat.reads(text, as_version=4) else: jupytext.reads(text, fmt) t1 = time.time() samples.loc[(i, fmt), 'read'] = t1 - t0 return samples def performance_plot(perf, title): formats = ['nbformat'] + JUPYTEXT_FORMATS mean = perf.groupby('implementation').mean().loc[formats] std = perf.groupby('implementation').std().loc[formats] data = [go.Bar(x=mean.index, y=mean[col], error_y=dict( type='data', array=std[col], color=color, thickness=0.5 ) if col != 'size' else dict(), name=col, yaxis={'read': 'y1', 'write': 'y2', 'size': 'y3'}[col]) for col, color in zip(mean.columns, DEFAULT_PLOTLY_COLORS)] layout = go.Layout(title=title, xaxis=dict(title='Implementation', anchor='y3'), yaxis=dict(domain=[0.7, 1], title='Read (secs)'), yaxis2=dict(domain=[0.35, .65], title='Write (secs)'), yaxis3=dict(domain=[0, .3], title='Size') ) return go.Figure(data=data, layout=layout) perf_no_outputs = sample_perf(notebook_no_outputs, 30) performance_plot(perf_no_outputs, 'Benchmarking Jupytext on the World Population notebook
(Outputs filtered)') perf = sample_perf(notebook, 30) performance_plot(perf, 'Benchmarking Jupytext on the World Population notebook
(With outputs)') ================================================ FILE: demo/Jupytext's word cloud.py ================================================ # This is a notebook that I used to generate Jupytext's word cloud. # To open this script as a notebook in JupyterLab, right-click on this file, and select _Open with/Notebook_. from wordcloud import WordCloud text = """ Jupytext Notebook JupyterLab Git GitHub Version control Markdown R Markdown Text Scripts Code Notebook Template Binder Visual Studio Code PyCharm Atom Spyder Hydrogen RStudio Sphinx-Gallery Documentation black pytest autopep8 Metadata Reproducible research R Julia Python Bash Powershell Scala Scheme Clojure Matlab Octave C++ q/kdb+ IDL TypeScript Javascript Scala Rust Robot Framework """ wordcloud = WordCloud( random_state=1, background_color='white', width=1200, height=500 ).generate_from_frequencies({word: 1 for word in text.splitlines()}) wordcloud.to_image() wordcloud.to_file('../docs/jupytext_word_cloud.png') ================================================ FILE: demo/Tests in a notebook.md ================================================ # Testing a Jupyter notebook with pytest In this notebook we describe how to test a notebook with `jupytext`. ## Writing assertions and tests in a notebook Our notebook defines a function that we wish to test. Our function is simply ```python def f(x, n=5): return [x + i for i in range(n)] ``` We can test the assertion in Jupyter with simply ```python assert f(5) == [5,6,7,8,9] ``` Since the assertion above works, we don't get any message. It's more interesting to see what happens when an assertion fails. Remove one element of the list above and change the assertion to, say, assert f(5) == [5,6,8,9] When we run the above in Jupyter, we get ```stderr --------------------------------------------------------------------------- AssertionError Traceback (most recent call last) in ----> 1 assert f(5) == [5,6,8,9] AssertionError: ``` Now if we run the notebook with `jupytext --check pytest 'Tests in a notebook.md'`, we get a more detailed description of the issue, thanks to `pytest`'s rewriting of assertions: ```output [jupytext] Reading Tests in a notebook.md =========================== test session starts =========================== platform win32 -- Python 3.7.5, pytest-5.2.2, py-1.8.0, pluggy-0.13.0 rootdir: C:\Users\Marco collected 0 items / 1 errors ================================ ERRORS =================================== _________ ERROR collecting Tests in a notebook vhs_lscr.py ________________ Tests in a notebook vhs_lscr.py:19: in assert f(5) == [5,6,8,9] E assert [5, 6, 7, 8, 9] == [5, 6, 8, 9] E + where [5, 6, 7, 8, 9] = (5) !!!!!!!!!!!!! Interrupted: 1 errors during collection !!!!!!!!!!!!!!!!!!!!! =========================== 1 error in 0.09s ============================== ``` Once all of our assertions pass, we can move them to a test function. In Jupyter the function is not evaluated - only when we run `jupytext --check pytest` on the notebook, the function is actually executed. ```python def test_f(): assert f(5) == [5,6,7,8,9] ``` ## Going further - [nbval](https://github.com/computationalmodelling/nbval) is a plugin for `pytest` that allows you to make sure that Jupyter notebooks run properly, and that their new outputs match the current ones. Use it as `pytest --nbval notebook.ipynb`. - [ipytest](https://github.com/chmp/ipytest) defines a `%%run_pytest` cell magic that allows you to execute the tests in a cell directly in Jupyter. ================================================ FILE: demo/World population.Rmd ================================================ --- jupyter: jupytext: cell_markers: region,endregion formats: ipynb,.pct.py:percent,.lgt.py:light,.spx.py:sphinx,md,Rmd,.pandoc.md:pandoc text_representation: extension: .Rmd format_name: rmarkdown format_version: '1.1' jupytext_version: 1.1.0 kernelspec: display_name: Python 3 language: python name: python3 --- # A quick insight at world population ## Collecting population data In the below we retrieve population data from the [World Bank](http://www.worldbank.org/) using the [wbdata](https://github.com/OliverSherouse/wbdata) python package ```{python} import pandas as pd import wbdata as wb pd.options.display.max_rows = 6 pd.options.display.max_columns = 20 ``` Corresponding indicator is found using search method - or, directly, the World Bank site. ```{python} wb.search_indicators('Population, total') # SP.POP.TOTL # wb.search_indicators('area') # => https://data.worldbank.org/indicator is easier to use ``` Now we download the population data ```{python} indicators = {'SP.POP.TOTL': 'Population, total', 'AG.SRF.TOTL.K2': 'Surface area (sq. km)', 'AG.LND.TOTL.K2': 'Land area (sq. km)', 'AG.LND.ARBL.ZS': 'Arable land (% of land area)'} data = wb.get_dataframe(indicators, convert_date=True).sort_index() data ``` World is one of the countries ```{python} data.loc['World'] ``` Can we classify over continents? ```{python} data.loc[(slice(None), '2017-01-01'), :]['Population, total'].dropna( ).sort_values().tail(60).index.get_level_values('country') ``` Extract zones manually (in order of increasing population) ```{python} zones = ['North America', 'Middle East & North Africa', 'Latin America & Caribbean', 'Europe & Central Asia', 'Sub-Saharan Africa', 'South Asia', 'East Asia & Pacific'][::-1] ``` And extract population information (and check total is right) ```{python} population = data.loc[zones]['Population, total'].swaplevel().unstack() population = population[zones] assert all(data.loc['World']['Population, total'] == population.sum(axis=1)) ``` ## Stacked area plot with matplotlib ```{python} import matplotlib.pyplot as plt ``` ```{python} plt.clf() plt.figure(figsize=(10, 5), dpi=100) plt.stackplot(population.index, population.values.T / 1e9) plt.legend(population.columns, loc='upper left') plt.ylabel('Population count (B)') plt.show() ``` ## Stacked bar plot with plotly ```{python} import plotly.offline as offline import plotly.graph_objs as go offline.init_notebook_mode() ``` ```{python} data = [go.Scatter(x=population.index, y=population[zone], name=zone, stackgroup='World') for zone in zones] fig = go.Figure(data=data, layout=go.Layout(title='World population')) offline.iplot(fig) ``` ================================================ FILE: demo/World population.ipynb ================================================ { "cells": [ { "cell_type": "markdown", "metadata": {}, "source": [ "# A quick insight at world population\n", "\n", "## Collecting population data\n", "\n", "In the below we retrieve population data from the\n", "[World Bank](http://www.worldbank.org/)\n", "using the [wbdata](https://github.com/OliverSherouse/wbdata) python package" ] }, { "cell_type": "code", "execution_count": 1, "metadata": {}, "outputs": [], "source": [ "import pandas as pd\n", "import wbdata as wb\n", "\n", "pd.options.display.max_rows = 6\n", "pd.options.display.max_columns = 20" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Corresponding indicator is found using search method - or, directly,\n", "the World Bank site." ] }, { "cell_type": "code", "execution_count": 2, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "SP.POP.TOTL\tPopulation, total\n" ] } ], "source": [ "wb.search_indicators('Population, total') # SP.POP.TOTL\n", "# wb.search_indicators('area')\n", "# => https://data.worldbank.org/indicator is easier to use" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Now we download the population data" ] }, { "cell_type": "code", "execution_count": 3, "metadata": {}, "outputs": [ { "data": { "text/html": [ "
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" ], "text/plain": [ " Population, total Surface area (sq. km) \\\n", "country date \n", "Afghanistan 1960-01-01 8996351.0 NaN \n", " 1961-01-01 9166764.0 652860.0 \n", " 1962-01-01 9345868.0 652860.0 \n", "... ... ... \n", "Zimbabwe 2015-01-01 15777451.0 390760.0 \n", " 2016-01-01 16150362.0 390760.0 \n", " 2017-01-01 16529904.0 390760.0 \n", "\n", " Land area (sq. km) Arable land (% of land area) \n", "country date \n", "Afghanistan 1960-01-01 NaN NaN \n", " 1961-01-01 652860.0 11.717673 \n", " 1962-01-01 652860.0 11.794259 \n", "... ... ... \n", "Zimbabwe 2015-01-01 386850.0 10.339925 \n", " 2016-01-01 386850.0 NaN \n", " 2017-01-01 386850.0 NaN \n", "\n", "[15312 rows x 4 columns]" ] }, "execution_count": 3, "metadata": {}, "output_type": "execute_result" } ], "source": [ "indicators = {'SP.POP.TOTL': 'Population, total',\n", " 'AG.SRF.TOTL.K2': 'Surface area (sq. km)',\n", " 'AG.LND.TOTL.K2': 'Land area (sq. km)',\n", " 'AG.LND.ARBL.ZS': 'Arable land (% of land area)'}\n", "data = wb.get_dataframe(indicators, convert_date=True).sort_index()\n", "data" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "World is one of the countries" ] }, { "cell_type": "code", "execution_count": 4, "metadata": {}, "outputs": [ { "data": { "text/html": [ "
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" ], "text/plain": [ " Population, total Surface area (sq. km) Land area (sq. km) \\\n", "date \n", "1960-01-01 3.032160e+09 NaN NaN \n", "1961-01-01 3.073369e+09 134043190.4 129721455.4 \n", "1962-01-01 3.126510e+09 134043190.4 129721435.4 \n", "... ... ... ... \n", "2015-01-01 7.357559e+09 134325130.2 129732901.8 \n", "2016-01-01 7.444157e+09 134325130.2 129733172.7 \n", "2017-01-01 7.530360e+09 134325130.2 129733172.7 \n", "\n", " Arable land (% of land area) \n", "date \n", "1960-01-01 NaN \n", "1961-01-01 9.693086 \n", "1962-01-01 9.726105 \n", "... ... \n", "2015-01-01 10.991288 \n", "2016-01-01 NaN \n", "2017-01-01 NaN \n", "\n", "[58 rows x 4 columns]" ] }, "execution_count": 4, "metadata": {}, "output_type": "execute_result" } ], "source": [ "data.loc['World']" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Can we classify over continents?" ] }, { "cell_type": "code", "execution_count": 5, "metadata": {}, "outputs": [ { "data": { "text/plain": [ "Index(['Iran, Islamic Rep.', 'Congo, Dem. Rep.', 'Germany', 'Vietnam',\n", " 'Egypt, Arab Rep.', 'Central Europe and the Baltics', 'Philippines',\n", " 'Ethiopia', 'Japan', 'Mexico', 'Russian Federation', 'Bangladesh',\n", " 'Nigeria', 'Pakistan', 'Brazil', 'Indonesia', 'United States',\n", " 'Euro area', 'North America',\n", " 'Middle East & North Africa (IDA & IBRD countries)',\n", " 'Middle East & North Africa (excluding high income)', 'Arab World',\n", " 'Europe & Central Asia (excluding high income)',\n", " 'Middle East & North Africa',\n", " 'Europe & Central Asia (IDA & IBRD countries)',\n", " 'Fragile and conflict affected situations', 'European Union',\n", " 'IDA blend', 'Latin America & Caribbean (excluding high income)',\n", " 'Latin America & the Caribbean (IDA & IBRD countries)',\n", " 'Latin America & Caribbean', 'Low income',\n", " 'Heavily indebted poor countries (HIPC)', 'Pre-demographic dividend',\n", " 'Europe & Central Asia', 'Least developed countries: UN classification',\n", " 'Sub-Saharan Africa (excluding high income)',\n", " 'Sub-Saharan Africa (IDA & IBRD countries)', 'Sub-Saharan Africa',\n", " 'IDA only', 'Post-demographic dividend', 'High income', 'OECD members',\n", " 'India', 'China', 'IDA total', 'South Asia (IDA & IBRD)', 'South Asia',\n", " 'East Asia & Pacific (IDA & IBRD countries)',\n", " 'East Asia & Pacific (excluding high income)',\n", " 'Late-demographic dividend', 'East Asia & Pacific',\n", " 'Upper middle income', 'Lower middle income',\n", " 'Early-demographic dividend', 'IBRD only', 'Middle income',\n", " 'Low & middle income', 'IDA & IBRD total', 'World'],\n", " dtype='object', name='country')" ] }, "execution_count": 5, "metadata": {}, "output_type": "execute_result" } ], "source": [ "data.loc[(slice(None), '2017-01-01'), :]['Population, total'].dropna(\n", ").sort_values().tail(60).index.get_level_values('country')" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Extract zones manually (in order of increasing population)" ] }, { "cell_type": "code", "execution_count": 6, "metadata": {}, "outputs": [], "source": [ "zones = ['North America', 'Middle East & North Africa',\n", " 'Latin America & Caribbean', 'Europe & Central Asia',\n", " 'Sub-Saharan Africa', 'South Asia',\n", " 'East Asia & Pacific'][::-1]" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "And extract population information (and check total is right)" ] }, { "cell_type": "code", "execution_count": 7, "metadata": {}, "outputs": [], "source": [ "population = data.loc[zones]['Population, total'].swaplevel().unstack()\n", "population = population[zones]\n", "assert all(data.loc['World']['Population, total'] == population.sum(axis=1))" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "## Stacked area plot with matplotlib" ] }, { "cell_type": "code", "execution_count": 8, "metadata": {}, "outputs": [], "source": [ "import matplotlib.pyplot as plt" ] }, { "cell_type": "code", "execution_count": 9, "metadata": {}, "outputs": [ { "data": { "text/plain": [ "
" ] }, "metadata": {}, "output_type": "display_data" }, { "data": { "image/png": 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\n", "text/plain": [ "
" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "plt.clf()\n", "plt.figure(figsize=(10, 5), dpi=100)\n", "plt.stackplot(population.index, population.values.T / 1e9)\n", "plt.legend(population.columns, loc='upper left')\n", "plt.ylabel('Population count (B)')\n", "plt.show()" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "## Stacked bar plot with plotly" ] }, { "cell_type": "code", "execution_count": 10, "metadata": {}, "outputs": [ { "data": { "text/html": [ "" ], "text/vnd.plotly.v1+html": [ "" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "import plotly.offline as offline\n", "import plotly.graph_objs as go\n", "\n", "offline.init_notebook_mode()" ] }, { "cell_type": "code", "execution_count": 12, "metadata": {}, "outputs": [ { "data": { "application/vnd.plotly.v1+json": { "data": [ { "name": "East Asia & Pacific", "stackgroup": "World", "type": "scatter", "uid": "e5b08b9e-fcb8-4246-87db-4cb5b960bdf4", "x": [ "1960-01-01", "1961-01-01", "1962-01-01", "1963-01-01", "1964-01-01", "1965-01-01", "1966-01-01", "1967-01-01", "1968-01-01", "1969-01-01", "1970-01-01", "1971-01-01", "1972-01-01", "1973-01-01", "1974-01-01", "1975-01-01", "1976-01-01", "1977-01-01", "1978-01-01", "1979-01-01", "1980-01-01", "1981-01-01", "1982-01-01", "1983-01-01", "1984-01-01", "1985-01-01", "1986-01-01", "1987-01-01", "1988-01-01", "1989-01-01", "1990-01-01", "1991-01-01", "1992-01-01", "1993-01-01", "1994-01-01", "1995-01-01", "1996-01-01", "1997-01-01", "1998-01-01", "1999-01-01", "2000-01-01", "2001-01-01", "2002-01-01", "2003-01-01", "2004-01-01", "2005-01-01", "2006-01-01", "2007-01-01", "2008-01-01", "2009-01-01", "2010-01-01", "2011-01-01", "2012-01-01", "2013-01-01", "2014-01-01", "2015-01-01", "2016-01-01", "2017-01-01" ], "y": [ 1039944591, 1043546747, 1058028199, 1083802299, 1109204182, 1135650895, 1165517894, 1194424326, 1223721283, 1256501008, 1289258962, 1322942750, 1354794332, 1385052014, 1415128313, 1442241325, 1466464716, 1489361661, 1512159741, 1535391301, 1558178982, 1581806986, 1607731269, 1633628203, 1658253758, 1683448851, 1710171170, 1738276268, 1766656203, 1794408755, 1821481246, 1847530233, 1871898268, 1895356643, 1918771287, 1941918800, 1964635058, 1986799861, 2008140141, 2028095314, 2047150745, 2065521836, 2082953527, 2099545576, 2115557365, 2131363078, 2147029631, 2162104019, 2177421759, 2192352319, 2207154641, 2221934584, 2237082761, 2252311022, 2267745366, 2283108073, 2298726779, 2314364990 ] }, { "name": "South Asia", "stackgroup": "World", "type": "scatter", "uid": "5ccdb42f-dbf4-4abc-a1de-851c1114c31b", "x": [ "1960-01-01", "1961-01-01", "1962-01-01", "1963-01-01", "1964-01-01", "1965-01-01", "1966-01-01", "1967-01-01", "1968-01-01", "1969-01-01", "1970-01-01", "1971-01-01", "1972-01-01", "1973-01-01", "1974-01-01", "1975-01-01", "1976-01-01", "1977-01-01", "1978-01-01", "1979-01-01", "1980-01-01", "1981-01-01", "1982-01-01", "1983-01-01", "1984-01-01", "1985-01-01", "1986-01-01", "1987-01-01", "1988-01-01", "1989-01-01", "1990-01-01", "1991-01-01", "1992-01-01", "1993-01-01", "1994-01-01", "1995-01-01", "1996-01-01", "1997-01-01", "1998-01-01", "1999-01-01", "2000-01-01", "2001-01-01", "2002-01-01", "2003-01-01", "2004-01-01", "2005-01-01", "2006-01-01", "2007-01-01", "2008-01-01", "2009-01-01", "2010-01-01", "2011-01-01", "2012-01-01", "2013-01-01", "2014-01-01", "2015-01-01", "2016-01-01", "2017-01-01" ], "y": [ 571835666, 583894094, 596413939, 609391805, 622822615, 636701820, 651036352, 665826653, 681054882, 696697198, 712740919, 729173562, 746012374, 763310561, 781140577, 799553306, 818560436, 838142287, 858277856, 878933031, 900076467, 921696915, 943781613, 966293643, 989188965, 1012429641, 1035982524, 1059829211, 1083963380, 1108386444, 1133089464, 1158058109, 1183253534, 1208612942, 1234059205, 1259530819, 1284978193, 1310387887, 1335777637, 1361185289, 1386625845, 1412104373, 1437568227, 1462906674, 1487975237, 1512670560, 1536943534, 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327892753, 331014940, 334184023, 337405012, 340465736, 343408819, 346051624, 348808615, 351451876, 354223012, 356937591, 359735880, 362492702 ] } ], "layout": { "title": "World population" } }, "text/html": [ "
" ], "text/vnd.plotly.v1+html": [ "
" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "data = [go.Scatter(x=population.index, y=population[zone], name=zone, stackgroup='World')\n", " for zone in zones]\n", "fig = go.Figure(data=data,\n", " layout=go.Layout(title='World population'))\n", "offline.iplot(fig)" ] } ], "metadata": { "jupytext": { "cell_markers": "region,endregion", "formats": "ipynb,.pct.py:percent,.lgt.py:light,.spx.py:sphinx,md,Rmd,.pandoc.md:pandoc" }, "kernelspec": { "display_name": "Python 3", "language": "python", "name": "python3" }, "language_info": { "codemirror_mode": { "name": "ipython", "version": 3 }, "file_extension": ".py", "mimetype": "text/x-python", "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", "version": "3.7.3" }, "toc": { "base_numbering": 1, "nav_menu": {}, "number_sections": true, "sideBar": true, "skip_h1_title": false, "title_cell": "Table of Contents", "title_sidebar": "Contents", "toc_cell": false, "toc_position": {}, "toc_section_display": true, "toc_window_display": false } }, "nbformat": 4, "nbformat_minor": 2 } ================================================ FILE: demo/World population.lgt.py ================================================ # --- # jupyter: # jupytext: # cell_markers: region,endregion # formats: ipynb,.pct.py:percent,.lgt.py:light,.spx.py:sphinx,md,Rmd,.pandoc.md:pandoc # text_representation: # extension: .py # format_name: light # format_version: '1.4' # jupytext_version: 1.1.0 # kernelspec: # display_name: Python 3 # language: python # name: python3 # --- # # A quick insight at world population # # ## Collecting population data # # In the below we retrieve population data from the # [World Bank](http://www.worldbank.org/) # using the [wbdata](https://github.com/OliverSherouse/wbdata) python package # region import pandas as pd import wbdata as wb pd.options.display.max_rows = 6 pd.options.display.max_columns = 20 # endregion # Corresponding indicator is found using search method - or, directly, # the World Bank site. wb.search_indicators('Population, total') # SP.POP.TOTL # wb.search_indicators('area') # => https://data.worldbank.org/indicator is easier to use # Now we download the population data indicators = {'SP.POP.TOTL': 'Population, total', 'AG.SRF.TOTL.K2': 'Surface area (sq. km)', 'AG.LND.TOTL.K2': 'Land area (sq. km)', 'AG.LND.ARBL.ZS': 'Arable land (% of land area)'} data = wb.get_dataframe(indicators, convert_date=True).sort_index() data # World is one of the countries data.loc['World'] # Can we classify over continents? data.loc[(slice(None), '2017-01-01'), :]['Population, total'].dropna( ).sort_values().tail(60).index.get_level_values('country') # Extract zones manually (in order of increasing population) zones = ['North America', 'Middle East & North Africa', 'Latin America & Caribbean', 'Europe & Central Asia', 'Sub-Saharan Africa', 'South Asia', 'East Asia & Pacific'][::-1] # And extract population information (and check total is right) population = data.loc[zones]['Population, total'].swaplevel().unstack() population = population[zones] assert all(data.loc['World']['Population, total'] == population.sum(axis=1)) # ## Stacked area plot with matplotlib import matplotlib.pyplot as plt plt.clf() plt.figure(figsize=(10, 5), dpi=100) plt.stackplot(population.index, population.values.T / 1e9) plt.legend(population.columns, loc='upper left') plt.ylabel('Population count (B)') plt.show() # ## Stacked bar plot with plotly # region import plotly.offline as offline import plotly.graph_objs as go offline.init_notebook_mode() # endregion data = [go.Scatter(x=population.index, y=population[zone], name=zone, stackgroup='World') for zone in zones] fig = go.Figure(data=data, layout=go.Layout(title='World population')) offline.iplot(fig) ================================================ FILE: demo/World population.md ================================================ --- jupyter: jupytext: cell_markers: region,endregion formats: ipynb,.pct.py:percent,.lgt.py:light,.spx.py:sphinx,md,Rmd,.pandoc.md:pandoc text_representation: extension: .md format_name: markdown format_version: '1.1' jupytext_version: 1.1.0 kernelspec: display_name: Python 3 language: python name: python3 --- # A quick insight at world population ## Collecting population data In the below we retrieve population data from the [World Bank](http://www.worldbank.org/) using the [wbdata](https://github.com/OliverSherouse/wbdata) python package ```python import pandas as pd import wbdata as wb pd.options.display.max_rows = 6 pd.options.display.max_columns = 20 ``` Corresponding indicator is found using search method - or, directly, the World Bank site. ```python wb.search_indicators('Population, total') # SP.POP.TOTL # wb.search_indicators('area') # => https://data.worldbank.org/indicator is easier to use ``` Now we download the population data ```python indicators = {'SP.POP.TOTL': 'Population, total', 'AG.SRF.TOTL.K2': 'Surface area (sq. km)', 'AG.LND.TOTL.K2': 'Land area (sq. km)', 'AG.LND.ARBL.ZS': 'Arable land (% of land area)'} data = wb.get_dataframe(indicators, convert_date=True).sort_index() data ``` World is one of the countries ```python data.loc['World'] ``` Can we classify over continents? ```python data.loc[(slice(None), '2017-01-01'), :]['Population, total'].dropna( ).sort_values().tail(60).index.get_level_values('country') ``` Extract zones manually (in order of increasing population) ```python zones = ['North America', 'Middle East & North Africa', 'Latin America & Caribbean', 'Europe & Central Asia', 'Sub-Saharan Africa', 'South Asia', 'East Asia & Pacific'][::-1] ``` And extract population information (and check total is right) ```python population = data.loc[zones]['Population, total'].swaplevel().unstack() population = population[zones] assert all(data.loc['World']['Population, total'] == population.sum(axis=1)) ``` ## Stacked area plot with matplotlib ```python import matplotlib.pyplot as plt ``` ```python plt.clf() plt.figure(figsize=(10, 5), dpi=100) plt.stackplot(population.index, population.values.T / 1e9) plt.legend(population.columns, loc='upper left') plt.ylabel('Population count (B)') plt.show() ``` ## Stacked bar plot with plotly ```python import plotly.offline as offline import plotly.graph_objs as go offline.init_notebook_mode() ``` ```python data = [go.Scatter(x=population.index, y=population[zone], name=zone, stackgroup='World') for zone in zones] fig = go.Figure(data=data, layout=go.Layout(title='World population')) offline.iplot(fig) ``` ================================================ FILE: demo/World population.myst.md ================================================ --- jupytext: formats: ipynb,.pct.py:percent,.lgt.py:light,.spx.py:sphinx,md,Rmd,.pandoc.md:pandoc,.myst.md:myst text_representation: extension: '.md' format_name: myst format_version: '0.7' jupytext_version: 1.4.0+dev kernelspec: display_name: Python 3 language: python name: python3 --- # A quick insight at world population ## Collecting population data In the below we retrieve population data from the [World Bank](http://www.worldbank.org/) using the [wbdata](https://github.com/OliverSherouse/wbdata) python package ```{code-cell} ipython3 import pandas as pd import wbdata as wb pd.options.display.max_rows = 6 pd.options.display.max_columns = 20 ``` Corresponding indicator is found using search method - or, directly, the World Bank site. ```{code-cell} ipython3 wb.search_indicators('Population, total') # SP.POP.TOTL # wb.search_indicators('area') # => https://data.worldbank.org/indicator is easier to use ``` Now we download the population data ```{code-cell} ipython3 indicators = {'SP.POP.TOTL': 'Population, total', 'AG.SRF.TOTL.K2': 'Surface area (sq. km)', 'AG.LND.TOTL.K2': 'Land area (sq. km)', 'AG.LND.ARBL.ZS': 'Arable land (% of land area)'} data = wb.get_dataframe(indicators, convert_date=True).sort_index() data ``` World is one of the countries ```{code-cell} ipython3 data.loc['World'] ``` Can we classify over continents? ```{code-cell} ipython3 data.loc[(slice(None), '2017-01-01'), :]['Population, total'].dropna( ).sort_values().tail(60).index.get_level_values('country') ``` Extract zones manually (in order of increasing population) ```{code-cell} ipython3 zones = ['North America', 'Middle East & North Africa', 'Latin America & Caribbean', 'Europe & Central Asia', 'Sub-Saharan Africa', 'South Asia', 'East Asia & Pacific'][::-1] ``` And extract population information (and check total is right) ```{code-cell} ipython3 population = data.loc[zones]['Population, total'].swaplevel().unstack() population = population[zones] assert all(data.loc['World']['Population, total'] == population.sum(axis=1)) ``` ## Stacked area plot with matplotlib ```{code-cell} ipython3 import matplotlib.pyplot as plt ``` ```{code-cell} ipython3 plt.clf() plt.figure(figsize=(10, 5), dpi=100) plt.stackplot(population.index, population.values.T / 1e9) plt.legend(population.columns, loc='upper left') plt.ylabel('Population count (B)') plt.show() ``` ## Stacked bar plot with plotly +++ Stacked area plots (with cumulated values computed depending on selected legends) are [on their way](https://github.com/plotly/plotly.js/pull/2960) at Plotly. For now we just do a stacked bar plot. ```{code-cell} ipython3 import plotly.offline as offline import plotly.graph_objs as go offline.init_notebook_mode() ``` ```{code-cell} ipython3 bars = [go.Bar(x=population.index, y=population[zone], name=zone) for zone in zones] fig = go.Figure(data=bars, layout=go.Layout(title='World population', barmode='stack')) offline.iplot(fig) ``` ================================================ FILE: demo/World population.pandoc.md ================================================ --- jupyter: jupytext: cell_markers: 'region,endregion' formats: 'ipynb,.pct.py:percent,.lgt.py:light,.spx.py:sphinx,md,Rmd,.pandoc.md:pandoc' text_representation: extension: '.md' format_name: pandoc format_version: '2.7.2' jupytext_version: '1.1.0' kernelspec: display_name: Python 3 language: python name: python3 nbformat: 4 nbformat_minor: 2 --- ::: {.cell .markdown} # A quick insight at world population ## Collecting population data In the below we retrieve population data from the [World Bank](http://www.worldbank.org/) using the [wbdata](https://github.com/OliverSherouse/wbdata) python package ::: ::: {.cell .code} ``` {.python} import pandas as pd import wbdata as wb pd.options.display.max_rows = 6 pd.options.display.max_columns = 20 ``` ::: ::: {.cell .markdown} Corresponding indicator is found using search method - or, directly, the World Bank site. ::: ::: {.cell .code} ``` {.python} wb.search_indicators('Population, total') # SP.POP.TOTL # wb.search_indicators('area') # => https://data.worldbank.org/indicator is easier to use ``` ::: ::: {.cell .markdown} Now we download the population data ::: ::: {.cell .code} ``` {.python} indicators = {'SP.POP.TOTL': 'Population, total', 'AG.SRF.TOTL.K2': 'Surface area (sq. km)', 'AG.LND.TOTL.K2': 'Land area (sq. km)', 'AG.LND.ARBL.ZS': 'Arable land (% of land area)'} data = wb.get_dataframe(indicators, convert_date=True).sort_index() data ``` ::: ::: {.cell .markdown} World is one of the countries ::: ::: {.cell .code} ``` {.python} data.loc['World'] ``` ::: ::: {.cell .markdown} Can we classify over continents? ::: ::: {.cell .code} ``` {.python} data.loc[(slice(None), '2017-01-01'), :]['Population, total'].dropna( ).sort_values().tail(60).index.get_level_values('country') ``` ::: ::: {.cell .markdown} Extract zones manually (in order of increasing population) ::: ::: {.cell .code} ``` {.python} zones = ['North America', 'Middle East & North Africa', 'Latin America & Caribbean', 'Europe & Central Asia', 'Sub-Saharan Africa', 'South Asia', 'East Asia & Pacific'][::-1] ``` ::: ::: {.cell .markdown} And extract population information (and check total is right) ::: ::: {.cell .code} ``` {.python} population = data.loc[zones]['Population, total'].swaplevel().unstack() population = population[zones] assert all(data.loc['World']['Population, total'] == population.sum(axis=1)) ``` ::: ::: {.cell .markdown} ## Stacked area plot with matplotlib ::: ::: {.cell .code} ``` {.python} import matplotlib.pyplot as plt ``` ::: ::: {.cell .code} ``` {.python} plt.clf() plt.figure(figsize=(10, 5), dpi=100) plt.stackplot(population.index, population.values.T / 1e9) plt.legend(population.columns, loc='upper left') plt.ylabel('Population count (B)') plt.show() ``` ::: ::: {.cell .markdown} ## Stacked bar plot with plotly ::: ::: {.cell .code} ``` {.python} import plotly.offline as offline import plotly.graph_objs as go offline.init_notebook_mode() ``` ::: ::: {.cell .code} ``` {.python} data = [go.Scatter(x=population.index, y=population[zone], name=zone, stackgroup='World') for zone in zones] fig = go.Figure(data=data, layout=go.Layout(title='World population')) offline.iplot(fig) ``` ::: ================================================ FILE: demo/World population.pct.py ================================================ # --- # jupyter: # jupytext: # cell_markers: region,endregion # formats: ipynb,.pct.py:percent,.lgt.py:light,.spx.py:sphinx,md,Rmd,.pandoc.md:pandoc # text_representation: # extension: .py # format_name: percent # format_version: '1.2' # jupytext_version: 1.1.0 # kernelspec: # display_name: Python 3 # language: python # name: python3 # --- # %% [markdown] # # A quick insight at world population # # ## Collecting population data # # In the below we retrieve population data from the # [World Bank](http://www.worldbank.org/) # using the [wbdata](https://github.com/OliverSherouse/wbdata) python package # %% import pandas as pd import wbdata as wb pd.options.display.max_rows = 6 pd.options.display.max_columns = 20 # %% [markdown] # Corresponding indicator is found using search method - or, directly, # the World Bank site. # %% wb.search_indicators('Population, total') # SP.POP.TOTL # wb.search_indicators('area') # => https://data.worldbank.org/indicator is easier to use # %% [markdown] # Now we download the population data # %% indicators = {'SP.POP.TOTL': 'Population, total', 'AG.SRF.TOTL.K2': 'Surface area (sq. km)', 'AG.LND.TOTL.K2': 'Land area (sq. km)', 'AG.LND.ARBL.ZS': 'Arable land (% of land area)'} data = wb.get_dataframe(indicators, convert_date=True).sort_index() data # %% [markdown] # World is one of the countries # %% data.loc['World'] # %% [markdown] # Can we classify over continents? # %% data.loc[(slice(None), '2017-01-01'), :]['Population, total'].dropna( ).sort_values().tail(60).index.get_level_values('country') # %% [markdown] # Extract zones manually (in order of increasing population) # %% zones = ['North America', 'Middle East & North Africa', 'Latin America & Caribbean', 'Europe & Central Asia', 'Sub-Saharan Africa', 'South Asia', 'East Asia & Pacific'][::-1] # %% [markdown] # And extract population information (and check total is right) # %% population = data.loc[zones]['Population, total'].swaplevel().unstack() population = population[zones] assert all(data.loc['World']['Population, total'] == population.sum(axis=1)) # %% [markdown] # ## Stacked area plot with matplotlib # %% import matplotlib.pyplot as plt # %% plt.clf() plt.figure(figsize=(10, 5), dpi=100) plt.stackplot(population.index, population.values.T / 1e9) plt.legend(population.columns, loc='upper left') plt.ylabel('Population count (B)') plt.show() # %% [markdown] # ## Stacked bar plot with plotly # %% import plotly.offline as offline import plotly.graph_objs as go offline.init_notebook_mode() # %% data = [go.Scatter(x=population.index, y=population[zone], name=zone, stackgroup='World') for zone in zones] fig = go.Figure(data=data, layout=go.Layout(title='World population')) offline.iplot(fig) ================================================ FILE: demo/World population.spx.py ================================================ # --- # jupyter: # jupytext: # cell_markers: region,endregion # formats: ipynb,.pct.py:percent,.lgt.py:light,.spx.py:sphinx,md,Rmd,.pandoc.md:pandoc # text_representation: # extension: .py # format_name: sphinx # format_version: '1.1' # jupytext_version: 1.1.0 # kernelspec: # display_name: Python 3 # language: python # name: python3 # --- """ # A quick insight at world population ## Collecting population data In the below we retrieve population data from the [World Bank](http://www.worldbank.org/) using the [wbdata](https://github.com/OliverSherouse/wbdata) python package """ import pandas as pd import wbdata as wb pd.options.display.max_rows = 6 pd.options.display.max_columns = 20 ############################################################################### # Corresponding indicator is found using search method - or, directly, # the World Bank site. wb.search_indicators('Population, total') # SP.POP.TOTL # wb.search_indicators('area') # => https://data.worldbank.org/indicator is easier to use ############################################################################### # Now we download the population data indicators = {'SP.POP.TOTL': 'Population, total', 'AG.SRF.TOTL.K2': 'Surface area (sq. km)', 'AG.LND.TOTL.K2': 'Land area (sq. km)', 'AG.LND.ARBL.ZS': 'Arable land (% of land area)'} data = wb.get_dataframe(indicators, convert_date=True).sort_index() data ############################################################################### # World is one of the countries data.loc['World'] ############################################################################### # Can we classify over continents? data.loc[(slice(None), '2017-01-01'), :]['Population, total'].dropna( ).sort_values().tail(60).index.get_level_values('country') ############################################################################### # Extract zones manually (in order of increasing population) zones = ['North America', 'Middle East & North Africa', 'Latin America & Caribbean', 'Europe & Central Asia', 'Sub-Saharan Africa', 'South Asia', 'East Asia & Pacific'][::-1] ############################################################################### # And extract population information (and check total is right) population = data.loc[zones]['Population, total'].swaplevel().unstack() population = population[zones] assert all(data.loc['World']['Population, total'] == population.sum(axis=1)) ############################################################################### # ## Stacked area plot with matplotlib import matplotlib.pyplot as plt "" plt.clf() plt.figure(figsize=(10, 5), dpi=100) plt.stackplot(population.index, population.values.T / 1e9) plt.legend(population.columns, loc='upper left') plt.ylabel('Population count (B)') plt.show() ############################################################################### # ## Stacked bar plot with plotly import plotly.offline as offline import plotly.graph_objs as go offline.init_notebook_mode() "" data = [go.Scatter(x=population.index, y=population[zone], name=zone, stackgroup='World') for zone in zones] fig = go.Figure(data=data, layout=go.Layout(title='World population')) offline.iplot(fig) ================================================ FILE: demo/get_started.md ================================================ --- jupyter: jupytext: formats: ipynb,md text_representation: extension: .md format_name: markdown format_version: '1.1' jupytext_version: 1.1.6 kernelspec: display_name: Python 3 language: python name: python3 --- # Getting started with Jupytext This small notebook shows you how to activate Jupytext in the JupyterLab environment. We'll show you a few things that you can do with Jupytext and a bit of what happens under the hood. **Note: to run this notebook locally, you need to first follow the Jupytext installation instructions and activate the JupyterLab plugin. If you're on Binder, it should already work.** ## Enabling Jupytext in a new notebook This notebook is brand new - it hasn't had any special extra metadata added to it. If we want Jupytext to save files in multiple formats automatically, we can use the JupyterLab **command palette** to do so. * In the _View_ menu, click on _Activate Command Palette_ * Then type **`Jupytext`**. You should see a number of commands come up. Each one tells Jupytext to save the notebook in a different file format automatically. * Select **Pair notebook with MyST Markdown** That's it! If you have Jupytext installed, it will now save your notebook in markdown format automatically when you save this `.ipynb` file **in addition to** saving the `.ipynb` file itself. After you've done this, save the notebook. You should now see a new file called **`get_started.md`** in the same directory as this notebook. ## How does Jupytext know to do this? Jupytext uses notebook-level metadata to keep track of what formats are paired with a notebook. Below we'll print the metadata of this notebook so you can see what the Jupytext metadata looks like. ```python import nbformat as nbf from IPython.display import JSON notebook = nbf.read('./get_started.ipynb', nbf.NO_CONVERT) JSON(notebook['metadata']) ``` As you select different formats from the command palette (following the instructions above) and save the notebook, you'll see this metadata change. ## That's it! Play around with different kinds of code and outputs to see how each is converted into its corresponding text format. 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"#E5ECF6", "polar": { "angularaxis": { "gridcolor": "white", "linecolor": "white", "ticks": "" }, "bgcolor": "#E5ECF6", "radialaxis": { "gridcolor": "white", "linecolor": "white", "ticks": "" } }, "scene": { "xaxis": { "backgroundcolor": "#E5ECF6", "gridcolor": "white", "gridwidth": 2, "linecolor": "white", "showbackground": true, "ticks": "", "zerolinecolor": "white" }, "yaxis": { "backgroundcolor": "#E5ECF6", "gridcolor": "white", "gridwidth": 2, "linecolor": "white", "showbackground": true, "ticks": "", "zerolinecolor": "white" }, "zaxis": { "backgroundcolor": "#E5ECF6", "gridcolor": "white", "gridwidth": 2, "linecolor": "white", "showbackground": true, "ticks": "", "zerolinecolor": "white" } }, "shapedefaults": { "line": { "color": "#2a3f5f" } }, "ternary": { "aaxis": { "gridcolor": "white", "linecolor": "white", "ticks": "" }, "baxis": { "gridcolor": "white", "linecolor": "white", "ticks": "" }, "bgcolor": "#E5ECF6", "caxis": { "gridcolor": "white", "linecolor": "white", "ticks": "" } }, "title": { "x": 0.05 }, "xaxis": { "automargin": true, "gridcolor": "white", "linecolor": "white", "ticks": "", "title": { "standoff": 15 }, "zerolinecolor": "white", "zerolinewidth": 2 }, "yaxis": { "automargin": true, "gridcolor": "white", "linecolor": "white", "ticks": "", "title": { "standoff": 15 }, "zerolinecolor": "white", "zerolinewidth": 2 } } }, "xaxis": { "anchor": "y", "domain": [ 0, 1 ], "title": { "text": "sepal_width" } }, "yaxis": { "anchor": "x", "domain": [ 0, 1 ], "title": { "text": "sepal_length" } } } } }, "metadata": {}, "output_type": "display_data" } ], "source": [ "px.scatter(\n", " px.data.iris(),\n", " x=\"sepal_width\",\n", " y=\"sepal_length\",\n", " color=\"species\",\n", ")" ] }, { "cell_type": "code", "execution_count": null, "id": "61adea94", "metadata": {}, "outputs": [], "source": [] } ], "metadata": { "jupytext": { "formats": "ipynb,py:percent" }, "kernelspec": { "display_name": "Python 3", "language": "python", "name": "python3" }, "language_info": { "codemirror_mode": { "name": "ipython", "version": 3 }, "file_extension": ".py", "mimetype": "text/x-python", "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", "version": "3.12.0" } }, "nbformat": 4, "nbformat_minor": 5 } ================================================ FILE: demo/vscode/notebook.py ================================================ # --- # jupyter: # jupytext: # formats: ipynb,py:percent # text_representation: # extension: .py # format_name: percent # format_version: '1.3' # jupytext_version: 1.18.0-dev # kernelspec: # display_name: Python 3 # language: python # name: python3 # --- # %% [markdown] # This paired notebook can be edited either as # a Python script or as a Jupyter notebook in # VS Code. Thanks to the Jupytext Sync # extension, changes are automatically synced to # the other paired file(s) when you save. # # 💡 Tip: don't forget to hit "Save" before # switching to the other editor. If you don't save # your changes, you will run into conflicting edits # as VS Code does not autoreload files that have # unsaved edits. # %% import plotly.express as px # %% px.scatter( px.data.iris(), x="sepal_width", y="sepal_length", color="species", ) # %% ================================================ FILE: docs/Makefile ================================================ # Minimal makefile for Sphinx documentation # # You can set these variables from the command line. SPHINXOPTS = SPHINXBUILD = sphinx-build SOURCEDIR = . BUILDDIR = _build # Put it first so that "make" without argument is like "make help". help: @$(SPHINXBUILD) -M help "$(SOURCEDIR)" "$(BUILDDIR)" $(SPHINXOPTS) $(O) .PHONY: help Makefile # Catch-all target: route all unknown targets to Sphinx using the new # "make mode" option. $(O) is meant as a shortcut for $(SPHINXOPTS). %: Makefile @$(SPHINXBUILD) -M $@ "$(SOURCEDIR)" "$(BUILDDIR)" $(SPHINXOPTS) $(O) ================================================ FILE: docs/advanced-options.md ================================================ # Advanced options ## Metadata filtering The metadata that is included in the text notebooks is governed by the two options `notebook_metadata_filter` and `cell_metadata_filter`. The default value for these options are - `notebook_metadata_filter="kernelspec,jupytext"`, i.e. by default, only the Jupytext and the kernel metadata are included: - `cell_metadata_filter=all,-autoscroll,-collapsed,-scrolled,-trusted,-ExecuteTime`, i.e. by default all the cell metadata are included, except those listed with a negative sign. Suppose you want to keep all the notebook metadata but `widgets` and `varInspector` in the YAML header, and that for cell metadata, you want to allow `ExecuteTime` and `autoscroll`, but not `hide_output`. Then, you could either add ```python notebook_metadata_filter="all,-widgets,-varInspector" cell_metadata_filter="ExecuteTime,autoscroll,-hide_output" ``` to your [`jupytext.toml`](config.md) file, or set these options for one notebook using the [Jupytext CLI](using-cli.md) with ``` jupytext --opt notebook_metadata_filter=all,-widgets,-varInspector --opt cell_metadata_filter=ExecuteTime,autoscroll,-hide_output notebook.py ``` If you wanted no notebook or cell metadata at all in the text notebooks, you could add this to your [`jupytext.toml`](config.md) file: ```python notebook_metadata_filter="-all" cell_metadata_filter="-all" ``` It is possible to filter nested metadata - use a dot to represent the nested fields. For example, if you wanted to include the Jupytext metadata, but not the Jupytext version number, you can use: ```python notebook_metadata_filter="-jupytext.text_representation.jupytext_version" ``` Finally, note that you can _hide_ the notebook metadata in an HTML comment in `.md` files - just set `hide_notebook_metadata=true` either at the command line or in the `jupytext.toml` file. ## Magic commands In the `percent` and `light` script formats, magic commands (Jupyter commands prefixed by `%` or `%%`) are commented out in scripts. You can change this by using the `comment_magics` option, either in the `jupytext.toml` file or at the command line with `jupytext --opt`. ## Active and inactive cells You might want to make some cell active only when the notebook is run in Jupyter, or active only when the `.py` file is interpreted by Python. To do so, add an `active-ipynb` tag to the cells that should only be executed in the `.ipynb` file, and an `active-py` tag to the cells that should be executed only in the Python script. ## More options There are a couple more options available - please have a look at the `JupytextConfiguration` class in [config.py](https://github.com/mwouts/jupytext/blob/main/src/jupytext/config.py). ================================================ FILE: docs/changelog.md ================================================ ```{include} ../CHANGELOG.md ``` ================================================ FILE: docs/conf.py ================================================ # Configuration file for the Sphinx documentation builder. # # This file only contains a selection of the most common options. For a full # list see the documentation: # http://www.sphinx-doc.org/en/master/config # -- Path setup -------------------------------------------------------------- # If extensions (or modules to document with autodoc) are in another directory, # add these directories to sys.path here. If the directory is relative to the # documentation root, use os.path.abspath to make it absolute, like shown here. # # import os # import sys # sys.path.insert(0, os.path.abspath('.')) # -- Project information ----------------------------------------------------- project = "Jupytext" copyright = "2018-2025, The Jupytext Team" author = "The Jupytext Team" # -- General configuration --------------------------------------------------- # Add any Sphinx extension module names here, as strings. They can be # extensions coming with Sphinx (named 'sphinx.ext.*') or your custom # ones. extensions = ["sphinx_copybutton", "myst_parser"] # Auto-generated header anchors myst_heading_anchors = 3 html_context = { "display_github": True, # Integrate GitHub "github_user": "mwouts", # Username "github_repo": "jupytext", # Repo name "github_version": "main", # Version "conf_py_path": "/docs/", # Path in the checkout to the docs root } # Add any paths that contain templates here, relative to this directory. templates_path = ["_templates"] # List of patterns, relative to source directory, that match files and # directories to ignore when looking for source files. # This pattern also affects html_static_path and html_extra_path. exclude_patterns = ["_build", "Thumbs.db", ".DS_Store", ".ipynb_checkpoints"] # -- Options for HTML output ------------------------------------------------- # The theme to use for HTML and HTML Help pages. See the documentation for # a list of builtin themes. html_theme = "alabaster" html_sidebars = {"**": ["about.html", "navigation.html", "searchbox.html"]} html_theme_options = { "github_button": True, "github_banner": True, "github_user": "mwouts", "github_repo": "jupytext", "github_type": "star", "logo": "logo.svg", "show_relbars": True, } pygments_style = "sphinx" master_doc = "index" # Makes `index.md` the main file # Add any paths that contain custom static files (such as style sheets) here, # relative to this directory. They are copied after the builtin static files, # so a file named "default.css" will overwrite the builtin "default.css". html_static_path = ["_static"] # Output file base name for HTML help builder. htmlhelp_basename = "jupytext" ================================================ FILE: docs/config.md ================================================ # Jupytext's configuration file Jupytext can use either `jupytext.toml` or `pyproject.toml` as its configuration file. ## Global pairing To [pair](paired-notebooks.md) all the notebooks in the current folder and subfolders, all you need to do is to create a `jupytext.toml` file with this content: ``` # Pair ipynb notebooks to py:percent text notebooks formats = "ipynb,py:percent" ``` With the above configuration, saving `notebook.ipynb` (or `notebook.py`) in Jupyter will have the effect to update both `notebook.ipynb` and `notebook.py` on disk. You can use other text formats like `md`, `md:myst`, `Rmd` or `qmd`. The percent format is available for many languages. Use `auto:percent` to infer the file extension from the programmation language used in the notebook. You can also configure Jupytext in a `pyproject.toml` config file rather than `jupytext.toml`. In that case, a sample configuration would be: ``` [tool.jupytext] formats = "ipynb,py:percent" ``` ## Pairing in subfolders If you want to store your `.ipynb` notebooks in a `notebooks` folder, and their `.py` representation in a `scripts` folder, you can use this `jupytext.toml` configuration: ``` [formats] "notebooks/" = "ipynb" "scripts/" = "py:percent" ``` or this `pyproject.toml` configuration: ``` [tool.jupytext.formats] "notebooks/" = "ipynb" "scripts/" = "py:percent" ``` The `notebook/` prefix above is matched with the top-most parent folder of the matching name, not above the Jupytext configuration file. ## Pairing with multiple format specifications You can define different pairing configurations for specific subsets of notebooks by using a list of format dictionaries. This is useful when you want to apply different pairing rules to notebooks in different locations, such as generating documentation markdown files only for tutorial notebooks. Since Jupytext v1.18.0, the `formats` option can be a list of format dictionaries, where the first matching format is used for each notebook. Here's an example that pairs tutorial notebooks to markdown documentation files, and all other notebooks to Python scripts: ```toml # jupytext.toml # Tutorial notebooks get paired to markdown docs [[formats]] "notebooks/tutorials/" = "ipynb" "docs/tutorials/" = "md" "scripts/tutorials/" = "py:percent" # Default pairing: all other notebooks are paired with Python scripts [[formats]] "notebooks/" = "ipynb" "scripts/" = "py:percent" ``` With this configuration: - Tutorial notebooks like `notebooks/tutorials/getting_started.ipynb` are paired with: - `docs/tutorials/getting_started.md` - `scripts/tutorials/getting_started.py` - Regular notebooks like `notebooks/hello.ipynb` are paired with `scripts/hello.py` You can define multiple format specifications for different subsets: ```toml # Tutorial notebooks [[formats]] "notebooks/tutorials/" = "ipynb" "docs/tutorials/" = "md" # Example notebooks with MyST format [[formats]] "notebooks/examples/" = "ipynb" "docs/examples/" = "md:myst" # Default for all other notebooks [[formats]] "notebooks/" = "ipynb" "scripts/" = "py:percent" ``` The first format specification that matches the notebook path is used. It's recommended to put more specific paths first and the default/catch-all formats last. ### Alternative syntaxes You can also use a semicolon-separated string for a more compact notation: ```toml # jupytext.toml formats = "notebooks///ipynb,scripts///py:percent;ipynb,py:percent" ``` Or a TOML list with string format specifications: ```toml # jupytext.toml formats = [ "notebooks///ipynb,scripts///py:percent", "ipynb,py:percent" ] ``` In `pyproject.toml`, the configuration would be: ```toml [[tool.jupytext.formats]] "notebooks/tutorials/" = "ipynb" "docs/tutorials/" = "md" [[tool.jupytext.formats]] "notebooks/" = "ipynb" "scripts/" = "py:percent" ``` ## Global pairing vs individual pairing Alternatively, notebooks can be paired individually using either the Jupytext commands in JupyterLab, or the command line interface: ```bash jupytext --set-formats ipynb,py:percent notebook.ipynb ``` The individual pairing takes precedence over the global pairing. You can disable the global pairing for an individual notebook by setting formats to a single format: ```bash jupytext --set-formats ipynb notebook.ipynb ``` Please note that, while Jupytext is Jupyter acts accordingly to both local or global Jupytext configuration files, the Jupyter commands in JupyterLab and the Jupytext menu in Jupyter only display the pairing information set in the notebooks itself and are not aware of the global configuration ([#177](https://github.com/mwouts/jupytext/issues/177)). ## Possible locations for the Jupytext configuration files The Jupytext configuration file(s) should be either in the local or a parent directory, or in any directory listed in ```python from jupytext.config import global_jupytext_configuration_directories list(global_jupytext_configuration_directories()) ``` which include `XDG_CONFIG_HOME` (defaults to `$HOME/.config`) and `XDG_CONFIG_DIR`. The name for the configuration file can be any of `jupytext.config.JUPYTEXT_CONFIG_FILES`, i.e. `.jupytext` (in TOML), `jupytext.toml`, `jupytext.yml`, `jupytext.yaml`, `jupytext.json` or `jupytext.py` (dot-files like `.jupytext.toml` are accepted by the CLI version of Jupytext, but are not effective in Jupyter). As mentionned above, you can also use your Python project's `pyproject.toml` file. If you want to know, for a given directory, which configuration file is used by Jupytext, run this in a Python shell: ```python from jupytext.config import find_jupytext_configuration_file find_jupytext_configuration_file('.') ``` If you want to limit the search for a configuration file to a given parent directory, you can create an empty `.jupytext` configuration file in that directory. Alternatively, you can set the search boundaries with an environment variable `JUPYTEXT_CEILING_DIRECTORIES` - a colon-separated list of absolute paths. If `JUPYTEXT_CEILING_DIRECTORIES` is defined, Jupytext will stop searching for configuration files when it meets one of these path. This can be helpful to avoid searching for configuration files on slow filesystems. It can also be useful if you don't want to use a global configuration - for instance, when running `pytest` on Jupytext, we use `JUPYTEXT_CEILING_DIRECTORIES="/tmp"`. ================================================ FILE: docs/contributing.md ================================================ # Contributing Thanks for reading this! Contributions to this project are welcome, and there are many ways you can contribute ## Improve the documentation You've spotted a typo, a paragraph that is not very clear, or an instruction that does not work? Please follow the _Fork me on Github_ link, edit the document, and submit a pull request. ## Report an issue You have seen an issue with Jupytext, or you can't find your way in the documentation? Please let us know, and provide enough information so that we can reproduce the problem. ## Propose enhancements You want to submit an enhancement on Jupytext? Unless this is a small change, we usually prefer that you let us know beforehand: open an issue that describe the problem you want to solve. ## Add support for another language A pull request for which you do not need to contact us in advance is the addition of a new language to Jupytext. In principle that should be easy - you would only have to: - document the language extension and comment by adding one line to `_SCRIPT_EXTENSIONS` in `jupytext/languages.py`. - add the language to `docs/languages.md` - contribute a sample notebook in `tests/data/notebooks/inputs/ipynb_[language]`. - run the tests suite (create a [development environment](developing.md), then execute `pytest` locally). The tests will generate various text representations corresponding to your notebook under `tests/data/notebooks/outputs/`. Please verify that these files are valid scripts, and include them in your PR. ================================================ FILE: docs/developing.md ================================================ # Developing Jupytext ## How to test development versions from GitHub If you want to test a feature that has been integrated in `main` but not delivered yet to `pip` or `conda`, use ``` HATCH_BUILD_HOOKS_ENABLE=true pip install git+https://github.com/mwouts/jupytext.git ``` The above requires `node`. You can install it with e.g. ``` conda install 'nodejs>=20' -c conda-forge ``` Alternatively you can build only Jupytext core (e.g. skip the JupyterLab extension). To do so, remove `HATCH_BUILD_HOOKS_ENABLE=true` in the above. Finally, if you want to test a development branch, use ``` HATCH_BUILD_HOOKS_ENABLE=true pip install git+https://github.com/mwouts/jupytext.git@branch ``` where `branch` is the name of the branch you want to test. ## Install and develop Jupytext locally Most of Jupytext's code is written in Python. To develop the Python part of Jupytext, you should clone Jupytext, then create a dedicated Python environment with [Pixi](https://pixi.sh): ``` pixi shell ``` Install the `jupytext` package in development mode with ``` HATCH_BUILD_HOOKS_ENABLE=true pip install -e '.[dev]' ``` We use the [pre-commit](https://pre-commit.com) package to run pre-commit scripts like `black` and `ruff` on the code. Install it with ``` pre-commit install ``` Tests are executed with `pytest`. You can run them in parallel with for instance ``` pytest -n 5 ``` Some tests require a Jupyter kernel pointing to the current environment: ``` python -m ipykernel install --name jupytext-dev --user ``` ## Jupytext's extension for JupyterLab Our extension for JupyterLab adds a series of Jupytext commands to JupyterLab. The code is in `packages/labextension`. See the `README.md` there for instructions on how to develop that extension. ## Jupytext's documentation You can build the HTML documentation locally with ``` rm -rf docs/_build pixi run -e docs sphinx-build docs docs/_build ``` ================================================ FILE: docs/doc-requirements.txt ================================================ sphinx sphinx_copybutton sphinx_rtd_theme jupytext myst_parser ================================================ FILE: docs/faq.md ================================================ # FAQ ## What is Jupytext? Jupytext is a Python package that provides _two-way_ conversion between Jupyter notebooks and several other text-based formats like Markdown documents or scripts. ## Why would I want to convert my notebooks to text? The text representation only contains the part of the notebook that you wrote (not the outputs). You get a cleaner diff history. Thanks to the _two-way_ conversion, you can also act on the text file and then propagate the changes to the original `.ipynb` file. Refactor your code or merge multiple contributions easily! ## How do I use Jupytext? Open the notebook that you want to version control. _Pair_ the notebook to a script or a Markdown file using the [Jupytext Commands](install.md#jupytext-commands-in-jupyterlab) in JupyterLab. Save the notebook, and you get two copies of the notebook: the original `*.ipynb` file, together with its paired text representation. ## Which Jupytext format do you recommend? Notebooks that contain more text than code are best represented as Markdown documents. These are conveniently edited in IDEs and are also well rendered on GitHub. Saving notebooks as scripts is an appropriate choice when you want to act on the code (refactor the code, import it in another script or notebook, etc). Use the `percent` format if you prefer to get explicit cell markers (compatible with VScode, PyCharm, Spyder, Hydrogen...). And if you prefer to get the minimal amount of cell markers, go for the `light` format. ## Can I see a sample of each format? Go to [our demo folder](https://github.com/mwouts/jupytext/tree/main/demo) and see how our sample `World population` notebook is represented in each format. ## Can I edit the paired text file? Yes! When you're done, reload the notebook in Jupyter. There, you will see the updated input cells combined with the matching output cells from the `.ipynb` file. ## Do I need to close my notebook in Jupyter? Closing the notebook in Jupyter while you refactor it in another editor will help you avoid the message _Untitled.ipynb has changed on disk_. However, you don't really need to close the notebook. You can simply use _Reload Notebook from disk_ to load the latest edits once you're done with the other editor. When you reload the notebook, the kernel variables are preserved (and the outputs too if the notebook is paired to an `.ipynb` file), so you can continue your work where you left it. 💡 **Tip:** You can automate the notebook reloading by installing the [Jupyter Collaboration](jupyter-collaboration.md) extension. ## How do paired notebooks work? The `.ipynb` file contains the full notebook. The paired text file only contains the input cells and selected metadata. When the notebook is loaded by Jupyter, input cells are loaded from the text file, while the output cells and the filtered metadata are restored using the `.ipynb` file. When the notebook is saved in Jupyter, the two files are updated to match the current content of the notebook. ## Can I create a notebook from a text file? Certainly. Open your pre-existing scripts or Markdown files as notebooks with the _Open as Notebook_ menu in JupyterLab. Output cells appear in the browser when you execute the notebook, but they are not written to the disk when you save the notebook. The output cells are lost when you reload the notebook - if you want to avoid this, just _pair_ the text file to an `.ipynb` file. If you want to convert text formats to notebooks programmatically, use one of ```shell jupytext --to ipynb *.md # convert all .md files to notebooks with no outputs jupytext --to ipynb --execute *.md # convert all .md files to notebooks and execute them jupytext --set-formats ipynb,md --execute *.md # convert all .md files to paired notebooks and execute them ``` Conversions the other way use a similar format ```shell jupytext --to md *.ipynb # convert all .ipynb files to .md files ``` ## I want a specific cell to be commented out in the paired script That's possible! See how to [activate or deactivate cells](advanced-options.md#active-and-inactive-cells). ## Which files should I version control? Unless you want to version the outputs, you should version *only the text representation*. The paired `.ipynb` file can safely be deleted. It will be recreated locally the next time you open the notebook (from the text file) and save it. Note that if you version both the `.md` and `.ipynb` files, you can configure `git diff` to [ignore the diffs on the `.ipynb` files](https://github.com/mwouts/jupytext/issues/251). ## I have modified a text file, but git reports no diff for the paired `.ipynb` file The synchronization between the two files happens when you reload and *save* the notebook in Jupyter, or when you explicitly run `jupytext --sync`. If you want to force the synchronization on every commit, you could use `jupytext` as a [pre-commit hook](using-pre-commit.md). ## Jupyter warns me that the file has changed on disk By default, Jupyter tries to save your notebooks every 2 minutes. If you have edited the text representation in another editor, it will detect that and ask you if you want to either overwrite, or _reload_ the notebook from disk. You should simply click on _Reload_. Note you can deactivate Jupyter's autosave function with the _Autosave Document_ setting in JupyterLab (search for _autosave_ in the _advanced settings editor_). ## When I reload, Jupyter warns me that my notebook has unsaved changes That happens if you have edited both the notebook and the paired text file at the same time... If you know which version you want to keep, save it and reload the other. If you want to compare and merge both versions, backup the text file (with e.g. `git stash`), save the notebook, and merge the updated paired file with the backup (with e.g. `git stash pop`). Then, refresh the notebook in Jupyter. ## Jupyter complains that the `.ipynb` file is more recent than the text representation This happens if you have edited the `.ipynb` file outside of Jupyter. This is a safeguard to avoid overwriting the notebook with an outdated text file. In this case, a manual action is requested. Remove the paired `.md` or `.py` file if it is outdated, otherwise, edit and save it to update the file timestamp. ## Can I use Jupytext with JupyterHub, Binder, Nteract, Colab, Saturn or Azure? Jupytext is compatible with JupyterHub (execute `pip install jupytext --user` to install it in user mode) and with Binder (add `jupytext` to the project requirements). If you use another editor than JupyterLab, you probably can't get Jupytext there. However, you can still use Jupytext at the command line to manually sync the two representations of the notebook: ```shell jupytext --set-formats ipynb,py:light notebook.ipynb # Pair a notebook to a light script jupytext --sync notebook.ipynb # Sync the two representations ``` ## Can I re-write my git history to use text files instead of notebooks? Indeed, you could substitute every `.ipynb` file in the project history with its Jupytext Markdown representation. Technically this is available in just one command, which results in a complete rewrite of the history. Please experiment that in a branch, and think twice before pushing the result... ```shell git filter-branch --tree-filter 'jupytext --to md */*.ipynb && rm -f */*.ipynb' HEAD ``` See the result and the cleaner diff history in the case of the [Python Data Science Handbook](https://github.com/mwouts/PythonDataScienceHandbook/tree/jupytext_no_ipynb). ================================================ FILE: docs/formats-markdown.md ================================================ # Notebooks as Markdown ## MyST Markdown [MyST (Markedly Structured Text)][myst-parser] is a markdown flavor that "implements the best parts of reStructuredText". It provides a way to call Sphinx directives and roles from within Markdown, using a *slight* extension of CommonMark markdown. [MyST-NB][myst-nb] and [Jupyter Book][jupyter-book] builds on this markdown flavor, to offer direct conversion of Jupyter Notebooks into Sphinx documents. Similar to the jupytext Markdown format, MyST Markdown uses code blocks to contain code cells. The difference though, is that the metadata is contained in a YAML block: ````md ```{code-cell} ipython3 --- other: more: true tags: [hide-output, show-input] --- print("Hallo!") ``` ```` The `ipython3` here is purely optional, as an aide for syntax highlighting. In the round-trip, it is copied from `notebook.metadata.language_info.pygments_lexer`. Also, where possible the conversion will use the short-hand metadata format (see the [MyST guide](https://myst-parser.readthedocs.io/en/latest/using/syntax.html#parameterizing-directives)): ````md ```{code-cell} ipython3 :tags: [hide-output, show-input] print("Hallo!") ``` ```` Raw cells are also represented in a similar fashion: ````md ```{raw-cell} :raw_mimetype: text/html Bold text ``` ```` Markdown cells are not wrapped. If a markdown cell has metadata, or directly proceeds another markdown cell, then a [block break] will be inserted above it, with an (optional) single line JSON representation of the metadata: ```md +++ {"slide": true} This is a markdown cell with metadata +++ This is a new markdown cell with no metadata ``` See for instance how our `World population.ipynb` notebook is [represented](https://github.com/mwouts/jupytext/blob/main/demo/World%20population.myst.md#) in the `myst` format. **Note**: The `myst` format requires Python >= 3.6 **Tip**: You can use the [myst-highlight] VS Code extension to provide better syntax highlighting for this format. [myst-parser]: https://myst-parser.readthedocs.io [myst-nb]: https://myst-nb.readthedocs.io [jupyter-book]: https://jupyterbook.org [block break]: https://myst-parser.readthedocs.io/en/latest/using/syntax.html#block-breaks [myst-highlight]: https://marketplace.visualstudio.com/items?itemName=ExecutableBookProject.myst-highlight ## Quarto [Quarto](https://quarto.org/) is a scientific and technical publishing system built on Pandoc. If you have `quarto` installed, Jupytext lets you edit `.qmd` documents as notebooks in Jupyter, and pair `.ipynb` notebooks with `.qmd` notebooks. The conversion from `.ipynb` to `.qmd` and back directly calls `quarto convert`, and consequently requires an installation of Quarto v0.2.134 or higher. Note that the round trip of `.ipynb` to `.qmd` to `.ipynb` has the effect of concatenating consecutive Markdown cells and turning raw cells into Markdown cells (since `.qmd` files represent all content as either Markdown or code cells). ## R Markdown [R Markdown](https://rmarkdown.rstudio.com/authoring_quick_tour.html) is [RStudio](https://www.rstudio.com/)'s format for notebooks, with support for R, Python, and many [other languages](https://bookdown.org/yihui/rmarkdown/language-engines.html). Jupytext's implementation of R Markdown is very similar to that of the Markdown format. The major difference is on code cells, which use R Markdown's convention, i.e. the language and options are surrounded by curly brackets, and the cell metadata are encoded as R objects. For instance our cell with the `parameters` tags would be represented as: ```{python tags=c("parameters")} param = 5 ``` Python and R notebooks represented in the R Markdown format can run both in Jupyter and RStudio. Note that you can change the default Python environment in RStudio with `RETICULATE_PYTHON` in a `.Renviron` file, see [here](https://github.com/mwouts/jupytext/issues/267#issuecomment-506994930). See how our `World population.ipynb` notebook in the [demo folder](https://github.com/mwouts/jupytext/tree/main/demo) is represented in [R Markdown](https://github.com/mwouts/jupytext/blob/main/demo/World%20population.Rmd). ## Jupytext Markdown Jupytext can save notebooks as [Markdown](https://daringfireball.net/projects/markdown/syntax) documents. This format is well adapted to tutorials, books, or more generally notebooks that contain more text than code. Notebooks represented in this form are well rendered by most Markdown editors or renderers, including GitHub. Like all the Jupytext formats, Jupytext Markdown notebooks start with an (optional) YAML header. This header is used to store selected notebook metadata like the kernel information, together with Jupytext's format and version information. ``` --- jupyter: jupytext: text_representation: extension: .md format_name: markdown format_version: '1.1' jupytext_version: 1.1.0 kernelspec: display_name: Python 3 language: python name: python3 --- ``` You can add custom notebook metadata like `author` or `title` under the `jupyter:` section, it will be synchronized with the notebook metadata. And if you wish to export more metadata from the notebook, have a look at the paragraph on [metadata filtering](advanced-options.md#metadata-filtering). In the Markdown format, markdown cells are inserted verbatim and separated with two blank lines. If you'd like that cell breaks also occurs on Markdown headers, add a `split_at_heading: true` entry in the `jupytext` section in the YAML header, or if you want that option to be the default for all Markdown documents in Jupyter, activate the option in the [`jupytext.toml` configuration file](config.md): ``` split_at_heading = true ``` Code cells are encoded using the classical triple backticks, followed by the notebook language. Cell metadata are appended after the language information, with a `key=value` syntax, where `value` is encoded in JSON format. For instance, in a Python notebook, a simple code cell with a `parameters` tag is represented as: ```python tags=["parameters"] param = 5 ``` Code snippets are turned into code cells in Jupyter as soon as they have an explicit language, when that language is supported in Jupyter. Thus, you have a code snippet that you don't want to execute in Jupyter, you can either - remove the language information, - or, start the code snippet with a triple tilde, e.g. `~~~python`, instead of ` ```python` - or, add an `active="md"` cell metadata, or a `.noeval` attribute after the language information, e.g. ` ```python .noeval ` - or, surround the code snippet with explicit Markdown cell markers (see below). Raw cells are delimited with HTML comments, and accept cell metadata in the same key=value format: raw text raw cell with metadata Markdown cells can also have explicit markers: use one of `` or `` or `` and the corresponding `` counterpart. Note that the `` and `` cells markers are [foldable](https://code.visualstudio.com/docs/editor/codebasics#_folding) in VS Code, and that you can also insert a title there, e.g. ``. Cell metadata are accepted in the format `key="value"` (`"value"` being encoded in JSON) as for the other cell types. For a concrete example, see how our `World population.ipynb` notebook in the [demo folder](https://github.com/mwouts/jupytext/tree/main/demo) is represented in [Markdown](https://github.com/mwouts/jupytext/blob/main/demo/World%20population.md#). ## Pandoc Markdown Pandoc, the _Universal document converter_, can read and write Jupyter notebooks - see [Pandoc's documentation](https://pandoc.org/MANUAL.html#creating-jupyter-notebooks-with-pandoc). In Pandoc Markdown, all cells are marked with pandoc divs (`:::`). The format is therefore slightly more verbose than the Jupytext Markdown format. See for instance how our `World population.ipynb` notebook is [represented](https://github.com/mwouts/jupytext/blob/main/demo/World%20population.pandoc.md#) in the `md:pandoc` format. If you wish to use that format, please install `pandoc` in version 2.7.2 or above, with e.g. `conda install pandoc -c conda-forge`. ================================================ FILE: docs/formats-scripts.md ================================================ # Notebooks as code ## The `percent` format The `percent` format is a representation of Jupyter notebooks as scripts, in which all cells are explicitly delimited with a commented double percent sign `# %%`. The `percent` format is currently available for these [languages](https://github.com/mwouts/jupytext/blob/main/src/jupytext/languages.py). The format was introduced by Spyder in 2013, and is now supported by many editors, including - [Spyder IDE](https://docs.spyder-ide.org/editor.html#defining-code-cells), - [Hydrogen](https://nteract.gitbooks.io/hydrogen/docs/Usage/NotebookFiles.html#notebook-export), a package for Atom, - [VS Code](https://code.visualstudio.com/docs/python/jupyter-support-py#_jupyter-code-cells), - [Python Tools for Visual Studio](https://docs.microsoft.com/en-us/visualstudio/python/python-interactive-repl-in-visual-studio?view=vs-2019#work-with-code-cells), - and [PyCharm Professional](https://www.jetbrains.com/help/pycharm/editing-jupyter-notebook-files.html#edit-content). Our implementation of the `percent` format is as follows: cells can have - a title - a cell type (`markdown`, `md` or `raw`, omitted for code cells) - and cell metadata like in this example: ```python # %% Optional title [cell type] key="value" ``` In the `percent` format, our previous example becomes: ```python # %% [markdown] # This is a multiline # Markdown cell # %% [markdown] # Another Markdown cell # %% # This is a code cell class A(): def one(): return 1 def two(): return 2 ``` In the case of Python scripts, Markdown cells do accept multiline comments: ```python # %% [markdown] """ This is a Markdown cell that uses multiline comments """ ``` By default Jupytext will use line comments when it converts your Jupyter notebooks for `percent` scripts. If you prefer to use multiline comments for all text cells, add a `{"jupytext": {"cell_markers": "\"\"\""}}` metadata to your notebook, either with the notebook metadata editor in Jupyter, or at the command line: ```bash jupytext --update-metadata '{"jupytext": {"cell_markers": "\"\"\""}}' notebook.ipynb --to py:percent ``` If you want to use multiline comments for all your paired notebooks, you could also add ```python cell_markers = '"""' ``` to your [`jupytext.toml` configuration file](config.md). See how our `World population.ipynb` notebook is [represented](https://github.com/mwouts/jupytext/blob/main/demo/World%20population.pct.py) in the `percent` format. ## The `marimo` format Since Jupytext v1.19, you can use the `py:marimo` format, in which text notebooks are converted to Jupyter notebooks, and back, using [Marimo](https://marimo.io/). Our [implementation](https://github.com/mwouts/jupytext/blob/main/src/jupytext/marimo.py) calls Marimo's converter directly (this requires Marimo v1.16.3 or later). Please note that: - The format is available only for Python notebooks. - Marimo will add a suffix to variables that are defined multiple times, to make them compatible with its reactive evaluation. - Notebook and cell metadata (except tags) cannot be stored in the `py:marimo` file. - As of Marimo 0.17.8, empty cells are removed during round trips. You can determine whether a given notebook is stable over a Marimo round trip with ``` jupytext --test --to py:marimo your_notebook.ipynb jupytext --test --to ipynb your_marimo_script.py ``` 💡 If you notice unexpected changes, and can reproduce them with `marimo convert` and `marimo export ipynb --sort top-down`, report the issue on the Marimo [tracker](https://github.com/marimo-team/marimo/issues), and ping `@mwouts`. If you believe the issue is on Jupytext’s side, use the Jupytext [issue tracker](https://github.com/mwouts/jupytext/issues). ## The `light` format The `light` format was introduced by Jupytext. That format can represent any script in one of these [languages](https://github.com/mwouts/jupytext/blob/main/src/jupytext/languages.py) as a Jupyter notebook. When a script in the `light` format is converted to a notebook, Jupytext code paragraphs are turned into code cells, and comments that are not adjacent to code are converted to Markdown cells. Cell breaks occurs on blank lines outside of functions, classes or multiline comments. For instance, in this example we have three cells: ```python # This is a multiline # Markdown cell # Another Markdown cell # This is a code cell class A(): def one(): return 1 def two(): return 2 ``` Code cells can contain multiple code paragraphs. In that case Jupytext uses an explicit start-of-cell delimiter that is, by default, `# +` (`// +` in C++, etc). The default end of cell delimiter is `# -`, and can be omitted when followed by another explicit start of cell marker, or the end of the file: ```python # + # A single code cell made of two paragraphs a = 1 def f(x): return x+a ``` Metadata can be associated to a given cell using a key/value representation: ```python # + key="value" # A code cell with metadata # + [markdown] key="value" # A Markdown cell with metadata ``` The `light` format can use custom cell markers instead of `# +` or `# -`. If you prefer to mark cells with VS Code/PyCharm (resp. Vim) folding markers, set `"cell_markers": "region,endregion"` (resp. `"{{{,}}}"`) in the jupytext section of the notebook metadata. If you want to configure this as a global default, add either ```python cell_markers = "region,endregion" # Use VS Code/PyCharm region folding delimiters ``` or ```python cell_markers = "{{{,}}}" # Use Vim region folding delimiters ``` to your [`jupytext.toml` configuration file](config.md#). See how our `World population.ipynb` notebook is [represented](https://github.com/mwouts/jupytext/blob/main/demo/World%20population.lgt.py) in that format. ## The `nomarker` format The `nomarker` format is a variation of the `light` format with no cell marker at all. Please note that this format does not provide round-trip consistency - code cells are split on code paragraphs. By default, the `nomarker` format still includes a YAML header - if you prefer to also remove the header, set `"notebook_metadata_filter": "-all"` in the jupytext section of your notebook metadata. ## Sphinx-gallery scripts Another popular notebook-like format for Python scripts is the Sphinx-gallery [format](https://sphinx-gallery.github.io/stable/syntax.html). Scripts that contain at least two lines with more than twenty hash signs are classified as Sphinx-Gallery notebooks by Jupytext. Comments in Sphinx-Gallery scripts are formatted using reStructuredText rather than markdown. They can be converted to markdown for a nicer display in Jupyter by adding a `sphinx_convert_rst2md = True` line to your Jupytext configuration file. Please note that this is a non-reversible transformation—use this only with Binder. Revert to the default value `sphinx_convert_rst2md = False` when you edit Sphinx-Gallery files with Jupytext. Turn a GitHub repository containing Sphinx-Gallery scripts into a live notebook repository with [Binder](https://mybinder.org/) and Jupytext by adding only two files to the repo: - `binder/requirements.txt`, a list of the required packages (including `jupytext`) - a [`jupytext.toml` configuration file](config.md#) with the following contents: ``` preferred_jupytext_formats_read = "py:sphinx" sphinx_convert_rst2md = true ``` Our sample notebook is also represented in `sphinx` format [here](https://github.com/mwouts/jupytext/blob/main/demo/World%20population.spx.py). ================================================ FILE: docs/index.md ================================================ ```{include} ../README.md :relative-docs: docs/ :start-after: ``` ## Table of Contents ```{toctree} :maxdepth: 1 install.md text-notebooks.md paired-notebooks.md jupyterlab-extension.md vs-code.md jupyter-collaboration.md config.md advanced-options.md formats-scripts.md formats-markdown.md languages.md using-cli.md using-pre-commit.md faq.md tutorials.md contributing.md developing.md changelog.md ``` ================================================ FILE: docs/install.md ================================================ # Installation Installing Jupytext is as simple as ```bash pip install jupytext ``` or ```bash conda install jupytext -c conda-forge ``` You should run either one of these commands in the Python environment from which you launch JupyterLab. Once you have installed Jupytext, you need to restart Jupyter to be able to use Jupytext within Jupyter. If the Python environment where the Jupyter server runs is read-only, for instance if your server is started using JupyterHub, you can still install Jupytext in user mode with: ``` /path_to_your_jupyter_environment/python -m pip install jupytext --user ``` Jupytext comes with a series of tools and plugin, which we will now briefly describe. ## Jupytext's contents manager Jupytext provides a contents manager that let Jupyter open and save notebooks as text files. Jupytext's contents manager is activated automatically by Jupytext's server extension. When you start either `jupyter lab` or `jupyter notebook`, you should see a line that looks like: ```bash [I 10:28:31.646 LabApp] [Jupytext Server Extension] Changing NotebookApp.contents_manager_class from LargeFileManager to jupytext.TextFileContentsManager ``` If you don't see the message above after a fresh restart of your Jupyter server, please enable our server extension explicitly with ``` jupyter serverextension enable jupytext ``` When [`jupyter-fs>=1.0.0`](https://github.com/jpmorganchase/jupyter-fs) is being used along with `jupytext`, use `SyncMetaManager` as the contents manager for `jupyter-fs` as `jupytext` do not support async contents manager which is used in default `MetaManager` of `jupyter-fs`. The `jupyter-fs` config must be as follows: ```json { "ServerApp": { "contents_manager_class": "jupyterfs.metamanager.SyncMetaManager", } } ``` so that `jupytext` will create its own contents manager derived from `SyncMetaManager`. ## Jupytext commands in JupyterLab Jupytext comes with a frontend extension for JupyterLab which provides pairing commands (accessible with View / Activate Command Palette, or Ctrl+Shift+C): ![](images/pair_commands.png) The Jupytext extension for JupyterLab is bundled with Jupytext. It should be installed and enabled automatically. You can `enable` or `disable` it manually with either ``` jupyter labextension enable jupyterlab-jupytext jupyter labextension disable jupyterlab-jupytext ``` From Jupytext 1.16.0 on, the version of the extension is compatible with JupyterLab 4.x only. If you wish to use Jupytext with JupyterLab 3.x or older, please - install the `jupytext` package using `pip` or `conda` - and then, install the last version of the `jupyterlab-jupytext` extension that is compatible with your version of JupyterLab, i.e. ``` jupyter labextension install jupyterlab-jupytext@1.3.11 # for JupyterLab 3.x jupyter labextension install jupyterlab-jupytext@1.2.2 # for JupyterLab 2.x jupyter labextension install jupyterlab-jupytext@1.1.1 # for JupyterLab 1.x ``` ## Jupytext menu in Jupyter Notebook In Jupyter Notebook 7 you can use the same pairing commands as in JupyterLab (see above). In Jupyter Notebook **classic**, i.e. Jupyter Notebook 6.x and below, Jupytext used to provided an extension that added a Jupytext section in the File menu. ![](images/jupytext_menu.png) That extension is available only for `jupytext<1.16`, and is automatically installed. If need be, you can install and activate it manually with ``` jupyter nbextension install --py jupytext [--user] jupyter nbextension enable --py jupytext [--user] ``` See also [Issue #1095](https://github.com/mwouts/jupytext/issues/1095) where we discuss how to add a Jupytext menu to JupyterLab and Notebook 7.x. ## Jupytext's command line interface Jupytext provides a `jupytext` command in the terminal that you can use to pair, synchronize or convert notebooks in different formats. The CLI is documented [here](using-cli.md). Run `jupytext --version` to check which version of Jupytext is installed. ## Jupytext as a Python library Jupytext is also available as a Python library. The `jupytext` package exposes the same `read`, `write`, `reads` and `writes` functions than `nbformat`, meaning that you can read and write notebooks within Python like this: ``` import jupytext # read a notebook from a file nb = jupytext.read("notebook.py") # or from a string nb = jupytext.reads(text, fmt="md:myst") # write a notebook to a file in the 'py:percent' format jupytext.write(nb, "notebook.py", fmt="py:percent") ``` In the above, `nb` is an instance of an `nbformat` `NotebookNode`. The notebook format is documented in the [nbformat documentation](https://nbformat.readthedocs.io). ================================================ FILE: docs/jupyter-collaboration.md ================================================ # Jupyter Collaboration [Jupyter Collaboration](https://github.com/jupyterlab/jupyter-collaboration) is an official Jupyter extension that enables real-time collaboration in JupyterLab. ## Autoreload Feature Beyond its collaboration features, Jupyter Collaboration also provides automatic file reloading. When the extension is installed, JupyterLab auto-reloads any file that gets modified on disk. This way, you can edit your notebook and text files outside of Jupyter, and the changes appear in Jupyter automatically without having to manually reload the document. Note that Jupyter Collaboration also comes with an auto-save feature. By [default](https://github.com/jupyterlab/jupyter-collaboration/blob/67453e04dad30978d42fdef07040ae94cabe2bf0/projects/jupyter-server-ydoc/jupyter_server_ydoc/app.py#L45-L84), notebooks and text documents are saved one second after your last change. ## Collaborating on text notebooks Currently, the real-time collaboration feature can be used: - in the notebook editor when opening `.ipynb` notebooks - in the text editor when opening `.py` or `.md` files However, it does not yet work on `.py` and `.md` files opened as notebooks. If you want to collaborate on text notebooks, we recommend that you collaborate on paired notebooks (see [#1432](https://github.com/mwouts/jupytext/issues/1432)). ## Known issues While using Jupytext and Jupyter Collaboration together mostly works, we have noticed a few side effects. Please review the list of [known issues](https://github.com/mwouts/jupytext/issues?q=state%3Aopen%20label%3A%22jupyter-collaboration%22) and make sure that you are comfortable with these. ================================================ FILE: docs/jupyterlab-extension.md ================================================ # Frontend extension Recent versions of Jupytext (`>=1.16.0`) ships frontend extension that enables users to create text notebooks and pair notebooks from main menu of JupyterLab 4 and Notebook 7. In addition, the frontend extension adds selected Jupytext text notebook formats to launcher in the `Jupytext` section so that users can launch text notebooks as they launch a regular notebook from JupyterLab launcher. ## Launcher icons After installing Jupytext extension, users will have a new category in the launcher called Jupytext as shown below: ![](../jupyterlab/packages/jupyterlab-jupytext-extension/ui-tests/tests/jupytext-launcher.spec.ts-snapshots/launcher-category-jupytext-linux.png) Users can remove and/or add new formats to the Jupytext section _via_ `Settings>Jupytext`. ![](../jupyterlab/packages/jupyterlab-jupytext-extension/ui-tests/tests/jupytext-settings.spec.ts-snapshots/jupytext-settings-panel-jupytext-linux.png) By (un)selecting different formats, users can filter the items in launcher and main menu. **Note** that users need to refresh the current browser tab when they modify the settings for them to take effect. ## Main menu It is also possible to create new text notebooks and/or pair existing notebooks from main menu and dedicated Jupytext main menu, respectively. Following screenshot shows the `New Text Notebook` submenu available in `File` menu. ![](../jupyterlab/packages/jupyterlab-jupytext-extension/ui-tests/tests/jupytext-menu.spec.ts-snapshots/opened-jupytext-menu-file-new-text-notebook-jupytext-linux.png) Similarly, to pair existing notebooks, users can go to `Jupytext` menu on main menu as shown below: ![](../jupyterlab/packages/jupyterlab-jupytext-extension/ui-tests/tests/jupytext-menu.spec.ts-snapshots/opened-jupytext-menu-file-jupytext-jupytext-linux.png) All the options are greyed out in the above screenshot as there is no notebook widget currently active. Once the user opens a new notebook, the options will become available. ================================================ FILE: docs/languages.md ================================================ # Supported Languages Jupytext works with notebooks in any of the following languages: - Bash - C# - C++ (using either the xeus-cling or the ROOT kernel) - Clojure - Coconut - F# - Gnuplot - Go - Groovy - Haskell - IDL - Java - Javascript - Julia - Logtalk - Lua - Matlab - OCaml - Octave - PowerShell - Python - q/kdb+ - R - Robot Framework - Rust/Evxcr - Sage - SAS - Scala - Scheme - Script of Script - Stata - Tcl - TypeScript - Wolfram Language - Note that Jupytext uses the non-standard `.wolfram` file extension for Wolfram Language files to avoid conflicts with Matlab. - Xonsh Extending Jupytext to more languages should be easy, see the sections on [contributing to](contributing.md) and [developing](developing.md) Jupytext. ================================================ FILE: docs/make.bat ================================================ @ECHO OFF pushd %~dp0 REM Command file for Sphinx documentation if "%SPHINXBUILD%" == "" ( set SPHINXBUILD=sphinx-build ) set SOURCEDIR=. set BUILDDIR=_build if "%1" == "" goto help %SPHINXBUILD% >NUL 2>NUL if errorlevel 9009 ( echo. echo.The 'sphinx-build' command was not found. Make sure you have Sphinx echo.installed, then set the SPHINXBUILD environment variable to point echo.to the full path of the 'sphinx-build' executable. Alternatively you echo.may add the Sphinx directory to PATH. echo. echo.If you don't have Sphinx installed, grab it from echo.http://sphinx-doc.org/ exit /b 1 ) %SPHINXBUILD% -M %1 %SOURCEDIR% %BUILDDIR% %SPHINXOPTS% goto end :help %SPHINXBUILD% -M help %SOURCEDIR% %BUILDDIR% %SPHINXOPTS% :end popd ================================================ FILE: docs/paired-notebooks.md ================================================ # Paired notebooks Both classical Jupyter Notebooks in the `.ipynb` format, and [text notebooks](text-notebooks.md), have great qualities. The former is a well established standard, contains all the notebook outputs, while the latter is lighter, easier to edit, and well suited for version control. _Paired notebooks_ give you the best of both worlds. They work as follows: - When a paired notebook is opened, the inputs are loaded from the most recent file in the pair, while the outputs are loaded from the `.ipynb` file, if it exists - When a paired notebook is saved, all the files in the pair are updated (or recreated) with the new notebook content. This means, in particular, that you can put under version control only the `.py` or `.md` representation of the notebook. When your collaborators check-out the updates on the text notebook, open it, then save it in Jupyter, the corresponding `.ipynb` file will be updated or even re-created if necessary. ## How to pair a notebook In JupyterLab, pair your notebook to one or more text formats with the [Jupytext commands](install.md#jupytext-commands-in-jupyterlab): ![](images/pair_commands.png) These commands simply add a `"jupytext": {"formats": "ipynb,md"}` entry to the notebook metadata. You can also configure the notebook pairing [globally](config.md) for all your notebooks. ## Can I edit a notebook simultaneously in Jupyter and in a text editor? When saving a paired notebook, Jupyter updates both the `.ipynb` and its text representation. The text representation can be edited outside of Jupyter. When the notebook is refreshed in Jupyter, the input cells are read from the text file, and the output cells from the `.ipynb` file. It is possible (and convenient) to leave the notebook open in Jupyter while you edit its text representation. However, you don't want the two editors to save the notebook simultaneously. To avoid this: - deactivate Jupyter's autosave, and - make sure you reload the notebook when you switch back from the editor to Jupyter. In case you forgot to reload, and saved the Jupyter notebook while the text representation had changed, no worries: Jupyter will ask you which version you want to keep: ![](https://github.com/mwouts/jupytext-screenshots/raw/master/JupytextDocumentation/NotebookChanged.png) If that happens, simply select the version that has the most recent changes (or: make a copy of the `.py` notebook on disk, click on _overwrite_ in Jupyter, and reconcile manually the two `.py` files). ================================================ FILE: docs/text-notebooks.md ================================================ # Text notebooks Jupytext can save Jupyter Notebooks as text files, with e.g. a `.py` or `.md` extension. These text files only contain the inputs of your notebooks, as well as [selected metadata](advanced-options.md#metadata-filtering). Text notebooks are well suited for version control. They are standard text files and you can easily edit or refactor them in the editor of your choice. The outputs of the notebook are not stored on disk, unless you decide to [pair](paired-notebooks.md) your text notebook to a regular `.ipynb` file. ## How to open a text notebook in JupyterLab Once you have [installed](install.md) Jupytext, you can open and run `.py` and `.md` files as notebooks. ### With a right click Right click on the text notebook, then select _Open With_ → _Notebook_: ![](images/jupyterlab_right_click.png) Notes: * you can achieve the same result if you use _Open With_ → _Jupytext Notebook_ * to open links to `.md` files in notebooks with the Notebook editor, you will need `jupyterlab>=3.6.0`. ### With a double click Right clicking and the _Open With_ submenu allows you to choose among several ways to open a file (several **viewers**, in JupyterLab jargon); and when you double click instead, you open the file using **its default viewer**. The default viewer for text notebooks is by default configured to be the **Editor** (which means: text editor); if you'd prefer to have the text files open as a notebook instead, you have the option to **redefine the default viewer**, which is something defined for each document type. Since version 1.15.1, `jupytext` comes with a helper command that allows you to do this from the command line; and essentially you would just need to run ```bash jupytext-config set-default-viewer ``` See also [the last section below](#more-on-default-viewers) for alternative means to change and inspect the default viewers configuration ## How to open a text notebook in Jupyter notebook (nb7) As of July 2023, Jupyter Notebook now comes as version 7.x - and is known in short as nb7 nb7 being built on top of JupyterLab, the principles described above apply as well in this context; which means that * you can always right-click a file and select *Open With* → *Notebook*; * and if you have properly defined the default viewers as described above, you can also double-click a file to open it as a notebook. ## How to open a text notebook in Jupyter Notebook (classic) Previous releases of Jupyter Notebook, i.e. up to version 6, were known as notebook classic By default, notebook classic opens scripts and Markdown documents as notebooks. If you want to open them with the text editor, select the document and click on _edit_: ![](https://github.com/mwouts/jupytext-screenshots/raw/master/JupytextDocumentation/OpenAsText.png) ## How to decide which extensions are notebooks By default, Jupytext will classify documents with a `.py`, `.R`, `.jl`, `.md`, `.Rmd`, `.qmd` extension (and more!) as notebooks. If you prefer to limit the notebook type to certain extensions, you can add a `notebook_extensions` option to your [Jupytext config file (`jupytext.toml`)](config.md) configuration file with, for instance, the following value: ``` notebook_extensions = "ipynb,md,qmd,Rmd" ``` ## More on default viewers ### `jupytext-config` This command has more options than the one shown above; in particular: * you can use `jupytext-config` to set only some of the default viewers; for example, if you want to have your `.py` and `.md` files open as a notebook when you double-click them e.g. `jupytext-config set-default-viewer python markdown` * you can use `jupytext-config` to inspect the current configuration, e.g. `jupytext-config list-default-viewer` * you can use `jupytext-config unset-default-viewer python` to remove some of the settings Here's an example of a session, starting from the default config of JupyterLab ```bash # starting from the default config of JupyterLab $ jupytext-config list-default-viewer # we add the default viewer for 2 doctypes $ jupytext-config set-default-viewer python markdown # we check what was done $ jupytext-config list-default-viewer python: Jupytext Notebook markdown: Jupytext Notebook # we can now remove the default viewer for markdown $ jupytext-config unset-default-viewer markdown # and check again $ jupytext-config list-default-viewer python: Jupytext Notebook $ ``` ### From JupyterLab settings dialog Alternatively to using `jupytext-config`, you can also find the configuration of the default viewers from JupyterLab interactively; to do so, go to _Settings_, _Advanced Settings Editor_, and in the JSON view for the `Document Manager` copy-paste the following settings (or the subset that matches your use case): ```json { "defaultViewers": { "markdown": "Jupytext Notebook", "myst": "Jupytext Notebook", "r-markdown": "Jupytext Notebook", "quarto": "Jupytext Notebook", "julia": "Jupytext Notebook", "python": "Jupytext Notebook", "r": "Jupytext Notebook" } } ``` Here is a screencast of the steps to follow: ![](images/jupyterlab_default_viewer.gif) ================================================ FILE: docs/tutorials.md ================================================ # Blog posts and talks Over the course of the years I wrote a few different blog posts about Jupytext, about text notebooks, their integration with the most popular IDEs, etc. They might help you get started with Jupytext: - Read the original [announcement](https://towardsdatascience.com/introducing-jupytext-9234fdff6c57) in _Towards Data Science_ (Sept. 2018), - Watch the [PyParis talk](https://github.com/mwouts/jupytext_pyparis_2018/blob/master/README.md) (Nov. 2018), - Read our article on [Jupytext and Papermill](https://medium.com/capital-fund-management/automated-reports-with-jupyter-notebooks-using-jupytext-and-papermill-619e60c37330) in _CFM Insights_ (Sept. 2019) - See how you can edit [Jupyter Notebooks in VS Code or PyCharm](https://towardsdatascience.com/jupyter-notebooks-in-the-ide-visual-studio-code-versus-pycharm-5e72218eb3e8) with (or without!) Jupytext (Jan. 2020) - Watch the [JupyterCon 2020 talk](https://github.com/mwouts/jupytext_jupytercon2020/blob/master/README.md) on Jupytext (Oct. 2020), - or, try Jupytext online with [binder](https://mybinder.org/v2/gh/mwouts/jupytext/main?urlpath=lab/tree/demo/get_started.ipynb)! ================================================ FILE: docs/using-cli.md ================================================ # Jupytext CLI ## Command line conversion Jupytext provides command line interface for converting notebooks between the different formats. ```bash jupytext --to py notebook.ipynb # convert notebook.ipynb to a .py file jupytext --to py:percent notebook.ipynb # convert notebook.ipynb to a .py file in the double percent format jupytext --to py:percent --opt comment_magics=false notebook.ipynb # same as above + do not comment magic commands jupytext --to markdown notebook.ipynb # convert notebook.ipynb to a .md file jupytext --output script.py notebook.ipynb # convert notebook.ipynb to a script.py file jupytext --to notebook notebook.py # convert notebook.py to an .ipynb file with no outputs jupytext --update --to notebook notebook.py # update the input cells in the .ipynb file and preserve outputs and metadata jupytext --to md --test notebook.ipynb # Test round trip conversion jupytext --to md --output - notebook.ipynb # display the markdown version on screen jupytext --from ipynb --to py:percent # read ipynb from stdin and write double percent script on stdout ``` Jupytext has a `--sync` mode that updates all the paired representations of a notebook based on timestamps: ```bash jupytext --set-formats ipynb,py notebook.ipynb # Turn notebook.ipynb into a paired ipynb/py notebook jupytext --sync notebook.ipynb # Update whichever of notebook.ipynb/notebook.py is outdated ``` You may also find useful to `--pipe` the text representation of a notebook into tools like `black`: ```bash jupytext --sync --pipe black notebook.ipynb # read most recent version of notebook, reformat with black, save ``` To reorder the imports in your notebook, use ```bash jupytext --pipe 'isort - --treat-comment-as-code "# %%" --float-to-top' notebook.ipynb ``` (remove the `--float-to-top` argument if you prefer to run `isort` per cell). For programs that don't accept pipes, use `{}` as a placeholder for the name of a temporary file that will contain the text representation of the notebook. For instance, run `pytest` on your notebook with: ```bash jupytext --check 'pytest {}' notebook.ipynb # export the notebook in format py:percent in a temp file, run pytest ``` Read more about running `pytest` on notebooks in our example [`Tests in a notebook.md`](https://github.com/mwouts/jupytext/blob/main/demo/Tests%20in%20a%20notebook.md#). Note also that on Windows you need to use double quotes instead of single quotes and type e.g. `jupytext --check "pytest {}" notebook.ipynb`. Execute `jupytext --help` to access the full documentation. ### Execute notebook cells For convenience, when creating a notebook from text you can execute it: ```bash jupytext --set-kernel - notebook.md # create a YAML header with kernel metadata matching the current python executable jupytext --set-formats md:myst notebook.md # create a YAML header with an explicit jupytext format jupytext --to notebook --execute notebook.md # convert notebook.md to an .ipynb file and run it ``` If you wanted to convert a collection of Markdown files to paired notebooks, and execute them in the current Python environment, you could run: ```bash jupytext --set-formats ipynb,md --execute *.md ``` #### Advanced usage: error tolerance If any notebook cell errors, execution will terminate and `jupytext` will not save the notebook. This can cause headaches as the details of any error would be encoded in the notebook, which would not have been saved. But there's an error-tolerant way to execute a notebook: `jupyter nbconvert` has a mode which will still save a notebook if a cell errors, producing something akin to what would happen if you ran all cells manually in Jupyter's notebook UI. ```bash # First, convert script (py/sh/R/jl etc) -> notebook. May need additional args to define input format etc as above. jupytext --to ipynb script.py # Then, execute notebook in place and allowing cells to produce errors jupyter nbconvert --to ipynb --inplace --execute --allow-errors script.ipynb # One can also combine these to a single command using jupytext --pipe jupytext --to ipynb --pipe-fmt ipynb \ --pipe 'jupyter nbconvert --to ipynb --execute --allow-errors --stdin --stdout' \ script.py ``` In each of the above, `jupyter nbconvert` could be replaced with any alternative tool to execute a jupyter notebook non-interactively, including [papermill](https://github.com/nteract/papermill) which would allow notebook parameterisation (see [@mwouts' post on the topic here](https://github.com/CFMTech/jupytext_papermill_post/blob/master/README.md)). ## Testing the round-trip conversion Representing Jupyter notebooks as scripts requires a solid round trip conversion. You don't want your notebooks (nor your scripts) to change because you are converting them to the other form. Our test suite includes a few hundred tests to ensure that round trip conversion is safe. You can test yourself that the round trip conversion preserves your Jupyter notebooks and scripts. Run for instance: ```bash # Test the ipynb -> py:percent -> ipynb round trip conversion jupytext --test notebook.ipynb --to py:percent # Test the ipynb -> (py:percent + ipynb) -> ipynb (à la paired notebook) conversion jupytext --test --update notebook.ipynb --to py:percent ``` Note that `jupytext --test` compares the resulting notebooks according to its expectations. If you wish to proceed to a strict comparison of the two notebooks, use `jupytext --test-strict`, and use the flag `-x` to report with more details on the first difference, if any. ## Cell and notebook metadata When a scripts is converted to an `.ipynb` notebook, Jupytext will set empty notebook and cell [metadata filters](advanced-options.md) to avoid having notebook or cell metadata added back to the script. Remove these filters if you want to store Jupytext's settings, or the kernel information, in the text file. Cell metadata are available in the `light` and `percent` formats, as well as in the MyST Markdown, R Markdown and Jupytext Markdown formats. R scripts in `spin` format support cell metadata for code cells only. Sphinx Gallery scripts in `sphinx` format do not support cell metadata. A few cell metadata are not included in the text representation of the notebook, and only the most standard notebook metadata are exported - see the section on [metadata filters](advanced-options.md). ================================================ FILE: docs/using-pre-commit.md ================================================ # Pre-commit hook Jupytext includes a hook for the [pre-commit](https://pre-commit.com/) framework. ## Do I need to use this hook? You don't need Jupytext's pre-commit hook if you commit only the `.py` (or `.md`) representation of notebooks in your Git repository. In that case, a possible pre-commit `.pre-commit-config.yaml` configuration that works well with `.py:percent` notebooks (and does not include a `jupytext` pre-commit hook!) is the following: ```yaml repos: - repo: https://github.com/pycqa/isort rev: 5.11.2 hooks: - id: isort args: [--treat-comment-as-code, "# %%", --float-to-top] - repo: https://github.com/astral-sh/ruff-pre-commit rev: v0.0.275 hooks: - id: ruff args: [--fix, --exit-non-zero-on-fix] - repo: https://github.com/psf/black rev: 23.3.0 hooks: - id: black language_version: python3 ``` ## What is the point of having a `jupytext` pre-commit hook? Jupyter keeps paired `.py` and `.ipynb` files in sync, but the synchronization happens only when you _save_ the notebook in Jupyter. If you edit the `.py` file manually, then the `.ipynb` file will be outdated until you reload and save the notebook in Jupyter, or execute `jupytext --sync`. Jupytext's pre-commit hook can enforce this synchronization on commits: ```yaml repos: - repo: https://github.com/mwouts/jupytext rev: v1.14.7 # CURRENT_TAG/COMMIT_HASH hooks: - id: jupytext args: [--sync] ``` If you combine Jupytext with other pre-commit hooks, you must ensure that all hooks will pass on any files you generate. For example, if you have a hook for using `black` to format all your python code, then you should use Jupytext's `--pipe` option to also format newly generated Python scripts before writing them: ```yaml repos: - repo: https://github.com/mwouts/jupytext rev: v1.14.7 # CURRENT_TAG/COMMIT_HASH hooks: - id: jupytext args: [--sync, --pipe, black] additional_dependencies: - black==23.3.0 # Matches hook - repo: https://github.com/psf/black rev: 23.3.0 hooks: - id: black language_version: python3 ``` Tested examples of how to use the pre-commit hook are available in our [tests](https://github.com/mwouts/jupytext/tree/main/tests/external/pre_commit) - see for instance [test_pre_commit_1_sync_with_config.py](https://github.com/mwouts/jupytext/blob/main/tests/external/pre_commit/test_pre_commit_1_sync_with_config.py). ================================================ FILE: docs/vs-code.md ================================================ # VS Code ## The Jupytext Sync Extension You can get the same pairing and synchronization functionality in VS Code as in Jupyter, thanks to the [Jupytext Sync](https://marketplace.visualstudio.com/items?itemName=caenrigen.jupytext-sync) extension for VS Code. The extension is developed by Victor Negîrneac on [GitHub](https://github.com/caenrigen/vscode-jupytext-sync) under a MIT license. ### Installation Install the extension from the [VS Code Marketplace](https://marketplace.visualstudio.com/items?itemName=caenrigen.jupytext-sync) or search for "Jupytext Sync" in the VS Code Extensions view. ### Usage With the Jupytext Sync extension active, open both the `.ipynb` and `.py` paired files in your editor. When you save changes to either file, they are automatically propagated to the other paired file(s). 💡 **Tip:** Save your changes before switching editors. If a file has unsaved edits, VS Code will not auto-reload it when the paired file is saved, until you either save (overwrite) or revert your changes. ![](images/paired_notebook_in_vs_code.png) ### Configuration The Jupytext Sync extension is aware of your `jupytext.toml` or `pyproject.toml` [configuration files](config.md), so you can use those to pair your notebooks or control which metadata you want in the text notebooks. The extension also gives you the option to pair the notebooks individually. Read more about these features in the extension's [documentation](https://marketplace.visualstudio.com/items?itemName=caenrigen.jupytext-sync). ### Requirements The Jupytext Sync extension requires Jupytext 1.17.3 or later to properly identify which files are paired. Additionally, the `jupytext --sync` command gained the ability to detect simultaneous modifications in Jupytext 1.18.0, so we recommend updating to the latest version if possible. ================================================ FILE: jupyterlab/.gitignore ================================================ .build .cache .coverage .pytest_cache .eggs .tox build /dist venv jupytext.egg-info future *.pyc gits* .ipynb_checkpoints jupyterlab_jupytext/labextension # Ignore node_modules and yarn cache node_modules/ .yarn *.bundle.* lib/ *.log .eslintcache .stylelintcache *.egg-info/ .ipynb_checkpoints *.tsbuildinfo # Ignore playwright stuff **/playwright-report **/test-results ================================================ FILE: jupyterlab/.prettierignore ================================================ node_modules **/node_modules **/lib **/labextension **/package.json **/venv **/.venv **/jupyter-config ================================================ FILE: jupyterlab/.yarnrc.yml ================================================ enableImmutableInstalls: false nodeLinker: node-modules ================================================ FILE: jupyterlab/install.json ================================================ { "packageManager": "python", "packageName": "jupytext", "uninstallInstructions": "Use your Python package manager (pip, conda, etc.) to uninstall the package jupytext" } ================================================ FILE: jupyterlab/jupyter-config/jupyter_notebook_config.d/jupytext.json ================================================ { "NotebookApp": { "nbserver_extensions": { "jupyterlab_jupytext": true } } } ================================================ FILE: jupyterlab/jupyter-config/jupyter_server_config.d/jupytext.json ================================================ { "ServerApp": { "jpserver_extensions": { "jupyterlab_jupytext": true } } } ================================================ FILE: jupyterlab/jupyterlab_jupytext/__init__.py ================================================ """Jupyter server and lab extension entry points""" import asyncio from jupytext.reraise import reraise try: from jupytext.async_contentsmanager import ( build_async_jupytext_contents_manager_class, ) except ImportError as err: build_async_jupytext_contents_manager_class = reraise(err) try: from jupytext.sync_contentsmanager import build_sync_jupytext_contents_manager_class except ImportError as err: build_sync_jupytext_contents_manager_class = reraise(err) def load_jupyter_server_extension(app): # pragma: no cover """Use Jupytext's contents manager""" if hasattr(app.contents_manager_class, "formats"): app.log.info( "[Jupytext Server Extension] NotebookApp.contents_manager_class is " "(a subclass of) jupytext.TextFileContentsManager already - OK" ) return # The server extension call is too late! # The contents manager was set at NotebookApp.init_configurables base_class = app.contents_manager_class asynchronous = asyncio.iscoroutinefunction(base_class.get) app.log.info( "[Jupytext Server Extension] Deriving " + ("an Async" if asynchronous else "a ") + "TextFileContentsManager from " + base_class.__name__ ) if asyncio.iscoroutinefunction(base_class.get): app.contents_manager_class = build_async_jupytext_contents_manager_class(base_class) else: app.contents_manager_class = build_sync_jupytext_contents_manager_class(base_class) try: # And rerun selected init steps from https://github.com/jupyter/notebook/blob/ # 132f27306522b32fa667a6b208034cb7a04025c9/notebook/notebookapp.py#L1634-L1638 # app.init_configurables() app.contents_manager = app.contents_manager_class(parent=app, log=app.log) app.session_manager.contents_manager = app.contents_manager # app.init_components() # app.init_webapp() app.web_app.settings["contents_manager"] = app.contents_manager # app.init_terminals() # app.init_signal() except Exception: app.log.error( """[Jupytext Server Extension] An error occurred. Please deactivate the server extension with jupyter serverextension disable jupytext and configure the contents manager manually by adding c.NotebookApp.contents_manager_class = "jupytext.TextFileContentsManager" to your .jupyter/jupyter_notebook_config.py file. """ ) raise def _jupyter_labextension_paths(): return [{"src": "labextension", "dest": "jupyterlab-jupytext"}] ================================================ FILE: jupyterlab/lerna.json ================================================ { "$schema": "node_modules/lerna/schemas/lerna-schema.json", "version": "independent", "npmClient": "yarn" } ================================================ FILE: jupyterlab/package.json ================================================ { "name": "jupyterlab-jupytext-extensions", "version": "1.0.0", "private": true, "files": [], "workspaces": [ "packages/*" ], "scripts": { "build": "lerna run --parallel build", "build:prod": "lerna run --parallel build:prod", "install-ext": "lerna run build:labextension:dev", "clean:all": "lerna run --parallel clean:all", "eslint": "eslint . --ext .ts,.tsx --fix", "eslint:check": "eslint . --ext .ts,.tsx", "prettier": "prettier --write \"**/*{.ts,.tsx,.js,.jsx,.css,.json,.md}\"", "prettier:check": "prettier --list-different \"**/*{.ts,.tsx,.js,.jsx,.css,.json,.md}\"", "stylelint": "jlpm stylelint:check --fix", "stylelint:check": "stylelint --cache \"packages/*/style/**/*.css\"", "stylelint:files": "stylelint --fix", "lint": "jlpm && jlpm prettier && jlpm eslint && jlpm stylelint", "lint:check": "jlpm prettier:check && jlpm eslint:check && jlpm stylelint:check", "update-dependency": "update-dependency --lerna", "watch": "lerna run --parallel watch" }, "devDependencies": { "@typescript-eslint/eslint-plugin": "~6.13.2", "@typescript-eslint/parser": "~6.13.2", "eslint": "~8.55.0", "eslint-config-prettier": "~9.1.0", "eslint-plugin-prettier": "~5.0.1", "lerna": "^7.1.4", "prettier": "^3.5.3", "stylelint": "^16.15.0", "stylelint-config-prettier": "^9.0.4", "stylelint-config-recommended": "^15.0.0", "stylelint-config-standard": "^37.0.0", "stylelint-prettier": "^5.0.3" }, "resolutions": { "tar": "7.5.3", "glob": "10.5.0", "systeminformation": "5.27.14" }, "styleModule": "packages/*/style/index.js", "eslintIgnore": [ "**/*.d.ts", "dist", "*node_modules*", "coverage", "tests", "venv", ".venv" ], "prettier": { "singleQuote": true }, "eslintConfig": { "extends": [ "eslint:recommended", "plugin:@typescript-eslint/eslint-recommended", "plugin:@typescript-eslint/recommended", "plugin:prettier/recommended" ], "parser": "@typescript-eslint/parser", "parserOptions": { "project": "packages/**/tsconfig.json", "sourceType": "module", "tsconfigRootDir": "." }, "plugins": [ "@typescript-eslint" ], "rules": { "@typescript-eslint/naming-convention": [ "error", { "selector": "interface", "format": [ "PascalCase" ], "custom": { "regex": "^I[A-Z]", "match": true } } ], "@typescript-eslint/no-unused-vars": [ "warn", { "args": "none" } ], "@typescript-eslint/no-explicit-any": "off", "@typescript-eslint/no-namespace": "off", "@typescript-eslint/no-use-before-define": "off", "@typescript-eslint/quotes": [ "error", "single", { "avoidEscape": true, "allowTemplateLiterals": false } ], "curly": [ "error", "all" ], "eqeqeq": "error", "prefer-arrow-callback": "error" } }, "stylelint": { "extends": [ "stylelint-config-recommended", "stylelint-config-standard", "stylelint-prettier/recommended" ], "rules": { "no-empty-source": null, "selector-class-pattern": null, "property-no-vendor-prefix": null, "selector-no-vendor-prefix": null, "value-no-vendor-prefix": null } } } ================================================ FILE: jupyterlab/packages/jupyterlab-jupytext-extension/.gitignore ================================================ *.bundle.* lib/ node_modules/ *.egg-info/ .ipynb_checkpoints *.tgz ================================================ FILE: jupyterlab/packages/jupyterlab-jupytext-extension/CHANGELOG.md ================================================ # 1.4.6 (2025-10-18) We have added support for pairing notebooks to Python scripts in the Marimo format # 1.4.5 (2025-08-09) The dependencies of the JupyterLab extension were updated to address [security issues](https://github.com/mwouts/jupytext/security/dependabot): - [#1360](https://github.com/mwouts/jupytext/pull/1360) - [#1410](https://github.com/mwouts/jupytext/pull/1410) - [#1412](https://github.com/mwouts/jupytext/pull/1412) # 1.4.4 (2025-04-05) The context menu has a "New Text Notebook" entry. Thanks to [Mahendra Paipuri](https://github.com/mahendrapaipuri) for this PR ([#1365](https://github.com/mwouts/jupytext/pull/1365))! We have updated the JupyterLab extension dependencies ([#1300](https://github.com/mwouts/jupytext/pull/1300), [#1355](https://github.com/mwouts/jupytext/pull/1355), [#1360](https://github.com/mwouts/jupytext/pull/1360)). Thanks to [Mahendra Paipuri](https://github.com/mahendrapaipuri) for these PRs! The dependencies of the JupyterLab extension were updated to address [security issues](https://github.com/mwouts/jupytext/security/dependabot): - [#1272](https://github.com/mwouts/jupytext/issues/1272) - [#1273](https://github.com/mwouts/jupytext/issues/1273) - [#1280](https://github.com/mwouts/jupytext/issues/1280) - [#1285](https://github.com/mwouts/jupytext/issues/1285) - [#1290](https://github.com/mwouts/jupytext/issues/1290) - [#1304](https://github.com/mwouts/jupytext/pull/1304) # 1.4.3 (2024-05-05) - JupyterLab's dependency `ejs` was updated from 3.1.9 to 3.1.10 ([#1231](https://github.com/mwouts/jupytext/issues/1231)) - JupyterLab's dependency `follow-redirects` was updated from 1.15.4 to 1.15.6 ([#1218](https://github.com/mwouts/jupytext/issues/1218)) - JupyterLab's dependency `ip` was updated from 2.0.0 to 2.0.1 ([#1216](https://github.com/mwouts/jupytext/issues/1216)) # 1.4.2 (2024-01-13) - Fixed an issue about unpairing notebooks from the Jupytext Menu ([#1197](https://github.com/mwouts/jupytext/issues/1197)) - JupyterLab's dependency `follow-redirects` was updated from 1.15.3 to 1.15.4 ([#1203](https://github.com/mwouts/jupytext/issues/1203)) # 1.4.1 (2023-11-27) - The Jupytext Menu is back! And text notebooks can be created directly from the launcher. This is an outstanding contribution by [Mahendra Paipuri](https://github.com/mahendrapaipuri) ([#1154](https://github.com/mwouts/jupytext/issues/1154), [#1163](https://github.com/mwouts/jupytext/issues/1163)). This requires JupyterLab 4.x or Jupyter Notebook 7.x. # 1.4.0 (2023-10-22) - This version of the JupyterLab extension is fully compatible with (and requires) JupyterLab 4.x. # 1.3.11 (2023-10-22) - This version is the same as 1.3.10. It was re-published to include the README that was missing in 1.3.10. # 1.3.10 (2023-10-22) - The server extension for `jupytext` has been moved from core Jupytext to the (Python) `jupyterlab-jupytext` extension. - The JupyterLab extension is now compatible with the [JupyterLab RISE](https://github.com/jupyterlab-contrib/rise) extension. Many thanks to [Frédéric Collonval](https://github.com/fcollonval) for his PR ([#1126](https://github.com/mwouts/jupytext/pull/1126))! - This version of the JupyterLab extension is compatible with JupyterLab 4.x. Many thanks to [Thierry Parmentelat](https://github.com/parmentelat) for his PRs! ([#1092](https://github.com/mwouts/jupytext/pull/1092), [#1109](https://github.com/mwouts/jupytext/pull/1109)) # 1.3.9 (2022-06-02) - We updated the `yarn.lock` file for the jupyter lab extension to address security vulnerabilities ([#904](https://github.com/mwouts/jupytext/issues/904), [#925](https://github.com/mwouts/jupytext/issues/925), [#935](https://github.com/mwouts/jupytext/issues/935), [#939](https://github.com/mwouts/jupytext/issues/939), [#984](https://github.com/mwouts/jupytext/issues/984), [#1005](https://github.com/mwouts/jupytext/issues/1005), [#1011](https://github.com/mwouts/jupytext/issues/1011), [#1030](https://github.com/mwouts/jupytext/issues/1030), [#1036](https://github.com/mwouts/jupytext/issues/1036), [#1052](https://github.com/mwouts/jupytext/pull/1052)) - This version is the last version that is compatible with `jupyterlab==3.x`. # 1.3.8 (2021-12-03) - The "Jupytext Notebook" factory that lets the user configure the Notebook viewer as the default for text notebooks accepts more filetypes: "myst", "r-markdown" and "quarto" ([#803](https://github.com/mwouts/jupytext/issues/803)) # 1.3.7 (2021-11-30) The extension for JupyterLab benefited from a series of improvements contributed by [Frédéric Collonval](https://github.com/fcollonval): - A new "Jupytext Notebook" factory offers the option to open text notebooks directly with the notebook view (#803). To use it, follow the instructions in the [documentation](https://github.com/mwouts/jupytext/blob/main/docs/index.md#Install). - The ICommandPalette is optional, for compatibility with RISE within JupyterLab [RISE#605](https://github.com/damianavila/RISE/pull/605) - Added support for translation. We also upgraded the extension dependency and especially `json-schema` to address a security vulnerability. # 1.3.6 (2021-09-23) - We have upgraded the extension dependencies and especially `ansi-regex` to fix a security vulnerability (#857) # 1.3.5 (2021-09-05) - The extension can pair notebooks with `.qmd` files (Quarto format) (#837) # 1.3.4 (2021-08-31) - We have upgraded the extension dependencies and especially `tar` and `url-parse` to fix two security vulnerabilities (#842) (#843) # 1.3.3 (2021-06-10) - We have upgraded the extension dependencies and especially `ws` to fix a security vulnerability (#798) # 1.3.2 (2021-05-21) - We have upgraded the extension dependencies and especially `hosted-git-info` to fix a security vulnerability (#783) # 1.3.1 (2021-03-07) - We have updated `yarn.lock` to upgrade `marked` to `2.0` and fix a moderate vulnerability in the extension dependencies (#750) # 1.3.0 (2021-01-05) - The `jupyterlab-jupytext` extension is now distributed using `jupyter-packaging`, thanks to Martin Renou's awesome contribution (#683). # 1.2.3 (2020-10-14) - Remove duplicate `jupyterlab` entry in `package.json` (#654) # 1.2.2 (2020-10-13) - The description of the `jupyterlab-jupytext` extension was updated (#654) - The explicit dependency on the `jupytext` Python package was documented in `package.json` (#654) # 1.2.1 (2020-03-18) - The extension can pair a notebook to the new MyST Markdown format, developed by the [ExecutableBookProject](https://github.com/ExecutableBookProject) team. Thanks to Chris Sewell for his PRs! (#447 #456 #458) # 1.2.0 (2020-03-09) - This version of the extension is compatible with JupyterLab 2.0. Many thanks to Jean Helie! (#449) # 1.1.1 (2019-12-26) - The `nomarker` format is available through the Jupytext commands (requires `jupytext>=1.3.1`). # 1.1.0 (2019-11-03) - Multiple pairings are supported (#290) - The documentation includes the last version numbers for both Jupytext Python and for this extension (#311) - Documentation says clearly that the extension is bundled with the Python package (#350) # 1.0.2 (2019-07-18) - Fixed an incorrect `target_format` entry inserted by the version 1.0.1 of the extension. # 1.0.1 (2019-07-18) - A click on a selected format toggle the pairing (#289) - Use `JupyterFrontEnd` and `JupyterFrontEndPlugin` from `@jupyterlab/application` rather than `JupyterLab` and `JupyterLabPlugin` for compatibility with JupyterLab 1.0. # 1.0.0 (2019-07-06) - First extension compatible with JupyterLab 1.0 # 0.19.0 (2019-07-06) - Last extension compatible with JupyterLab 0.35 # 0.1.0 (2018-10-02) - Initial release of the extension ================================================ FILE: jupyterlab/packages/jupyterlab-jupytext-extension/README.md ================================================ # A JupyterLab extension for Jupytext This extension adds a few [Jupytext](https://github.com/mwouts/jupytext) commands to the command palette. Use these to select the desired ipynb/text pairing for your notebook. The latest version for this extension is [![npm version](https://badge.fury.io/js/jupyterlab-jupytext.svg)](https://badge.fury.io/js/jupyterlab-jupytext). Most users do not need to install this extension, since it is already included in the latest [jupytext](https://github.com/mwouts/jupytext/), both on [![Pypi](https://img.shields.io/pypi/v/jupytext.svg)](https://pypi.python.org/pypi/jupytext) and [![Conda Version](https://img.shields.io/conda/vn/conda-forge/jupytext.svg)](https://anaconda.org/conda-forge/jupytext). ![](https://raw.githubusercontent.com/mwouts/jupytext/main/packages/labextension/jupytext_commands.png) ## Installation Please install [Jupytext](https://github.com/mwouts/jupytext/blob/main/README.md#Install) first. As mentioned above, both the `pip` and `conda` packages do include the latest version of the JupyterLab extension, so in most cases you don't need to specifically install this `npm` package. In case you're not using JupyterLab 4.x, you will have to install an older version of the extension that is compatible with your version. Please first install `jupytext` using `pip` or `conda`, and then downgrade the extension to a version compatible with your version of JupyterLab with: ```bash jupyter labextension install jupyterlab-jupytext@1.3.11 # for JupyterLab 3.x jupyter labextension install jupyterlab-jupytext@1.2.2 # for JupyterLab 2.x jupyter labextension install jupyterlab-jupytext@1.1.1 # for JupyterLab 1.x ``` # How to develop this extension For fine-grained access to the `jlpm` command and various build steps: ```bash pip install -e '.[dev]' cd jupyterlab/packages/jupyterlab-jupytext-extension jlpm jlpm install:extension # Symlink into `{sys.prefix}/share/jupyter/labextensions` ``` (see also the instructions at [developing.md](../../../docs/developing.md) on how to create a Python environment with a recent version of `nodejs`) Watch the source directory and automatically rebuild the `lib` folder: ```bash cd jupyterlab/packages/jupyterlab-jupytext-extension # Watch the source directory in one terminal, automatically rebuilding when needed jlpm watch # Run JupyterLab in another terminal jupyter lab ``` While running `jlpm watch`, every saved change to a `.ts` file will immediately be built locally and available in your running Jupyter client. "Hard" refresh JupyterLab or Notebook with CTRL-F5 or ⌘-F5 to load the change in your browser (you may need to wait several seconds for the extension to be fully rebuilt). Read more on this on the [JupyterLab documentation](https://jupyterlab.readthedocs.io/en/latest/extension/extension_dev.html#developing-a-prebuilt-extension). # How to publish a new version of the extension on npm Please note that the main purpose of updating the extension on [npm](https://www.npmjs.com) is to keep the npm documentation up-to-date, since the extension is made available within the Python package itself. Make sure you have `nodejs>=18` installed, bump the version in `package.json`, and then: ```bash cd jupyterlab/packages/jupyterlab-jupytext-extension # Package the extension npm pack # Test the extension locally jupyter labextension install jupyterlab-jupytext-xxx.tgz # Publish the package on npm with npm publish --access=public ``` ================================================ FILE: jupyterlab/packages/jupyterlab-jupytext-extension/package.json ================================================ { "name": "jupyterlab-jupytext", "version": "1.4.6", "description": "Save Jupyter Notebooks as Scripts or Markdown files that work well with version control & external text editors", "keywords": [ "jupyter", "jupytext", "jupyterlab", "jupyterlab-extension" ], "homepage": "https://github.com/mwouts/jupytext/tree/main/jupyterlab/packages/jupyterlab-jupytext", "bugs": { "url": "https://github.com/mwouts/jupytext/issues" }, "license": "MIT", "author": "Marc Wouts", "files": [ "lib/**/*.{d.ts,eot,gif,html,jpg,js,js.map,json,png,svg,woff2,ttf}", "style/**/*.{css,eot,gif,html,jpg,json,png,svg,woff2,ttf}" ], "main": "lib/index.js", "types": "lib/index.d.ts", "repository": { "type": "git", "url": "https://github.com/mwouts/jupytext.git" }, "workspaces": [ "ui-tests" ], "scripts": { "build": "jlpm run build:lib && jlpm run build:labextension:dev && jlpm run copy:extensioncfgfile", "build:labextension": "jupyter labextension build .", "build:labextension:dev": "jupyter labextension build --development True .", "build:lib": "tsc", "build:prod": "jlpm run build:lib && jlpm run build:labextension && jlpm run copy:extensioncfgfile", "copy:extensioncfgfile": "cp ../../install.json ../../jupyterlab_jupytext/labextension", "clean": "jlpm run clean:lib", "clean:all": "jlpm run clean:lib && jlpm run clean:labextension", "clean:labextension": "rimraf ../../jupyterlab_jupytext/labextension", "clean:lib": "rimraf lib tsconfig.tsbuildinfo", "install:extension": "python ../../scripts/install_extension.py", "watch": "run-p watch:src watch:labextension", "watch:labextension": "jupyter labextension watch .", "watch:src": "tsc -w" }, "jupyterlab": { "discovery": { "server": { "managers": [ "pip", "conda" ], "base": { "name": "jupyterlab_jupytext" } } }, "extension": true, "schemaDir": "schema", "outputDir": "../../jupyterlab_jupytext/labextension", "sharedPackages": { "jupyterlab-rise": { "singleton": true } } }, "dependencies": { "@jupyterlab/application": "^4.4.9", "@jupyterlab/apputils": "^4.4.9", "@jupyterlab/codeeditor": "^4.4.9", "@jupyterlab/docregistry": "^4.4.9", "@jupyterlab/filebrowser": "^4.4.9", "@jupyterlab/launcher": "^4.4.9", "@jupyterlab/nbformat": "^4.4.9", "@jupyterlab/notebook": "^4.4.9", "@jupyterlab/rendermime": "^4.4.9", "@jupyterlab/settingregistry": "^4.4.9", "@jupyterlab/translation": "^4.4.9", "@jupyterlab/ui-components": "^4.4.9", "@lumino/commands": "^2.3.3", "@lumino/coreutils": "^2.2.2", "@lumino/disposable": "^2.1.5", "buffer": "^6.0.3", "jupyterlab-rise": "^0.43.1" }, "devDependencies": { "@jupyterlab/builder": "^4.4.9", "npm-run-all": "^4.1.5", "rimraf": "^6.0.1", "typescript": "~5.9.3" } } ================================================ FILE: jupyterlab/packages/jupyterlab-jupytext-extension/schema/plugin.json ================================================ { "title": "Jupytext", "description": "List of Jupytext Text Notebook formats that will be added to launcher and jupytext menu.", "properties": { "auto:percent": { "type": "boolean", "title": "Text Notebook as Script in Percent Format", "default": true }, "auto:light": { "type": "boolean", "title": "Text Notebook as Script in Light Format", "default": false }, "auto:hydrogen": { "type": "boolean", "title": "Text Notebook as Script in Hydrogen Format", "default": false }, "auto:nomarker": { "type": "boolean", "title": "Text Notebook as Script in Nomarker Format", "default": false }, "py:marimo": { "type": "boolean", "title": "Text Notebook as Marimo Script", "default": false }, "md:myst": { "type": "boolean", "title": "MyST Markdown Notebook", "default": true }, "md": { "type": "boolean", "title": "Markdown Notebook", "default": false }, "Rmd": { "type": "boolean", "title": "R Markdown Notebook", "default": false }, "qmd": { "type": "boolean", "title": "Quarto Markdown Notebook", "default": false }, "NOTE": { "description": "Refresh the current browser tab for the changes to take effect.", "type": "null" } }, "additionalProperties": false, "type": "object" } ================================================ FILE: jupyterlab/packages/jupyterlab-jupytext-extension/src/commands.ts ================================================ import { showErrorMessage } from '@jupyterlab/apputils'; import { INotebookTracker } from '@jupyterlab/notebook'; import * as nbformat from '@jupyterlab/nbformat'; import { TranslationBundle } from '@jupyterlab/translation'; import { LANGUAGE_INDEPENDENT_NOTEBOOK_EXTENSIONS, JUPYTEXT_FORMATS, IJupytextSection, } from './tokens'; /** * Get Jupytext format of current widget if it is a text notebook */ function getWidgetJupytextFormats( notebookTracker: INotebookTracker, ): Array { const model = notebookTracker.currentWidget.context.model; const jupytext: IJupytextSection = (model as any).getMetadata('jupytext'); if (!jupytext) { return []; } const formats: Array = jupytext.formats ? jupytext.formats.split(',') : []; return formats.filter((format) => { return format !== ''; }); } /** * Get file extension of current notebook widget */ function getNotebookFileExtension(notebookTracker: INotebookTracker): string { let notebookFileExtension: string | undefined = notebookTracker.currentWidget.context.path.split('.').pop(); if (!notebookFileExtension) { return ''; } notebookFileExtension = LANGUAGE_INDEPENDENT_NOTEBOOK_EXTENSIONS.includes( notebookFileExtension, ) ? notebookFileExtension : 'auto'; return notebookFileExtension; } /** * Get a list of all selected formats */ function getSelectedFormats(notebookTracker: INotebookTracker): Array { if (!notebookTracker.currentWidget) { return []; } let formats = getWidgetJupytextFormats(notebookTracker); const model = notebookTracker.currentWidget.context.model; const languageInfo = (model as any).getMetadata( 'language_info', ) as nbformat.ILanguageInfoMetadata; if (languageInfo && languageInfo.file_extension) { const scriptExt = languageInfo.file_extension.substring(1); formats = formats.map((format) => { // By default use percent format if (format === scriptExt) { return 'auto:percent'; } // Replace language specific extension with auto return format.replace(`${scriptExt}:`, 'auto:'); }); } const notebookFileExtension = getNotebookFileExtension(notebookTracker); if (!notebookFileExtension) { return formats; } // Remove variant after : in format const formatExtensions = formats.map((format) => { return format.split(':')[0]; }); // If current notebook file extension in formats, return if (formatExtensions.includes(notebookFileExtension)) { return formats; } // When notebook loads for the first time, ipynb extension would not be // in the formats. Here we add it and return formats if ( LANGUAGE_INDEPENDENT_NOTEBOOK_EXTENSIONS.includes(notebookFileExtension) ) { formats.push(notebookFileExtension); } else { const model = notebookTracker.currentWidget.context.model; const jupytext: IJupytextSection = (model as any).getMetadata( 'jupytext', ) as IJupytextSection; const formatName = jupytext ? jupytext?.text_representation?.formatName || 'percent' : 'percent'; formats.push(`auto:${formatName}`); } return formats; } /** * Toggle pair command */ export function isPairCommandToggled( format: string, notebookTracker: INotebookTracker, ): boolean { if (!notebookTracker.currentWidget) { return false; } // Get selected formats on current widget const selectedFormats = getSelectedFormats(notebookTracker); if (format === 'custom') { for (const selectedFormat of selectedFormats) { if (!JUPYTEXT_FORMATS.includes(selectedFormat)) { return true; } } return false; } return selectedFormats.includes(format); } /** * Enable pair command */ export function isPairCommandEnabled( format: string, notebookTracker: INotebookTracker, ): boolean { if (!notebookTracker.currentWidget) { return false; } const notebookFileExtension: string | undefined = notebookTracker.currentWidget.context.path.split('.').pop(); if (format === notebookFileExtension) { return false; } // Get selected formats on current widget const selectedFormats = getSelectedFormats(notebookTracker); if (format === 'none') { return selectedFormats.length > 1; } return true; } /** * Execute pair command */ export function executePairCommand( command: string, format: string, notebookTracker: INotebookTracker, trans: TranslationBundle, ): void { if (!notebookTracker.currentWidget) { return; } const model = notebookTracker.currentWidget.context.model; let jupytext: IJupytextSection = (model as any).getMetadata('jupytext') as | IJupytextSection | undefined; // Get selected formats on current widget let selectedFormats = getSelectedFormats(notebookTracker); // Toggle the selected format console.debug('Jupytext: executing command=' + command); if (format === 'custom') { showErrorMessage( trans.__('Error'), trans.__( 'Please edit the notebook metadata directly if you wish a custom configuration.', ), ); return; } // Get current notebook widget extension const notebookFileExtension = getNotebookFileExtension(notebookTracker); // Toggle the selected format const index = selectedFormats.indexOf(format); if (format === 'none') { // Only keep one format - one that matches the current extension for (const selectedFormat of selectedFormats) { if (selectedFormat.split(':')[0] === notebookFileExtension) { selectedFormats = [selectedFormat]; break; } } } else if (index !== -1) { selectedFormats.splice(index, 1); // The current file extension can't be unpaired let extFound = false; for (const selectedFormat of selectedFormats) { if (selectedFormat.split(':')[0] === notebookFileExtension) { extFound = true; break; } } if (!extFound) { return; } } else { // We can't have the same extension multiple times const newFormats = []; for (const selectedFormat of selectedFormats) { if (selectedFormat.split(':')[0] !== format.split(':')[0]) { newFormats.push(selectedFormat); } } selectedFormats = newFormats; selectedFormats.push(format); } if (selectedFormats.length === 1) { if (notebookFileExtension !== 'auto') { selectedFormats = []; } else if (jupytext?.text_representation) { jupytext.text_representation.formatName = selectedFormats[0].split(':')[1]; selectedFormats = []; } } if (selectedFormats.length === 0) { // an older version was re-fetching the jupytext metadata here // but this is not necessary, as the metadata is already available if (!jupytext) { return; } if (jupytext.formats) { delete jupytext.formats; } if (Object.keys(jupytext).length === 0) { (model as any).deleteMetadata('jupytext'); } (model as any).setMetadata('jupytext', jupytext); return; } // set the desired format if (jupytext) { jupytext.formats = selectedFormats.join(); } else { jupytext = { formats: selectedFormats.join() }; } (model as any).setMetadata('jupytext', jupytext); } /** * Toggle metadata command */ export function isMetadataCommandToggled( notebookTracker: INotebookTracker, ): boolean { if (!notebookTracker.currentWidget) { return false; } const model = notebookTracker.currentWidget.context.model; const jupytextMetadata = (model as any).getMetadata('jupytext'); if (!jupytextMetadata) { return false; } const jupytext: IJupytextSection = jupytextMetadata as unknown as IJupytextSection; if (jupytext.notebook_metadata_filter === '-all') { return false; } return true; } /** * Enable metadata command */ export function isMetadataCommandEnabled( notebookTracker: INotebookTracker, ): boolean { if (!notebookTracker.currentWidget) { return false; } const model = notebookTracker.currentWidget.context.model; const jupytextMetadata = (model as any).getMetadata('jupytext'); if (!jupytextMetadata) { return false; } const jupytext: IJupytextSection = jupytextMetadata as unknown as IJupytextSection; if (jupytext.notebook_metadata_filter === undefined) { return true; } if (jupytext.notebook_metadata_filter === '-all') { return true; } return false; } /** * Execute metadata command */ export function executeMetadataCommand( notebookTracker: INotebookTracker, ): void { console.debug('Jupytext: toggling YAML header'); if (!notebookTracker.currentWidget) { return; } const model = notebookTracker.currentWidget.context.model; const jupytextMetadata = (model as any).getMetadata('jupytext'); if (!jupytextMetadata) { return; } const jupytext = ((jupytextMetadata as unknown) ?? {}) as IJupytextSection; if (jupytext.notebook_metadata_filter) { delete jupytext.notebook_metadata_filter; if (jupytext.notebook_metadata_filter === '-all') { delete jupytext.notebook_metadata_filter; } } else { jupytext.notebook_metadata_filter = '-all'; if (jupytext.notebook_metadata_filter === undefined) { jupytext.notebook_metadata_filter = '-all'; } } (model as any).setMetadata('jupytext', jupytext); } ================================================ FILE: jupyterlab/packages/jupyterlab-jupytext-extension/src/factory.ts ================================================ import { IToolbarWidgetRegistry, createToolbarFactory, } from '@jupyterlab/apputils'; import { INotebookTracker, NotebookPanel, NotebookWidgetFactory, } from '@jupyterlab/notebook'; import { ISettingRegistry } from '@jupyterlab/settingregistry'; import { DocumentRegistry } from '@jupyterlab/docregistry'; import { IRenderMimeRegistry } from '@jupyterlab/rendermime'; import { IEditorServices } from '@jupyterlab/codeeditor'; import { ITranslator, TranslationBundle } from '@jupyterlab/translation'; import { IDisposable } from '@lumino/disposable'; import { IRisePreviewFactory } from 'jupyterlab-rise'; import { FACTORY, FILE_TYPES } from './tokens'; export function createFactory( kernelFileTypeNames: string[], toolbarRegistry: IToolbarWidgetRegistry, settingRegistry: ISettingRegistry, docRegistry: DocumentRegistry, notebookTracker: INotebookTracker, notebookFactory: NotebookWidgetFactory.IFactory, contentFactory: NotebookPanel.IContentFactory, editorServices: IEditorServices, rendermime: IRenderMimeRegistry, translator: ITranslator, trans: TranslationBundle, riseFactory: IRisePreviewFactory | null, ) { const allFileTypes = FILE_TYPES.concat(kernelFileTypeNames); // primarily this block is copied/pasted from jlab4 code and specifically // jupyterlab/packages/notebook-extension/src/index.ts // inside the function `activateWidgetFactory` at line 1150 as of this writing // const toolbarFactory = createToolbarFactory( toolbarRegistry, settingRegistry, 'Notebook', '@jupyterlab/notebook-extension:panel', translator, ); // Duplicate notebook factory to apply it on Jupytext notebooks // Mirror: https://github.com/jupyterlab/jupyterlab/blob/8a8c3752564f37493d4eb6b4c59008027fa83880/packages/notebook-extension/src/index.ts#L860 const factory = new NotebookWidgetFactory({ name: FACTORY, label: trans.__(FACTORY), fileTypes: allFileTypes, modelName: notebookFactory.modelName ?? 'notebook', preferKernel: notebookFactory.preferKernel ?? true, canStartKernel: notebookFactory.canStartKernel ?? true, rendermime, contentFactory, editorConfig: notebookFactory.editorConfig, notebookConfig: notebookFactory.notebookConfig, mimeTypeService: editorServices.mimeTypeService, toolbarFactory: toolbarFactory, translator, }); docRegistry.addWidgetFactory(factory); // The list of extensions in the Jupytext Notebook factory. const factoryExtensions: IDisposable[] = []; const updateWidgetExtensions = () => { // Dispose of all existing extensions. factoryExtensions.forEach((extension) => extension.dispose()); // Add all the widgets extensions in the Notebook factory. for (const extension of docRegistry.widgetExtensions('Notebook')) { docRegistry.addWidgetExtension(FACTORY, extension); } }; // Listen for changes in Notebook factory extensions. docRegistry.changed.connect((_, change) => { if (change.type === 'widgetExtension' && change.name === 'Notebook') { updateWidgetExtensions(); } }); updateWidgetExtensions(); // Register widget created with the new factory in the notebook tracker // This is required to activate notebook commands (and therefore shortcuts) let id = 0; // The ID counter for notebook panels. const ft = docRegistry.getFileType('notebook'); factory.widgetCreated.connect((sender, widget) => { // If the notebook panel does not have an ID, assign it one. widget.id = widget.id || `notebook-jupytext-${++id}`; // Set up the title icon widget.title.icon = ft?.icon; widget.title.iconClass = ft?.iconClass ?? ''; widget.title.iconLabel = ft?.iconLabel ?? ''; // Notify the widget tracker if restore data needs to update. widget.context.pathChanged.connect(() => { // @ts-expect-error Trick using private API void notebookTracker.save(widget); }); // Add the notebook panel to the tracker. // @ts-expect-error Trick using private API void notebookTracker.add(widget); }); // Add support for RISE slides if (riseFactory) { for (const fileType of allFileTypes) { riseFactory.addFileType(fileType); } } } ================================================ FILE: jupyterlab/packages/jupyterlab-jupytext-extension/src/index.ts ================================================ import { JupyterFrontEnd, JupyterFrontEndPlugin, } from '@jupyterlab/application'; import { ICommandPalette, IToolbarWidgetRegistry, showErrorMessage, } from '@jupyterlab/apputils'; import { IDocumentManager } from '@jupyterlab/docmanager'; import { IEditorLanguageRegistry } from '@jupyterlab/codemirror'; import { Contents } from '@jupyterlab/services'; import { ILauncher } from '@jupyterlab/launcher'; import { ISettingRegistry } from '@jupyterlab/settingregistry'; import { IEditorServices } from '@jupyterlab/codeeditor'; import { INotebookTracker, INotebookWidgetFactory, NotebookPanel, NotebookWidgetFactory, } from '@jupyterlab/notebook'; import { IRenderMimeRegistry } from '@jupyterlab/rendermime'; import { IDefaultFileBrowser } from '@jupyterlab/filebrowser'; import { IMainMenu } from '@jupyterlab/mainmenu'; import { ITranslator, nullTranslator } from '@jupyterlab/translation'; import { LabIcon } from '@jupyterlab/ui-components'; import { DisposableSet } from '@lumino/disposable'; import { Menu } from '@lumino/widgets'; import { JSONExt, ReadonlyJSONValue } from '@lumino/coreutils'; import { IRisePreviewFactory } from 'jupyterlab-rise'; import { JUPYTEXT_EXTENSION_ID, JUPYTEXT_PAIR_COMMANDS_FILETYPE_DATA, JUPYTEXT_FORMATS, TEXT_NOTEBOOKS_LAUNCHER_ICONS, CommandIDs, IFileTypeData, JupytextIcon, AUTO_LANGUAGE_FILETYPE_DATA, } from './tokens'; import { isPairCommandToggled, isPairCommandEnabled, executePairCommand, isMetadataCommandToggled, isMetadataCommandEnabled, executeMetadataCommand, } from './commands'; import { registerFileTypes } from './registry'; import { createFactory } from './factory'; import { getAvailableKernelLanguages, getAvailableCreateTextNotebookCommands, createNewTextNotebook, } from './utils'; /** * Initialization data for the jupyterlab-jupytext extension. */ const extension: JupyterFrontEndPlugin = { id: JUPYTEXT_EXTENSION_ID, autoStart: true, optional: [ ILauncher, IMainMenu, IDefaultFileBrowser, ITranslator, ICommandPalette, IRisePreviewFactory, ], requires: [ NotebookPanel.IContentFactory, IEditorServices, IDocumentManager, IEditorLanguageRegistry, IRenderMimeRegistry, INotebookWidgetFactory, INotebookTracker, ISettingRegistry, IToolbarWidgetRegistry, ], activate: async ( app: JupyterFrontEnd, contentFactory: NotebookPanel.IContentFactory, editorServices: IEditorServices, docManager: IDocumentManager, languages: IEditorLanguageRegistry, rendermime: IRenderMimeRegistry, notebookFactory: NotebookWidgetFactory.IFactory, notebookTracker: INotebookTracker, settingRegistry: ISettingRegistry, toolbarRegistry: IToolbarWidgetRegistry, launcher: ILauncher | null, mainmenu: IMainMenu | null, defaultBrowser: IDefaultFileBrowser | null, translator: ITranslator | null, palette: ICommandPalette | null, riseFactory: IRisePreviewFactory | null, ) => { console.log('JupyterLab extension jupytext is activating...'); const trans = (translator ?? nullTranslator).load('jupytext'); // Load settings const includeFormats = TEXT_NOTEBOOKS_LAUNCHER_ICONS; if (settingRegistry) { const settings = await settingRegistry.load(extension.id); for (const format of JUPYTEXT_FORMATS) { const addFormat = settings.get(format).composite as boolean; if (addFormat && !includeFormats.includes(format)) { includeFormats.push(format); } else if (!addFormat && includeFormats.includes(format)) { includeFormats.splice(includeFormats.indexOf(format), 1); } } } // Unpack necessary components const { commands, serviceManager, docRegistry } = app; // Initialise Jupytext create notebook submenu and add it to File menu const jupytextCreateMenu = new Menu({ commands: app.commands }); jupytextCreateMenu.id = 'jp-mainmenu-jupytext-new-menu'; jupytextCreateMenu.title.label = trans.__('New Text Notebook'); mainmenu.fileMenu.addItem({ rank: 0.97, type: 'submenu', submenu: jupytextCreateMenu, }); // Add create text notebook submenu to context menu // Rank 53 as 52 is used for classic notebook // https://github.com/jupyterlab/jupyterlab/blob/4d34bbbea2afc7385169d92bf7bc0c9e0face3a9/packages/notebook-extension/schema/tracker.json#L363-L369 app.contextMenu.addItem({ submenu: jupytextCreateMenu, type: 'submenu', selector: '.jp-DirListing-content', rank: 53, }); // Initialise Jupytext menu and add it to main menu const jupytextMenu = new Menu({ commands: app.commands }); mainmenu.fileMenu.addItem({ rank: 0.98, type: 'submenu', submenu: jupytextMenu, }); jupytextMenu.id = 'jp-mainmenu-jupytext-menu'; jupytextMenu.title.label = trans.__('Jupytext'); // Get all Jupytext formats let rank = 0; const separatorIndex: number[] = []; JUPYTEXT_PAIR_COMMANDS_FILETYPE_DATA.forEach( (value: IFileTypeData[], key: string) => { value.map((fileType: IFileTypeData) => { const format = key; const command = `jupytext:pair-nb-with-${format}`; commands.addCommand(command, { label: (args) => { if (args.isPalette) { return ( (fileType.paletteLabel as string) ?? trans.__('Pair notebook') ); } return (fileType.caption as string) ?? trans.__('Pair notebook'); }, caption: trans.__(fileType.caption), icon: (args) => { if (args.isPalette) { return undefined; } else { return fileType.iconName ? LabIcon.resolve({ icon: fileType.iconName as string, }) : undefined; } }, isToggled: () => { return isPairCommandToggled(format, notebookTracker); }, isEnabled: () => { return isPairCommandEnabled(format, notebookTracker); }, execute: () => { return executePairCommand( command, format, notebookTracker, trans, ); }, }); console.debug( 'Registering pairing command=' + command + ' with rank=' + rank, ); palette?.addItem({ command, args: { isPalette: true }, rank: rank + 1, category: 'Jupytext', }); // Add to jupytext pair menu jupytextMenu.addItem({ command: command, }); if (fileType.separator) { separatorIndex.push(rank); } rank += 1; }); }, ); // Add separators in jupytext pair menu separatorIndex.map((index, idx) => { jupytextMenu.insertItem(index + idx + 1, { type: 'separator', }); }); // Metadata in text representation commands.addCommand(CommandIDs.metadata, { label: trans.__('Include Metadata'), icon: (args) => { if (args.isPalette) { return undefined; } else { return JupytextIcon; } }, isToggled: () => { return isMetadataCommandToggled(notebookTracker); }, isEnabled: () => { return isMetadataCommandEnabled(notebookTracker); }, execute: () => { return executeMetadataCommand(notebookTracker); }, }); palette?.addItem({ command: CommandIDs.metadata, args: { isPalette: true }, rank: 98, category: 'Jupytext', }); jupytextMenu.addItem({ type: 'separator', }); jupytextMenu.addItem({ command: CommandIDs.metadata, }); jupytextMenu.addItem({ type: 'separator', }); // Register Jupytext FAQ command commands.addCommand(CommandIDs.faq, { label: trans.__('Jupytext FAQ'), icon: (args) => { if (args.isPalette) { return undefined; } else { return JupytextIcon; } }, execute: () => { window.open('https://jupytext.readthedocs.io/en/latest/faq.html'); }, }); palette?.addItem({ command: CommandIDs.faq, args: { isPalette: true }, rank: 99, category: 'Jupytext', }); jupytextMenu.addItem({ command: CommandIDs.faq, }); // Register Jupytext Reference commands.addCommand(CommandIDs.reference, { label: trans.__('Jupytext Reference'), icon: (args) => { if (args.isPalette) { return undefined; } else { return JupytextIcon; } }, execute: () => { window.open('https://jupytext.readthedocs.io/en/latest/'); }, }); palette?.addItem({ command: CommandIDs.reference, args: { isPalette: true }, rank: 100, category: 'Jupytext', }); jupytextMenu.addItem({ command: CommandIDs.reference, }); // Register a new command to create untitled file. This snippet is taken // from docManager package https://github.com/jupyterlab/jupyterlab/blob/c106f0a19110efad7c5e1b136144985819e21100/packages/docmanager-extension/src/index.tsx#L679-L680 // We are "duplicating" it as base command adds extension to the options // only if it is of type file. But we are interested in creating notebook type // files with different Jupytext supported extensions. So we create a dedicated // create new text notebook command here and make sure we pass extension in options commands.addCommand(CommandIDs.newUntitled, { execute: async (args) => { const errorTitle = (args['error'] as string) || trans.__('Error'); const path = typeof args['path'] === 'undefined' ? '' : (args['path'] as string); const options: Partial = { type: args['type'] as Contents.ContentType, path, }; // Ensure we pass extension to command always options.ext = (args['ext'] as string) || '.txt'; return docManager.services.contents .newUntitled(options) .catch((error) => showErrorMessage(errorTitle, error)); }, label: (args) => (args['label'] as string) || `New ${args['type'] as string}`, }); // We dont need to add this command to palettte as it is a utility one // which does not have direct usage // palette?.addItem({ // command: CommandIDs.newUntitled, // rank: 50, // category: 'Jupytext', // }); // Get a map of available kernel languages in current widget const availableKernelLanguages = await getAvailableKernelLanguages( languages, docRegistry, serviceManager, ); // Get a map of all create text notebook commands const createTextNotebookCommands = await getAvailableCreateTextNotebookCommands( includeFormats, availableKernelLanguages, ); // Register Jupytext text notebooks file types registerFileTypes( availableKernelLanguages, [ ...[...JUPYTEXT_PAIR_COMMANDS_FILETYPE_DATA.values()].flat(), ...[...AUTO_LANGUAGE_FILETYPE_DATA.values()].flat(), ], docRegistry, trans, ); // Get all kernel file types to add to Jupytext factory const kernelLanguageNames: string[] = []; for (const kernelLanguage of availableKernelLanguages.keys()) { kernelLanguageNames.push(kernelLanguage); } // Create a factory for Jupytext createFactory( kernelLanguageNames, toolbarRegistry, settingRegistry, docRegistry, notebookTracker, notebookFactory, contentFactory, editorServices, rendermime, translator, trans, riseFactory, ); // Register all the commands that create text notebooks with different formats // Nicked from notebook-extension package in JupyterLab // https://github.com/jupyterlab/jupyterlab/blob/c106f0a19110efad7c5e1b136144985819e21100/packages/notebook-extension/src/index.ts#L1902-L1965 createTextNotebookCommands.forEach((fileTypes: IFileTypeData[], _) => { fileTypes.map((fileType: IFileTypeData) => { const format = fileType.fileExt; const command = `jupytext:create-new-text-notebook-${format}`; const iconName = fileType.iconName; const kernelIcon = fileType.kernelIcon; commands.addCommand(command, { label: (args) => { if (args['isLauncher']) { return trans.__(fileType.launcherLabel); } return trans.__(fileType.paletteLabel); }, caption: trans.__(fileType.caption), icon: (args) => { if (args.isPalette) { return undefined; } else { if (iconName) { return LabIcon.resolve({ icon: iconName as string, }); } if (kernelIcon) { return kernelIcon; } return LabIcon.resolve({ icon: 'ui-components:kernel', }); } }, execute: (args) => { const cwd = (args['cwd'] as string) || (defaultBrowser?.model.path ?? ''); const kernelId = (args['kernelId'] as string) || ''; const kernelName = (args['kernelName'] as string) || ''; return createNewTextNotebook( cwd, kernelId, kernelName, format, commands, ); }, }); console.debug( 'Registering create new text notebook command=' + command + ' with rank=' + rank, ); palette?.addItem({ command, args: { isPalette: true }, rank: rank, category: 'Jupytext', }); if (includeFormats.includes(format)) { jupytextCreateMenu.addItem({ command: command, args: { isMainMenu: true }, }); // Add separator after each kernel type if (fileType.separator) { jupytextCreateMenu.addItem({ type: 'separator', }); } } // Add a launcher item if the launcher is available. if (launcher && includeFormats.includes(format)) { void serviceManager.ready.then(() => { let disposables: DisposableSet | null = null; const onSpecsChanged = () => { if (disposables) { disposables.dispose(); disposables = null; } const specs = serviceManager.kernelspecs.specs; if (!specs) { return; } disposables = new DisposableSet(); const kernelIconUrl = specs.kernelspecs[fileType.kernelName]?.resources['logo-svg'] || specs.kernelspecs[fileType.kernelName]?.resources['logo-64x64']; disposables.add( launcher.add({ command: command, args: { isLauncher: true, kernelName: fileType.kernelName }, category: trans.__('Jupytext'), rank: rank++, kernelIconUrl, metadata: { kernel: JSONExt.deepCopy( specs.kernelspecs[fileType.kernelName]?.metadata || {}, ) as ReadonlyJSONValue, }, }), ); }; onSpecsChanged(); serviceManager.kernelspecs.specsChanged.connect(onSpecsChanged); }); } // Increment rank rank += 1; }); }); }, }; export default extension; ================================================ FILE: jupyterlab/packages/jupyterlab-jupytext-extension/src/registry.ts ================================================ import { DocumentRegistry } from '@jupyterlab/docregistry'; import { TranslationBundle } from '@jupyterlab/translation'; import { markdownIcon, LabIcon, fileIcon } from '@jupyterlab/ui-components'; import { IFileTypeData } from './tokens'; export function registerFileTypes( availableKernelLanguages: Map, jupytextFormatsWithFileTypeData: IFileTypeData[], docRegistry: DocumentRegistry, trans: TranslationBundle, ) { const mystExtensions = ['myst', 'mystnb', 'mnb']; const rmdExtensions = ['Rmd']; const quartoExtensions = ['qmd']; const extensionsWithFactory = [ ...mystExtensions, ...rmdExtensions, ...quartoExtensions, ]; // Add a catch-all file type to overrride icon which by default is derive from model type. // Because jupytext changes the type of all files it can handle to Notebook, we need to // override it. We exclude file types which have dedicated icons (handled later). const excludedExtensions = [ 'ipynb', ...jupytextFormatsWithFileTypeData.map((f) => f.fileExt), ...extensionsWithFactory, ].join('|'); docRegistry.addFileType({ name: 'jupytext-notebook-file', contentType: 'notebook', pattern: `^(?!.*\\.(${excludedExtensions})$).*$`, icon: fileIcon, }); // Handle file types with dedicated icons for (const format of jupytextFormatsWithFileTypeData) { if (!extensionsWithFactory.includes(format.fileExt)) { docRegistry.addFileType({ name: `${format.fileExt}-jupytext-notebook`, contentType: 'notebook', // `pattern` field gives it precedence over other file type information when resolving the icon pattern: `\\.${format.fileExt}$`, extensions: [`.${format.fileExt}`], icon: format.iconName ? LabIcon.resolve({ icon: format.iconName }) : format.kernelIcon, }); } } // Add kernel file types to registry availableKernelLanguages.forEach( (kernelFileTypes: IFileTypeData[], kernelLanguage: string) => { kernelFileTypes.map((kernelFileType) => { docRegistry.addFileType({ name: kernelLanguage, contentType: 'notebook', pattern: `\\.${kernelFileType.fileExt}$`, displayName: trans.__( kernelFileType.paletteLabel.split('New')[1].trim(), ), extensions: [`.${kernelFileType.fileExt}`], icon: kernelFileType.iconName ? LabIcon.resolve({ icon: kernelFileType.iconName }) : kernelFileType.kernelIcon, }); }); }, ); const markdownNotebookIcon = markdownIcon.bindprops({ boxSizing: 'border-box', border: '2px solid var(--jp-notebook-icon-color)', borderRadius: '2px', }); // Add markdown file types to registry - these will be open with Notebook by default docRegistry.addFileType( { name: 'myst', contentType: 'notebook', displayName: trans.__('MyST Markdown Notebook'), extensions: mystExtensions.map((ext) => '.' + ext), icon: markdownNotebookIcon, }, ['Notebook'], ); docRegistry.addFileType( { name: 'r-markdown', contentType: 'notebook', displayName: trans.__('R Markdown Notebook'), // Extension file are transformed to lower case... extensions: rmdExtensions.map((ext) => '.' + ext), icon: markdownNotebookIcon, }, ['Notebook'], ); docRegistry.addFileType( { name: 'quarto', contentType: 'notebook', displayName: trans.__('Quarto Notebook'), extensions: quartoExtensions.map((ext) => '.' + ext), pattern: '\\.qmd$', icon: markdownNotebookIcon, }, ['Notebook'], ); } ================================================ FILE: jupyterlab/packages/jupyterlab-jupytext-extension/src/svg.d.ts ================================================ declare module '*.svg' { const image: string; export default image; } ================================================ FILE: jupyterlab/packages/jupyterlab-jupytext-extension/src/tokens.ts ================================================ import { ServerConnection } from '@jupyterlab/services'; import { LabIcon } from '@jupyterlab/ui-components'; import jupytextSvgstr from '../style/icons/logo.svg'; /** * Jupytext extension ID */ export const JUPYTEXT_EXTENSION_ID = 'jupyterlab-jupytext:plugin'; /** * Jupytext widget factory */ export const FACTORY = 'Jupytext Notebook'; /** * Supported file formats. */ export const LANGUAGE_INDEPENDENT_NOTEBOOK_EXTENSIONS = [ 'ipynb', 'md', 'Rmd', 'qmd', ]; /** * Supported file types names. */ export const FILE_TYPES = [ 'markdown', 'myst', 'r-markdown', 'quarto', 'julia', 'python', 'r', ]; /** * The short namespace for commands, etc. */ export const NS = 'jupytext'; /** * Command IDs of Jupytext */ export namespace CommandIDs { export const metadata = `${NS}:metadata`; export const reference = `${NS}:reference`; export const faq = `${NS}:faq`; export const newUntitled = `${NS}:new-untitled-text-notebook`; } /** * Jupytext logo icon */ export const JupytextIcon = new LabIcon({ name: `${NS}:icon:logo`, svgstr: jupytextSvgstr, }); /** * Current Jupyter server settings */ export const SERVER_SETTINGS = ServerConnection.makeSettings(); /** * Supported Jupytext pairings along with metadata. */ export const JUPYTEXT_PAIR_COMMANDS_FILETYPE_DATA = new Map< string, IFileTypeData[] >([ [ 'ipynb', [ { fileExt: 'ipynb', paletteLabel: 'Pair with ipynb', caption: 'Pair Notebook with ipynb document', iconName: 'ui-components:notebook', separator: true, }, ], ], [ 'auto:percent', [ { fileExt: 'auto:percent', paletteLabel: 'Pair with percent script', caption: 'Pair Notebook with Percent Format', iconName: 'ui-components:text-editor', }, ], ], [ 'auto:light', [ { fileExt: 'auto:light', paletteLabel: 'Pair with light script', caption: 'Pair Notebook with Light Format', iconName: 'ui-components:text-editor', }, ], ], [ 'auto:nomarker', [ { fileExt: 'auto:nomarker', paletteLabel: 'Pair with nomarker script', caption: 'Pair Notebook with Nomarker Format', iconName: 'ui-components:text-editor', separator: true, }, ], ], [ 'py:marimo', [ { fileExt: 'py:marimo', paletteLabel: 'Pair with Marimo Python script', caption: 'Pair Notebook with Marimo Python script', iconName: 'ui-components:text-editor', separator: true, }, ], ], [ 'md', [ { fileExt: 'md', paletteLabel: 'Pair with md', caption: 'Pair Notebook with Markdown', iconName: 'ui-components:markdown', }, ], ], [ 'md:myst', [ { fileExt: 'md:myst', paletteLabel: 'Pair with myst md', caption: 'Pair Notebook with MyST Markdown', iconName: 'ui-components:markdown', separator: true, }, ], ], [ 'Rmd', [ { fileExt: 'Rmd', paletteLabel: 'Pair with Rmd', caption: 'Pair Notebook with R Markdown', iconName: 'ui-components:markdown', }, ], ], [ 'qmd', [ { fileExt: 'qmd', paletteLabel: 'Pair with qmd', caption: 'Pair Notebook with Quarto (qmd)', iconName: 'ui-components:markdown', separator: true, }, ], ], [ 'custom', [ { fileExt: 'custom', paletteLabel: 'Custom pair', caption: 'Custom Pairing', iconName: 'ui-components:text-editor', }, ], ], [ 'none', [ { fileExt: 'none', paletteLabel: 'Unpair', caption: 'Unpair Current Notebook', }, ], ], ]); /** * Supported kernels file types metadata */ export const AUTO_LANGUAGE_FILETYPE_DATA = new Map([ [ 'python', [ { fileExt: 'py', paletteLabel: 'New Python Text Notebook', caption: 'Create a new Python Text Notebook', iconName: 'ui-components:python', launcherLabel: 'Python', kernelName: 'python3', }, ], ], [ 'julia', [ { fileExt: 'jl', paletteLabel: 'New Julia Text Notebook', caption: 'Create a new Julia Text Notebook', iconName: 'ui-components:julia', launcherLabel: 'Julia', kernelName: 'julia', }, ], ], [ 'R', [ { fileExt: 'R', paletteLabel: 'New R Text Notebook', caption: 'Create a new R Text Notebook', iconName: 'ui-components:r-kernel', launcherLabel: 'R', kernelName: 'ir', }, ], ], ]); /** * Supported Jupytext create new text notebooks file types */ export const JUPYTEXT_CREATE_TEXT_NOTEBOOK_FILETYPE_DATA = new Map< string, IFileTypeData[] >([ [ 'auto:percent', [ { fileExt: 'auto:percent', paletteLabel: 'Percent Format', caption: 'Percent Format', launcherLabel: 'Percent Format', }, ], ], [ 'auto:light', [ { fileExt: 'auto:light', paletteLabel: 'Light Format', caption: 'Light Format', launcherLabel: 'Light Format', }, ], ], [ 'auto:nomarker', [ { fileExt: 'auto:nomarker', paletteLabel: 'Nomarker Format', caption: 'Nomarker Format', launcherLabel: 'Nomarker Format', }, ], ], [ 'py:marimo', [ { fileExt: 'py:marimo', paletteLabel: 'Marimo Format', caption: 'Marimo Format', launcherLabel: 'Marimo Format', }, ], ], [ 'md', [ { fileExt: 'md', paletteLabel: 'New Markdown Text Notebook', caption: 'Create a new Markdown Text Notebook', iconName: 'ui-components:markdown', launcherLabel: 'Markdown', }, ], ], [ 'md:myst', [ { fileExt: 'md:myst', paletteLabel: 'New MyST Markdown Text Notebook', caption: 'Create a new MyST Markdown Text Notebook', iconName: 'ui-components:markdown', launcherLabel: 'MyST Markdown', }, ], ], [ 'Rmd', [ { fileExt: 'Rmd', paletteLabel: 'New R Markdown Text Notebook', caption: 'Create a new R Markdown Text Notebook', iconName: 'ui-components:markdown', launcherLabel: 'R Markdown', }, ], ], [ 'qmd', [ { fileExt: 'qmd', paletteLabel: 'New Quarto Markdown Text Notebook', caption: 'Create a new Quarto Markdown Text Notebook', iconName: 'ui-components:markdown', launcherLabel: 'Quarto Markdown', }, ], ], ]); /** * Supported Jupytext format extensions bar custom and none */ export const JUPYTEXT_FORMATS = Array.from( JUPYTEXT_PAIR_COMMANDS_FILETYPE_DATA.keys(), ) .map((format) => { return format; }) .filter((format) => { return !['custom', 'none'].includes(format); }); /** * List of formats that would be added to launcher icons */ export const TEXT_NOTEBOOKS_LAUNCHER_ICONS = JUPYTEXT_FORMATS.filter( (format) => { return !['ipynb', 'auto:nomarker', 'qmd', 'custom', 'none'].includes( format, ); }, ); /** * An interface for file type metadata */ export interface IFileTypeData { fileExt: string; paletteLabel: string; caption: string; iconName?: string; kernelIcon?: LabIcon; launcherLabel?: string; kernelName?: string; separator?: boolean; } /** * An interface for Jupytext representation */ export interface IJupytextRepresentation { formatName: string; extension: string; } /** * An interface for Jupytext metadata */ export interface IJupytextSection { formats?: string; notebook_metadata_filter?: string; cell_metadata_filer?: string; text_representation?: IJupytextRepresentation; } ================================================ FILE: jupyterlab/packages/jupyterlab-jupytext-extension/src/utils.ts ================================================ import { IEditorLanguageRegistry } from '@jupyterlab/codemirror'; import { ServiceManager, ServerConnection, KernelSpec, } from '@jupyterlab/services'; import { LabIcon } from '@jupyterlab/ui-components'; import { URLExt } from '@jupyterlab/coreutils'; import { DocumentRegistry, IDocumentWidget } from '@jupyterlab/docregistry'; import { CommandRegistry } from '@lumino/commands'; import { Buffer } from 'buffer'; import { NS, SERVER_SETTINGS, AUTO_LANGUAGE_FILETYPE_DATA, JUPYTEXT_CREATE_TEXT_NOTEBOOK_FILETYPE_DATA, FACTORY, CommandIDs, IFileTypeData, } from './tokens'; /** * Get kernel icon SVG string */ async function getKernelIconBase64String( kernelIconUrl: string, ): Promise { // Seems like URL prefix is already included in kernelIconUrl. We need to strip // it off as baseUrl will already has url prefix. kernelIconUrl = `/kernelspecs${kernelIconUrl.split('kernelspecs')[1]}`; const url = URLExt.join(SERVER_SETTINGS.baseUrl, kernelIconUrl); const response = await ServerConnection.makeRequest(url, {}, SERVER_SETTINGS); const blob = await response.arrayBuffer(); const contentType = response.headers.get('content-type'); return `data:${contentType};base64,${Buffer.from(blob).toString('base64')}`; } /** * Make a SVG string from base64 image */ function base64ToSvgStr(width: number, imageBase64: string): string { return ` `.replace(/\n/g, ' '); } /** * Get kernel Icon */ async function getKernelIcon( specModel: KernelSpec.ISpecModel, fileType: DocumentRegistry.IFileType | undefined, ): Promise { // First check for logo-svg if (specModel.resources['logo-svg']) { const svgStr = await getKernelIconBase64String( specModel.resources['logo-svg'], ); return new LabIcon({ name: `${NS}:icon:${specModel.name}`, svgstr: svgStr, }); } // Else check if 64x64 kernel icon is available if (specModel.resources['logo-64x64']) { const iconBase64String = await getKernelIconBase64String( specModel.resources['logo-64x64'], ); return new LabIcon({ name: `${NS}:icon:${specModel.name}`, svgstr: base64ToSvgStr(64, iconBase64String), }); } // Finally check for 32x32 kernel icon if (specModel.resources['logo-32x32']) { const iconBase64String = await getKernelIconBase64String( specModel.resources['logo-32x32'], ); return new LabIcon({ name: `${NS}:icon:${specModel.name}`, svgstr: base64ToSvgStr(32, iconBase64String), }); } if (fileType && fileType.icon) { return fileType.icon; } // If not found, make a generic kernel icon return LabIcon.resolve({ icon: 'ui-components:kernel', }); } /** * Get all available kernel languages so that we replace auto format * with these language file extensions */ export async function getAvailableKernelLanguages( languages: IEditorLanguageRegistry, docRegistry: DocumentRegistry, serviceManager: ServiceManager.IManager, ): Promise> { const specsManager = serviceManager.kernelspecs; await specsManager.ready; const fileTypes = new Map(); const specs = specsManager.specs?.kernelspecs ?? {}; for (const [spec, specModel] of Object.entries(specs)) { if (specModel) { // First check if kernel is one of the pre-defined types (Python, R, Julia) const exts = AUTO_LANGUAGE_FILETYPE_DATA.get(specModel.language); if (exts !== undefined) { fileTypes.set(specModel.language, exts); } else { // If not, try to get languageInfo from codemirror languages const languageInfo = languages.findByName(specModel.language); // If we managed to find the language, construct the FileTypeData // Here we make an assumption that first extension in // languageInfo.extensions is the most common one. const fileExt = languageInfo.extensions[0]; const fileType = docRegistry.getFileTypesForPath(`test.${fileExt}`)[0]; if (languageInfo) { // We attempt to get kernelIcon here for specModel.resources // If none provided, we return generic kernel icon const kernelIcon = await getKernelIcon(specModel, fileType); const displayName = languageInfo.displayName || specModel.display_name; const exts: IFileTypeData[] = [ { fileExt, paletteLabel: `New ${displayName} Text Notebook`, caption: `Create a new ${displayName} Text Notebook`, kernelIcon: kernelIcon, launcherLabel: displayName, kernelName: spec, }, ]; fileTypes.set(specModel.language, exts); } } } } return fileTypes; } /** * Get all available 'Create New Text Notebook' commands based on configured * formats and available kernels */ export async function getAvailableCreateTextNotebookCommands( includeFormats: string[], availableKernelLanguages: Map, ): Promise> { const numKernels = availableKernelLanguages.size; // Initialise a map of 'Create New Text Notebook' command filetypes const createTextNotebookCommands = new Map(); // Iterate through all JUPYTEXT_CREATE_TEXT_NOTEBOOK_FILETYPE_DATA file types. JUPYTEXT_CREATE_TEXT_NOTEBOOK_FILETYPE_DATA.forEach( (fileTypes: IFileTypeData[], format: string) => { fileTypes.map((fileType: IFileTypeData) => { // If format is auto, we need to add all currently available kernels // For instance if there are Python and R kernels available, format // auto:percent will be replaced by py:percent and R:percent if (format.startsWith('auto')) { const formatType = format.split(':')[1]; let mapIndex = 0; availableKernelLanguages.forEach( (kernelLanguages: IFileTypeData[], kernelKey: string) => { const updatedKernelKey = `${kernelKey}:${formatType}`; createTextNotebookCommands.set(updatedKernelKey, []); mapIndex += 1; kernelLanguages.map((kernelLanguageFileType) => { // Merge fileType object from kernel and Jupytext format and push // it to createTextNotebookCommands const updatedKernelLanguageFileType = { ...kernelLanguageFileType, }; updatedKernelLanguageFileType.fileExt = `${updatedKernelLanguageFileType.fileExt}:${formatType}`; updatedKernelLanguageFileType.paletteLabel = `${updatedKernelLanguageFileType.paletteLabel} with ${fileType.paletteLabel}`; updatedKernelLanguageFileType.caption = `${updatedKernelLanguageFileType.caption} with ${fileType.caption}`; updatedKernelLanguageFileType.launcherLabel = `${updatedKernelLanguageFileType.launcherLabel} - ${fileType.launcherLabel}`; if (numKernels === mapIndex) { updatedKernelLanguageFileType.separator = true; } createTextNotebookCommands .get(updatedKernelKey) .push(updatedKernelLanguageFileType); // Update includeFormats with the language specific formats // Effectiviely we will add formats like py:light, js:light here if (includeFormats.includes(format)) { includeFormats.push(updatedKernelLanguageFileType.fileExt); } }); }, ); } else { if (createTextNotebookCommands.get(format) === undefined) { createTextNotebookCommands.set(format, []); } createTextNotebookCommands.get(format).push(fileType); } }); }, ); return createTextNotebookCommands; } /** * Create New Text Notebook file */ export const createNewTextNotebook = async ( cwd: string, kernelId: string, kernelName: string, format: string, commands: CommandRegistry, ) => { const model = await commands.execute(CommandIDs.newUntitled, { path: cwd, type: 'notebook', // We should not have auto in format at this point. If somehow we end up having // it, ensure we replace by py as Python kernel exists always ext: format.replace('auto', 'py'), }); if (model !== undefined) { const widget = (await commands.execute('docmanager:open', { path: model.path, factory: FACTORY, kernel: { id: kernelId, name: kernelName }, })) as unknown as IDocumentWidget; widget.isUntitled = true; return widget; } }; ================================================ FILE: jupyterlab/packages/jupyterlab-jupytext-extension/style/base.css ================================================ ================================================ FILE: jupyterlab/packages/jupyterlab-jupytext-extension/style/index.css ================================================ @import url('base.css'); ================================================ FILE: jupyterlab/packages/jupyterlab-jupytext-extension/style/index.js ================================================ import './base.css'; ================================================ FILE: jupyterlab/packages/jupyterlab-jupytext-extension/tsconfig.json ================================================ { "compilerOptions": { "declaration": true, "lib": ["es2018", "dom"], "module": "commonjs", "moduleResolution": "node", "noEmitOnError": true, "noUnusedLocals": true, "outDir": "lib", "rootDir": "src", "strict": true, "strictNullChecks": false, "target": "es2018", "types": ["node"], "esModuleInterop": true, "skipLibCheck": true }, "include": ["src/*"] } ================================================ FILE: jupyterlab/packages/jupyterlab-jupytext-extension/ui-tests/README.md ================================================ # Integration Testing This folder contains the integration tests of the extension. They are defined using [Playwright](https://playwright.dev/docs/intro) test runner and [Galata](https://github.com/jupyterlab/jupyterlab/tree/main/galata) helper. The Playwright configuration is defined in [playwright.config.js](./playwright.config.js). The JupyterLab server configuration to use for the integration test is defined in [jupyter_server_test_config.py](./jupyter_server_test_config.py). The default configuration will produce video for failing tests and an HTML report. > There is a new experimental UI mode that you may fall in love with; see [that video](https://www.youtube.com/watch?v=jF0yA-JLQW0). ## Run the tests > All commands are assumed to be executed from the _jupyterlab-jupytext-extension_ directory To run the tests, you need to: 1. Compile the extension: ```sh jlpm install jlpm build:prod ``` > Check the extension is installed in JupyterLab. 2. Install test dependencies (needed only once): ```sh cd ./ui-tests jlpm install jlpm playwright install cd .. ``` 3. Execute the [Playwright](https://playwright.dev/docs/intro) tests: ```sh cd ./ui-tests jlpm playwright test ``` Test results will be shown in the terminal. In case of any test failures, the test report will be opened in your browser at the end of the tests execution; see [Playwright documentation](https://playwright.dev/docs/test-reporters#html-reporter) for configuring that behavior. ## Update the tests snapshots > All commands are assumed to be executed from the _main-menu_ directory If you are comparing snapshots to validate your tests, you may need to update the reference snapshots stored in the repository. To do that, you need to: 1. Compile the extension: ```sh jlpm install jlpm build:prod ``` > Check the extension is installed in JupyterLab. 2. Install test dependencies (needed only once): ```sh cd ./ui-tests jlpm install jlpm playwright install cd .. ``` 3. Execute the [Playwright](https://playwright.dev/docs/intro) command: ```sh cd ./ui-tests jlpm playwright test -u ``` > Some discrepancy may occurs between the snapshots generated on your computer and > the one generated on the CI. To ease updating the snapshots on a PR, you can > type `please update playwright snapshots` to trigger the update by a bot on the CI. > Once the bot has computed new snapshots, it will commit them to the PR branch. ## Create tests > All commands are assumed to be executed from the _main-menu_ directory To create tests, the easiest way is to use the code generator tool of playwright: 1. Compile the extension: ```sh jlpm install jlpm build:prod ``` > Check the extension is installed in JupyterLab. 2. Install test dependencies (needed only once): ```sh cd ./ui-tests jlpm install jlpm playwright install cd .. ``` 3. Start the server: ```sh cd ./ui-tests jlpm start ``` 4. Execute the [Playwright code generator](https://playwright.dev/docs/codegen) in **another terminal**: ```sh cd ./ui-tests jlpm playwright codegen localhost:8888 ``` ## Debug tests > All commands are assumed to be executed from the _main-menu_ directory To debug tests, a good way is to use the inspector tool of playwright: 1. Compile the extension: ```sh jlpm install jlpm build:prod ``` > Check the extension is installed in JupyterLab. 2. Install test dependencies (needed only once): ```sh cd ./ui-tests jlpm install jlpm playwright install cd .. ``` 3. Execute the Playwright tests in [debug mode](https://playwright.dev/docs/debug): ```sh cd ./ui-tests jlpm playwright test --debug ``` ## Upgrade Playwright and the browsers To update the web browser versions, you must update the package `@playwright/test`: ```sh cd ./ui-tests jlpm up "@playwright/test" jlpm playwright install ``` ================================================ FILE: jupyterlab/packages/jupyterlab-jupytext-extension/ui-tests/jupyter_server_test_config.py ================================================ """Server configuration for integration tests. !! Never use this configuration in production because it opens the server to the world and provide access to JupyterLab JavaScript objects through the global window variable. """ from jupyterlab.galata import configure_jupyter_server configure_jupyter_server(c) # noqa: F821 # Uncomment to set server log level to debug level # c.ServerApp.log_level = "DEBUG" ================================================ FILE: jupyterlab/packages/jupyterlab-jupytext-extension/ui-tests/package.json ================================================ { "name": "jupyterlab-jupytext-ui-tests", "version": "1.4.1", "description": "Basic Integration Tests", "private": true, "scripts": { "start": "python -m bash_kernel.install && jupyter lab --allow-root --config jupyter_server_test_config.py", "test": "jlpm playwright test", "test:update": "jlpm playwright test --update-snapshots" }, "devDependencies": { "@jupyterlab/galata": "^5.5.2", "@playwright/test": "^1.55.1" } } ================================================ FILE: jupyterlab/packages/jupyterlab-jupytext-extension/ui-tests/playwright.config.js ================================================ /** * Configuration for Playwright using default from @jupyterlab/galata */ const baseConfig = require('@jupyterlab/galata/lib/playwright-config'); module.exports = { ...baseConfig, projects: [ { name: 'jupytext', testMatch: 'tests/*.ts', testIgnore: '**/.ipynb_checkpoints/**', timeout: 60000, // use: { // launchOptions: { // // Force slow motion // slowMo: 1000, // }, // }, }, ], // Visual comparison of screenshots can be flaky. Use a tolerance expect: { toMatchSnapshot: { maxDiffPixelRatio: 0.02, }, }, webServer: { command: 'jlpm start', url: 'http://localhost:8888/lab', timeout: 120 * 1000, reuseExistingServer: !process.env.CI, }, // Switch to 'always' to keep raw assets for all tests preserveOutput: 'failures-only', // Breaks HTML report if use.video == 'on' // Try 3 retries as some tests are flaky retries: process.env.CI ? 3 : 0, }; ================================================ FILE: jupyterlab/packages/jupyterlab-jupytext-extension/ui-tests/tests/jupytext-launcher.spec.ts ================================================ import { expect, test } from '@jupyterlab/galata'; test.describe('Jupytext Launcher Category', () => { test.use({ autoGoto: false, viewport: { height: 1020, width: 1280 } }); test('should have Jupytext category in launcher', async ({ page }) => { await page.goto(); await page.waitForSelector('.jp-LauncherCard-label'); const imageName = 'launcher-category.png'; expect(await page.screenshot()).toMatchSnapshot(imageName.toLowerCase()); }); }); test.describe('Jupytext Context Menu', () => { test.use({ autoGoto: false, viewport: { height: 1020, width: 1280 } }); test('should have New Text Notebook in Context Menu', async ({ page }) => { await page.goto(); await page.waitForSelector('.jp-FileBrowser'); // Right click within file browser await page.locator('.jp-FileBrowser').click({ button: 'right' }); // Wait for a moment to observe the context menu await page.waitForTimeout(5000); const imageName = 'context-menu.png'; expect(await page.screenshot()).toMatchSnapshot(imageName.toLowerCase()); }); }); ================================================ FILE: jupyterlab/packages/jupyterlab-jupytext-extension/ui-tests/tests/jupytext-menu.spec.ts ================================================ import { expect, test } from '@jupyterlab/galata'; // Main Jupytext menu const jupytextMenu = ['File>New Text Notebook', 'File>Jupytext']; test.describe('Jupytext Menu Tests', () => { test.use({ autoGoto: false }); jupytextMenu.forEach((menuPath) => { test(`Open menu item ${menuPath}`, async ({ page }) => { await page.goto(); await page.menu.open(menuPath); expect(await page.menu.isOpen(menuPath)).toBeTruthy(); const imageName = `opened-jupytext-menu-${menuPath.replace( />/g, '-', )}.png`; // const menu = await page.menu.getOpenMenu(); expect(await page!.screenshot()).toMatchSnapshot(imageName.toLowerCase()); }); }); }); ================================================ FILE: jupyterlab/packages/jupyterlab-jupytext-extension/ui-tests/tests/jupytext-notebook.spec.ts ================================================ import { expect, test } from '@jupyterlab/galata'; // Currently we are enabling only percent and MyST formats in Jupytext menu // So test for only these cases. // If we update our test env with more external kernels, we can include them // here in the formats const createTests = [ { label: 'New Python Text Notebook with Percent Format', extension: '.py', }, { label: 'New Shell Text Notebook with Percent Format', extension: '.sh', }, { label: 'New MyST Markdown Text Notebook', extension: '.md', }, ]; const pairTests = [ { label: 'Percent Format', extension: '.py', }, { label: 'Light Format', extension: '.py', }, { label: 'MyST Markdown', extension: '.md', }, ]; // Get all possible menuPaths const createNewMenuPaths = createTests.map((format) => { return { menuPath: `File>New Text Notebook>${format.label}`, extension: format.extension, }; }); const pairMenuPaths = pairTests.map((format) => { return { menuPath: `File>Jupytext>Pair Notebook>Pair Notebook with ${format.label}`, extension: format.extension, }; }); // Toggle metadata const toggleMetadataPath = 'File>Jupytext>Include Metadata'; // Name of notebook file const fileName = 'notebook.ipynb'; /** * Helper function to populate notebook cells and run them */ async function populateNotebook(extension, page) { await page.notebook.setCell(0, 'raw', 'Just a raw cell'); await page.notebook.addCell( 'markdown', '## This is **bold** and *italic* [link to jupyter.org!](http://jupyter.org)', ); await page.notebook.runCell(1, true); // For bash, use shell code if (extension === '.sh') { await page.notebook.addCell('code', 'echo "This is Bash Kernel"'); } else { await page.notebook.addCell('code', '2 ** 3'); } await page.notebook.runCell(2, true); } test.describe('Jupytext Create Text Notebooks from Menu Tests', () => { createNewMenuPaths.forEach((paths) => { test(`Open menu item ${paths.menuPath}`, async ({ page }) => { // await page.goto(); // Create new text notebook by clicking menupath item await page.menu.clickMenuItem(paths.menuPath); // Wait for the kernel dialog and accept it await page.waitForSelector('.jp-Dialog'); const select = await page.$('.jp-Dialog-body >> select'); // Select appropriate kernel let option: any; if (paths.extension === '.sh') { option = await select!.$('option:has-text("Bash")'); } else { option = await select!.$('option:has-text("Python")'); } await select!.selectOption(option); await page.click('.jp-Dialog .jp-mod-accept'); const firstCell = await page.notebook.getCellLocator(0); await firstCell?.hover(); await expect(firstCell!.locator('.jp-cell-toolbar')).toHaveCount(1); // Populate page await populateNotebook(paths.extension, page); // Toggle Include Metadata. It is enabled by default. // It is to avoid having Jupytext version in metadata in snapshot // If we include it, for every version bump we need to update snapshots as // version changes which will fail UI tests. Just do not include metadata // which will ensure smooth version bumping await page.menu.clickMenuItem(toggleMetadataPath); // Save notebook await page.notebook.save(); // Try to open saved text notebook with Editor factory await page.filebrowser.open(`Untitled${paths.extension}`, 'Editor'); // Compare text notebook contents const imageName = `opened-${paths.menuPath.replace(/>/g, '-')}-text.png`; expect(await page.screenshot()).toMatchSnapshot(imageName.toLowerCase()); }); }); }); test.describe('Jupytext Pair Python Notebooks from Menu Tests', () => { // Before each test start a new notebook and add some cell data test.beforeEach(async ({ page }) => { await page.notebook.createNew(fileName, { kernel: 'python3' }); await populateNotebook('.py', page); }); pairMenuPaths.forEach((paths) => { test(`Open menu item ${paths.menuPath}`, async ({ page }) => { // Click pairing command await page.menu.clickMenuItem(paths.menuPath); // Toggle Include Metadata. It is enabled by default. // It is to avoid having Jupytext version in metadata in snapshot // If we include it, for every version bump we need to update snapshots as // version changes which will fail UI tests. Just do not include metadata // which will ensure smooth version bumping await page.menu.clickMenuItem(toggleMetadataPath); // Wait until we save notebook. Once we save it, paired file appears await page.notebook.save(); // Try to open paired file await page.filebrowser.open(fileName.replace('.ipynb', paths.extension)); const imageName = `paired-jupytext-${paths.menuPath.replace( />/g, '-', )}.png`; expect(await page.screenshot()).toMatchSnapshot(imageName.toLowerCase()); }); }); }); ================================================ FILE: jupyterlab/packages/jupyterlab-jupytext-extension/ui-tests/tests/jupytext-settings.spec.ts ================================================ import { expect, test } from '@jupyterlab/galata'; test('Open the settings editor with a Jupytext query', async ({ page }) => { await page.evaluate(async () => { await window.jupyterapp.commands.execute('settingeditor:open', { query: 'Jupytext', }); }); // Seems like this test is very flaky. Moreover it does not add a lot of value // expect( // await page.locator('.jp-PluginList .jp-FilterBox input').inputValue() // ).toEqual('Jupytext'); await expect(page.locator('.jp-SettingsForm')).toHaveCount(1); const pluginList = page.locator('.jp-PluginList'); expect(await pluginList.screenshot()).toMatchSnapshot( 'jupytext-settings-plugin-list.png', ); const settingsPanel = page.locator('.jp-SettingsPanel'); expect(await settingsPanel.screenshot()).toMatchSnapshot( 'jupytext-settings-panel.png', ); }); ================================================ FILE: jupyterlab/scripts/install_extension.py ================================================ # This script does the "same" job as `jupyter labextension develop --overwrite .` # # Seems like we cannot use the upstream script on our repo organization. # If we want to use the upstream script we need to have a setup.py or pyproject.toml # in jupyterlab/jupyterlab-jupytext folder with the name of the package. # # We are only interested in making a symlink to the # sys.prefix/share/jupyter/labextensions folder for development. We should be able # to do it in simple script # import os import jupyterlab_jupytext from jupyterlab.federated_labextensions import build_labextension, develop_labextension def main(): """Create symlink in sys.prefix based on name of extension""" labexts = jupyterlab_jupytext._jupyter_labextension_paths() base_path = os.path.join( os.path.dirname(os.path.dirname(os.path.abspath(__file__))), "jupyterlab_jupytext", ) for labext in labexts: src = os.path.join(base_path, labext["src"]) dest = labext["dest"] print(f"Installing {src} -> {dest}") if not os.path.exists(src): build_labextension(base_path) full_dest = develop_labextension( src, overwrite=True, symlink=True, user=False, sys_prefix=True, labextensions_dir="", destination=dest, ) print(f"Creating symlink at {full_dest}") if __name__ == "__main__": main() ================================================ FILE: jupyterlab/tsconfig.eslint.json ================================================ { "compilerOptions": { "declaration": true, "lib": ["es2018", "dom"], "module": "commonjs", "moduleResolution": "node", "noEmitOnError": true, "noUnusedLocals": true, "outDir": "lib", "rootDir": "src", "strict": true, "strictNullChecks": false, "target": "es2018", "types": [], "esModuleInterop": true }, "extends": "../../tsconfig.eslint.json", "include": ["**/src/*"] } ================================================ FILE: pyproject.toml ================================================ [build-system] requires = ["hatchling>=1.5.0", "hatch-jupyter-builder>=0.5", "jupyterlab>=4"] build-backend = "hatchling.build" [project] name = "jupytext" description = "Jupyter notebooks as Markdown documents, Julia, Python or R scripts" license = { file = "LICENSE" } authors = [ { name = "Marc Wouts", email = "marc.wouts@gmail.com" }, ] readme = "build/README_with_absolute_links.md" requires-python = ">=3.9" classifiers = [ "Development Status :: 5 - Production/Stable", "License :: OSI Approved :: MIT License", "Environment :: Console", "Framework :: Jupyter", "Framework :: Jupyter :: JupyterLab :: 4", "Framework :: Jupyter :: JupyterLab :: Extensions", "Framework :: Jupyter :: JupyterLab :: Extensions :: Prebuilt", "Intended Audience :: Developers", "Intended Audience :: Science/Research", "Topic :: Text Processing :: Markup", "Programming Language :: Python", "Programming Language :: Python :: 3", "Programming Language :: Python :: 3.9", "Programming Language :: Python :: 3.10", "Programming Language :: Python :: 3.11", "Programming Language :: Python :: 3.12", "Programming Language :: Python :: 3.13", "Programming Language :: Python :: 3.14", ] dependencies = [ "nbformat", "mdit-py-plugins", "markdown-it-py>=1.0", "packaging", "pyyaml", "tomli;python_version<\"3.11\"", ] dynamic = ["version"] [project.urls] Homepage = "https://github.com/mwouts/jupytext" "Source Code" = "https://github.com/mwouts/jupytext" Documentation = "https://jupytext.readthedocs.io" [project.optional-dependencies] # Test related dependencies test = [ "pytest", "pytest-asyncio", "pytest-xdist", "pytest-randomly" ] test-functional = [ "jupytext[test]", "black", ] test-integration = [ "jupytext[test-functional]", "jupyter-server!=2.11", # issue 1165 # jupytext --execute "nbconvert", "ipykernel", ] test-external = [ "jupytext[test-integration]", # jupytext --pipe and --check "autopep8", "isort", "flake8", # Sphinx gallery "sphinx", "sphinx-gallery>=0.8", # Pre-commit tests "gitpython", "pre-commit", # Marimo notebooks "marimo>=0.17.6,<=0.19.4", #1485 # Interaction with other contents managers "jupyter-fs[fs]>=1.0" # 1398 ] # Coverage requirements test-cov = [ "jupytext[test-integration]", "pytest-cov>=2.6.1", ] # Galata test env # Install a non python kernel to ensure extension is working as expected # Kernel spec is installed before running UI tests test-ui = [ "bash_kernel", ] dev = [ "jupytext[test-cov,test-external]", ] # Documentation dependencies docs = [ "sphinx", "sphinx-copybutton", "sphinx-rtd-theme", "myst-parser", ] [project.scripts] "jupytext" = "jupytext.cli:jupytext" "jupytext-config" = "jupytext_config.__main__:main" [tool.hatch.metadata.hooks.custom] path = "tools/absolute_links_in_readme.py" [tool.hatch.version] # Read version string from version.py and use it for the package path = "src/jupytext/version.py" # Hatch first build sdist and then builds a wheel out of that sdist # By using the below config, we remove path prefixes in sdist meaning # that sdist will not have a src in root but directly jupytext and other # modules. # # So when it attempts to build wheel out of the sdist there is no more # src folder and hence it complains about not finding src/jupytext/version.py # file. So, we **should not** use hatch.build.sources here which removes # path prefixes # [tool.hatch.build] # sources = ["src", "jupyterlab"] # Following config is related to JupyterLab extension [tool.hatch.build.targets.sdist] artifacts = ["jupyterlab/jupyterlab_jupytext/labextension"] [tool.hatch.build.targets.wheel] packages = ["src/jupytext", "src/jupytext_config", "jupyterlab/jupyterlab_jupytext"] [tool.hatch.build.targets.wheel.shared-data] "jupyterlab/jupyter-config" = "etc/jupyter" "jupyterlab/jupyterlab_jupytext/labextension" = "share/jupyter/labextensions/jupyterlab-jupytext" [tool.hatch.build.hooks.jupyter-builder] enable-by-default = false # We enable this hook by setting env var HATCH_BUILD_HOOKS_ENABLE=true # So `pip install .` will **not** build JupyterLab related # extension. To install the extension, it is required to run # `HATCH_BUILD_HOOKS_ENABLE=true pip install .` # Runtime dependency for this build hook # We need jupyterlab as build time depdendency to get jlpm (wrapper around yarn) # UPDATE 20260118: Based on https://github.com/jupyterlab/hatch-jupyter-builder/issues/146 # we moved all the dependencies to build system dependencies # We use npm_builder to build the jupyterlab extension build-function = "hatch_jupyter_builder.npm_builder" # Hatch will mark this hook as success upon creation of following files # in the build_dir ensured-targets = [ "jupyterlab/jupyterlab_jupytext/labextension/static/style.js", "jupyterlab/jupyterlab_jupytext/labextension/package.json", ] # If these files already exists in build_dir (after first build), # hatch will skip build step. If there are changes in src/ of # the extension, build will be triggered even if the build assets exist skip-if-exists = ["jupyterlab/jupyterlab_jupytext/labextension/static/style.js"] [tool.hatch.build.hooks.jupyter-builder.build-kwargs] # Root directory where build should be done path = "jupyterlab" # Build command that is defined in package.json build_cmd = "build:prod" # We use jlpm, which is wrapper around yarn to build transpiled assets npm = ["jlpm"] [tool.hatch.build.hooks.jupyter-builder.editable-build-kwargs] path = "jupyterlab" build_cmd = "build" npm = ["jlpm"] # hatch-jupyter-builder hook will check the mtime of source_dir and # compare it with build_dir to decide if build is necessary or not source_dir = "jupyterlab/packages" build_dir = "jupyterlab/jupyterlab_jupytext/labextension" [tool.check-wheel-contents] ignore = ["W002"] # flake8 config has been moved to ruff and a pre-commit config has been # added [tool.ruff] line-length = 127 exclude = [ "tests/data/notebooks/*", ] # Seems like W503 is not implemented in ruff # ref: https://github.com/astral-sh/ruff/issues/4125 lint.ignore = [ "E203", "E231", ] [tool.pytest.ini_options] markers = [ "requires_black", "requires_isort", "requires_flake8", "requires_autopep8", "requires_nbconvert", "requires_myst", "requires_no_myst", "requires_quarto", "requires_marimo", "requires_pandoc", "requires_no_pandoc", "requires_sphinx_gallery", "requires_user_kernel_python3", "requires_ir_kernel", "skip_on_windows", "pre_commit", "asyncio" ] filterwarnings = [ # Uncomment this "error" to turn all unfiltered warnings into errors # "error", # Our cwd_tmpdir fixture "ignore:pathlib.Path.__enter__\\(\\) is deprecated and scheduled for removal in Python 3.13:DeprecationWarning", # Pre-commit "ignore:read_text is deprecated. Use files\\(\\) instead:DeprecationWarning", "ignore:open_text is deprecated. Use files\\(\\) instead:DeprecationWarning", # Jupyter "ignore:Jupyter is migrating its paths to use standard platformdirs:DeprecationWarning", # Jupyter notebook "ignore:Support for bleach <5 will be removed in a future version of nbconvert:DeprecationWarning", # jupyterfs "ignore:run_pre_save_hook is deprecated, use run_pre_save_hooks instead:DeprecationWarning", "ignore:run_post_save_hook is deprecated, use run_post_save_hooks instead:DeprecationWarning", "ignore:Deprecated call to `pkg_resources.declare_namespace:DeprecationWarning", "ignore:pkg_resources is deprecated as an API:DeprecationWarning", # use single quote to denote raw strings in toml # (10 warnings) 'ignore:Passing unrecognized arguments to super\(KernelSpec\).__init__:DeprecationWarning', # Not seen any more with latest Python + libs "ignore:Passing a schema to Validator.iter_errors is deprecated and will be removed in a future release:DeprecationWarning", # in test_utf8_out_331 and two others # Not seen any more with latest Python + libs 'ignore:Exception ignored in. (fmt, formats) where # fmt is the current format, and formats the paired formats. self.paired_notebooks = dict() # Configuration cache, useful when notebooks are listed in a given directory self.cached_config = namedtuple("cached_config", "path config_file config") self.super = super() self.super.__init__(*args, **kwargs) def all_nb_extensions(self, config): """All extensions that should be classified as notebooks""" return [ext if ext.startswith(".") else "." + ext for ext in config.notebook_extensions] def drop_paired_notebook(self, path): """Remove the current notebook from the list of paired notebooks""" if path not in self.paired_notebooks: return fmt, formats = self.paired_notebooks.pop(path) prev_paired_paths = paired_paths(path, fmt, formats) for alt_path, _ in prev_paired_paths: if alt_path in self.paired_notebooks: self.drop_paired_notebook(alt_path) def update_paired_notebooks(self, path, formats): """Update the list of paired notebooks to include/update the current pair""" if not formats: self.drop_paired_notebook(path) return formats = long_form_multiple_formats(formats) _, fmt = find_base_path_and_format(path, formats) new_paired_paths = paired_paths(path, fmt, formats) for alt_path, _ in new_paired_paths: self.drop_paired_notebook(alt_path) if len(formats) == 1 and set(formats[0]) <= {"extension"}: return short_formats = short_form_multiple_formats(formats) for alt_path, alt_fmt in new_paired_paths: self.paired_notebooks[alt_path] = ( short_form_one_format(alt_fmt), short_formats, ) async def create_prefix_dir(self, path, fmt): """Create the prefix dir, if missing""" if "prefix" in fmt and "/" in path: parent_dir = self.get_parent_dir(path) if not await self.dir_exists(parent_dir): await self.create_prefix_dir(parent_dir, fmt) self.log.info("Creating directory %s", parent_dir) await self.super.save(dict(type="directory"), parent_dir) async def save(self, model, path=""): """Save the file model and return the model with no content.""" if model["type"] != "notebook": return await self.super.save(model, path) path = path.strip("/") nbk = model["content"] try: config = await self.get_config(path) jupytext_formats = notebook_formats(nbk, config, path) _, jupytext_formats = self._drop_formats_if_they_dont_match_path(path, None, jupytext_formats) self.update_paired_notebooks(path, jupytext_formats) async def save_one_file(path, fmt): if "format_name" in fmt and fmt["extension"] not in [ ".md", ".markdown", ".Rmd", ]: self.log.info( "Saving %s in format %s:%s", os.path.basename(path), fmt["extension"][1:], fmt["format_name"], ) else: self.log.info("Saving %s", os.path.basename(path)) await self.create_prefix_dir(path, fmt) if fmt["extension"] == ".ipynb": return await self.super.save( dict( type="notebook", content=drop_text_representation_metadata(model["content"]), ), path, ) if model["content"]["metadata"].get("jupytext", {}).get("notebook_metadata_filter") == "-all": self.log.warning( "Stripping metadata from {} as 'Include Metadata' is off " "(toggle 'Include Metadata' in the Jupytext Menu or Commands if desired)".format(path) ) text_model = dict( type="file", format="text", content=writes(nbformat.from_dict(model["content"]), fmt=fmt, config=config), ) return await self.super.save(text_model, path) return await write_pair(path, jupytext_formats, save_one_file) except Exception as e: self.log.error("Error while saving file: %s %s", path, e, exc_info=True) raise HTTPError(500, f"Unexpected error while saving file: {path} {e}") async def _get_with_no_require_hash_argument( self, path, content=True, type=None, format=None, load_alternative_format=True, ): return await self._get_with_require_hash_argument( path, content=content, type=type, format=format, require_hash=False, load_alternative_format=load_alternative_format, ) async def _get_with_require_hash_argument( self, path, content=True, type=None, format=None, require_hash=False, load_alternative_format=True, ): """Takes a path for an entity and returns its model""" path = path.strip("/") ext = os.path.splitext(path)[1] super_kwargs = {"content": content, "type": type, "format": format} if require_hash: super_kwargs["require_hash"] = require_hash # Not a notebook? if not await self.file_exists(path) or await self.dir_exists(path) or (type is not None and type != "notebook"): return await self.super.get(path, **super_kwargs) config = await self.get_config(path, use_cache=content is False) if ext not in self.all_nb_extensions(config): return await self.super.get(path, **super_kwargs) fmt = preferred_format(ext, config.preferred_jupytext_formats_read) if ext == ".ipynb": super_kwargs["type"] = "notebook" model = await self.super.get(path, **super_kwargs) else: super_kwargs["type"] = "file" super_kwargs["format"] = "text" model = await self.super.get(path, **super_kwargs) model["type"] = "notebook" if content: # We may need to update these keys, inherited from text files formats # Cf. https://github.com/mwouts/jupytext/issues/659 model["format"] = "json" model["mimetype"] = None try: model["content"] = reads(model["content"], fmt=fmt, config=config) # mark all code cells from text notebooks as 'trusted' # as they don't have any outputs, cf. #941 for cell in model["content"].cells: if cell.cell_type == "code": cell["metadata"]["trusted"] = True except Exception as err: self.log.error("Error while reading file: %s %s", path, err, exc_info=True) raise HTTPError(500, str(err)) if not load_alternative_format: return model # We will now read a second file if this is a paired notebooks. if content: nbk = model["content"] formats = nbk.metadata.get("jupytext", {}).get("formats") or config.default_formats(path) formats = long_form_multiple_formats(formats, nbk.metadata, auto_ext_requires_language_info=False) else: if path not in self.paired_notebooks: return model _, formats = self.paired_notebooks.get(path) formats = long_form_multiple_formats(formats) # Compute paired notebooks from formats alt_paths = [(path, fmt)] fmt, formats = self._drop_formats_if_they_dont_match_path(path, fmt, formats) if formats: try: _, fmt = find_base_path_and_format(path, formats) alt_paths = paired_paths(path, fmt, formats) self.update_paired_notebooks(path, formats) except InconsistentPath as err: self.log.error( "Unable to read paired notebook: %s %s", path, err, exc_info=True, ) raise HTTPError(500, f"Unable to read paired notebook: {path} {err}") else: if path in self.paired_notebooks: fmt, formats = self.paired_notebooks.get(path) alt_paths = paired_paths(path, fmt, formats) formats = long_form_multiple_formats(formats) if content and len(alt_paths) > 1 and ext == ".ipynb": # Apply default options (like saving and reloading would do) jupytext_metadata = model["content"]["metadata"].get("jupytext", {}) config.set_default_format_options(jupytext_metadata, read=True) if jupytext_metadata: model["content"]["metadata"]["jupytext"] = jupytext_metadata async def get_timestamp(alt_path): # self.exists is not async for AsyncLargeManager, # but MetaManager from fs_manager has an async version exists = self.exists(alt_path) if inspect.isawaitable(exists): exists = await exists if not exists: return None if alt_path == path: return model["last_modified"] return (await self.super.get(alt_path, content=False))["last_modified"] async def read_one_file(alt_path, alt_fmt): if alt_path == path: return model["content"] if alt_path.endswith(".ipynb"): self.log.info(f"Reading OUTPUTS from {alt_path}") return (await self.super.get(alt_path, content=True, type="notebook", format=format))["content"] self.log.info(f"Reading SOURCE from {alt_path}") text = ( await self.super.get( alt_path, content=True, type="file", # Don't use the parent format, see https://github.com/mwouts/jupytext/issues/1124 format=None, ) )["content"] return reads(text, fmt=alt_fmt, config=config) timestamps = {alt_path: await get_timestamp(alt_path) for alt_path, alt_fmt in paired_paths(path, fmt, formats)} inputs, outputs = latest_inputs_and_outputs( path, fmt, formats, lambda alt_path: timestamps[alt_path], contents_manager_mode=True, ) # Modification time of a paired notebook is the timestamp of inputs #118 #978 model["last_modified"] = inputs.timestamp if require_hash: if inputs.path is not None and outputs.path is not None and inputs.path != outputs.path: model_other = await self.super.get( inputs.path if path == outputs.path else outputs.path, content=False, require_hash=True, ) # The hash of a paired file is the concatenation of # the hashes of the input and output files if path == outputs.path: model["hash"] = model_other["hash"] + model["hash"] else: model["hash"] = model["hash"] + model_other["hash"] if not content: return model # Before we combine the two files, we make sure we're not overwriting ipynb cells # with an outdated text file content = None try: if outputs.timestamp and outputs.timestamp > inputs.timestamp + timedelta( seconds=config.outdated_text_notebook_margin ): ts_mismatch = ( "{out} (last modified {out_last}) is more recent than {src} (last modified {src_last})".format( src=inputs.path, src_last=inputs.timestamp, out=outputs.path, out_last=outputs.timestamp, ) ) self.log.warning(ts_mismatch) try: content = await read_pair(inputs, outputs, read_one_file, must_match=True) self.log.warning( "The inputs in {src} and {out} are identical, so the mismatch in timestamps was ignored".format( src=inputs.path, out=outputs.path ) ) except HTTPError: raise except PairedFilesDiffer as diff: raise HTTPError( 400, """{ts_mismatch} Differences (jupytext --diff {src} {out}) are: {diff} Please either: - open {src} in a text editor, make sure it is up to date, and save it, - or delete {src} if not up to date, - or increase check margin by adding, say, outdated_text_notebook_margin = 5 # default is 1 (second) to your jupytext.toml file """.format( ts_mismatch=ts_mismatch, src=inputs.path, out=outputs.path, diff=diff, ), ) except OverflowError: pass if content is not None: model["content"] = content else: try: model["content"] = await read_pair(inputs, outputs, read_one_file) except HTTPError: raise except Exception as err: self.log.error("Error while reading file: %s %s", path, err, exc_info=True) raise HTTPError(500, str(err)) if not outputs.timestamp: set_kernelspec_from_language(model["content"]) return model async def new_untitled(self, path="", type="", ext=""): """Create a new untitled file or directory in path We override the base function because that one does not take the 'ext' argument into account when type=="notebook". See https://github.com/mwouts/jupytext/issues/443 """ if type != "notebook" and ext != ".ipynb": return await self.super.new_untitled(path, type, ext) ext = ext or ".ipynb" if ":" in ext: ext, format_name = ext.split(":", 1) else: format_name = "" path = path.strip("/") if not await self.dir_exists(path): raise HTTPError(404, "No such directory: %s" % path) untitled = self.untitled_notebook config = await self.get_config(path) name = self.increment_notebook_filename(config, untitled + ext, path) path = f"{path}/{name}" model = {"type": "notebook"} if format_name: model["format"] = "json" model["content"] = nbformat.v4.nbbase.new_notebook(metadata={"jupytext": {"formats": ext + ":" + format_name}}) return await self.new(model, path) def increment_notebook_filename(self, config, filename, path=""): """Increment a notebook filename until it is unique, regardless of extension""" # Extract the full suffix from the filename (e.g. .tar.gz) path = path.strip("/") basename, dot, ext = filename.partition(".") ext = dot + ext for i in itertools.count(): if i: insert_i = f"{i}" else: insert_i = "" basename_i = basename + insert_i name = basename_i + ext if not any(self.exists(f"{path}/{basename_i}{nb_ext}") for nb_ext in config.notebook_extensions): break return name async def trust_notebook(self, path): """Trust the current notebook""" if path.endswith(".ipynb") or path not in self.paired_notebooks: await self.super.trust_notebook(path) return fmt, formats = self.paired_notebooks[path] for alt_path, alt_fmt in paired_paths(path, fmt, formats): if alt_fmt["extension"] == ".ipynb": await self.super.trust_notebook(alt_path) async def rename_file(self, old_path, new_path): """ Rename the current file. If the file is a notebook, we rename the paired files as well """ # If the file is not a notebook, we call the parent rename_file method ext = os.path.splitext(old_path)[1] config = await self.get_config(old_path, use_cache=True) if ext not in self.all_nb_extensions(config): await self.super.rename_file(old_path, new_path) return if old_path not in self.paired_notebooks: try: # we do not know yet if this is a paired notebook (#190) # -> to get this information we open the notebook self.log.info("Opening %s to check if it is a paired notebook", old_path) await self.get(old_path, content=True) except Exception: pass if old_path not in self.paired_notebooks: await self.super.rename_file(old_path, new_path) return fmt, formats = self.paired_notebooks.get(old_path) fmt, formats = self._drop_formats_if_they_dont_match_path(new_path, fmt, formats) old_alt_paths = paired_paths(old_path, fmt, formats) # Is the new file name consistent with suffix? try: new_base = base_path(new_path, fmt) except HTTPError: raise except Exception as err: self.log.error( "Error while renaming file from %s to %s: %s", old_path, new_path, err, exc_info=True, ) raise HTTPError(500, str(err)) for old_alt_path, alt_fmt in old_alt_paths: new_alt_path = full_path(new_base, alt_fmt) if self.exists(old_alt_path): await self.create_prefix_dir(new_alt_path, alt_fmt) await self.super.rename_file(old_alt_path, new_alt_path) self.drop_paired_notebook(old_path) self.update_paired_notebooks(new_path, formats) def get_parent_dir(self, path): """The parent directory""" if "/" in path: return path.rsplit("/", 1)[0] # jupyter-fs if ":" in path and hasattr(self, "_managers"): if path.endswith(":"): return "" return path.rsplit(":", 1)[0] + ":" return "" async def get_config_file(self, directory): """Return the jupytext configuration file, if any""" for jupytext_config_file in JUPYTEXT_CONFIG_FILES: path = directory + "/" + jupytext_config_file if await self.file_exists(path): if not self.allow_hidden and jupytext_config_file.startswith("."): self.log.warning(f"Ignoring config file {path} (see Jupytext issue #964)") continue return path pyproject_path = directory + "/" + PYPROJECT_FILE if await self.file_exists(pyproject_path): model = await self.get(pyproject_path, type="file") try: doc = tomllib.loads(model["content"]) except tomllib.TOMLDecodeError as e: self.log.warning(f"Cannot load {pyproject_path}: {e}") else: if doc.get("tool", {}).get("jupytext") is not None: return pyproject_path if not directory: return None parent_dir = self.get_parent_dir(directory) return await self.get_config_file(parent_dir) async def load_config_file(self, config_file, *, prev_config_file, prev_config, is_os_path=False): """Load the configuration file""" if config_file is None: return None if config_file.endswith(".py") and not is_os_path: config_file = self._get_os_path(config_file) is_os_path = True config_content = None if not is_os_path: try: model = await self.super.get(config_file, content=True, type="file") config_content = model["content"] except HTTPError: pass config = load_jupytext_configuration_file(config_file, config_content) if config is None: return config log_level = config.cm_config_log_level if log_level == "info_if_changed": if config_file != prev_config_file or config != prev_config: log_level = "info" else: log_level = "none" if log_level != "none": getattr(self.log, log_level)("Loaded Jupytext configuration file at %s", config_file) return config async def get_config(self, path, use_cache=False): """Return the Jupytext configuration for the given path""" parent_dir = self.get_parent_dir(path) # When listing the notebooks for the tree view, we use a cache for the configuration file # The cache will be refreshed when a notebook is opened or saved, or when we go # to a different directory. if not use_cache or parent_dir != self.cached_config.path: try: config_file = await self.get_config_file(parent_dir) if config_file: self.cached_config.config = await self.load_config_file( config_file, prev_config_file=self.cached_config.config_file, prev_config=self.cached_config.config, ) else: config_file = find_global_jupytext_configuration_file() self.cached_config.config = await self.load_config_file( config_file, prev_config_file=self.cached_config.config_file, prev_config=self.cached_config.config, is_os_path=True, ) self.cached_config.config_file = config_file self.cached_config.path = parent_dir except JupytextConfigurationError as err: self.log.error( "Error while reading config file: %s %s", config_file, err, exc_info=True, ) raise HTTPError(500, f"{err}") if self.cached_config.config is not None: return self.cached_config.config if isinstance(self.notebook_extensions, str): self.notebook_extensions = self.notebook_extensions.split(",") return self def _drop_formats_if_they_dont_match_path(self, path, fmt, formats): if formats is None: return fmt, formats list_of_formats = long_form_multiple_formats(formats) try: _, _ = find_base_path_and_format(path, list_of_formats) except InconsistentPath: for fmt in list_of_formats: try: _, adjusted_format = base_path_and_adjusted_fmt(path, fmt) except InconsistentPath: continue else: self.log.warning( "Notebook %s matches none of the expected formats. " 'Ignoring formats="%s" and using formats="%s" instead.', path, short_form_multiple_formats(formats), short_form_one_format(adjusted_format), ) new_formats = [adjusted_format] if isinstance(formats, list): return adjusted_format, new_formats return short_form_one_format(adjusted_format), short_form_multiple_formats(new_formats) return fmt, formats if "require_hash" in inspect.signature(base_contents_manager_class.get).parameters: AsyncJupytextContentsManager.get = AsyncJupytextContentsManager._get_with_require_hash_argument else: AsyncJupytextContentsManager.get = AsyncJupytextContentsManager._get_with_no_require_hash_argument return AsyncJupytextContentsManager try: # The AsyncLargeFileManager is taken by default from jupyter_server if available from jupyter_server.services.contents.largefilemanager import AsyncLargeFileManager AsyncTextFileContentsManager = build_async_jupytext_contents_manager_class(AsyncLargeFileManager) except ImportError: # If we can't find jupyter_server then we take the file manager from notebook # import notebook.transutils needs to happen before notebook.services.contents.filemanager, see #75 try: import notebook.transutils # noqa except ImportError: pass try: from notebook.services.contents.largefilemanager import AsyncLargeFileManager AsyncTextFileContentsManager = build_async_jupytext_contents_manager_class(AsyncLargeFileManager) except ImportError: # Older versions of notebook do not have the LargeFileManager #217 from notebook.services.contents.filemanager import FileContentsManager AsyncTextFileContentsManager = build_async_jupytext_contents_manager_class(FileContentsManager) ================================================ FILE: src/jupytext/async_pairs.py ================================================ import jupytext from .combine import combine_inputs_with_outputs from .compare import compare from .formats import check_file_version, long_form_multiple_formats from .paired_paths import find_base_path_and_format, full_path from .pairs import PairedFilesDiffer async def read_pair(inputs, outputs, read_one_file, must_match=False): """Read a notebook given its inputs and outputs path and formats""" if not outputs.path or outputs.path == inputs.path: return await read_one_file(inputs.path, inputs.fmt) notebook = await read_one_file(inputs.path, inputs.fmt) check_file_version(notebook, inputs.path, outputs.path) notebook_with_outputs = await read_one_file(outputs.path, outputs.fmt) if must_match: in_text = jupytext.writes(notebook, inputs.fmt) out_text = jupytext.writes(notebook_with_outputs, inputs.fmt) diff = compare(out_text, in_text, outputs.path, inputs.path, return_diff=True) if diff: raise PairedFilesDiffer(diff) notebook = combine_inputs_with_outputs(notebook, notebook_with_outputs, fmt=inputs.fmt) return notebook async def write_pair(path, formats, write_one_file): """ Call the function 'write_one_file' on each of the paired path/formats """ formats = long_form_multiple_formats(formats) base, _ = find_base_path_and_format(path, formats) # Save as ipynb first return_value = None value = None ipynb_changed = False for fmt in formats[::-1]: if fmt["extension"] != ".ipynb": continue alt_path = full_path(base, fmt) value = await write_one_file(alt_path, fmt) ipynb_changed = ipynb_changed or value.get("modified", False) if alt_path == path: return_value = value # And then to the other formats, in reverse order so that # the first format is the most recent for fmt in formats[::-1]: if fmt["extension"] == ".ipynb": continue alt_path = full_path(base, fmt) if ipynb_changed: value = await write_one_file(alt_path, fmt, force_update_timestamp=True) else: # in the contents manager the write_one_file always writes anyway value = await write_one_file(alt_path, fmt) if alt_path == path: return_value = value # Update modified timestamp to match that of the pair #207 if isinstance(return_value, dict) and "last_modified" in return_value: return_value["last_modified"] = value["last_modified"] return return_value ================================================ FILE: src/jupytext/cell_metadata.py ================================================ """ Convert between text notebook metadata and jupyter cell metadata. Standard cell metadata are documented here: See also https://ipython.org/ipython-doc/3/notebook/nbformat.html#cell-metadata """ import ast import re from json import dumps, loads try: from json import JSONDecodeError except ImportError: JSONDecodeError = ValueError from .languages import _JUPYTER_LANGUAGES # Map R Markdown's "echo", "results" and "include" to "hide_input" and "hide_output", that are understood by the # `runtools` extension for Jupyter notebook, and by nbconvert (use the `hide_input_output.tpl` template). # See http://jupyter-contrib-nbextensions.readthedocs.io/en/latest/nbextensions/runtools/readme.html _RMARKDOWN_TO_RUNTOOLS_OPTION_MAP = [ (("include", "FALSE"), [("hide_input", True), ("hide_output", True)]), (("echo", "FALSE"), [("hide_input", True)]), (("results", "'hide'"), [("hide_output", True)]), (("results", '"hide"'), [("hide_output", True)]), ] # Alternatively, Jupytext can also map the Jupyter Book options to R Markdown _RMARKDOWN_TO_JUPYTER_BOOK_MAP = [ (("include", "FALSE"), "remove_cell"), (("echo", "FALSE"), "remove_input"), (("results", "'hide'"), "remove_output"), (("results", '"hide"'), "remove_output"), ] _JUPYTEXT_CELL_METADATA = [ # Pre-jupytext metadata "skipline", "noskipline", # Jupytext metadata "cell_marker", "lines_to_next_cell", "lines_to_end_of_cell_marker", ] _IGNORE_CELL_METADATA = ",".join( f"-{name}" for name in [ # Frequent cell metadata that should not enter the text representation # (these metadata are preserved in the paired Jupyter notebook). "autoscroll", "collapsed", "scrolled", "trusted", "execution", "ExecuteTime", ] + _JUPYTEXT_CELL_METADATA ) # In R Markdown we might have options without a value _IS_IDENTIFIER = re.compile(r"^[a-zA-Z_\.]+[a-zA-Z0-9_\.]*$") _IS_VALID_METADATA_KEY = re.compile(r"^[a-zA-Z0-9_\.@/-]+$") class RLogicalValueError(Exception): """Incorrect value for R boolean""" class RMarkdownOptionParsingError(Exception): """Error when parsing Rmd cell options""" def _py_logical_values(rbool): if rbool in ["TRUE", "T"]: return True if rbool in ["FALSE", "F"]: return False raise RLogicalValueError def metadata_to_rmd_options(language, metadata, use_runtools=False): """Convert language and metadata information to their rmd representation""" options = (language or "R").lower() if "name" in metadata: options += " " + metadata["name"] + "," del metadata["name"] if use_runtools: for rmd_option, jupyter_options in _RMARKDOWN_TO_RUNTOOLS_OPTION_MAP: if all([metadata.get(opt_name) == opt_value for opt_name, opt_value in jupyter_options]): options += " {}={},".format(rmd_option[0], "FALSE" if rmd_option[1] is False else rmd_option[1]) for opt_name, _ in jupyter_options: metadata.pop(opt_name) else: for rmd_option, tag in _RMARKDOWN_TO_JUPYTER_BOOK_MAP: if tag in metadata.get("tags", []): options += " {}={},".format(rmd_option[0], "FALSE" if rmd_option[1] is False else rmd_option[1]) metadata["tags"] = [i for i in metadata["tags"] if i != tag] if not metadata["tags"]: metadata.pop("tags") for opt_name in metadata: opt_value = metadata[opt_name] opt_name = opt_name.strip() if opt_name == "active": options += f' {opt_name}="{str(opt_value)}",' elif isinstance(opt_value, bool): options += " {}={},".format(opt_name, "TRUE" if opt_value else "FALSE") elif isinstance(opt_value, list): options += " {}={},".format( opt_name, "c({})".format(", ".join([f'"{str(v)}"' for v in opt_value])), ) elif isinstance(opt_value, str): if opt_value.startswith("#R_CODE#"): options += f" {opt_name}={opt_value[8:]}," elif '"' not in opt_value: options += f' {opt_name}="{opt_value}",' else: options += f" {opt_name}='{opt_value}'," else: options += f" {opt_name}={str(opt_value)}," if not language: options = options[2:] return options.strip(",").strip() def update_metadata_from_rmd_options(name, value, metadata, use_runtools=False): """Map the R Markdown cell visibility options to the Jupyter ones""" if use_runtools: for rmd_option, jupyter_options in _RMARKDOWN_TO_RUNTOOLS_OPTION_MAP: if name == rmd_option[0] and value == rmd_option[1]: for opt_name, opt_value in jupyter_options: metadata[opt_name] = opt_value return True else: for rmd_option, tag in _RMARKDOWN_TO_JUPYTER_BOOK_MAP: if name == rmd_option[0] and value == rmd_option[1]: metadata.setdefault("tags", []).append(tag) return True return False class ParsingContext: """ Class for determining where to split rmd options """ parenthesis_count = 0 curly_bracket_count = 0 square_bracket_count = 0 in_single_quote = False in_double_quote = False def __init__(self, line): self.line = line def in_global_expression(self): """Currently inside an expression""" return ( self.parenthesis_count == 0 and self.curly_bracket_count == 0 and self.square_bracket_count == 0 and not self.in_single_quote and not self.in_double_quote ) def count_special_chars(self, char, prev_char): """Update parenthesis counters""" if char == "(": self.parenthesis_count += 1 elif char == ")": self.parenthesis_count -= 1 if self.parenthesis_count < 0: raise RMarkdownOptionParsingError(f'Option line "{self.line}" has too many closing parentheses') elif char == "{": self.curly_bracket_count += 1 elif char == "}": self.curly_bracket_count -= 1 if self.curly_bracket_count < 0: raise RMarkdownOptionParsingError(f'Option line "{self.line}" has too many closing curly brackets') elif char == "[": self.square_bracket_count += 1 elif char == "]": self.square_bracket_count -= 1 if self.square_bracket_count < 0: raise RMarkdownOptionParsingError(f'Option line "{self.line}" has too many closing square brackets') elif char == "'" and prev_char != "\\" and not self.in_double_quote: self.in_single_quote = not self.in_single_quote elif char == '"' and prev_char != "\\" and not self.in_single_quote: self.in_double_quote = not self.in_double_quote def parse_rmd_options(line): """ Given a R markdown option line, returns a list of pairs name,value :param line: :return: """ parsing_context = ParsingContext(line) result = [] prev_char = "" name = "" value = "" for char in "," + line + ",": if parsing_context.in_global_expression(): if char == ",": if name != "" or value != "": if result and name == "": raise RMarkdownOptionParsingError(f'Option line "{line}" has no name for option value {value}') result.append((name.strip(), value.strip())) name = "" value = "" elif char == "=": if name == "": name = value value = "" else: value += char else: parsing_context.count_special_chars(char, prev_char) value += char else: parsing_context.count_special_chars(char, prev_char) value += char prev_char = char if not parsing_context.in_global_expression(): raise RMarkdownOptionParsingError(f'Option line "{line}" is not properly terminated') return result def rmd_options_to_metadata(options, use_runtools=False): """Parse rmd options and return a metadata dictionary""" options = re.split(r"\s|,", options, maxsplit=1) # Special case Wolfram Language, which sadly has a space in the language # name. if options[0:2] == ["wolfram", "language"]: options[0:2] = ["wolfram language"] if len(options) == 1: language = options[0] chunk_options = [] else: language, others = options language = language.rstrip(" ,") others = others.lstrip(" ,") chunk_options = parse_rmd_options(others) language = "R" if language == "r" else language metadata = {} for i, opt in enumerate(chunk_options): name, value = opt if i == 0 and name == "": metadata["name"] = value continue if update_metadata_from_rmd_options(name, value, metadata, use_runtools=use_runtools): continue try: metadata[name] = _py_logical_values(value) continue except RLogicalValueError: metadata[name] = value for name in metadata: try_eval_metadata(metadata, name) if "eval" in metadata and not is_active(".Rmd", metadata): del metadata["eval"] return metadata.get("language") or language, metadata def try_eval_metadata(metadata, name): """Evaluate the metadata to a python object, if possible""" value = metadata[name] if not isinstance(value, str): return if (value.startswith('"') and value.endswith('"')) or (value.startswith("'") and value.endswith("'")): metadata[name] = value[1:-1] return if value.startswith("c(") and value.endswith(")"): value = "[" + value[2:-1] + "]" elif value.startswith("list(") and value.endswith(")"): value = "[" + value[5:-1] + "]" try: metadata[name] = ast.literal_eval(value) except (SyntaxError, ValueError): if name != "name": metadata[name] = "#R_CODE#" + value return def is_active(ext, metadata, default=True): """Is the cell active for the given file extension?""" if metadata.get("run_control", {}).get("frozen") is True: return ext == ".ipynb" for tag in metadata.get("tags", []): if tag.startswith("active-"): return ext.replace(".", "") in tag.split("-") if "active" not in metadata: return default return ext.replace(".", "") in re.split(r"\.|,", metadata["active"]) def metadata_to_double_percent_options(metadata, plain_json): """Metadata to double percent lines""" text = [] if "title" in metadata: text.append(metadata.pop("title")) if "cell_depth" in metadata: text.insert(0, "%" * metadata.pop("cell_depth")) if "cell_type" in metadata: text.append("[{}]".format(metadata.pop("region_name", metadata.pop("cell_type")))) return metadata_to_text(" ".join(text), metadata, plain_json=plain_json) def incorrectly_encoded_metadata(text): """Encode a text that Jupytext cannot parse as a cell metadata""" return {"incorrectly_encoded_metadata": text} def is_identifier(text): return bool(_IS_IDENTIFIER.match(text)) def is_valid_metadata_key(text): """Can this text be a proper key?""" return bool(_IS_VALID_METADATA_KEY.match(text)) def is_jupyter_language(language): """Is this a jupyter language?""" for lang in _JUPYTER_LANGUAGES: if language.lower() == lang.lower(): return True return False def parse_key_equal_value(text): """Parse a string of the form 'key1=value1 key2=value2'""" # Empty metadata? text = text.strip() if not text: return {} last_space_pos = text.rfind(" ") # Just an identifier? if not text.startswith("--") and is_identifier(text[last_space_pos + 1 :]): key = text[last_space_pos + 1 :] value = None result = {key: value} if last_space_pos > 0: result.update(parse_key_equal_value(text[:last_space_pos])) return result # Iterate on the '=' signs, starting from the right equal_sign_pos = None while True: equal_sign_pos = text.rfind("=", None, equal_sign_pos) if equal_sign_pos < 0: return incorrectly_encoded_metadata(text) # Do we have an identifier on the left of the equal sign? prev_whitespace = text[:equal_sign_pos].rstrip().rfind(" ") key = text[prev_whitespace + 1 : equal_sign_pos].strip() if not is_valid_metadata_key(key): continue try: value = relax_json_loads(text[equal_sign_pos + 1 :]) except (ValueError, SyntaxError): # try with a longer expression continue # Combine with remaining metadata metadata = parse_key_equal_value(text[:prev_whitespace]) if prev_whitespace > 0 else {} # Append our value metadata[key] = value # And return return metadata def relax_json_loads(text, catch=False): """Parse a JSON string or similar""" text = text.strip() try: return loads(text) except JSONDecodeError: pass if not catch: return ast.literal_eval(text) try: return ast.literal_eval(text) except (ValueError, SyntaxError): pass return incorrectly_encoded_metadata(text) def is_json_metadata(text): """Is this a JSON metadata?""" first_curly_bracket = text.find("{") if first_curly_bracket < 0: return False first_equal_sign = text.find("=") if first_equal_sign < 0: return True return first_curly_bracket < first_equal_sign def text_to_metadata(text, allow_title=False): """Parse the language/cell title and associated metadata""" # Parse the language or cell title = everything before the last blank space before { or = text = text.strip() first_curly_bracket = text.find("{") first_equal_sign = text.find("=") if first_curly_bracket < 0 or (0 <= first_equal_sign < first_curly_bracket): # this is a key=value metadata line # case one = the options may be preceded with a language if not allow_title: if is_jupyter_language(text): return text, {} if " " not in text: return "", parse_key_equal_value(text) language, options = text.split(" ", 1) if is_jupyter_language(language): return language, parse_key_equal_value(options) return "", parse_key_equal_value(text) # case two = a title may be before the options # we split the title into words if first_equal_sign >= 0: words = text[:first_equal_sign].split(" ") # last word is the key before the equal sign! while words and not words[-1]: words.pop() if words: words.pop() else: words = text.split(" ") # and we remove words on the right that are attributes (they start with '.') while words and (not words[-1].strip() or words[-1].startswith(".")): words.pop() title = " ".join(words) return title, parse_key_equal_value(text[len(title) :]) # json metadata line return ( text[:first_curly_bracket].strip(), relax_json_loads(text[first_curly_bracket:], catch=True), ) def metadata_to_text(language_or_title, metadata=None, plain_json=False): """Write the cell metadata in the format key=value""" # Was metadata the first argument? if metadata is None: metadata, language_or_title = language_or_title, metadata metadata = {key: metadata[key] for key in metadata if key not in _JUPYTEXT_CELL_METADATA} text = [language_or_title] if language_or_title else [] if language_or_title is None: if "title" in metadata and "{" not in metadata["title"] and "=" not in metadata["title"]: text.append(metadata.pop("title")) if plain_json: if metadata: text.append(dumps(metadata)) else: for key in metadata: if key == "incorrectly_encoded_metadata": text.append(metadata[key]) elif metadata[key] is None: text.append(key) else: text.append(f"{key}={dumps(metadata[key])}") return " ".join(text) ================================================ FILE: src/jupytext/cell_reader.py ================================================ """Read notebook cells from their text representation""" import re from collections import defaultdict from copy import copy from itertools import count from nbformat.v4.nbbase import new_code_cell, new_markdown_cell, new_raw_cell from .doxygen import doxygen_to_markdown from .languages import _SCRIPT_EXTENSIONS # Sphinx Gallery is an optional dependency. And we intercept the SyntaxError for #301 try: from sphinx_gallery.notebook import rst2md except (ImportError, SyntaxError): # pragma: no cover rst2md = None from .cell_metadata import ( is_active, is_json_metadata, rmd_options_to_metadata, text_to_metadata, ) from .languages import _JUPYTER_LANGUAGES_LOWER_AND_UPPER from .magics import is_magic, need_explicit_marker, uncomment_magic, unescape_code_start from .pep8 import pep8_lines_between_cells from .stringparser import StringParser _BLANK_LINE = re.compile(r"^\s*$") _PY_INDENTED = re.compile(r"^\s") def uncomment(lines, prefix="#", suffix=""): """Remove prefix and space, or only prefix, when possible""" if prefix: prefix_and_space = prefix + " " length_prefix = len(prefix) length_prefix_and_space = len(prefix_and_space) lines = [ ( line[length_prefix_and_space:] if line.startswith(prefix_and_space) else (line[length_prefix:] if line.startswith(prefix) else line) ) for line in lines ] if suffix: space_and_suffix = " " + suffix length_suffix = len(suffix) length_space_and_suffix = len(space_and_suffix) lines = [ ( line[:-length_space_and_suffix] if line.endswith(space_and_suffix) else (line[:-length_suffix] if line.endswith(suffix) else line) ) for line in lines ] return lines def paragraph_is_fully_commented(lines, comment, main_language): """Is the paragraph fully commented?""" for i, line in enumerate(lines): if line.startswith(comment): if line[len(comment) :].lstrip().startswith(comment): continue if is_magic(line, main_language): return False continue return i > 0 and _BLANK_LINE.match(line) return True def next_code_is_indented(lines): """Is the next unescaped line indented?""" for line in lines: if _BLANK_LINE.match(line): continue return _PY_INDENTED.match(line) return False def count_lines_to_next_cell(cell_end_marker, next_cell_start, total, explicit_eoc): """How many blank lines between end of cell marker and next cell?""" if cell_end_marker < total: lines_to_next_cell = next_cell_start - cell_end_marker if explicit_eoc: lines_to_next_cell -= 1 if next_cell_start >= total: lines_to_next_cell += 1 return lines_to_next_cell return 1 def last_two_lines_blank(source): """Are the two last lines blank, and not the third last one?""" if len(source) < 3: return False return not _BLANK_LINE.match(source[-3]) and _BLANK_LINE.match(source[-2]) and _BLANK_LINE.match(source[-1]) class BaseCellReader: """A class that can read notebook cells from their text representation""" default_comment_magics = None lines_to_next_cell = 1 start_code_re = None simple_start_code_re = None end_code_re = None # How to make code inactive comment = "" # Any specific prefix for lines in markdown cells (like in R spin format?) markdown_prefix = None def __init__(self, fmt=None, default_language=None): """Create a cell reader with empty content""" if not fmt: fmt = {} self.ext = fmt.get("extension") self.default_language = default_language or _SCRIPT_EXTENSIONS.get(self.ext, {}).get("language", "python") self.comment_magics = fmt.get("comment_magics", self.default_comment_magics) self.use_runtools = fmt.get("use_runtools", False) self.format_version = fmt.get("format_version") self.metadata = None self.org_content = [] self.content = [] self.explicit_soc = None self.explicit_eoc = None self.cell_type = None self.language = None self.cell_metadata_json = fmt.get("cell_metadata_json", False) self.doxygen_equation_markers = fmt.get("doxygen_equation_markers", False) def read(self, lines): """Read one cell from the given lines, and return the cell, plus the position of the next cell """ # Do we have an explicit code marker on the first line? self.metadata_and_language_from_option_line(lines[0]) if self.metadata and "language" in self.metadata: self.language = self.metadata.pop("language") # Parse cell till its end and set content, lines_to_next_cell pos_next_cell = self.find_cell_content(lines) if self.cell_type == "code": new_cell = new_code_cell elif self.cell_type == "markdown": new_cell = new_markdown_cell else: new_cell = new_raw_cell if not self.metadata: self.metadata = {} if self.ext == ".py": expected_blank_lines = pep8_lines_between_cells(self.org_content or [""], lines[pos_next_cell:], self.ext) else: expected_blank_lines = 1 if self.lines_to_next_cell != expected_blank_lines: self.metadata["lines_to_next_cell"] = self.lines_to_next_cell if self.language: self.metadata["language"] = self.language return ( new_cell(source="\n".join(self.content), metadata=self.metadata), pos_next_cell, ) def metadata_and_language_from_option_line(self, line): """Parse code options on the given line. When a start of a code cell is found, self.metadata is set to a dictionary.""" if self.start_code_re.match(line): self.language, self.metadata = self.options_to_metadata(self.start_code_re.findall(line)[0]) def options_to_metadata(self, options): """Return language (str) and metadata (dict) from the option line""" raise NotImplementedError("Option parsing must be implemented in a sub class") def find_cell_end(self, lines): """Return position of end of cell marker, and position of first line after cell""" raise NotImplementedError("This method must be implemented in a sub class") def find_cell_content(self, lines): """Parse cell till its end and set content, lines_to_next_cell. Return the position of next cell start""" cell_end_marker, next_cell_start, self.explicit_eoc = self.find_cell_end(lines) # Metadata to dict if self.metadata is None: cell_start = 0 self.metadata = {} else: cell_start = 1 # Cell content source = lines[cell_start:cell_end_marker] self.org_content = copy(source) # Exactly two empty lines at the end of cell (caused by PEP8)? if self.ext == ".py" and self.explicit_eoc: if last_two_lines_blank(source): source = source[:-2] lines_to_end_of_cell_marker = 2 else: lines_to_end_of_cell_marker = 0 pep8_lines = pep8_lines_between_cells(source, lines[cell_end_marker:], self.ext) if lines_to_end_of_cell_marker != (0 if pep8_lines == 1 else 2): self.metadata["lines_to_end_of_cell_marker"] = lines_to_end_of_cell_marker # Uncomment content self.explicit_soc = cell_start > 0 self.content = self.extract_content(source) # Is this an inactive cell? if self.cell_type == "code": if not is_active(".ipynb", self.metadata): if self.metadata.get("active") == "": del self.metadata["active"] self.cell_type = "raw" elif self.ext in [".md", ".markdown"] and not self.language: # Markdown files in version >= 1.3 represent code chunks with no language as Markdown cells if self.format_version not in ["1.0", "1.1"]: self.cell_type = "markdown" self.explicit_eoc = False cell_end_marker += 1 self.content = lines[:cell_end_marker] # Previous versions mapped those to raw cells else: self.cell_type = "raw" # Explicit end of cell marker? if ( next_cell_start + 1 < len(lines) and _BLANK_LINE.match(lines[next_cell_start]) and not _BLANK_LINE.match(lines[next_cell_start + 1]) ): next_cell_start += 1 elif ( self.explicit_eoc and next_cell_start + 2 < len(lines) and _BLANK_LINE.match(lines[next_cell_start]) and _BLANK_LINE.match(lines[next_cell_start + 1]) and not _BLANK_LINE.match(lines[next_cell_start + 2]) ): next_cell_start += 2 self.lines_to_next_cell = count_lines_to_next_cell(cell_end_marker, next_cell_start, len(lines), self.explicit_eoc) return next_cell_start def uncomment_code_and_magics(self, lines): """Uncomment code and possibly commented magic commands""" raise NotImplementedError("This method must be implemented in a sub class") def extract_content(self, lines): # Code cells with just a multiline string become Markdown cells if self.ext == ".py" and not is_active(self.ext, self.metadata, self.cell_type == "code"): content = "\n".join(lines).strip() for prefix in [""] if self.ext != ".py" else ["", "r", "R"]: for triple_quote in ['"""', "'''"]: left = prefix + triple_quote right = triple_quote if content.startswith(left) and content.endswith(right) and len(content) >= len(left + right): content = content[len(left) : -len(right)] # Trim first/last line return if content.startswith("\n"): content = content[1:] left = left + "\n" if content.endswith("\n"): content = content[:-1] right = "\n" + right if not prefix: if len(left) == len(right) == 4: self.metadata["cell_marker"] = left[:3] elif len(left[1:]) == len(right) == 4: self.metadata["cell_marker"] = left[:4] else: self.metadata["cell_marker"] = left + "," + right return content.splitlines() if not is_active(self.ext, self.metadata) or ( "active" not in self.metadata and self.language and self.language != self.default_language ): return uncomment(lines, self.comment if self.ext not in [".r", ".R"] else "#") return self.uncomment_code_and_magics(lines) class MarkdownCellReader(BaseCellReader): """Read notebook cells from Markdown documents""" comment = "" start_code_re = re.compile( r"^```(`*)(\s*)({})($|\s.*$)".format("|".join(_JUPYTER_LANGUAGES_LOWER_AND_UPPER).replace("+", "\\+")) ) non_jupyter_code_re = re.compile(r"^```") end_code_re = re.compile(r"^```\s*$") start_region_re = re.compile(r"^\s*$") end_region_re = None default_comment_magics = False def __init__(self, fmt=None, default_language=None): super().__init__(fmt, default_language) self.split_at_heading = (fmt or {}).get("split_at_heading", False) self.in_region = False self.in_raw = False if self.format_version in ["1.0", "1.1"] and self.ext != ".Rmd": # Restore the pattern used in Markdown <= 1.1 self.start_code_re = re.compile(r"^```(.*)") self.non_jupyter_code_re = re.compile(r"^```\{") def metadata_and_language_from_option_line(self, line): match_region = self.start_region_re.match(line) if match_region: self.in_region = True groups = match_region.groups() region_name = groups[0] self.end_region_re = re.compile(rf"^\s*$") self.cell_metadata_json = self.cell_metadata_json or is_json_metadata(groups[1]) title, self.metadata = text_to_metadata(groups[1], allow_title=True) if region_name == "raw": self.cell_type = "raw" else: self.cell_type = "markdown" if title: self.metadata["title"] = title if region_name in ["markdown", "md"]: self.metadata["region_name"] = region_name elif self.start_code_re.match(line): self.language, self.metadata = self.options_to_metadata(self.start_code_re.findall(line)[0]) # Cells with a .noeval attribute are markdown cells #347 if self.metadata.get(".noeval", "") is None: self.cell_type = "markdown" self.metadata = {} self.language = None def options_to_metadata(self, options): if isinstance(options, tuple): self.end_code_re = re.compile("```" + options[0]) options = " ".join(options[1:]) else: self.end_code_re = re.compile(r"^```\s*$") self.cell_metadata_json = self.cell_metadata_json or is_json_metadata(options) return text_to_metadata(options) def find_cell_end(self, lines): """Return position of end of cell marker, and position of first line after cell""" if self.in_region: for i, line in enumerate(lines): if self.end_region_re.match(line): return i, i + 1, True elif self.metadata is None: # default markdown: (last) two consecutive blank lines, except when in code blocks self.cell_type = "markdown" prev_blank = 0 in_explicit_code_block = False in_indented_code_block = False for i, line in enumerate(lines): if in_explicit_code_block and self.end_code_re.match(line): in_explicit_code_block = False continue if prev_blank and line.startswith(" ") and not _BLANK_LINE.match(line): in_indented_code_block = True prev_blank = 0 continue if in_indented_code_block and not _BLANK_LINE.match(line) and not line.startswith(" "): in_indented_code_block = False if in_indented_code_block or in_explicit_code_block: continue if self.start_region_re.match(line): if i > 1 and prev_blank: return i - 1, i, False return i, i, False if self.start_code_re.match(line): language, metadata = self.options_to_metadata(self.start_code_re.findall(line)[0]) # Cells with a .noeval attribute are markdown cells #347 # R Markdown notebooks can have bibliography and index blocks, cf #1161 and #1429 if language not in _JUPYTER_LANGUAGES_LOWER_AND_UPPER or metadata.get(".noeval", "") is None: in_explicit_code_block = True prev_blank = 0 continue if i > 1 and prev_blank: return i - 1, i, False return i, i, False elif line.startswith("```{"): # These are non-code blocks but we still need to look for their end in_explicit_code_block = True prev_blank = 0 continue if self.non_jupyter_code_re.match(line): if prev_blank >= 2: return i - 2, i, True in_explicit_code_block = True prev_blank = 0 continue if self.split_at_heading and line.startswith("#") and prev_blank >= 1: return i - 1, i, False if _BLANK_LINE.match(lines[i]): prev_blank += 1 elif prev_blank >= 2: return i - 2, i, True else: prev_blank = 0 else: self.cell_type = "code" # At some point we could remove the below, in which we make sure not to break language strings # into multiple cells (#419). Indeed, now that the markdown cell uses one extra backtick (#712) # we should not have the issue any more parser = StringParser(self.language or self.default_language) for i, line in enumerate(lines): # skip cell header if i == 0: continue if parser.is_quoted(): parser.read_line(line) continue parser.read_line(line) if self.end_code_re.match(line): return i, i + 1, True # End not found return len(lines), len(lines), False def uncomment_code_and_magics(self, lines): if self.cell_type == "code" and self.comment_magics: lines = uncomment_magic(lines, self.language) if self.cell_type == "markdown" and self.doxygen_equation_markers: lines = doxygen_to_markdown("\n".join(lines)).splitlines() return lines class RMarkdownCellReader(MarkdownCellReader): """Read notebook cells from R Markdown notebooks""" comment = "" start_code_re = re.compile(r"^```{(.*)}\s*$") non_jupyter_code_re = re.compile(r"^```([^\{]|\s*$)") default_language = "R" default_comment_magics = True def options_to_metadata(self, options): return rmd_options_to_metadata(options, self.use_runtools) def uncomment_code_and_magics(self, lines): if self.cell_type == "code" and self.comment_magics and is_active(self.ext, self.metadata): uncomment_magic(lines, self.language or self.default_language) return lines class ScriptCellReader(BaseCellReader): # pylint: disable=W0223 """Read notebook cells from scripts (common base for R and Python scripts)""" def uncomment_code_and_magics(self, lines): if self.cell_type == "code" or self.comment != "#'": if self.comment_magics: if is_active(self.ext, self.metadata): uncomment_magic( lines, self.language or self.default_language, explicitly_code=self.explicit_soc, ) if ( self.cell_type == "code" and not self.explicit_soc and need_explicit_marker(lines, self.language or self.default_language) ): self.metadata["comment_questions"] = False else: lines = uncomment(lines) if self.default_language == "go" and self.language is None: lines = [re.sub(r"^((//\s*)*)(//\s*gonb:%%)", r"\1%%", line) for line in lines] if self.cell_type == "code": return unescape_code_start(lines, self.ext, self.language or self.default_language) return uncomment(lines, self.markdown_prefix or self.comment, self.comment_suffix) class RScriptCellReader(ScriptCellReader): """Read notebook cells from R scripts written according to the knitr-spin syntax""" comment = "#'" comment_suffix = "" markdown_prefix = "#'" default_language = "R" start_code_re = re.compile(r"^#\+(.*)\s*$") default_comment_magics = True def options_to_metadata(self, options): return rmd_options_to_metadata("r " + options, self.use_runtools) def find_cell_end(self, lines): """Return position of end of cell marker, and position of first line after cell""" if self.metadata is None and lines[0].startswith("#'"): self.cell_type = "markdown" for i, line in enumerate(lines): if not line.startswith("#'"): if _BLANK_LINE.match(line): return i, i + 1, False return i, i, False return len(lines), len(lines), False if self.metadata and "cell_type" in self.metadata: self.cell_type = self.metadata.pop("cell_type") else: self.cell_type = "code" parser = StringParser(self.language or self.default_language) for i, line in enumerate(lines): # skip cell header if self.metadata is not None and i == 0: continue if parser.is_quoted(): parser.read_line(line) continue parser.read_line(line) if self.start_code_re.match(line) or (self.markdown_prefix and line.startswith(self.markdown_prefix)): if i > 0 and _BLANK_LINE.match(lines[i - 1]): if i > 1 and _BLANK_LINE.match(lines[i - 2]): return i - 2, i, False return i - 1, i, False return i, i, False if _BLANK_LINE.match(line): if not next_code_is_indented(lines[i:]): if i > 0: return i, i + 1, False if len(lines) > 1 and not _BLANK_LINE.match(lines[1]): return 1, 1, False return 1, 2, False return len(lines), len(lines), False class LightScriptCellReader(ScriptCellReader): """Read notebook cells from plain Python or Julia files. Cells are identified by line breaks, unless they start with an explicit marker '# +'""" default_comment_magics = True cell_marker_start = None cell_marker_end = None def __init__(self, fmt=None, default_language=None): super().__init__(fmt, default_language) self.ext = self.ext or ".py" script = _SCRIPT_EXTENSIONS[self.ext] self.default_language = default_language or script["language"] self.comment = script["comment"] self.comment_suffix = script.get("comment_suffix", "") self.ignore_end_marker = True self.explicit_end_marker_required = False if fmt and fmt.get("format_name", "light") == "light" and "cell_markers" in fmt and fmt["cell_markers"] != "+,-": self.cell_marker_start, self.cell_marker_end = fmt["cell_markers"].split(",", 1) self.start_code_re = re.compile("^" + re.escape(self.comment) + r"\s*" + self.cell_marker_start + r"(.*)$") self.end_code_re = re.compile("^" + re.escape(self.comment) + r"\s*" + self.cell_marker_end + r"\s*$") else: self.start_code_re = re.compile("^" + re.escape(self.comment) + r"\s*\+(.*)$") def metadata_and_language_from_option_line(self, line): if self.start_code_re.match(line): # Remove the OCAML suffix if self.comment_suffix: if line.endswith(" " + self.comment_suffix): line = line[: -len(" " + self.comment_suffix)] elif line.endswith(self.comment_suffix): line = line[: -len(self.comment_suffix)] # We want to parse inner most regions as cells. # Thus, if we find another region start before the end for this region, # we will have ignore the metadata that we found here, and move on to the next cell. groups = self.start_code_re.match(line).groups() self.language, self.metadata = self.options_to_metadata(groups[0]) self.ignore_end_marker = False if self.cell_marker_start: self.explicit_end_marker_required = True elif self.simple_start_code_re and self.simple_start_code_re.match(line): self.metadata = {} self.ignore_end_marker = False elif self.cell_marker_end and self.end_code_re.match(line): self.metadata = None self.cell_type = "code" def options_to_metadata(self, options): self.cell_metadata_json = self.cell_metadata_json or is_json_metadata(options) title, metadata = text_to_metadata(options, allow_title=True) # Cell type for cell_type in ["markdown", "raw", "md"]: code = f"[{cell_type}]" if code in title: title = title.replace(code, "").strip() metadata["cell_type"] = cell_type if cell_type == "md": metadata["region_name"] = cell_type metadata["cell_type"] = "markdown" break # Spyder has sub cells cell_depth = 0 while title.startswith("%"): cell_depth += 1 title = title[1:] if cell_depth: metadata["cell_depth"] = cell_depth title = title.strip() if title: metadata["title"] = title return None, metadata def find_cell_end(self, lines): """Return position of end of cell marker, and position of first line after cell""" if ( self.metadata is None and not (self.cell_marker_end and self.end_code_re.match(lines[0])) and paragraph_is_fully_commented(lines, self.comment, self.default_language) ): self.cell_type = "markdown" for i, line in enumerate(lines): if _BLANK_LINE.match(line): return i, i + 1, False return len(lines), len(lines), False if self.metadata is None: self.end_code_re = None elif not self.cell_marker_end: end_of_cell = self.metadata.get("endofcell", "-") self.end_code_re = re.compile("^" + re.escape(self.comment) + " " + end_of_cell + r"\s*$") return self.find_region_end(lines) def find_region_end(self, lines): """Find the end of the region started with start and end markers""" if self.metadata and "cell_type" in self.metadata: self.cell_type = self.metadata.pop("cell_type") else: self.cell_type = "code" parser = StringParser(self.language or self.default_language) for i, line in enumerate(lines): # skip cell header if self.metadata is not None and i == 0: continue if parser.is_quoted(): parser.read_line(line) continue parser.read_line(line) # New code region # Simple code pattern in LightScripts must be preceded with a blank line if self.start_code_re.match(line) or ( self.simple_start_code_re and self.simple_start_code_re.match(line) and (self.cell_marker_start or i == 0 or _BLANK_LINE.match(lines[i - 1])) ): if self.explicit_end_marker_required: # Metadata here was conditioned on finding an explicit end marker # before the next start marker. So we dismiss it. self.metadata = None self.language = None if i > 0 and _BLANK_LINE.match(lines[i - 1]): if i > 1 and _BLANK_LINE.match(lines[i - 2]): return i - 2, i, False return i - 1, i, False return i, i, False if not self.ignore_end_marker and self.end_code_re: if self.end_code_re.match(line): return i, i + 1, True elif _BLANK_LINE.match(line): if not next_code_is_indented(lines[i:]): if i > 0: return i, i + 1, False if len(lines) > 1 and not _BLANK_LINE.match(lines[1]): return 1, 1, False return 1, 2, False return len(lines), len(lines), False class DoublePercentScriptCellReader(LightScriptCellReader): """Read notebook cells from Spyder/VScode scripts (#59)""" default_comment_magics = True def __init__(self, fmt, default_language=None): LightScriptCellReader.__init__(self, fmt, default_language) script = _SCRIPT_EXTENSIONS[self.ext] self.default_language = default_language or script["language"] self.comment = script["comment"] self.comment_suffix = script.get("comment_suffix", "") self.start_code_re = re.compile(rf"^\s*{re.escape(self.comment)}\s*%%(%*)\s(.*)$") self.alternative_start_code_re = re.compile(rf"^\s*{re.escape(self.comment)}\s*(%%||In\[[0-9 ]*\]:?)\s*$") self.explicit_soc = True def metadata_and_language_from_option_line(self, line): """Parse code options on the given line. When a start of a code cell is found, self.metadata is set to a dictionary.""" if self.start_code_re.match(line): line = uncomment([line], self.comment, self.comment_suffix)[0] self.language, self.metadata = self.options_to_metadata(line[line.find("%%") + 2 :]) else: self.metadata = {} def find_cell_content(self, lines): """Parse cell till its end and set content, lines_to_next_cell. Return the position of next cell start""" cell_end_marker, next_cell_start, explicit_eoc = self.find_cell_end(lines) # Metadata to dict if self.start_code_re.match(lines[0]) or self.alternative_start_code_re.match(lines[0]): cell_start = 1 else: cell_start = 0 # Cell content source = lines[cell_start:cell_end_marker] self.org_content = copy(source) self.content = self.extract_content(source) self.lines_to_next_cell = count_lines_to_next_cell(cell_end_marker, next_cell_start, len(lines), explicit_eoc) return next_cell_start def find_cell_end(self, lines): """Return position of end of cell marker, and position of first line after cell""" if self.metadata and "cell_type" in self.metadata: self.cell_type = self.metadata.pop("cell_type") elif not is_active(".ipynb", self.metadata): if self.metadata.get("active") == "": del self.metadata["active"] self.cell_type = "raw" if is_active(self.ext, self.metadata): self.comment = "" else: self.cell_type = "code" next_cell = len(lines) parser = StringParser(self.language or self.default_language) for i, line in enumerate(lines): if parser.is_quoted(): parser.read_line(line) continue parser.read_line(line) if i > 0 and (self.start_code_re.match(line) or self.alternative_start_code_re.match(line)): next_cell = i break if last_two_lines_blank(lines[:next_cell]): return next_cell - 2, next_cell, False if next_cell > 0 and _BLANK_LINE.match(lines[next_cell - 1]): return next_cell - 1, next_cell, False return next_cell, next_cell, False class HydrogenCellReader(DoublePercentScriptCellReader): """Read notebook cells from Hydrogen scripts (#59)""" default_comment_magics = False class SphinxGalleryScriptCellReader(ScriptCellReader): # pylint: disable=W0223 """Read notebook cells from Sphinx Gallery scripts (#80)""" comment = "#" default_language = "python" default_comment_magics = True twenty_hash = re.compile(r"^#( |)#{19,}\s*$") default_markdown_cell_marker = "#" * 79 markdown_marker = None def __init__(self, fmt=None, default_language="python"): super().__init__(fmt, default_language) self.ext = ".py" self.rst2md = (fmt or {}).get("rst2md", False) def start_of_new_markdown_cell(self, line): """Does this line starts a new markdown cell? Then, return the cell marker""" for empty_markdown_cell in ['""', "''"]: if line == empty_markdown_cell: return empty_markdown_cell for triple_quote in ['"""', "'''"]: if line.startswith(triple_quote): return triple_quote if self.twenty_hash.match(line): return line return None def metadata_and_language_from_option_line(self, line): self.markdown_marker = self.start_of_new_markdown_cell(line) if self.markdown_marker: self.cell_type = "markdown" if self.markdown_marker != self.default_markdown_cell_marker: self.metadata = {"cell_marker": self.markdown_marker} else: self.cell_type = "code" def find_cell_end(self, lines): """Return position of end of cell, and position of first line after cell, and whether there was an explicit end of cell marker""" if self.cell_type == "markdown": # Empty cell "" or '' if len(self.markdown_marker) <= 2: if len(lines) == 1 or _BLANK_LINE.match(lines[1]): return 0, 2, True return 0, 1, True # Multi-line comment with triple quote if len(self.markdown_marker) == 3: for i, line in enumerate(lines): if (i > 0 or line.strip() != self.markdown_marker) and line.rstrip().endswith(self.markdown_marker): explicit_end_of_cell_marker = line.strip() == self.markdown_marker if explicit_end_of_cell_marker: end_of_cell = i else: end_of_cell = i + 1 if len(lines) <= i + 1 or _BLANK_LINE.match(lines[i + 1]): return end_of_cell, i + 2, explicit_end_of_cell_marker return end_of_cell, i + 1, explicit_end_of_cell_marker else: # 20 # or more for i, line in enumerate(lines[1:], 1): if not line.startswith(self.comment): if _BLANK_LINE.match(line): return i, i + 1, False return i, i, False elif self.cell_type == "code": parser = StringParser("python") for i, line in enumerate(lines): if parser.is_quoted(): parser.read_line(line) continue if self.start_of_new_markdown_cell(line): if i > 0 and _BLANK_LINE.match(lines[i - 1]): return i - 1, i, False return i, i, False parser.read_line(line) return len(lines), len(lines), False def find_cell_content(self, lines): """Parse cell till its end and set content, lines_to_next_cell. Return the position of next cell start""" cell_end_marker, next_cell_start, explicit_eoc = self.find_cell_end(lines) # Metadata to dict cell_start = 0 if self.cell_type == "markdown": if self.markdown_marker in ['"""', "'''"]: # Remove the triple quotes if lines[0].strip() == self.markdown_marker: cell_start = 1 else: lines[0] = lines[0][3:] if not explicit_eoc: last = lines[cell_end_marker - 1] lines[cell_end_marker - 1] = last[: last.rfind(self.markdown_marker)] if self.twenty_hash.match(self.markdown_marker): cell_start = 1 else: self.metadata = {} # Cell content source = lines[cell_start:cell_end_marker] self.org_content = copy(source) if self.cell_type == "code" and self.comment_magics: uncomment_magic(source, self.language or self.default_language) if self.cell_type == "markdown" and source: if self.markdown_marker.startswith(self.comment): source = uncomment(source, self.comment) if self.rst2md: if rst2md: gallery_conf = {"notebook_images": False} heading_level_counter = count(start=1) heading_levels = defaultdict(lambda: next(heading_level_counter)) source = rst2md("\n".join(source), gallery_conf, "", heading_levels).splitlines() else: raise ImportError("Could not import rst2md from sphinx_gallery.notebook") # pragma: no cover self.content = source self.lines_to_next_cell = count_lines_to_next_cell(cell_end_marker, next_cell_start, len(lines), explicit_eoc) return next_cell_start ================================================ FILE: src/jupytext/cell_to_text.py ================================================ """Export notebook cells as text""" import re import warnings from copy import copy from .cell_metadata import ( _IGNORE_CELL_METADATA, is_active, metadata_to_double_percent_options, metadata_to_rmd_options, metadata_to_text, ) from .cell_reader import LightScriptCellReader, MarkdownCellReader, RMarkdownCellReader from .doxygen import markdown_to_doxygen from .languages import _SCRIPT_EXTENSIONS, cell_language, comment_lines, same_language from .magics import comment_magic, escape_code_start, need_explicit_marker from .metadata_filter import filter_metadata from .pep8 import pep8_lines_between_cells def cell_source(cell): """Return the source of the current cell, as an array of lines""" source = cell.source if source == "": return [""] if source.endswith("\n"): return source.splitlines() + [""] return source.splitlines() def three_backticks_or_more(lines): """Return a string with enough backticks to encapsulate the given code cell in Markdown cf. https://github.com/mwouts/jupytext/issues/712""" code_cell_delimiter = "```" for line in lines: if not line.startswith(code_cell_delimiter): continue for char in line[len(code_cell_delimiter) :]: if char != "`": break code_cell_delimiter += "`" code_cell_delimiter += "`" return code_cell_delimiter class BaseCellExporter: """A class that represent a notebook cell as text""" default_comment_magics = None parse_cell_language = True def __init__(self, cell, default_language, fmt=None, unsupported_keys=None): self.fmt = fmt or {} self.ext = self.fmt.get("extension") self.cell_type = cell.cell_type self.source = cell_source(cell) self.unfiltered_metadata = cell.metadata self.metadata = filter_metadata( cell.metadata, self.fmt.get("cell_metadata_filter"), _IGNORE_CELL_METADATA, unsupported_keys=unsupported_keys, ) if self.parse_cell_language: custom_cell_magics = self.fmt.get("custom_cell_magics", "").split(",") self.language, magic_args = cell_language(self.source, default_language, custom_cell_magics) if magic_args: self.metadata["magic_args"] = magic_args else: self.language = None if self.language and not self.ext.endswith(".Rmd"): self.metadata["language"] = self.language self.language = self.language or cell.metadata.get("language", default_language) self.default_language = default_language self.comment = _SCRIPT_EXTENSIONS.get(self.ext, {}).get("comment", "#") self.comment_suffix = _SCRIPT_EXTENSIONS.get(self.ext, {}).get("comment_suffix", "") self.comment_magics = self.fmt.get("comment_magics", self.default_comment_magics) self.cell_metadata_json = self.fmt.get("cell_metadata_json", False) self.use_runtools = self.fmt.get("use_runtools", False) self.doxygen_equation_markers = self.fmt.get("doxygen_equation_markers", False) # how many blank lines before next cell self.lines_to_next_cell = cell.metadata.get("lines_to_next_cell") self.lines_to_end_of_cell_marker = cell.metadata.get("lines_to_end_of_cell_marker") if ( cell.cell_type == "raw" and "active" not in self.metadata and not any(tag.startswith("active-") for tag in self.metadata.get("tags", [])) ): self.metadata["active"] = "" def is_code(self): """Is this cell a code cell?""" if self.cell_type == "code": return True if ( self.cell_type == "raw" and "active" in self.metadata or any(tag.startswith("active-") for tag in self.metadata.get("tags", [])) ): return True return False def use_triple_quotes(self): """Should this markdown cell use triple quote?""" if "cell_marker" not in self.unfiltered_metadata: return False cell_marker = self.unfiltered_metadata["cell_marker"] if cell_marker in ['"""', "'''"]: return True if "," not in cell_marker: return False left, right = cell_marker.split(",") return left[:3] == right[-3:] and left[:3] in ['"""', "'''"] def cell_to_text(self): """Return the text representation for the cell""" # Trigger cell marker in case we are using multiline quotes if self.cell_type != "code" and not self.metadata and self.use_triple_quotes(): self.metadata["cell_type"] = self.cell_type # Go notebooks have '%%' or '%% -' magic commands that need to be escaped if self.default_language == "go" and self.language == "go": self.source = [re.sub(r"^(//\s*)*(%%\s*$|%%\s+-.*$)", r"\1//gonb:\2", line) for line in self.source] if self.is_code(): return self.code_to_text() source = copy(self.source) if not self.comment: escape_code_start(source, self.ext, None) return self.markdown_to_text(source) def markdown_to_text(self, source): """Escape the given source, for a markdown cell""" cell_markers = self.unfiltered_metadata.get("cell_marker", self.fmt.get("cell_markers")) if cell_markers: if "," in cell_markers: left, right = cell_markers.split(",", 1) else: left = cell_markers + "\n" if cell_markers.startswith(("r", "R")): cell_markers = cell_markers[1:] right = "\n" + cell_markers if (left[:3] == right[-3:] or (left[:1] in ["r", "R"] and left[1:4] == right[-3:])) and right[-3:] in [ '"""', "'''", ]: # Markdown cells that contain a backslash should be encoded as raw strings if left[:1] not in ["r", "R"] and "\\" in "\n".join(source) and self.fmt.get("format_name") == "percent": left = "r" + left source = copy(source) source[0] = left + source[0] source[-1] = source[-1] + right return source if ( self.comment and self.comment != "#'" and is_active(self.ext, self.metadata) and self.fmt.get("format_name") not in ["percent", "hydrogen"] ): source = copy(source) comment_magic( source, self.language, self.comment_magics, explicitly_code=self.cell_type == "code", ) return comment_lines(source, self.comment, self.comment_suffix) def code_to_text(self): """Return the text representation of this cell as a code cell""" raise NotImplementedError("This method must be implemented in a sub-class") def remove_eoc_marker(self, text, next_text): """Remove end-of-cell marker when possible""" # pylint: disable=W0613,R0201 return text class MarkdownCellExporter(BaseCellExporter): """A class that represent a notebook cell as Markdown""" default_comment_magics = False cell_reader = MarkdownCellReader def __init__(self, *args, **kwargs): BaseCellExporter.__init__(self, *args, **kwargs) self.comment = "" def html_comment(self, metadata, code="region"): """Protect a Markdown or Raw cell with HTML comments""" if metadata: region_start = [ "", ] region_start = " ".join(region_start) else: region_start = f"" return [region_start] + self.source + [f""] def cell_to_text(self): """Return the text representation of a cell""" if self.cell_type == "markdown": if self.doxygen_equation_markers and self.cell_type == "markdown": self.source = markdown_to_doxygen("\n".join(self.source)).splitlines() # Is an explicit region required? if self.metadata: protect = True else: # Would the text be parsed to a shorter cell/a cell with a different type? cell, pos = self.cell_reader(self.fmt).read(self.source) protect = pos < len(self.source) or cell.cell_type != self.cell_type if protect: return self.html_comment(self.metadata, self.metadata.pop("region_name", "region")) return self.source return self.code_to_text() def code_to_text(self): """Return the text representation of a code cell""" source = copy(self.source) comment_magic(source, self.language, self.comment_magics) if self.metadata.get("active") == "": self.metadata.pop("active") self.language = self.metadata.pop("language", self.language) if self.cell_type == "raw" and not is_active(self.ext, self.metadata, False): return self.html_comment(self.metadata, "raw") options = metadata_to_text(self.language, self.metadata) code_cell_delimiter = three_backticks_or_more(self.source) return [code_cell_delimiter + options] + source + [code_cell_delimiter] class RMarkdownCellExporter(MarkdownCellExporter): """A class that represent a notebook cell as R Markdown""" default_comment_magics = True cell_reader = RMarkdownCellReader def __init__(self, *args, **kwargs): MarkdownCellExporter.__init__(self, *args, **kwargs) self.ext = ".Rmd" self.comment = "" def code_to_text(self): """Return the text representation of a code cell""" active = is_active(self.ext, self.metadata) source = copy(self.source) if active: comment_magic(source, self.language, self.comment_magics) lines = [] if not is_active(self.ext, self.metadata): self.metadata["eval"] = False options = metadata_to_rmd_options(self.language, self.metadata, self.use_runtools) lines.append(f"```{{{options}}}") lines.extend(source) lines.append("```") return lines def endofcell_marker(source, comment): """Issues #31 #38: does the cell contain a blank line? In that case we add an end-of-cell marker""" endofcell = "-" while True: endofcell_re = re.compile(rf"^{re.escape(comment)}( )" + endofcell + r"\s*$") if list(filter(endofcell_re.match, source)): endofcell = endofcell + "-" else: return endofcell class LightScriptCellExporter(BaseCellExporter): """A class that represent a notebook cell as a Python or Julia script""" default_comment_magics = True use_cell_markers = True cell_marker_start = None cell_marker_end = None def __init__(self, *args, **kwargs): BaseCellExporter.__init__(self, *args, **kwargs) if "cell_markers" in self.fmt: if "," not in self.fmt["cell_markers"]: warnings.warn( "Ignored cell markers '{}' as it does not match the expected 'start,end' pattern".format( self.fmt.pop("cell_markers") ) ) elif self.fmt["cell_markers"] != "+,-": self.cell_marker_start, self.cell_marker_end = self.fmt["cell_markers"].split(",", 1) for key in ["endofcell"]: if key in self.unfiltered_metadata: self.metadata[key] = self.unfiltered_metadata[key] def is_code(self): # Treat markdown cells with metadata as code cells (#66) if (self.cell_type == "markdown" and self.metadata) or self.use_triple_quotes(): if is_active(self.ext, self.metadata): self.metadata["cell_type"] = self.cell_type self.source = self.markdown_to_text(self.source) self.cell_type = "code" self.unfiltered_metadata = copy(self.unfiltered_metadata) self.unfiltered_metadata.pop("cell_marker", "") return True return super().is_code() def code_to_text(self): """Return the text representation of a code cell""" active = is_active(self.ext, self.metadata, same_language(self.language, self.default_language)) source = copy(self.source) escape_code_start(source, self.ext, self.language) comment_questions = self.metadata.pop("comment_questions", True) if active: comment_magic(source, self.language, self.comment_magics, comment_questions) else: source = self.markdown_to_text(source) if ( active and comment_questions and need_explicit_marker(self.source, self.language, self.comment_magics) ) or self.explicit_start_marker(source): self.metadata["endofcell"] = self.cell_marker_end or endofcell_marker(source, self.comment) if not self.metadata or not self.use_cell_markers: return source lines = [] endofcell = self.metadata["endofcell"] if endofcell == "-" or self.cell_marker_end: del self.metadata["endofcell"] cell_start = [self.comment, self.cell_marker_start or "+"] options = metadata_to_double_percent_options(self.metadata, self.cell_metadata_json) if options: cell_start.append(options) lines.append(" ".join(cell_start)) lines.extend(source) lines.append(self.comment + f" {endofcell}") return lines def explicit_start_marker(self, source): """Does the python representation of this cell requires an explicit start of cell marker?""" if not self.use_cell_markers: return False if self.metadata: return True if self.cell_marker_start: start_code_re = re.compile("^" + self.comment + r"\s*" + self.cell_marker_start + r"\s*(.*)$") end_code_re = re.compile("^" + self.comment + r"\s*" + self.cell_marker_end + r"\s*$") if start_code_re.match(source[0]) or end_code_re.match(source[0]): return False if all([line.startswith(self.comment) for line in self.source]): return True if LightScriptCellReader(self.fmt).read(source)[1] < len(source): return True return False def remove_eoc_marker(self, text, next_text): """Remove end of cell marker when next cell has an explicit start marker""" if self.cell_marker_start: return text if self.is_code() and text[-1] == self.comment + " -": # remove end of cell marker when redundant with next explicit marker if not next_text or next_text[0].startswith(self.comment + " +"): text = text[:-1] # When we do not need the end of cell marker, number of blank lines is the max # between that required at the end of the cell, and that required before the next cell. if self.lines_to_end_of_cell_marker and ( self.lines_to_next_cell is None or self.lines_to_end_of_cell_marker > self.lines_to_next_cell ): self.lines_to_next_cell = self.lines_to_end_of_cell_marker else: # Insert blank lines at the end of the cell blank_lines = self.lines_to_end_of_cell_marker if blank_lines is None: # two blank lines when required by pep8 blank_lines = pep8_lines_between_cells(text[:-1], next_text, self.ext) blank_lines = 0 if blank_lines < 2 else 2 text = text[:-1] + [""] * blank_lines + text[-1:] return text class BareScriptCellExporter(LightScriptCellExporter): """A class that writes notebook cells as scripts with no cell markers""" use_cell_markers = False class RScriptCellExporter(BaseCellExporter): """A class that can represent a notebook cell as a R script""" default_comment_magics = True def __init__(self, *args, **kwargs): BaseCellExporter.__init__(self, *args, **kwargs) self.comment = "#'" def code_to_text(self): """Return the text representation of a code cell""" active = is_active(self.ext, self.metadata) source = copy(self.source) escape_code_start(source, self.ext, self.language) if active: comment_magic(source, self.language, self.comment_magics) if not active: source = ["# " + line if line else "#" for line in source] lines = [] if not is_active(self.ext, self.metadata): self.metadata["eval"] = False options = metadata_to_rmd_options(None, self.metadata, self.use_runtools) if options: lines.append(f"#+ {options}") lines.extend(source) return lines class DoublePercentCellExporter(BaseCellExporter): # pylint: disable=W0223 """A class that can represent a notebook cell as a Spyder/VScode script (#59)""" default_comment_magics = True parse_cell_language = True def __init__(self, *args, **kwargs): BaseCellExporter.__init__(self, *args, **kwargs) self.cell_markers = self.fmt.get("cell_markers") def cell_to_text(self): """Return the text representation for the cell""" # Go notebooks have '%%' or '%% -' magic commands that need to be escaped if self.default_language == "go" and self.language == "go": self.source = [re.sub(r"^(//\s*)*(%%\s*$|%%\s+-.*$)", r"\1//gonb:\2", line) for line in self.source] active = is_active(self.ext, self.metadata, same_language(self.language, self.default_language)) if self.cell_type == "raw" and "active" in self.metadata and self.metadata["active"] == "": del self.metadata["active"] if not self.is_code(): self.metadata["cell_type"] = self.cell_type options = metadata_to_double_percent_options(self.metadata, self.cell_metadata_json) indent = "" if self.is_code() and active and self.source: first_line = self.source[0] if first_line.strip(): left_space = re.compile(r"^(\s*)").match(first_line) if left_space: indent = left_space.groups()[0] if options.startswith("%") or not options: lines = comment_lines(["%%" + options], indent + self.comment, self.comment_suffix) else: lines = comment_lines(["%% " + options], indent + self.comment, self.comment_suffix) if self.is_code() and active: source = copy(self.source) comment_magic(source, self.language, self.comment_magics) if source == [""]: return lines return lines + source return lines + self.markdown_to_text(self.source) class HydrogenCellExporter(DoublePercentCellExporter): # pylint: disable=W0223 """A class that can represent a notebook cell as a Hydrogen script (#59)""" default_comment_magics = False parse_cell_language = False class SphinxGalleryCellExporter(BaseCellExporter): # pylint: disable=W0223 """A class that can represent a notebook cell as a Sphinx Gallery script (#80)""" default_cell_marker = "#" * 79 default_comment_magics = True def __init__(self, *args, **kwargs): BaseCellExporter.__init__(self, *args, **kwargs) self.comment = "#" for key in ["cell_marker"]: if key in self.unfiltered_metadata: self.metadata[key] = self.unfiltered_metadata[key] if self.fmt.get("rst2md"): raise ValueError( "The 'rst2md' option is a read only option. The reverse conversion is not " "implemented. Please either deactivate the option, or save to another format." ) # pragma: no cover def cell_to_text(self): """Return the text representation for the cell""" if self.cell_type == "code": source = copy(self.source) return comment_magic(source, self.language, self.comment_magics) if "cell_marker" in self.metadata: cell_marker = self.metadata.pop("cell_marker") else: cell_marker = self.default_cell_marker if self.source == [""]: return [cell_marker] if cell_marker in ['""', "''"] else ['""'] if cell_marker in ['"""', "'''"]: return [cell_marker] + self.source + [cell_marker] return [(cell_marker if cell_marker.startswith("#" * 20) else self.default_cell_marker)] + comment_lines( self.source, self.comment, self.comment_suffix ) ================================================ FILE: src/jupytext/cli.py ================================================ """`jupytext` as a command line tool""" import argparse import glob import json import os import re import shlex import subprocess import sys import warnings from copy import copy from tempfile import NamedTemporaryFile from typing import Optional from .combine import combine_inputs_with_outputs from .compare import NotebookDifference, compare, test_round_trip_conversion from .config import load_jupytext_config, notebook_formats from .formats import ( _BINARY_FORMAT_OPTIONS, _VALID_FORMAT_OPTIONS, JUPYTEXT_FORMATS, NOTEBOOK_EXTENSIONS, check_auto_ext, check_file_version, long_form_multiple_formats, long_form_one_format, short_form_one_format, ) from .header import recursive_update from .jupytext import ( create_prefix_dir, get_formats_from_notebook_path, read, reads, write, writes, ) from .kernels import find_kernel_specs, get_kernel_spec, kernelspec_from_language from .languages import _SCRIPT_EXTENSIONS from .paired_paths import ( InconsistentPath, base_path, find_base_path_and_format, full_path, paired_paths, ) from .pairs import latest_inputs_and_outputs from .sync_pairs import read_pair, write_pair from .version import __version__ def system(*args, **kwargs): """Execute the given bash command""" kwargs.setdefault("stdout", subprocess.PIPE) proc = subprocess.Popen(args, **kwargs) out, _ = proc.communicate() if proc.returncode: raise SystemExit(proc.returncode) return out.decode("utf-8") def tool_version(tool): try: args = tool.split(" ") args.append("--version") return system(*args) except (OSError, SystemExit): # pragma: no cover return None def str2bool(value): """Parse Yes/No/Default string https://stackoverflow.com/questions/15008758/parsing-boolean-values-with-argparse""" if value.lower() in ("yes", "true", "t", "y", "1"): return True if value.lower() in ("no", "false", "f", "n", "0"): return False if value.lower() in ("d", "default", ""): return None raise argparse.ArgumentTypeError("Expected: (Y)es/(T)rue/(N)o/(F)alse/(D)efault") def parse_jupytext_args(args=None): """Command line parser for jupytext""" parser = argparse.ArgumentParser( description="Jupyter Notebooks as Markdown Documents, Julia, Python or R Scripts", formatter_class=argparse.ArgumentDefaultsHelpFormatter, ) # Input parser.add_argument( "notebooks", help="One or more notebook(s). Notebook is read from stdin when this argument is empty.", nargs="*", ) parser.add_argument( "--from", dest="input_format", help="Jupytext format for the input(s). Inferred from the file extension and content when missing.", ) # Destination format & act on metadata selected_file_extensions = ["md", "Rmd", "jl", "py", "R"] parser.add_argument( "--to", dest="output_format", help=( "The destination format: 'ipynb', 'markdown' or 'script', or a file extension: " "'{}', ... or 'auto' (script extension matching the notebook language), " "or a combination of an extension and a format name, e.g. {} ".format( "', '".join(selected_file_extensions), ", ".join({f"md:{fmt.format_name}" for fmt in JUPYTEXT_FORMATS if fmt.extension == ".md"}), ) + " or {}. ".format(", ".join({f"py:{fmt.format_name}" for fmt in JUPYTEXT_FORMATS if fmt.extension == ".py"})) + "The default format for scripts is the 'percent' format, " "which uses '# %%%%' as cell markers and is compatible with VS Code and PyCharm. " "Alternatively, you can also use the 'light' format, which uses fewer cell markers. " "The main formats (MyST Markdown, Markdown, percent, light) preserve " "notebooks and text documents in a roundtrip. Use the " "--test and and --test-strict commands to test the roundtrip on your files. " "Read more about the available formats at " "https://jupytext.readthedocs.io/en/latest/formats.html. " "NB: in addition to the extensions listed above, you can also use these: '{}'".format( "', '".join( sorted( {ext.removeprefix(".") for ext in NOTEBOOK_EXTENSIONS} - set(selected_file_extensions + ["auto", "ipynb"]) ) ) ) ), ) # Destination file parser.add_argument( "-o", "--output", help="Destination file. Defaults to the original file, " "with prefix/suffix/extension changed according to " "the destination format. " "Use '-' to print the notebook on stdout.", ) parser.add_argument( "--update", action="store_true", help="Preserve the output cells when the destination notebook is an .ipynb file that already exists", ) parser.add_argument( "--set-formats", type=str, help="Turn the notebook or text document to one or more alternative representations " "with e.g. '--set-formats ipynb,py:light'. " "The --set-formats option also triggers the creation/update of all paired files", ) # Action: convert(default)/version/list paired paths/sync/apply/test action = parser.add_mutually_exclusive_group() action.add_argument( "--sync", "-s", help="Synchronize the content of the paired representations of " "the given notebook. Input cells are taken from the file that " "was last modified, and outputs are read from the ipynb file, " "if present.", action="store_true", ) action.add_argument( "--paired-paths", "-p", help="List the locations of the alternative representations for this notebook.", action="store_true", ) parser.add_argument( "--format-options", "--opt", action="append", help="Set format options with e.g. '--opt comment_magics=true' or '--opt notebook_metadata_filter=-kernelspec'.", ) parser.add_argument( "--update-metadata", default={}, type=json.loads, help="Update the notebook metadata with the desired dictionary. " "Argument must be given in JSON format. For instance, if you " "want to activate a pairing in the generated file, use e.g. " """--update-metadata '{"jupytext":{"formats":"ipynb,py:light"}}' """ "See also the --opt and --set-formats options for other ways " "to operate on the Jupytext metadata.", ) parser.add_argument( "--use-source-timestamp", help="Set the modification timestamp of the output file(s) equal" "to that of the source file, and keep the source file and " "its timestamp unchanged.", action="store_true", ) parser.add_argument( "--check-source-is-newer", help="Check that the file given as argument is the most recent of all paired files, and " "if applicable, checks that it is newer than the destination file.", action="store_true", ) parser.add_argument( "--warn-only", "-w", action="store_true", help="Only issue a warning and continue processing other notebooks when the conversion of a given notebook fails", ) action.add_argument( "--test", action="store_true", help="Test that the notebook is stable under a round trip conversion, up to the expected changes", ) action.add_argument( "--test-strict", action="store_true", help="Test that the notebook is strictly stable under a round trip conversion", ) parser.add_argument( "--stop", "-x", dest="stop_on_first_error", action="store_true", help="In --test mode, stop on first round trip conversion error, and report stack traceback", ) # Pipe notebook inputs into other commands parser.add_argument( "--pipe", action="append", help="Pipe the text representation (in format --pipe-fmt) of the notebook into " "another program, and read the notebook back. For instance, reformat " "your notebook with: " "'jupytext notebook.ipynb --pipe black' " "If you want to reformat it and sync the paired representation, execute: " "'jupytext notebook.ipynb --sync --pipe black' " "In case the program that you want to execute does not accept pipes, use {} " "as a placeholder for a temporary file name into which jupytext will " "write the text representation of the notebook, e.g.: " "jupytext notebook.ipynb --pipe 'black {}'", ) parser.add_argument( "--diff", "-d", action="store_true", help="Show the differences between (the inputs) of two notebooks", ) parser.add_argument( "--diff-format", help="The text format used to show differences in --diff", ) parser.add_argument( "--check", action="append", help="Pipe the text representation (in format --pipe-fmt) of the notebook into " "another program, and test that the returned value is non zero. For " "instance, test that your notebook is pep8 compliant with: " "'jupytext notebook.ipynb --check flake8' " "or run pytest on your notebook with: " "'jupytext notebook.ipynb --check pytest' " "In case the program that you want to execute does not accept pipes, use {} " "as a placeholder for a temporary file name into which jupytext will " "write the text representation of the notebook, e.g.: " "jupytext notebook.ipynb --check 'pytest {}'", ) parser.add_argument( "--pipe-fmt", default="auto:percent", help="The format in which the notebook should be piped to other programs, " "when using the --pipe and/or --check commands.", ) # Execute the notebook parser.add_argument( "--set-kernel", "-k", type=str, help="Set the kernel with the given name on the notebook. " "Use '--set-kernel -' to set a kernel matching the current " "environment on Python notebooks, and matching the notebook " "language otherwise (get the list of available kernels with " "'jupyter kernelspec list')", ) parser.add_argument( "--execute", action="store_true", help="Execute the notebook with the given kernel. In the " "--pre-commit-mode, the notebook is executed only if a code " "cell changed, or if some execution outputs are missing " "or not ordered.", ) parser.add_argument( "--run-path", type=str, help="Execute the notebook at the given path (defaults to the notebook parent directory)", ) parser.add_argument( "--quiet", "-q", action="store_true", help="Quiet mode: do not comment about files being updated or created", ) parser.add_argument( "--show-changes", action="store_true", help="Display the diff for each output file", ) action.add_argument( "--version", "-v", action="store_true", help="Show jupytext's version number and exit", ) parser.add_argument( "--pre-commit", action="store_true", help="Ignore the notebook argument, and instead apply Jupytext " "on the notebooks found in the git index, which have an " "extension that matches the (optional) --from argument.", ) parser.add_argument( "--pre-commit-mode", action="store_true", help="This is a mode that is compatible with the pre-commit framework. " "In this mode, --sync won't use timestamp but instead will " "determines the source notebook as the element of the pair " "that is added to the git index. An alert is raised if multiple inconsistent representations are " "in the index. It also raises an alert after updating the paired files or outputs if those " "files need to be added to the index. Finally, filepaths that aren't in the source format " "you are trying to convert from are ignored.", ) return parser.parse_args(args) def jupytext(args=None): """Entry point for the jupytext script""" args = parse_jupytext_args(args) def log(text): if not args.quiet: sys.stdout.write(text + "\n") if args.version: log(__version__) return 0 if args.pre_commit: warnings.warn( "The --pre-commit argument is deprecated. " "Please consider switching to the pre-commit.com framework " "(let us know at https://github.com/mwouts/jupytext/issues " "if that is an issue for you)", DeprecationWarning, ) if args.notebooks: raise ValueError("--pre-commit takes notebooks from the git index. Do not pass any notebook here.") args.notebooks = notebooks_in_git_index(args.input_format) log("[jupytext] Notebooks in git index are:") for nb_file in args.notebooks: log(nb_file) # Read notebook from stdin if not args.notebooks: if not args.pre_commit: args.notebooks = ["-"] if args.set_formats is not None: # Replace empty string with None args.update_metadata = recursive_update(args.update_metadata, {"jupytext": {"formats": args.set_formats or None}}) args.sync = True if args.paired_paths: if len(args.notebooks) != 1: raise ValueError("--paired-paths applies to a single notebook") print_paired_paths(args.notebooks[0], args.input_format) return 1 if args.run_path: args.execute = True if (args.test or args.test_strict) and not args.output_format and not args.output and not args.sync: raise ValueError("Please provide one of --to, --output or --sync") if ( not args.output_format and not args.output and not args.sync and not args.pipe and not args.diff and not args.check and not args.update_metadata and not args.format_options and not args.set_kernel and not args.execute ): raise ValueError( "Please provide one of --to, --output, --set-formats, --sync, --pipe, --diff, " "--check, --update-metadata, --format-options, --set-kernel or --execute" ) if args.diff: if ( len(args.notebooks) != 2 or args.output_format or args.output or args.sync or args.pipe or args.check or args.update_metadata or args.format_options or args.set_kernel or args.execute ): raise ValueError( "Please provide two notebooks after 'jupytext --diff'.\n" "NB: Use --show-changes if you wish to see the changes in " "a notebook being updated by Jupytext." ) nb_file1, nb_file2 = args.notebooks nb1 = read(nb_file1) nb2 = read(nb_file2) def fmt_if_not_ipynb(nb): fmt = nb.metadata["jupytext"]["text_representation"] if fmt["extension"] == ".ipynb": return None return short_form_one_format(fmt) diff_fmt = args.diff_format or fmt_if_not_ipynb(nb1) or fmt_if_not_ipynb(nb2) or "md" diff = compare( writes(nb2, diff_fmt), writes(nb1, diff_fmt), nb_file2, nb_file1, return_diff=True, ) sys.stdout.write(diff) return if args.output and len(args.notebooks) != 1: raise ValueError("Please input a single notebook when using --output") # Warn if '--to' is used in place of '--output' if ( not args.output and args.output_format and "." in args.output_format # a suffix is expected to start with one of these characters #901 and not args.output_format.startswith((".", "-", "_")) and "//" not in args.output_format ): def single_line(msg, *args, **kwargs): return f"[warning] {msg}\n" warnings.formatwarning = single_line warnings.warn( "You might have passed a file name to the '--to' option, " "when a format description was expected. Maybe you want to use the '-o' option instead?" ) if args.input_format: args.input_format = long_form_one_format(args.input_format) if args.output_format: args.output_format = long_form_one_format(args.output_format) set_format_options(args.output_format, args.format_options) # Wildcard extension on Windows #202 notebooks = [] for pattern in args.notebooks: if "*" in pattern or "?" in pattern: # Exclude the .jupytext.py configuration file notebooks.extend(glob.glob(pattern, recursive=True)) else: notebooks.append(pattern) # Count how many files have round-trip issues when testing exit_code = 0 for nb_file in notebooks: if not args.warn_only: exit_code += jupytext_single_file(nb_file, args, log) else: try: exit_code += jupytext_single_file(nb_file, args, log) except Exception as err: sys.stderr.write(f"[jupytext] Error: {str(err)}\n") return exit_code def jupytext_single_file(nb_file, args, log): """Apply the jupytext command, with given arguments, to a single file""" if nb_file == "-" and args.sync: msg = "Missing notebook path." if args.set_formats is not None and os.path.isfile(args.set_formats): msg += f" Did you mean 'jupytext --sync {args.set_formats}' ?" raise ValueError(msg) nb_dest = None if args.output: nb_dest = args.output elif nb_file == "-": nb_dest = "-" else: try: bp = base_path(nb_file, args.input_format) except InconsistentPath: if args.pre_commit_mode: log( "[jupytext] Ignoring unmatched input path {}{}".format( nb_file, f" for format {args.input_format}" if args.input_format else "", ) ) return 0 raise if args.output_format: nb_dest = full_path(bp, args.output_format) config = load_jupytext_config(os.path.abspath(nb_file)) # Just acting on metadata / pipe => save in place save_in_place = not nb_dest and not args.sync if save_in_place: nb_dest = nb_file if nb_dest == "-": args.quiet = True # I. ### Read the notebook ### fmt = copy(args.input_format) or {} if not fmt: ext = os.path.splitext(nb_file)[1] if ext: fmt = {"extension": ext} if fmt: set_format_options(fmt, args.format_options) log( "[jupytext] Reading {}{}".format( nb_file if nb_file != "-" else "stdin", f" in format {short_form_one_format(fmt)}" if "extension" in fmt else "", ) ) timestamp_checker = TimestampChecker(pre_commit_mode=args.pre_commit_mode) timestamp_checker.get_and_check_timestamp(nb_file) notebook = read(nb_file, fmt=fmt, config=config) if "extension" in fmt and "format_name" not in fmt: text_representation = notebook.metadata.get("jupytext", {}).get("text_representation", {}) if text_representation.get("extension") == fmt["extension"]: fmt["format_name"] = text_representation["format_name"] # Compute actual extension when using script/auto, and update nb_dest if necessary dest_fmt = args.output_format if dest_fmt and dest_fmt["extension"] == ".auto": dest_fmt = check_auto_ext(dest_fmt, notebook.metadata, "--to") if not args.output and nb_file != "-": nb_dest = full_path(base_path(nb_file, args.input_format), dest_fmt) # Set the kernel set_kernel = args.set_kernel if (not set_kernel) and args.execute and notebook.metadata.get("kernelspec", {}).get("name") is None: set_kernel = "-" if set_kernel: if set_kernel == "-": language = ( notebook.metadata.get("jupytext", {}).get("main_language") or notebook.metadata["kernelspec"]["language"] ) if not language: raise ValueError("Cannot infer a kernel as notebook language is not defined") kernelspec = kernelspec_from_language(language) else: try: kernelspec = get_kernel_spec(set_kernel) except KeyError as err: raise KeyError(f"Please choose a kernel name among {find_kernel_specs().keys()}") from err kernelspec = { "name": args.set_kernel, "language": kernelspec.language, "display_name": kernelspec.display_name, } log("[jupytext] Setting kernel {}".format(kernelspec.get("name"))) args.update_metadata["kernelspec"] = kernelspec # Read paired notebooks nb_files = [nb_file, nb_dest] if args.sync: # If we are also setting the formats, we take the information # from the --set-formats option if args.set_formats is not None: formats = long_form_multiple_formats(args.set_formats) else: formats = notebook_formats(notebook, config, nb_file, fallback_on_current_fmt=False) set_prefix_and_suffix(fmt, formats, nb_file) try: notebook, inputs_nb_file, outputs_nb_file = load_paired_notebook( notebook, fmt, config, formats, nb_file, log, args.pre_commit_mode, timestamp_checker ) nb_files = [inputs_nb_file, outputs_nb_file] except NotAPairedNotebook as err: sys.stderr.write("[jupytext] Warning: " + str(err) + "\n") return 0 except InconsistentVersions as err: sys.stderr.write("[jupytext] Error: " + str(err) + "\n") return 1 # Are we updating a text file that has a metadata filter? #212 if args.update_metadata or args.format_options: if notebook.metadata.get("jupytext", {}).get("notebook_metadata_filter") == "-all": notebook.metadata.get("jupytext", {}).pop("notebook_metadata_filter") # Update the metadata if args.update_metadata: log(f"[jupytext] Updating notebook metadata with '{json.dumps(args.update_metadata)}'") if "kernelspec" in args.update_metadata and "main_language" in notebook.metadata.get("jupytext", {}): notebook.metadata["jupytext"].pop("main_language") recursive_update(notebook.metadata, args.update_metadata) # II. ### Apply commands onto the notebook ### # Pipe the notebook into the desired commands if nb_file == "-": prefix = None directory = None else: prefix = os.path.splitext(os.path.basename(nb_file))[0] directory = os.path.dirname(nb_file) for cmd in args.pipe or []: notebook = pipe_notebook( notebook, cmd, args.pipe_fmt, quiet=args.quiet, prefix=prefix, directory=directory, warn_only=args.warn_only, ) # and/or test the desired commands onto the notebook for cmd in args.check or []: pipe_notebook( notebook, cmd, args.pipe_fmt, update=False, quiet=args.quiet, prefix=prefix, directory=directory, warn_only=args.warn_only, ) if ( args.execute and args.pre_commit_mode and execution_counts_are_in_order(notebook) and not code_cells_have_changed(notebook, nb_files) ): log(f"[jupytext] Execution of {shlex.quote(nb_file)} skipped as code cells have not changed and outputs are present.") args.execute = False # Execute the notebook if args.execute: kernel_name = notebook.metadata.get("kernelspec", {}).get("name") log(f"[jupytext] Executing notebook with kernel {kernel_name}") if nb_dest is not None and nb_dest != "-": nb_path = os.path.dirname(nb_dest) elif nb_file != "-": nb_path = os.path.dirname(nb_file) else: nb_path = None run_path = args.run_path or nb_path if args.run_path and not os.path.isdir(run_path): # is this a relative directory? for base_dir in [nb_path, os.getcwd()]: try_path = os.path.join(base_dir, run_path) if os.path.isdir(try_path): run_path = try_path break if not os.path.isdir(run_path): raise ValueError(f"--run-path={args.run_path} is not a valid path") if run_path: resources = {"metadata": {"path": run_path}} else: resources = {} try: from nbconvert.preprocessors import ExecutePreprocessor exec_proc = ExecutePreprocessor(timeout=None, kernel_name=kernel_name) exec_proc.preprocess(notebook, resources=resources) except (ImportError, RuntimeError) as err: if args.pre_commit_mode: raise RuntimeError( "An error occurred while executing the notebook. Please " "make sure that you have listed 'nbconvert' and 'ipykernel' " "under 'additional_dependencies' in the jupytext hook." ) from err raise RuntimeError( "An error occurred while executing the notebook. Please " "make sure that 'nbconvert' and 'ipykernel' are installed." ) from err # III. ### Possible actions ### # a. Test round trip conversion if args.test or args.test_strict: try: # Round trip from an ipynb document if fmt["extension"] == ".ipynb": test_round_trip_conversion( notebook, dest_fmt, update=args.update, allow_expected_differences=not args.test_strict, stop_on_first_error=args.stop_on_first_error, ) # Round trip from a text file else: # We read the original text from disk a second time with open(nb_file, encoding="utf-8") as fp: org_text = fp.read() # We also make sure that the text file # has not changed since we first read it! timestamp_checker.check_timestamp(nb_file) # If the destination is not ipynb, we convert to/back that format if dest_fmt["extension"] != ".ipynb": dest_text = writes(notebook, fmt=dest_fmt) notebook = reads(dest_text, fmt=dest_fmt) text = writes(notebook, fmt=fmt, config=config) if args.test_strict: compare(text, org_text) else: # we ignore the YAML header in the comparison #414 comment = _SCRIPT_EXTENSIONS.get(fmt["extension"], {}).get("comment", "") # white spaces between the comment char and the YAML delimiters are allowed if comment: comment = comment + r"\s*" yaml_header = re.compile( r"^{comment}---\s*\n.*\n{comment}---\s*\n".format(comment=comment), re.MULTILINE | re.DOTALL, ) compare(re.sub(yaml_header, "", text), re.sub(yaml_header, "", org_text)) except (NotebookDifference, AssertionError) as err: sys.stdout.write(f"{nb_file}: {str(err)}") return 1 return 0 # b. Output to the desired file or format untracked_files = 0 def lazy_write( path, fmt=None, action=None, update_timestamp_only=False, force_update_timestamp=False, ): """Write the notebook only if it has changed""" # Used in tests only if _callback_on_lazy_write is not None: _callback_on_lazy_write(path) if path == "-": timestamp_checker.check_all_timestamps() write(notebook, "-", fmt=fmt) return nonlocal untracked_files if update_timestamp_only: modified = False else: _, ext = os.path.splitext(path) fmt = copy(fmt or {}) fmt = long_form_one_format(fmt, update={"extension": ext}) new_content = writes(notebook, fmt=fmt, config=config) diff = None if not new_content.endswith("\n"): new_content += "\n" if not os.path.isfile(path): modified = True diff = "(file did not exist)" else: # We load the current file from disk # NB: in the --to mode, it might be the first # time we actually read this file timestamp_checker.get_and_check_timestamp(path) with open(path, encoding="utf-8") as fp: current_content = fp.read() timestamp_checker.check_timestamp(path) modified = new_content != current_content if modified and args.show_changes: diff = compare( new_content, current_content, "", "", return_diff=True, ) tmp_path = path if modified: # The text representation of the notebook has changed, we write it on disk create_prefix_dir(path, fmt) # Create a temporary file in the same directory as path. Later on we will move # that temporary file back to path (os.replace is atomic on most OS) name, ext = os.path.splitext(path) tmp_path = name + f"_tmp_jupytext_{os.getpid()}" + ext with open(tmp_path, "w", encoding="utf-8") as fp: fp.write(new_content) # We check that none of the input files changed while we were # doing our processing. If they did, we abort as we would # otherwise overwrite the modifications. try: timestamp_checker.check_all_timestamps() except SynchronousModificationError: if modified: os.remove(tmp_path) raise # When the content is unchanged, we still need to update the timestamp of # the text file to make sure they remain more recent than the ipynb file, for compatibility with the # Jupytext contents manager for Jupyter if args.use_source_timestamp: if tmp_path != nb_file: log(f"[jupytext] Setting the timestamp of {shlex.quote(path)} equal to that of {shlex.quote(nb_file)}") os.utime(tmp_path, (os.stat(nb_file).st_atime, os.stat(nb_file).st_mtime)) elif not modified: if path.endswith(".ipynb"): # No need to update the timestamp of ipynb files log(f"[jupytext] Unchanged {shlex.quote(path)}") elif args.sync and not force_update_timestamp: # if the content is unchanged (and matches ipynb), we don't need # to update the timestamp as the contents manager will not throw in # that case (see the try/catch on read_pair(... must_match=True)) log(f"[jupytext] Unchanged {shlex.quote(path)}") else: log(f"[jupytext] Updating the timestamp of {shlex.quote(path)}") os.utime(path, None) if modified: if action is None: message = f"[jupytext] Updating {shlex.quote(path)}" else: message = "[jupytext] Writing {path}{format}{action}".format( path=shlex.quote(path), format=(" in format " + short_form_one_format(fmt) if fmt and "format_name" in fmt else ""), action=action, ) if args.show_changes: message += " with this change:\n" + diff log(message) os.replace(tmp_path, path) # If we changed the file timestamp, we update our checker accordingly if modified or args.use_source_timestamp or force_update_timestamp: timestamp_checker.update_timestamp(path) if args.pre_commit: system("git", "add", path) if args.pre_commit_mode and is_untracked(path): log( f"[jupytext] Error: the git index is outdated.\n" f"Please add the paired notebook with:\n" f" git add {shlex.quote(path)}" ) untracked_files += 1 return {"modified": modified} if nb_dest: if args.check_source_is_newer: ts_src = timestamp_checker.check_file_is_newest(nb_file) ts_dest = timestamp_checker.get_and_check_timestamp(nb_dest) if ts_dest is not None and ts_dest > ts_src: raise ValueError(f"Source {nb_file} is older than destination {nb_dest}") if nb_dest == nb_file and not dest_fmt: dest_fmt = fmt # Test consistency between dest name and output format if dest_fmt and nb_dest != "-": base_path(nb_dest, dest_fmt) # Describe what jupytext is doing if save_in_place: action = "" elif os.path.isfile(nb_dest) and args.update: if not nb_dest.endswith(".ipynb"): raise ValueError("--update is only for ipynb files") action = " (destination file updated)" check_file_version(notebook, nb_file, nb_dest) notebook = combine_inputs_with_outputs(notebook, read(nb_dest), fmt=fmt) elif os.path.isfile(nb_dest): suggest_update = " [use --update to preserve cell outputs and ids]" if nb_dest.endswith(".ipynb") else "" action = f" (destination file replaced{suggest_update})" else: action = "" formats = notebook.metadata.get("jupytext", {}).get("formats") formats = long_form_multiple_formats(formats) if formats: try: base_path_out, _ = find_base_path_and_format(nb_dest, formats) except InconsistentPath: # Drop 'formats' if the destination is not part of the paired notebooks formats = {} notebook.metadata.get("jupytext", {}).pop("formats") lazy_write(nb_dest, fmt=dest_fmt, action=action) nb_dest_in_pair = formats and any( os.path.exists(alt_path) and os.path.samefile(nb_dest, alt_path) for alt_path, _ in paired_paths(nb_file, fmt, formats) ) if ( nb_dest_in_pair and os.path.isfile(nb_file) and not nb_file.endswith(".ipynb") and os.path.isfile(nb_dest) and nb_dest.endswith(".ipynb") ): # If the destination is an ipynb file and is in the pair, then we # update the original text file timestamp, as required by our Content Manager # Otherwise Jupyter will refuse to open the paired notebook #335 # NB: An alternative is --use-source-timestamp lazy_write(nb_file, update_timestamp_only=True) # c. Synchronize paired notebooks elif args.sync: if args.check_source_is_newer: timestamp_checker.check_file_is_newest(nb_file) write_pair(nb_file, formats, lazy_write) return untracked_files def notebooks_in_git_index(fmt): """Return the list of modified and deleted ipynb files in the git index that match the given format""" git_status = system("git", "status", "--porcelain") re_modified = re.compile(r"^[AM]+\s+(?P.*)", re.MULTILINE) modified_files_in_git_index = re_modified.findall(git_status) files = [] for nb_file in modified_files_in_git_index: if nb_file.startswith('"') and nb_file.endswith('"'): nb_file = nb_file[1:-1] try: base_path(nb_file, fmt) files.append(nb_file) except InconsistentPath: continue return files def is_untracked(filepath): """Check whether a file was created or modified and needs to be added to the git index""" if not filepath: return False output = system("git", "ls-files", filepath).strip() if output == "": return True output = system("git", "diff", filepath).strip() if output != "": return True return False def print_paired_paths(nb_file, fmt): """Display the paired paths for this notebook""" formats = get_formats_from_notebook_path(nb_file, fmt) if formats: for path, _ in paired_paths(nb_file, fmt, formats): if path != nb_file: sys.stdout.write(path + "\n") def set_format_options(fmt, format_options): """Apply the desired format options to the format description fmt""" if not format_options: return for opt in format_options: try: key, value = opt.split("=") except ValueError as err: raise ValueError(f"Format options are expected to be of the form key=value, not '{opt}'") from err if key not in _VALID_FORMAT_OPTIONS: raise ValueError( "'{}' is not a valid format option. Expected one of '{}'".format(key, "', '".join(_VALID_FORMAT_OPTIONS)) ) if key in _BINARY_FORMAT_OPTIONS: value = str2bool(value) fmt[key] = value def set_prefix_and_suffix(fmt, formats, nb_file): """Add prefix and suffix information from jupytext.formats if format and path matches""" for alt_fmt in long_form_multiple_formats(formats): if alt_fmt["extension"] == fmt["extension"] and fmt.get("format_name") == alt_fmt.get("format_name"): try: base_path(nb_file, alt_fmt) fmt.update(alt_fmt) return except InconsistentPath: continue class NotAPairedNotebook(ValueError): """An error raised when a notebook is not a paired notebook""" class InconsistentVersions(ValueError): """An error raised when two paired files in the git index contain inconsistent representations""" def file_in_git_index(path): if not os.path.isfile(path): return False return system("git", "status", "--porcelain", path).strip().startswith(("M", "A")) def git_timestamp(path): if not os.path.isfile(path): return None # Files that are in the git index are considered most recent if file_in_git_index(path): return float("inf") # Return the commit timestamp try: git_ts_str = system("git", "log", "-1", "--pretty=%ct", "--no-show-signature", path).strip() except SystemExit as err: if err.code == 128: # git not initialized git_ts_str = "" else: raise if git_ts_str: return float(git_ts_str) # The file is not in the git index return get_timestamp(path) def get_timestamp(path: str) -> Optional[float]: if not os.path.isfile(path): return None return os.stat(path).st_mtime class SynchronousModificationError(OSError): """An error raised when a file was modified while Jupytext was running""" class TimestampChecker: """ This class keeps track of the timestamps of files that have been used by Jupytext when loading a paired notebook. Either the timestamp of each file was consulted to identify the most recent input file, or its content was read. """ def __init__(self, pre_commit_mode: bool = False): self.pre_commit_mode = pre_commit_mode self._timestamps: dict[str, Optional[float]] = {} def get_and_check_timestamp(self, path: str) -> Optional[float]: if path in self._timestamps: ts = self.check_timestamp(path) else: ts = get_timestamp(path) self._timestamps[path] = ts if self.pre_commit_mode: return git_timestamp(path) return ts def check_timestamp(self, path: str) -> Optional[float]: if path not in self._timestamps: raise ValueError( f"The timestamp of {shlex.quote(path)} was not previously recorded. So far Jupytext has only recorded timestamps for {', '.join(shlex.quote(p) for p in self._timestamps)}" ) ts = get_timestamp(path) old_ts = self._timestamps[path] if old_ts is None and ts is not None: raise SynchronousModificationError(f"The file {shlex.quote(path)} was created while Jupytext was running") if old_ts is not None and ts is None: raise SynchronousModificationError(f"The file {shlex.quote(path)} was deleted while Jupytext was running") if ts != old_ts: raise SynchronousModificationError(f"The file {shlex.quote(path)} was modified while Jupytext was running") return ts def update_timestamp(self, path: str): ts = get_timestamp(path) if ts is None: raise FileNotFoundError(f"The file {shlex.quote(path)} does not exist") self._timestamps[path] = ts def check_all_timestamps(self): for path in self._timestamps: self.check_timestamp(path) def check_file_is_newest(self, path: str) -> Optional[float]: """Check that the given file is the most recent among all files whose timestamp was recorded by this TimestampChecker. Return its timestamp.""" ts = self._timestamps[path] assert ts is not None, f"The timestamp of {shlex.quote(path)} was not previously recorded" for p, p_ts in self._timestamps.items(): if p == path or p_ts is None: continue if p_ts > ts: raise ValueError(f"Source {shlex.quote(path)} is older than paired file {shlex.quote(p)}") return ts # If not none, this function is called with the path of each file # that Jupytext CLI considers to write back (to be used in tests) _callback_on_lazy_write = None def load_paired_notebook( notebook, fmt, config, formats, nb_file, log, pre_commit_mode: bool, timestamp_checker: TimestampChecker ): """Update the notebook with the inputs and outputs of the most recent paired files""" if not formats: raise NotAPairedNotebook(f"{shlex.quote(nb_file)} is not a paired notebook") formats = long_form_multiple_formats(formats) _, fmt_with_prefix_suffix = find_base_path_and_format(nb_file, formats) fmt.update(fmt_with_prefix_suffix) def read_one_file(path, fmt): if path == nb_file: return notebook log(f"[jupytext] Loading {shlex.quote(path)}") timestamp_checker.get_and_check_timestamp(path) return read(path, fmt=fmt, config=config) if pre_commit_mode and file_in_git_index(nb_file): # We raise an error if two representations of this notebook in the git index are inconsistent nb_files_in_git_index = sorted( ((alt_path, alt_fmt) for alt_path, alt_fmt in paired_paths(nb_file, fmt, formats) if file_in_git_index(alt_path)), key=lambda x: 0 if x[1]["extension"] != ".ipynb" else 1, ) if len(nb_files_in_git_index) > 1: path0, fmt0 = nb_files_in_git_index[0] timestamp_checker.get_and_check_timestamp(path0) with open(path0, encoding="utf-8") as fp: text0 = fp.read() for alt_path, alt_fmt in nb_files_in_git_index[1:]: timestamp_checker.get_and_check_timestamp(alt_path) nb = read(alt_path, fmt=alt_fmt, config=config) alt_text = writes(nb, fmt=fmt0, config=config) if alt_text != text0: diff = compare(alt_text, text0, alt_path, path0, return_diff=True) raise InconsistentVersions( f"{shlex.quote(alt_path)} and {shlex.quote(path0)} are inconsistent.\n" + diff + f"\nPlease revert JUST ONE of the files with EITHER\n" f" git reset {shlex.quote(alt_path)} && git checkout -- {shlex.quote(alt_path)}\nOR\n" f" git reset {shlex.quote(path0)} && git checkout -- {shlex.quote(path0)}\n" ) inputs, outputs = latest_inputs_and_outputs(nb_file, fmt, formats, timestamp_checker.get_and_check_timestamp) notebook = read_pair(inputs, outputs, read_one_file) return notebook, inputs.path, outputs.path def exec_command(command, input=None, capture=False, warn_only=False, quiet=False): """Execute the desired command, and pipe the given input into it""" assert isinstance(command, list) if not quiet: sys.stdout.write("[jupytext] Executing {}\n".format(" ".join(command))) process = subprocess.Popen( command, **(dict(stdout=subprocess.PIPE, stdin=subprocess.PIPE) if input is not None else {}), ) out, err = process.communicate(input=input) if out and not capture and not quiet: sys.stdout.write(out.decode("utf-8")) if err: sys.stderr.write(err.decode("utf-8")) if process.returncode: msg = f"The command '{' '.join(command)}' exited with code {process.returncode}" hint = "" if warn_only else " (use --warn-only to turn this error into a warning)" sys.stderr.write(f"[jupytext] {'Warning' if warn_only else 'Error'}: {msg}{hint}\n") if not warn_only: raise SystemExit(process.returncode) return out def pipe_notebook( notebook, command, fmt="py:percent", update=True, quiet=False, prefix=None, directory=None, warn_only=False, ): """Pipe the notebook, in the desired representation, to the given command. Update the notebook with the returned content if desired.""" if command in ["black", "flake8", "autopep8"]: command = command + " -" elif command in ["pytest", "unittest"]: command = command + " {}" fmt = long_form_one_format(fmt, notebook.metadata, auto_ext_requires_language_info=False) fmt = check_auto_ext(fmt, notebook.metadata, "--pipe-fmt") text = writes(notebook, fmt) command = shlex.split(command) if "{}" in command: if prefix is not None: prefix = prefix + "-" tmp_file_args = dict( mode="w+", encoding="utf8", prefix=prefix, suffix=fmt["extension"], dir=directory, delete=False, ) try: tmp = NamedTemporaryFile(**tmp_file_args) except TypeError: # NamedTemporaryFile does not have an 'encoding' argument on pypy tmp_file_args.pop("encoding") tmp = NamedTemporaryFile(**tmp_file_args) try: tmp.write(text) tmp.close() exec_command( [cmd if cmd != "{}" else tmp.name for cmd in command], capture=update, quiet=quiet, warn_only=warn_only, ) if not update: return notebook piped_notebook = read(tmp.name, fmt=fmt) finally: os.remove(tmp.name) else: cmd_output = exec_command( command, text.encode("utf-8"), capture=update, warn_only=warn_only, quiet=quiet, ) if not update: return notebook if not cmd_output: sys.stderr.write( "[jupytext] The command '{}' had no output. As a result, the notebook is empty. " "Is this expected? If not, use --check rather than --pipe for this command.".format(command) ) piped_notebook = reads(cmd_output.decode("utf-8"), fmt) if fmt["extension"] != ".ipynb": piped_notebook = combine_inputs_with_outputs(piped_notebook, notebook, fmt) # Remove jupytext / text_representation entry if "jupytext" in notebook.metadata: piped_notebook.metadata["jupytext"] = notebook.metadata["jupytext"] else: piped_notebook.metadata.pop("jupytext", None) return piped_notebook def execution_counts_are_in_order(notebook): """Returns True if all the code cells have an execution count, ordered from 1 to N with no missing number""" expected_execution_count = 1 for cell in notebook.cells: if cell.cell_type == "code": if cell.execution_count != expected_execution_count: return False expected_execution_count += 1 return True def code_cells_have_changed(notebook, nb_files): """The source for the code cells has not changed""" for nb_file in nb_files: if not os.path.exists(nb_file): return True nb_ref = read(nb_file) # Are the new code cells equals to those in the file? ref = [cell.source for cell in nb_ref.cells if cell.cell_type == "code"] new = [cell.source for cell in notebook.cells if cell.cell_type == "code"] if ref != new: return True return False ================================================ FILE: src/jupytext/combine.py ================================================ """Combine source and outputs from two notebooks""" import re from copy import copy from nbformat import NotebookNode from .cell_metadata import _IGNORE_CELL_METADATA from .formats import long_form_one_format from .header import _DEFAULT_NOTEBOOK_METADATA from .metadata_filter import restore_filtered_metadata _BLANK_LINE = re.compile(r"^\s*$") def black_invariant(text, chars=None): """Remove characters that may be changed when reformatting the text with black""" if chars is None: chars = [" ", "\t", "\n", ",", "'", '"', "(", ")", "\\"] for char in chars: text = text.replace(char, "") return text def same_content(ref, test, endswith=False): """Is the content of two cells the same, up to reformatting by black""" ref = black_invariant(ref) test = black_invariant(test) if endswith and test: return ref.endswith(test) return ref == test def combine_inputs_with_outputs(nb_source, nb_outputs, fmt=None): """Return a notebook that combines the text and metadata from the first notebook, with the outputs and metadata of the second notebook.""" # nbformat version number taken from the notebook with outputs assert nb_outputs.nbformat == nb_source.nbformat, ( "The notebook with outputs is in format {}.{}, please upgrade it to {}.x".format( nb_outputs.nbformat, nb_outputs.nbformat_minor, nb_source.nbformat ) ) nb_source.nbformat_minor = nb_outputs.nbformat_minor fmt = long_form_one_format(fmt) text_repr = nb_source.metadata.get("jupytext", {}).get("text_representation", {}) ext = fmt.get("extension") or text_repr.get("extension") format_name = fmt.get("format_name") or text_repr.get("format_name") notebook_metadata_filter = nb_source.metadata.get("jupytext", {}).get("notebook_metadata_filter") if notebook_metadata_filter == "-all": nb_metadata = nb_outputs.metadata else: nb_metadata = restore_filtered_metadata( nb_source.metadata, nb_outputs.metadata, notebook_metadata_filter, _DEFAULT_NOTEBOOK_METADATA, ) source_is_md_version_one = ext in [".md", ".markdown", ".Rmd"] and text_repr.get("format_version") == "1.0" if nb_metadata.get("jupytext", {}).get("formats") or ext in [ ".md", ".markdown", ".Rmd", ]: nb_metadata.get("jupytext", {}).pop("text_representation", None) if not nb_metadata.get("jupytext", {}): nb_metadata.pop("jupytext", {}) if format_name in ["nomarker", "sphinx", "marimo"] or source_is_md_version_one: cell_metadata_filter = "-all" else: cell_metadata_filter = nb_metadata.get("jupytext", {}).get("cell_metadata_filter") outputs_map = map_outputs_to_inputs(nb_source.cells, nb_outputs.cells) cells = [] for source_cell, j in zip(nb_source.cells, outputs_map): if j is None: cells.append(source_cell) continue output_cell = nb_outputs.cells[j] # Outputs and optional attributes are taken from the notebook with outputs cell = copy(output_cell) # Cell text is taken from the source notebook cell.source = source_cell.source # We also restore the cell metadata that has been filtered cell.metadata = restore_filtered_metadata( source_cell.metadata, output_cell.metadata, # The 'spin' format does not allow metadata on non-code cells ("-all" if format_name == "spin" and source_cell.cell_type != "code" else cell_metadata_filter), _IGNORE_CELL_METADATA, ) cells.append(cell) # We call NotebookNode rather than new_notebook as we don't want to validate # the notebook (some of the notebook in the collection of test notebooks # do have some invalid properties - probably inherited from an older version # of the notebook format). return NotebookNode( cells=cells, metadata=nb_metadata, nbformat=nb_outputs.nbformat, nbformat_minor=nb_outputs.nbformat_minor, ) def map_outputs_to_inputs(cells_inputs, cells_outputs): """Returns a map i->(j or None) that maps the cells with outputs to the input cells""" n_in = len(cells_inputs) n_out = len(cells_outputs) outputs_map = [None] * n_in # First rule: match based on cell type, content, in increasing order, for each cell type first_unmatched_output_per_cell_type = {} for i in range(n_in): cell_input = cells_inputs[i] for j in range(first_unmatched_output_per_cell_type.get(cell_input.cell_type, 0), n_out): cell_output = cells_outputs[j] if cell_input.cell_type == cell_output.cell_type and same_content(cell_input.source, cell_output.source): outputs_map[i] = j first_unmatched_output_per_cell_type[cell_input.cell_type] = j + 1 break # Second rule: match unused outputs based on cell type and content # Third rule: is the new cell the final part of a previous cell with outputs? unused_ouputs = set(range(n_out)).difference(outputs_map) for endswith in [False, True]: if not unused_ouputs: return outputs_map for i in range(n_in): if outputs_map[i] is not None: continue cell_input = cells_inputs[i] for j in unused_ouputs: cell_output = cells_outputs[j] if cell_input.cell_type == cell_output.cell_type and same_content( cell_output.source, cell_input.source, endswith ): outputs_map[i] = j unused_ouputs.remove(j) break # Fourth rule: match based on increasing index (and cell type) for non-empty cells if not unused_ouputs: return outputs_map prev_j = -1 for i in range(n_in): if outputs_map[i] is not None: prev_j = outputs_map[i] continue j = prev_j + 1 if j not in unused_ouputs: continue cell_input = cells_inputs[i] cell_output = cells_outputs[j] if cell_input.cell_type == cell_output.cell_type and cell_input.source.strip() != "": outputs_map[i] = j unused_ouputs.remove(j) prev_j = j return outputs_map ================================================ FILE: src/jupytext/compare.py ================================================ """Compare two Jupyter notebooks""" import difflib import json import os import re from jupytext.marimo import marimo_version from jupytext.paired_paths import full_path from .cell_metadata import _IGNORE_CELL_METADATA from .combine import combine_inputs_with_outputs from .formats import check_auto_ext, long_form_one_format from .header import _DEFAULT_NOTEBOOK_METADATA from .jupytext import read, reads, write, writes from .metadata_filter import filter_metadata _BLANK_LINE = re.compile(r"^\s*$") def _multilines(obj): try: lines = obj.splitlines() return lines + [""] if obj.endswith("\n") else lines except AttributeError: # Remove the final blank space on Python 2.7 # return json.dumps(obj, indent=True, sort_keys=True).splitlines() return [line.rstrip() for line in json.dumps(obj, indent=True, sort_keys=True).splitlines()] def compare(actual, expected, actual_name="actual", expected_name="expected", return_diff=False): """Compare two strings, lists or dict-like objects""" if actual != expected: diff = difflib.unified_diff( _multilines(expected), _multilines(actual), expected_name, actual_name, lineterm="", ) if expected_name == "" and actual_name == "": diff = list(diff)[2:] diff = "\n".join(diff) if return_diff: return diff raise AssertionError("\n" + diff) return "" if return_diff else None def filtered_cell(cell, preserve_outputs, cell_metadata_filter): """Cell type, metadata and source from given cell""" filtered = { "cell_type": cell.cell_type, "source": cell.source, "metadata": filter_metadata(cell.metadata, cell_metadata_filter, _IGNORE_CELL_METADATA), } if preserve_outputs: for key in ["execution_count", "outputs"]: if key in cell: filtered[key] = cell[key] return filtered def filtered_notebook_metadata(notebook, ignore_kernelspec=False): """Notebook metadata, filtered for metadata added by Jupytext itself""" metadata = filter_metadata( notebook.metadata, notebook.metadata.get("jupytext", {}).get("notebook_metadata_filter"), _DEFAULT_NOTEBOOK_METADATA, ) # Quarto round-trips may change the kernelspec if ignore_kernelspec: metadata.pop("kernelspec", None) if "jupytext" in metadata: del metadata["jupytext"] return metadata class NotebookDifference(Exception): """Report notebook differences""" def same_content(ref_source, test_source, allow_removed_final_blank_line): """Is the content of two cells the same, except for an optional final blank line?""" if ref_source == test_source: return True if not allow_removed_final_blank_line: return False # Is ref identical to test, plus one blank line? ref_source = ref_source.splitlines() test_source = test_source.splitlines() if not ref_source: return False if ref_source[:-1] != test_source: return False return _BLANK_LINE.match(ref_source[-1]) def compare_notebooks( notebook_actual, notebook_expected, fmt=None, allow_expected_differences=True, raise_on_first_difference=True, compare_outputs=False, compare_ids=None, ): """Compare the two notebooks, and raise with a meaningful message that explains the differences, if any""" fmt = long_form_one_format(fmt) format_name = fmt.get("format_name") if format_name == "sphinx" and notebook_actual.cells and notebook_actual.cells[0].source == "%matplotlib inline": notebook_actual.cells = notebook_actual.cells[1:] if compare_ids is None: compare_ids = compare_outputs modified_cells, modified_cell_metadata = compare_cells( notebook_actual.cells, notebook_expected.cells, raise_on_first_difference, compare_outputs=compare_outputs, compare_ids=compare_ids, cell_metadata_filter="-all" if format_name == "marimo" else notebook_actual.get("jupytext", {}).get("cell_metadata_filter"), allow_missing_code_cell_metadata=(allow_expected_differences and format_name in ["sphinx", "marimo"]), allow_missing_markdown_cell_metadata=(allow_expected_differences and format_name in ["sphinx", "spin", "marimo"]), allow_filtered_cell_metadata=allow_expected_differences, allow_removed_final_blank_line=allow_expected_differences, ) # Compare notebook metadata modified_metadata = False if fmt.get("format_name") != "marimo": try: ignore_kernelspec = fmt.get("extension") == ".qmd" and allow_expected_differences compare( filtered_notebook_metadata(notebook_actual, ignore_kernelspec), filtered_notebook_metadata(notebook_expected, ignore_kernelspec), ) except AssertionError as error: if raise_on_first_difference: raise NotebookDifference(f"Notebook metadata differ: {str(error)}") modified_metadata = True error = [] if modified_cells: error.append( "Cells {} differ ({}/{})".format( ",".join([str(i) for i in modified_cells]), len(modified_cells), len(notebook_expected.cells), ) ) if modified_cell_metadata: error.append("Cell metadata '{}' differ".format("', '".join([str(i) for i in modified_cell_metadata]))) if modified_metadata: error.append("Notebook metadata differ") if error: raise NotebookDifference(" | ".join(error)) def compare_cells( actual_cells, expected_cells, raise_on_first_difference=True, compare_outputs=True, compare_ids=True, cell_metadata_filter=None, allow_missing_code_cell_metadata=False, allow_missing_markdown_cell_metadata=False, allow_filtered_cell_metadata=False, allow_removed_final_blank_line=False, ): """Compare two collection of notebook cells""" test_cell_iter = iter(actual_cells) modified_cells = set() modified_cell_metadata = set() for i, ref_cell in enumerate(expected_cells, 1): try: test_cell = next(test_cell_iter) except StopIteration: if raise_on_first_difference: raise NotebookDifference(f"No cell corresponding to {ref_cell.cell_type} cell #{i}:\n{ref_cell.source}") modified_cells.update(range(i, len(expected_cells) + 1)) break ref_lines = [line for line in ref_cell.source.splitlines() if not _BLANK_LINE.match(line)] test_lines = [] # 1. test cell type if ref_cell.cell_type != test_cell.cell_type: if raise_on_first_difference: raise NotebookDifference( f"When comparing cell #{i}: " f"expecting a {ref_cell.cell_type} cell, but got a {test_cell.cell_type} cell.\n" f"Expected content:\n{ref_cell.source}\nActual content:\n{test_cell.source}" ) modified_cells.add(i) # Compare cell ids (introduced in nbformat 5.1.0) if compare_ids and test_cell.get("id") != ref_cell.get("id"): if raise_on_first_difference: raise NotebookDifference( f"Cell ids differ on {test_cell['cell_type']} cell #{i}: '{test_cell.get('id')}' != '{ref_cell.get('id')}'" ) modified_cells.add(i) # 2. test cell metadata if (ref_cell.cell_type == "code" and not allow_missing_code_cell_metadata) or ( ref_cell.cell_type != "code" and not allow_missing_markdown_cell_metadata ): ref_metadata = ref_cell.metadata test_metadata = test_cell.metadata if allow_filtered_cell_metadata: ref_metadata = {key: ref_metadata[key] for key in ref_metadata if key not in _IGNORE_CELL_METADATA} test_metadata = {key: test_metadata[key] for key in test_metadata if key not in _IGNORE_CELL_METADATA} if ref_metadata != test_metadata: if raise_on_first_difference: try: compare(test_metadata, ref_metadata) except AssertionError as error: raise NotebookDifference( "Metadata differ on {} cell #{}: {}\nCell content:\n{}".format( test_cell.cell_type, i, str(error), ref_cell.source ) ) else: modified_cell_metadata.update(set(test_metadata).difference(ref_metadata)) modified_cell_metadata.update(set(ref_metadata).difference(test_metadata)) for key in set(ref_metadata).intersection(test_metadata): if ref_metadata[key] != test_metadata[key]: modified_cell_metadata.add(key) test_lines.extend([line for line in test_cell.source.splitlines() if not _BLANK_LINE.match(line)]) # 3. test cell content if ref_lines != test_lines: if raise_on_first_difference: try: compare("\n".join(test_lines), "\n".join(ref_lines)) except AssertionError as error: raise NotebookDifference(f"Cell content differ on {test_cell.cell_type} cell #{i}: {str(error)}") else: modified_cells.add(i) # 3. bis test entire cell content if not same_content(ref_cell.source, test_cell.source, allow_removed_final_blank_line): if ref_cell.source != test_cell.source: if raise_on_first_difference: diff = compare(test_cell.source, ref_cell.source, return_diff=True) raise NotebookDifference(f"Cell content differ on {test_cell.cell_type} cell #{i}: {diff}") modified_cells.add(i) if not compare_outputs: continue if ref_cell.cell_type != "code": continue ref_cell = filtered_cell( ref_cell, preserve_outputs=compare_outputs, cell_metadata_filter=cell_metadata_filter, ) test_cell = filtered_cell( test_cell, preserve_outputs=compare_outputs, cell_metadata_filter=cell_metadata_filter, ) try: compare(test_cell, ref_cell) except AssertionError as error: if raise_on_first_difference: raise NotebookDifference( "Cell outputs differ on {} cell #{}: {}".format(test_cell["cell_type"], i, str(error)) ) modified_cells.add(i) # More cells in the actual notebook? remaining_cell_count = 0 while True: try: test_cell = next(test_cell_iter) if raise_on_first_difference: raise NotebookDifference(f"Additional {test_cell.cell_type} cell: {test_cell.source}") remaining_cell_count += 1 except StopIteration: break if remaining_cell_count and not raise_on_first_difference: modified_cells.update( range( len(expected_cells) + 1, len(expected_cells) + 1 + remaining_cell_count, ) ) return modified_cells, modified_cell_metadata def test_round_trip_conversion(notebook, fmt, update, allow_expected_differences=True, stop_on_first_error=True): """Test round trip conversion for a Jupyter notebook""" text = writes(notebook, fmt) round_trip = reads(text, fmt) if update: round_trip = combine_inputs_with_outputs(round_trip, notebook, fmt) compare_notebooks( round_trip, notebook, fmt, allow_expected_differences, raise_on_first_difference=stop_on_first_error, ) # The functions below are used in the Jupytext text collection def create_mirror_file_if_missing(mirror_file, notebook, fmt): if not os.path.isfile(mirror_file): write(notebook, mirror_file, fmt=fmt) def assert_conversion_same_as_mirror(nb_file, fmt, mirror_name, compare_notebook=False): """This function is used in the tests""" dirname, basename = os.path.split(nb_file) file_name, org_ext = os.path.splitext(basename) fmt = long_form_one_format(fmt) notebook = read(nb_file, fmt=fmt) fmt = check_auto_ext(fmt, notebook.metadata, "") ext = fmt["extension"] mirror_file = os.path.join(dirname, "..", "..", "outputs", mirror_name, full_path(file_name, fmt)) # it's better not to have Jupytext metadata in test notebooks: if fmt == "ipynb" and "jupytext" in notebook.metadata: # pragma: no cover notebook.metadata.pop("jupytext") write(nb_file, fmt=fmt) create_mirror_file_if_missing(mirror_file, notebook, fmt) # Compare the text representation of the two notebooks if compare_notebook: # Read and convert the mirror file to the latest nbformat version if necessary nb_mirror = read(mirror_file, as_version=notebook.nbformat) nb_mirror.nbformat_minor = notebook.nbformat_minor compare_notebooks(nb_mirror, notebook) return elif ext == ".ipynb": notebook = read(mirror_file) fmt.update({"extension": org_ext}) actual = writes(notebook, fmt) with open(nb_file, encoding="utf-8") as fp: expected = fp.read() else: actual = writes(notebook, fmt) with open(mirror_file, encoding="utf-8") as fp: expected = fp.read() if not actual.endswith("\n"): actual = actual + "\n" if fmt.get("format_name") == "marimo": lines = expected.splitlines() lines = [ # mirror files were generated with marimo 0.17.8 f'__generated_with = "{marimo_version()}"' if line == '__generated_with = "0.17.8"' else line for line in lines ] expected = "\n".join(lines) + "\n" compare(actual, expected) # Compare the two notebooks if ext != ".ipynb": notebook = read(nb_file) nb_mirror = read(mirror_file, fmt=fmt) if fmt.get("format_name") == "sphinx": nb_mirror.cells = nb_mirror.cells[1:] for cell in notebook.cells: cell.metadata = {} for cell in nb_mirror.cells: cell.metadata = {} compare_notebooks(nb_mirror, notebook, fmt) nb_mirror = combine_inputs_with_outputs(nb_mirror, notebook) compare_notebooks(nb_mirror, notebook, fmt, compare_outputs=True) def notebook_model(nb): """Return a notebook model, with content a dictionary rather than a notebook object. To be used in tests only.""" return dict(type="notebook", content=json.loads(json.dumps(nb))) ================================================ FILE: src/jupytext/config.py ================================================ """Find and read Jupytext configuration files""" import json import os from pathlib import Path try: import tomllib except ImportError: import tomli as tomllib import warnings import yaml from traitlets import Bool, Dict, Enum, Float, List, Unicode, Union from traitlets.config import Configurable from traitlets.config.loader import PyFileConfigLoader from traitlets.traitlets import TraitError import typing from .formats import ( NOTEBOOK_EXTENSIONS, get_formats_from_notebook_metadata, long_form_multiple_formats, long_form_one_format, short_form_multiple_formats, ) class JupytextConfigurationError(ValueError): """Error in the specification of the format for the text notebook""" JUPYTEXT_CONFIG_FILES = [ "jupytext", "jupytext.toml", "jupytext.yml", "jupytext.yaml", "jupytext.json", ] JUPYTEXT_CONFIG_FILES.extend(["." + filename for filename in JUPYTEXT_CONFIG_FILES] + [".jupytext.py"]) PYPROJECT_FILE = "pyproject.toml" JUPYTEXT_CEILING_DIRECTORIES = [path for path in os.environ.get("JUPYTEXT_CEILING_DIRECTORIES", "").split(":") if path] class JupytextConfiguration(Configurable): """Jupytext Configuration's options""" formats = Union( [Unicode(), List(Unicode()), List(Dict(Unicode())), Dict(Unicode())], help="Save notebooks to these file extensions. " "Can be any of ipynb,Rmd,md,jl,py,R,nb.jl,nb.py,nb.R " "comma separated. If you want another format than the " "default one, append the format name to the extension, " "e.g. ipynb,py:percent to save the notebook to " "hydrogen/spyder/vscode compatible scripts. " "Can also be a list of format dictionaries for first-match pairing.", config=True, ) default_jupytext_formats = Unicode(help="Deprecated. Use 'formats' instead", config=True) preferred_jupytext_formats_save = Unicode( help="Preferred format when saving notebooks as text, per extension. " 'Use "jl:percent,py:percent,R:percent" if you want to save ' "Julia, Python and R scripts in the double percent format and " 'only write "jupytext_formats": "py" in the notebook metadata.', config=True, ) preferred_jupytext_formats_read = Unicode( help="Preferred format when reading notebooks from text, per " 'extension. Use "py:sphinx" if you want to read all python ' "scripts as Sphinx gallery scripts.", config=True, ) notebook_metadata_filter = Unicode( help="Notebook metadata that should be save in the text representations. " "Examples: 'all', '-all', 'widgets,nteract', 'kernelspec,jupytext-all'", config=True, ) default_notebook_metadata_filter = Unicode("", help="Deprecated. Use 'notebook_metadata_filter' instead", config=True) hide_notebook_metadata = Enum( values=[True, False], allow_none=True, help="Should the notebook metadata be wrapped into an HTML comment in the Markdown format?", config=True, ) root_level_metadata_as_raw_cell = Bool( True, help="Should the root level metadata of text documents (like the fields 'title' or 'author' in " "R Markdown document) appear as a raw cell in the notebook (True), or go to the notebook" "metadata?", config=True, ) root_level_metadata_filter = Unicode( help="Notebook metadata that should be promoted to the root level in the text representations. " "Examples: 'all', '-all', 'kernelspec,jupytext'", config=True, ) cell_metadata_filter = Unicode( help="Cell metadata that should be saved in the text representations. Examples: 'all', 'hide_input,hide_output'", config=True, ) default_cell_metadata_filter = Unicode("", help="Deprecated. Use 'cell_metadata_filter' instead", config=True) comment_magics = Enum( values=[True, False], allow_none=True, help="Should Jupyter magic commands be commented out in the text representation?", config=True, ) split_at_heading = Bool( False, help="Split markdown cells on headings (Markdown and R Markdown formats only)", config=True, ) sphinx_convert_rst2md = Bool( False, help="When opening a Sphinx Gallery script, convert the reStructuredText to markdown", config=True, ) doxygen_equation_markers = Bool( False, help="Should equation markers use the DOxygen format? (see https://github.com/mwouts/jupytext/issues/517)", config=True, ) outdated_text_notebook_margin = Float( 1.0, help="Refuse to overwrite inputs of a ipynb notebooks with those of a " "text notebook when the text notebook plus margin is older than " "the ipynb notebook (NB: This option is ignored by Jupytext CLI)", config=True, ) cm_config_log_level = Enum( values=["warning", "info", "info_if_changed", "debug", "none"], default_value="info_if_changed", help="The log level for config file logs in the Jupytext contents manager", config=True, ) cell_markers = Unicode( help='Start and end cell markers for the light format, comma separated. Use "{{{,}}}" to mark cells' 'as foldable regions in Vim, and "region,endregion" to mark cells as Vscode/PyCharm regions', config=True, ) default_cell_markers = Unicode(help="Deprecated. Use 'cell_markers' instead", config=True) notebook_extensions = Union( [List(Unicode(), NOTEBOOK_EXTENSIONS), Unicode()], help="A list of notebook extensions", config=True, ) custom_cell_magics = Unicode( help='A comma separated list of cell magics. Use e.g. custom_cell_magics = "configure,local" ' 'if you want code cells starting with the Spark magic cell commands "configure" and "local" ' "to be commented out when converted to scripts.", config=True, ) def set_default_format_options(self, format_options, read=False): """Set default format option""" if self.default_notebook_metadata_filter: warnings.warn( "The option 'default_notebook_metadata_filter' is deprecated. Please use 'notebook_metadata_filter' instead.", FutureWarning, ) format_options.setdefault("notebook_metadata_filter", self.default_notebook_metadata_filter) if self.notebook_metadata_filter: format_options.setdefault("notebook_metadata_filter", self.notebook_metadata_filter) if self.default_cell_metadata_filter: warnings.warn( "The option 'default_cell_metadata_filter' is deprecated. Please use 'cell_metadata_filter' instead.", FutureWarning, ) format_options.setdefault("cell_metadata_filter", self.default_cell_metadata_filter) if self.root_level_metadata_filter: format_options.setdefault("root_level_metadata_filter", self.root_level_metadata_filter) if self.cell_metadata_filter: format_options.setdefault("cell_metadata_filter", self.cell_metadata_filter) if self.hide_notebook_metadata is not None: format_options.setdefault("hide_notebook_metadata", self.hide_notebook_metadata) if self.root_level_metadata_as_raw_cell is False: format_options.setdefault("root_level_metadata_as_raw_cell", self.root_level_metadata_as_raw_cell) if self.comment_magics is not None: format_options.setdefault("comment_magics", self.comment_magics) if self.split_at_heading: format_options.setdefault("split_at_heading", self.split_at_heading) if self.doxygen_equation_markers: format_options.setdefault("doxygen_equation_markers", self.doxygen_equation_markers) if not read: if self.default_cell_markers: warnings.warn( "The option 'default_cell_markers' is deprecated. Please use 'cell_markers' instead.", FutureWarning, ) format_options.setdefault("cell_markers", self.default_cell_markers) if self.cell_markers: format_options.setdefault("cell_markers", self.cell_markers) if read and self.sphinx_convert_rst2md: format_options.setdefault("rst2md", self.sphinx_convert_rst2md) if self.custom_cell_magics: format_options.setdefault("custom_cell_magics", self.custom_cell_magics) def default_formats(self, path): """Return the default formats, if they apply to the current path #157""" from .paired_paths import InconsistentPath, base_path if self.default_jupytext_formats: warnings.warn( "The option 'default_jupytext_formats' is deprecated. Please use 'formats' instead.", FutureWarning, ) # formats is a list of paired formats - find the first match for paired_formats in normalize_formats(self.formats or self.default_jupytext_formats): # Check if one of the paired format matches the current path for fmt in long_form_multiple_formats(paired_formats): try: base_path(path, fmt) return paired_formats except InconsistentPath: continue return None def __eq__(self, other): for key in self.class_trait_names(): if getattr(self, key) != getattr(other, key): return False return True def preferred_format(incomplete_format, preferred_formats): """Return the preferred format for the given extension""" incomplete_format = long_form_one_format(incomplete_format) if "format_name" in incomplete_format: return incomplete_format for fmt in long_form_multiple_formats(preferred_formats): if ( ( incomplete_format["extension"] == fmt["extension"] or ( fmt["extension"] == ".auto" and incomplete_format["extension"] not in [".md", ".markdown", ".Rmd", ".ipynb"] ) ) and incomplete_format.get("suffix") == fmt.get("suffix", incomplete_format.get("suffix")) and incomplete_format.get("prefix") == fmt.get("prefix", incomplete_format.get("prefix")) ): fmt.update(incomplete_format) return fmt return incomplete_format def global_jupytext_configuration_directories(): """Return the directories in which Jupytext will search for a configuration file""" config_dirs = [] if "XDG_CONFIG_HOME" in os.environ: config_dirs.extend(os.environ["XDG_CONFIG_HOME"].split(":")) elif "USERPROFILE" in os.environ: config_dirs.append(os.environ["USERPROFILE"]) elif "HOME" in os.environ: config_dirs.append(os.path.join(os.environ["HOME"], ".config")) config_dirs.append(os.environ["HOME"]) if "XDG_CONFIG_DIRS" in os.environ: config_dirs.extend(os.environ["XDG_CONFIG_DIRS"].split(":")) elif "ALLUSERSPROFILE" in os.environ: config_dirs.append(os.environ["ALLUSERSPROFILE"]) else: config_dirs.extend(["/usr/local/share/", "/usr/share/"]) for config_dir in config_dirs: yield from [ os.path.join(config_dir, "jupytext"), config_dir, ] def find_global_jupytext_configuration_file(): """Return the global Jupytext configuration file, if any""" for config_dir in global_jupytext_configuration_directories(): config_file = find_jupytext_configuration_file(config_dir, False) if config_file: return config_file return None def find_jupytext_configuration_file(path: typing.Union[str, Path], search_parent_dirs=True) -> str: """Return the first jupytext configuration file in the current directory, or any parent directory""" path = Path(path).absolute() if path.is_dir(): for filename in JUPYTEXT_CONFIG_FILES: full_path = path / filename if full_path.is_file(): return str(full_path) pyproject_path = path / PYPROJECT_FILE if pyproject_path.is_file(): with pyproject_path.open() as stream: doc = tomllib.loads(stream.read()) if doc.get("tool", {}).get("jupytext") is not None: return str(pyproject_path) if not search_parent_dirs: return None if JUPYTEXT_CEILING_DIRECTORIES and path.is_dir(): for ceiling_dir in JUPYTEXT_CEILING_DIRECTORIES: if Path(ceiling_dir).is_dir() and path.absolute() == Path(ceiling_dir).absolute(): return None parent_dir = path.parent if parent_dir == path: return find_global_jupytext_configuration_file() return find_jupytext_configuration_file(parent_dir, True) def parse_jupytext_configuration_file(jupytext_config_file, stream=None): """Read a Jupytext config file, and return a dict""" if not jupytext_config_file.endswith(".py") and stream is None: with open(jupytext_config_file, encoding="utf-8") as stream: return parse_jupytext_configuration_file(jupytext_config_file, stream.read()) try: if jupytext_config_file.endswith((".toml", "jupytext")): doc = tomllib.loads(stream) if jupytext_config_file.endswith(PYPROJECT_FILE): return doc["tool"]["jupytext"] else: return doc if jupytext_config_file.endswith((".yml", ".yaml")): return yaml.safe_load(stream) if jupytext_config_file.endswith(".json"): return json.loads(stream) return PyFileConfigLoader(jupytext_config_file).load_config() except (ValueError, NameError) as err: raise JupytextConfigurationError(f"The Jupytext configuration file {jupytext_config_file} is incorrect: {err}") def normalize_formats(formats) -> list[str]: """Normalize the formats option into a list of string-encoded paired formats""" # Process formats - can be string, dict, or list if isinstance(formats, str): # Split on semicolon for multiple format groups formats = formats.split(";") elif isinstance(formats, dict): # Single dict - wrap in list for uniform processing formats = [formats] elif formats is None: formats = [] elif not isinstance(formats, list): raise JupytextConfigurationError( f"Invalid type for 'formats': {type(formats).__name__}. Expected str, dict, list of str or dict." ) # Each group of paired formats can be a string or a dict string_encoded_pairing_formats = [] for paired_formats in formats: if isinstance(paired_formats, str): string_encoded_pairing_formats.append(paired_formats) elif isinstance(paired_formats, dict): # Convert dict to format string paired_formats = [ (f if not prefix else (prefix[:-1] if prefix.endswith("/") else prefix) + "///" + f) for prefix, f in paired_formats.items() ] string_encoded_pairing_formats.append(short_form_multiple_formats(paired_formats)) else: raise JupytextConfigurationError( f"Invalid paired formats: {paired_formats}. Expected str or dict, got {type(paired_formats).__name__}." ) return string_encoded_pairing_formats def load_jupytext_configuration_file(config_file, stream=None): """Read and validate a Jupytext configuration file, and return a JupytextConfiguration object""" config_dict = parse_jupytext_configuration_file(config_file, stream) config = validate_jupytext_configuration_file(config_file, config_dict) config.formats = normalize_formats(config.formats or config.default_jupytext_formats) if isinstance(config.notebook_extensions, str): config.notebook_extensions = config.notebook_extensions.split(",") return config def load_jupytext_config(nb_file): """Return the jupytext configuration file in the same folder, or in a parent folder, of the current file, if any""" config_file = find_jupytext_configuration_file(nb_file) if config_file is None: return None if os.path.isfile(nb_file) and os.path.samefile(config_file, nb_file): return None config_file = find_jupytext_configuration_file(nb_file) return load_jupytext_configuration_file(config_file) def validate_jupytext_configuration_file(config_file, config_dict): """Turn a dict-like config into a JupytextConfiguration object""" if config_dict is None: return None try: config = JupytextConfiguration(**config_dict) except TraitError as err: raise JupytextConfigurationError(f"The Jupytext configuration file {config_file} is incorrect: {err}") invalid_options = set(config_dict).difference(dir(JupytextConfiguration())) if any(invalid_options): raise JupytextConfigurationError( "The Jupytext configuration file {} is incorrect: options {} are not supported".format( config_file, ",".join(invalid_options) ) ) return config def notebook_formats(nbk, config, path, fallback_on_current_fmt=True): """Return the list of formats for the current notebook""" metadata = nbk.get("metadata") jupytext_metadata = metadata.get("jupytext", {}) formats = jupytext_metadata.get("formats") or metadata.get("jupytext_formats") if formats: formats = long_form_multiple_formats(formats, metadata, auto_ext_requires_language_info=False) elif config: current_format = jupytext_metadata.get("text_representation", {"extension": os.path.splitext(path)[1]}) default_formats = long_form_multiple_formats( config.default_formats(path), metadata, auto_ext_requires_language_info=False, ) if any( current_format.get("extension") == fmt["extension"] and ( "format_name" not in fmt or "format_name" not in current_format or current_format["format_name"] == fmt.get("format_name") ) for fmt in default_formats ): formats = default_formats if not formats: if not fallback_on_current_fmt: return None text_repr = jupytext_metadata.get("text_representation", {}) ext = os.path.splitext(path)[1] fmt = {"extension": ext} if ext == text_repr.get("extension") and text_repr.get("format_name"): fmt["format_name"] = text_repr.get("format_name") formats = [fmt] # Set preferred formats if no format name has been given yet if config: formats = [preferred_format(f, config.preferred_jupytext_formats_save) for f in formats] return formats def get_formats_from_notebook_and_config(notebook, config, nb_file): """ Get the notebook formats from notebook metadata or config. Notebook metadata takes precedence over config. If the notebook metadata contains pairing information, it is used; otherwise, the configuration is used as a fallback. Parameters ---------- notebook : dict The notebook object (as a dictionary). config : JupytextConfiguration or None The Jupytext configuration object. nb_file : str The path to the notebook file. Returns ------- list A list of format dictionaries describing the notebook's paired formats. """ formats = get_formats_from_notebook_metadata(notebook) if formats: return long_form_multiple_formats(formats) else: return notebook_formats(notebook, config, nb_file) ================================================ FILE: src/jupytext/doxygen.py ================================================ """Convert Markdown equations to doxygen equations and back See https://github.com/mwouts/jupytext/issues/517""" import re def markdown_to_doxygen(string): """Markdown to Doxygen equations""" long_equations = re.sub(r"(?\\f]", string, flags=re.DOTALL) inline_equations = re.sub(r"(?$$", string, flags=re.DOTALL) inline_equations = re.sub(r"\\f\$", "$", long_equations) return inline_equations ================================================ FILE: src/jupytext/formats.py ================================================ """ In this file the various text notebooks formats are defined. Please contribute new formats here! """ import os import re import warnings import nbformat import yaml from .cell_reader import ( DoublePercentScriptCellReader, HydrogenCellReader, LightScriptCellReader, MarkdownCellReader, RMarkdownCellReader, RScriptCellReader, SphinxGalleryScriptCellReader, ) from .cell_to_text import ( BareScriptCellExporter, DoublePercentCellExporter, HydrogenCellExporter, LightScriptCellExporter, MarkdownCellExporter, RMarkdownCellExporter, RScriptCellExporter, SphinxGalleryCellExporter, ) from .header import header_to_metadata_and_cell, insert_or_test_version_number from .languages import _COMMENT_CHARS, _SCRIPT_EXTENSIONS, same_language from .magics import is_magic from .metadata_filter import metadata_filter_as_string from .myst import ( MYST_FORMAT_NAME, is_myst_available, matches_mystnb, myst_extensions, myst_version, ) from .pandoc import is_pandoc_available, pandoc_version from .stringparser import StringParser from .version import __version__ class JupytextFormatError(ValueError): """Error in the specification of the format for the text notebook""" class NotebookFormatDescription: """Description of a notebook format""" def __init__( self, format_name, extension, header_prefix, cell_reader_class, cell_exporter_class, current_version_number, header_suffix="", min_readable_version_number=None, ): self.format_name = format_name self.extension = extension self.header_prefix = header_prefix self.header_suffix = header_suffix self.cell_reader_class = cell_reader_class self.cell_exporter_class = cell_exporter_class self.current_version_number = current_version_number self.min_readable_version_number = min_readable_version_number JUPYTEXT_FORMATS = ( [ NotebookFormatDescription( format_name="markdown", extension=".md", header_prefix="", cell_reader_class=MarkdownCellReader, cell_exporter_class=MarkdownCellExporter, # Version 1.0 on 2018-08-31 - jupytext v0.6.0 : Initial version # Version 1.1 on 2019-03-24 - jupytext v1.1.0 : Markdown regions and cell metadata # Version 1.2 on 2019-09-21 - jupytext v1.3.0 : Raw regions are now encoded with HTML comments (#321) # and by default, cell metadata use the key=value representation (#347) # Version 1.3 on 2021-01-24 - jupytext v1.10.0 : Code cells may start with more than three backticks (#712) current_version_number="1.3", min_readable_version_number="1.0", ), NotebookFormatDescription( format_name="markdown", extension=".markdown", header_prefix="", cell_reader_class=MarkdownCellReader, cell_exporter_class=MarkdownCellExporter, current_version_number="1.2", min_readable_version_number="1.0", ), NotebookFormatDescription( format_name="rmarkdown", extension=".Rmd", header_prefix="", cell_reader_class=RMarkdownCellReader, cell_exporter_class=RMarkdownCellExporter, # Version 1.0 on 2018-08-22 - jupytext v0.5.2 : Initial version # Version 1.1 on 2019-03-24 - jupytext v1.1.0 : Markdown regions and cell metadata # Version 1.2 on 2019-09-21 - jupytext v1.3.0 : Raw regions are now encoded with HTML comments (#321) # and by default, cell metadata use the key=value representation in raw and markdown cells (#347) current_version_number="1.2", min_readable_version_number="1.0", ), ] + [ NotebookFormatDescription( format_name="light", extension=ext, header_prefix=_SCRIPT_EXTENSIONS[ext]["comment"], header_suffix=_SCRIPT_EXTENSIONS[ext].get("comment_suffix", ""), cell_reader_class=LightScriptCellReader, cell_exporter_class=LightScriptCellExporter, # Version 1.5 on 2019-10-19 - jupytext v1.3.0 - Cell metadata represented as key=value by default # Version 1.4 on 2019-03-30 - jupytext v1.1.0 - custom cell markers allowed # Version 1.3 on 2018-09-22 - jupytext v0.7.0rc0 : Metadata are # allowed for all cell types (and then include 'cell_type') # Version 1.2 on 2018-09-05 - jupytext v0.6.3 : Metadata bracket # can be omitted when empty, if previous line is empty #57 # Version 1.1 on 2018-08-25 - jupytext v0.6.0 : Cells separated # with one blank line #38 # Version 1.0 on 2018-08-22 - jupytext v0.5.2 : Initial version current_version_number="1.5", min_readable_version_number="1.1", ) for ext in _SCRIPT_EXTENSIONS ] + [ NotebookFormatDescription( format_name="nomarker", extension=ext, header_prefix=_SCRIPT_EXTENSIONS[ext]["comment"], header_suffix=_SCRIPT_EXTENSIONS[ext].get("comment_suffix", ""), cell_reader_class=LightScriptCellReader, cell_exporter_class=BareScriptCellExporter, current_version_number="1.0", min_readable_version_number="1.0", ) for ext in _SCRIPT_EXTENSIONS ] + [ NotebookFormatDescription( format_name="percent", extension=ext, header_prefix=_SCRIPT_EXTENSIONS[ext]["comment"], header_suffix=_SCRIPT_EXTENSIONS[ext].get("comment_suffix", ""), cell_reader_class=DoublePercentScriptCellReader, cell_exporter_class=DoublePercentCellExporter, # Version 1.3 on 2019-09-21 - jupytext v1.3.0: Markdown cells can be quoted using triple quotes #305 # and cell metadata are represented as key=value by default # Version 1.2 on 2018-11-18 - jupytext v0.8.6: Jupyter magics are commented by default #126, #132 # Version 1.1 on 2018-09-23 - jupytext v0.7.0rc1 : [markdown] and # [raw] for markdown and raw cells. # Version 1.0 on 2018-09-22 - jupytext v0.7.0rc0 : Initial version current_version_number="1.3", min_readable_version_number="1.1", ) for ext in _SCRIPT_EXTENSIONS ] + [ NotebookFormatDescription( format_name="hydrogen", extension=ext, header_prefix=_SCRIPT_EXTENSIONS[ext]["comment"], header_suffix=_SCRIPT_EXTENSIONS[ext].get("comment_suffix", ""), cell_reader_class=HydrogenCellReader, cell_exporter_class=HydrogenCellExporter, # Version 1.2 on 2018-12-14 - jupytext v0.9.0: same as percent - only magics are not commented by default current_version_number="1.3", min_readable_version_number="1.1", ) for ext in _SCRIPT_EXTENSIONS ] + [ NotebookFormatDescription( format_name="spin", extension=ext, header_prefix="#'", cell_reader_class=RScriptCellReader, cell_exporter_class=RScriptCellExporter, # Version 1.0 on 2018-08-22 - jupytext v0.5.2 : Initial version current_version_number="1.0", ) for ext in [".r", ".R"] ] + [ NotebookFormatDescription( format_name="sphinx", extension=".py", header_prefix="#", cell_reader_class=SphinxGalleryScriptCellReader, cell_exporter_class=SphinxGalleryCellExporter, # Version 1.0 on 2018-09-22 - jupytext v0.7.0rc0 : Initial version current_version_number="1.1", ), NotebookFormatDescription( format_name="pandoc", extension=".md", header_prefix="", cell_reader_class=None, cell_exporter_class=None, current_version_number=pandoc_version(), ), NotebookFormatDescription( format_name="quarto", extension=".qmd", header_prefix="", cell_reader_class=None, cell_exporter_class=None, # Version 1.0 on 2021-09-07 = quarto --version >= 0.2.134, # cf. https://github.com/mwouts/jupytext/issues/837 current_version_number="1.0", ), NotebookFormatDescription( format_name="marimo", extension=".py", header_prefix="", cell_reader_class=None, cell_exporter_class=None, # Version 1.0 on 2025-09-07 current_version_number="1.0", ), ] + [ NotebookFormatDescription( format_name=MYST_FORMAT_NAME, extension=ext, header_prefix="", cell_reader_class=None, cell_exporter_class=None, current_version_number=myst_version(), ) for ext in myst_extensions() ] ) NOTEBOOK_EXTENSIONS = list(dict.fromkeys([".ipynb"] + [fmt.extension for fmt in JUPYTEXT_FORMATS])) EXTENSION_PREFIXES = [".lgt", ".spx", ".pct", ".hyd", ".nb"] FORMATS_WITH_NO_CELL_METADATA = {"sphinx", "nomarker", "spin", "quarto", "marimo"} def get_format_implementation(ext, format_name=None): """Return the implementation for the desired format""" # remove pre-extension if any ext = "." + ext.split(".")[-1] formats_for_extension = [] for fmt in JUPYTEXT_FORMATS: if fmt.extension == ext: if fmt.format_name == format_name or not format_name: return fmt formats_for_extension.append(fmt.format_name) if formats_for_extension: raise JupytextFormatError( "Format '{}' is not associated to extension '{}'. Please choose one of: {}.".format( format_name, ext, ", ".join(formats_for_extension) ) ) raise JupytextFormatError(f"No format associated to extension '{ext}'") def read_metadata(text, ext): """Return the header metadata""" ext = "." + ext.split(".")[-1] lines = text.splitlines() if ext in [".md", ".markdown", ".Rmd"]: comment = comment_suffix = "" else: comment = _SCRIPT_EXTENSIONS.get(ext, {}).get("comment", "#") comment_suffix = _SCRIPT_EXTENSIONS.get(ext, {}).get("comment_suffix", "") metadata, _, _, _ = header_to_metadata_and_cell(lines, comment, comment_suffix, ext) if ext in [".r", ".R"] and not metadata: metadata, _, _, _ = header_to_metadata_and_cell(lines, "#'", "", ext) # metadata in MyST format may be at root level (i.e. not caught above) if not metadata and ext in myst_extensions() and text.startswith("---"): for header in yaml.safe_load_all(text): if not isinstance(header, dict): continue if header.get("jupytext", {}).get("text_representation", {}).get("format_name") == MYST_FORMAT_NAME: return header return metadata return metadata def read_format_from_metadata(text, ext): """Return the format of the file, when that information is available from the metadata""" metadata = read_metadata(text, ext) rearrange_jupytext_metadata(metadata) return format_name_for_ext(metadata, ext, explicit_default=False) def guess_format(text, ext): """Guess the format and format options of the file, given its extension and content""" metadata = read_metadata(text, ext) if "text_representation" in metadata.get("jupytext", {}): return format_name_for_ext(metadata, ext), {} if is_myst_available() and ext in myst_extensions() and matches_mystnb(text, ext, requires_meta=False): return MYST_FORMAT_NAME, {} lines = text.splitlines() # Is this a Hydrogen-like script? # Or a Sphinx-gallery script? if ext in _SCRIPT_EXTENSIONS: unescaped_comment = _SCRIPT_EXTENSIONS[ext]["comment"] comment = re.escape(unescaped_comment) language = _SCRIPT_EXTENSIONS[ext]["language"] twenty_hash_re = re.compile(r"^#( |)#{19,}\s*$") double_percent_re = re.compile(rf"^{comment}( %%|%%)$") double_percent_and_space_re = re.compile(rf"^{comment}( %%|%%)\s") nbconvert_script_re = re.compile(rf"^{comment}( | In\[[0-9 ]*\]:?)") vim_folding_markers_re = re.compile(rf"^{comment}\s*" + "{{{") vscode_folding_markers_re = re.compile(rf"^{comment}\s*region") marimo_cell_re = re.compile(r"^@app.cell.*") twenty_hash_count = 0 double_percent_count = 0 magic_command_count = 0 rspin_comment_count = 0 vim_folding_markers_count = 0 vscode_folding_markers_count = 0 marimo_app_count = 0 parser = StringParser(language="R" if ext in [".r", ".R"] else "python") for line in lines: parser.read_line(line) if parser.is_quoted(): continue # Don't count escaped Jupyter magics (no space between %% and command) as cells if double_percent_re.match(line) or double_percent_and_space_re.match(line) or nbconvert_script_re.match(line): double_percent_count += 1 if not line.startswith(unescaped_comment) and is_magic(line, language): magic_command_count += 1 if twenty_hash_re.match(line) and ext == ".py": twenty_hash_count += 1 if line.startswith("#'") and ext in [".R", ".r"]: rspin_comment_count += 1 if vim_folding_markers_re.match(line): vim_folding_markers_count += 1 if vscode_folding_markers_re.match(line): vscode_folding_markers_count += 1 if ext == ".py" and (line in {"import marimo", "app = marimo.App()"} or marimo_cell_re.match(line)): marimo_app_count += 1 if double_percent_count >= 1: if magic_command_count: return "hydrogen", {} return "percent", {} if marimo_app_count >= 2: return "marimo", {} if vim_folding_markers_count: return "light", {"cell_markers": "{{{,}}}"} if vscode_folding_markers_count: return "light", {"cell_markers": "region,endregion"} if twenty_hash_count >= 2: return "sphinx", {} if rspin_comment_count >= 1: return "spin", {} if ext in [".md", ".markdown"]: for line in lines: if line.startswith(":::"): # Pandoc div return "pandoc", {} # Default format return get_format_implementation(ext).format_name, {} def divine_format(text): """Guess the format of the notebook, based on its content #148""" try: nbformat.reads(text, as_version=4) return "ipynb" except nbformat.reader.NotJSONError: pass lines = text.splitlines() for comment in ["", "#"] + _COMMENT_CHARS: metadata, _, _, _ = header_to_metadata_and_cell(lines, comment, "") ext = metadata.get("jupytext", {}).get("text_representation", {}).get("extension") if ext: return ext[1:] + ":" + guess_format(text, ext)[0] # No metadata, but ``` on at least one line => markdown for line in lines: if line == "```": return "md" return "py:" + guess_format(text, ".py")[0] def check_file_version(notebook, source_path, outputs_path): """Raise if file version in source file would override outputs""" if not insert_or_test_version_number(): return if source_path == "-": # https://github.com/mwouts/jupytext/issues/1282 ext = notebook.metadata["jupytext"]["text_representation"]["extension"] else: _, ext = os.path.splitext(source_path) assert not ext.endswith(".ipynb"), f"source_path={source_path} should be a text file" version = notebook.metadata.get("jupytext", {}).get("text_representation", {}).get("format_version") format_name = format_name_for_ext(notebook.metadata, ext) fmt = get_format_implementation(ext, format_name) current = fmt.current_version_number # Missing version, still generated by jupytext? if notebook.metadata and not version: version = current # Same version? OK if version == fmt.current_version_number: return # Version larger than minimum readable version if (fmt.min_readable_version_number or current) <= version <= current: return jupytext_version_in_file = ( notebook.metadata.get("jupytext", {}).get("text_representation", {}).get("jupytext_version", "N/A") ) raise JupytextFormatError( "The file {source_path} was generated with jupytext version {jupytext_version_in_file} " "but you have {jupytext_version} installed. Please upgrade jupytext to version " "{jupytext_version_in_file}, or remove either {source_path} or {output_path}. " "This error occurs because {source_path} is in the {format_name} format in version {format_version}, " "while jupytext version {jupytext_version} installed at {jupytext_path} can only read the " "{format_name} format in versions {min_format_version} to {current_format_version}.".format( source_path=os.path.basename(source_path), output_path=os.path.basename(outputs_path), format_name=format_name, format_version=version, jupytext_version_in_file=jupytext_version_in_file, jupytext_version=__version__, jupytext_path=os.path.dirname(os.path.dirname(__file__)), min_format_version=fmt.min_readable_version_number or current, current_format_version=current, ) ) def format_name_for_ext(metadata, ext, cm_default_formats=None, explicit_default=True): """Return the format name for that extension""" # Is the format information available in the text representation? text_repr = metadata.get("jupytext", {}).get("text_representation", {}) if text_repr.get("extension", "").endswith(ext) and text_repr.get("format_name"): return text_repr.get("format_name") # Format from jupytext.formats formats = metadata.get("jupytext", {}).get("formats", "") or cm_default_formats formats = long_form_multiple_formats(formats) for fmt in formats: if fmt["extension"] == ext: if (not explicit_default) or fmt.get("format_name"): return fmt.get("format_name") if (not explicit_default) or ext in [".md", ".markdown", ".Rmd"]: return None return get_format_implementation(ext).format_name def identical_format_path(fmt1, fmt2): """Do the two (long representation) of formats target the same file?""" for key in ["extension", "prefix", "suffix"]: if fmt1.get(key) != fmt2.get(key): return False return True def update_jupytext_formats_metadata(metadata, new_format): """Update the jupytext_format metadata in the Jupyter notebook""" new_format = long_form_one_format(new_format) formats = long_form_multiple_formats(metadata.get("jupytext", {}).get("formats", "")) if not formats: return for fmt in formats: if identical_format_path(fmt, new_format): fmt["format_name"] = new_format.get("format_name") break metadata.setdefault("jupytext", {})["formats"] = short_form_multiple_formats(formats) def rearrange_jupytext_metadata(metadata): """Convert the jupytext_formats metadata entry to jupytext/formats, etc. See #91""" # Backward compatibility with nbrmd for key in ["nbrmd_formats", "nbrmd_format_version"]: if key in metadata: metadata[key.replace("nbrmd", "jupytext")] = metadata.pop(key) jupytext_metadata = metadata.get("jupytext", {}) if "jupytext_formats" in metadata: jupytext_metadata["formats"] = metadata.pop("jupytext_formats") if "jupytext_format_version" in metadata: jupytext_metadata["text_representation"] = {"format_version": metadata.pop("jupytext_format_version")} if "main_language" in metadata: jupytext_metadata["main_language"] = metadata.pop("main_language") for entry in ["encoding", "executable"]: if entry in metadata: jupytext_metadata[entry] = metadata.pop(entry) filters = jupytext_metadata.pop("metadata_filter", {}) if "notebook" in filters: jupytext_metadata["notebook_metadata_filter"] = filters["notebook"] if "cells" in filters: jupytext_metadata["cell_metadata_filter"] = filters["cells"] for filter_level in ["notebook_metadata_filter", "cell_metadata_filter"]: if filter_level in jupytext_metadata: jupytext_metadata[filter_level] = metadata_filter_as_string(jupytext_metadata[filter_level]) if jupytext_metadata.get("text_representation", {}).get("jupytext_version", "").startswith("0."): formats = jupytext_metadata.get("formats") if formats: jupytext_metadata["formats"] = ",".join(["." + fmt if fmt.rfind(".") > 0 else fmt for fmt in formats.split(",")]) # auto to actual extension formats = jupytext_metadata.get("formats") if formats: jupytext_metadata["formats"] = short_form_multiple_formats(long_form_multiple_formats(formats, metadata)) if jupytext_metadata: metadata["jupytext"] = jupytext_metadata def long_form_one_format(jupytext_format, metadata=None, update=None, auto_ext_requires_language_info=True): """Parse 'sfx.py:percent' into {'suffix':'sfx', 'extension':'py', 'format_name':'percent'}""" if isinstance(jupytext_format, dict): if update: jupytext_format.update(update) return validate_one_format(jupytext_format) if not jupytext_format: return {} common_name_to_ext = { "notebook": "ipynb", "rmarkdown": "Rmd", "quarto": "qmd", "marimo": "py", "markdown": "md", "script": "auto", "c++": "cpp", "myst": "md:myst", "pandoc": "md:pandoc", } if jupytext_format.lower() in common_name_to_ext: jupytext_format = common_name_to_ext[jupytext_format.lower()] fmt = {} if jupytext_format.rfind("/") > 0: fmt["prefix"], jupytext_format = jupytext_format.rsplit("/", 1) if jupytext_format.rfind(":") >= 0: ext, fmt["format_name"] = jupytext_format.rsplit(":", 1) if fmt["format_name"] == "bare": warnings.warn( "The `bare` format has been renamed to `nomarker` - (see https://github.com/mwouts/jupytext/issues/397)", DeprecationWarning, ) fmt["format_name"] = "nomarker" elif not jupytext_format or "." in jupytext_format or ("." + jupytext_format) in NOTEBOOK_EXTENSIONS + [".auto"]: ext = jupytext_format elif jupytext_format in _VALID_FORMAT_NAMES: fmt["format_name"] = jupytext_format ext = "" else: raise JupytextFormatError( "'{}' is not a notebook extension (one of {}), nor a notebook format (one of {})".format( jupytext_format, ", ".join(NOTEBOOK_EXTENSIONS), ", ".join(_VALID_FORMAT_NAMES), ) ) if ext.rfind(".") > 0: fmt["suffix"], ext = os.path.splitext(ext) if not ext.startswith("."): ext = "." + ext if ext == ".auto": ext = auto_ext_from_metadata(metadata) if metadata is not None else ".auto" if not ext: if auto_ext_requires_language_info: raise JupytextFormatError( "No language information in this notebook. Please replace 'auto' with an actual script extension." ) ext = ".auto" fmt["extension"] = ext if update: fmt.update(update) return validate_one_format(fmt) def long_form_multiple_formats( jupytext_formats: str, metadata=None, auto_ext_requires_language_info=True ) -> list[dict[str, str]]: """Convert a concise encoding of jupytext.formats to a list of formats, encoded as dictionaries""" if not jupytext_formats: return [] if not isinstance(jupytext_formats, list): jupytext_formats = [fmt for fmt in jupytext_formats.split(",") if fmt] jupytext_formats = [ long_form_one_format( fmt, metadata, auto_ext_requires_language_info=auto_ext_requires_language_info, ) for fmt in jupytext_formats ] if not auto_ext_requires_language_info: jupytext_formats = [fmt for fmt in jupytext_formats if fmt["extension"] != ".auto"] return jupytext_formats def short_form_one_format(jupytext_format: dict[str, str]) -> str: """Represent one jupytext format as a string""" if not isinstance(jupytext_format, dict): return jupytext_format fmt = jupytext_format["extension"] if "suffix" in jupytext_format: fmt = jupytext_format["suffix"] + fmt elif fmt.startswith("."): fmt = fmt[1:] if "prefix" in jupytext_format: fmt = jupytext_format["prefix"] + "/" + fmt if jupytext_format.get("format_name"): if jupytext_format["extension"] not in [ ".md", ".markdown", ".Rmd", ] or jupytext_format["format_name"] in ["pandoc", MYST_FORMAT_NAME]: fmt = fmt + ":" + jupytext_format["format_name"] return fmt def short_form_multiple_formats(jupytext_formats: list[dict[str, str]]) -> str: """Convert jupytext formats, represented as a list of dictionaries, to a comma separated list""" if not isinstance(jupytext_formats, list): return jupytext_formats jupytext_formats = [short_form_one_format(fmt) for fmt in jupytext_formats] return ",".join(jupytext_formats) _VALID_FORMAT_INFO = ["extension", "format_name", "suffix", "prefix"] _BINARY_FORMAT_OPTIONS = [ "comment_magics", "hide_notebook_metadata", "root_level_metadata_as_raw_cell", "split_at_heading", "rst2md", "cell_metadata_json", "use_runtools", "doxygen_equation_markers", ] _VALID_FORMAT_OPTIONS = _BINARY_FORMAT_OPTIONS + [ "notebook_metadata_filter", "root_level_metadata_filter", "cell_metadata_filter", "cell_markers", "custom_cell_magics", ] _VALID_FORMAT_NAMES = {fmt.format_name for fmt in JUPYTEXT_FORMATS} def validate_one_format(jupytext_format: dict[str, str]) -> dict[str, str]: """Validate extension and options for the given format""" if not isinstance(jupytext_format, dict): raise JupytextFormatError("Jupytext format should be a dictionary") if "format_name" in jupytext_format and jupytext_format["format_name"] not in _VALID_FORMAT_NAMES: raise JupytextFormatError( "{} is not a valid format name. Please choose one of {}".format( jupytext_format.get("format_name"), ", ".join(_VALID_FORMAT_NAMES) ) ) for key in jupytext_format: if key not in _VALID_FORMAT_INFO + _VALID_FORMAT_OPTIONS: raise JupytextFormatError( "Unknown format option '{}' - should be one of '{}'".format(key, "', '".join(_VALID_FORMAT_OPTIONS)) ) value = jupytext_format[key] if key in _BINARY_FORMAT_OPTIONS: if not isinstance(value, bool): raise JupytextFormatError(f"Format option '{key}' should be a bool, not '{str(value)}'") if "extension" not in jupytext_format: raise JupytextFormatError("Missing format extension") ext = jupytext_format["extension"] if ext not in NOTEBOOK_EXTENSIONS + [".auto"]: raise JupytextFormatError( "Extension '{}' is not a notebook extension. Please use one of '{}'.".format( ext, "', '".join(NOTEBOOK_EXTENSIONS + [".auto"]) ) ) return jupytext_format def auto_ext_from_metadata(metadata): """Script extension from notebook metadata""" auto_ext = metadata.get("language_info", {}).get("file_extension") # Sage notebooks have ".py" as the associated extension in "language_info", # so we change it to ".sage" in that case, see #727 if auto_ext == ".py" and metadata.get("kernelspec", {}).get("language") == "sage": auto_ext = ".sage" if auto_ext is None: language = metadata.get("kernelspec", {}).get("language") or metadata.get("jupytext", {}).get("main_language") if language: for ext in _SCRIPT_EXTENSIONS: if same_language(language, _SCRIPT_EXTENSIONS[ext]["language"]): auto_ext = ext break if auto_ext == ".r": return ".R" if auto_ext == ".fs": return ".fsx" if auto_ext == ".resource": return ".robot" # Handle ROOT C++ notebooks # https://tinyurl.com/root-cpp-notebook-doc if auto_ext == ".C": return ".cpp" return auto_ext def check_auto_ext(fmt, metadata, option): """Replace the auto extension with the actual file extension, and raise a ValueError if it cannot be determined""" if fmt["extension"] != ".auto": return fmt auto_ext = auto_ext_from_metadata(metadata) if auto_ext: fmt = fmt.copy() fmt["extension"] = auto_ext return fmt raise ValueError( "The notebook does not have a 'language_info' metadata. " "Please replace 'auto' with the actual language extension in the {} option (currently {}).".format( option, short_form_one_format(fmt) ) ) def formats_with_support_for_cell_metadata(): for fmt in JUPYTEXT_FORMATS: if fmt.format_name == "myst" and not is_myst_available(): continue if fmt.format_name == "pandoc" and not is_pandoc_available(): continue if fmt.format_name in FORMATS_WITH_NO_CELL_METADATA: continue yield f"{fmt.extension[1:]}:{fmt.format_name}" def get_formats_from_notebook_metadata(notebook): """ Get the pairing information from the notebook metadata. Parameters ---------- notebook : nbformat.NotebookNode The notebook object whose metadata will be inspected. Returns ------- formats : None or str The value of the 'formats' field in the 'jupytext' metadata, which can be None or a string. """ return notebook.metadata.get("jupytext", {}).get("formats") ================================================ FILE: src/jupytext/header.py ================================================ """Parse header of text notebooks""" import logging import re import nbformat import yaml from nbformat.v4.nbbase import new_raw_cell from yaml.representer import SafeRepresenter from .languages import ( _SCRIPT_EXTENSIONS, comment_lines, default_language_from_metadata_and_ext, ) from .metadata_filter import ( _DEFAULT_NOTEBOOK_METADATA, _DEFAULT_ROOT_LEVEL_METADATA, _JUPYTER_METADATA_NAMESPACE, filter_metadata, ) from .myst import MYST_FORMAT_NAME from .pep8 import pep8_lines_between_cells from .version import __version__ SafeRepresenter.add_representer(nbformat.NotebookNode, SafeRepresenter.represent_dict) _HEADER_RE = re.compile(r"^---\s*$") _BLANK_RE = re.compile(r"^\s*$") _JUPYTER_RE = re.compile(r"^jupyter\s*:\s*$") _LEFTSPACE_RE = re.compile(r"^\s") _UTF8_HEADER = " -*- coding: utf-8 -*-" # Change this to False in tests INSERT_AND_CHECK_VERSION_NUMBER = True def insert_or_test_version_number(): """Should the format name and version number be inserted in text representations (not in tests!)""" return INSERT_AND_CHECK_VERSION_NUMBER def uncomment_line(line, prefix, suffix=""): """Remove prefix (and space) from line""" if prefix: if line.startswith(prefix + " "): line = line[len(prefix) + 1 :] elif line.startswith(prefix): line = line[len(prefix) :] if suffix: if line.endswith(suffix + " "): line = line[: -(1 + len(suffix))] elif line.endswith(suffix): line = line[: -len(suffix)] return line def encoding_and_executable(notebook, metadata, ext): """Return encoding and executable lines for a notebook, if applicable""" lines = [] comment = _SCRIPT_EXTENSIONS.get(ext, {}).get("comment") jupytext_metadata = metadata.get("jupytext", {}) if comment is not None and "executable" in jupytext_metadata: lines.append("#!" + jupytext_metadata.pop("executable")) if comment is not None: if "encoding" in jupytext_metadata: lines.append(jupytext_metadata.pop("encoding")) elif default_language_from_metadata_and_ext(metadata, ext) != "python": for cell in notebook.cells: try: cell.source.encode("ascii") except (UnicodeEncodeError, UnicodeDecodeError): lines.append(comment + _UTF8_HEADER) break return lines def insert_jupytext_info_and_filter_metadata(metadata, fmt, text_format, unsupported_keys): """Update the notebook metadata to include Jupytext information, and filter the notebook metadata according to the default or user filter""" if insert_or_test_version_number(): metadata.setdefault("jupytext", {})["text_representation"] = { "extension": fmt["extension"], "format_name": text_format.format_name, "format_version": text_format.current_version_number, "jupytext_version": __version__, } if "jupytext" in metadata and not metadata["jupytext"]: del metadata["jupytext"] notebook_metadata_filter = fmt.get("notebook_metadata_filter") return filter_metadata( metadata, notebook_metadata_filter, _DEFAULT_NOTEBOOK_METADATA, unsupported_keys=unsupported_keys, ) def metadata_and_cell_to_header(notebook, metadata, text_format, fmt, unsupported_keys=None): """ Return the text header corresponding to a notebook, and remove the first cell of the notebook if it contained the header """ header = [] lines_to_next_cell = None root_level_metadata = {} root_level_metadata_as_raw_cell = fmt.get("root_level_metadata_as_raw_cell", True) if not root_level_metadata_as_raw_cell: root_level_metadata = metadata.get("jupytext", {}).pop("root_level_metadata", {}) elif notebook.cells: cell = notebook.cells[0] if cell.cell_type == "raw": lines = cell.source.strip("\n\t ").splitlines() if len(lines) >= 2 and _HEADER_RE.match(lines[0]) and _HEADER_RE.match(lines[-1]): header = lines[1:-1] lines_to_next_cell = cell.metadata.get("lines_to_next_cell") notebook.cells = notebook.cells[1:] metadata = insert_jupytext_info_and_filter_metadata(metadata, fmt, text_format, unsupported_keys) if metadata: root_level_metadata["jupyter"] = metadata if root_level_metadata: header.extend(yaml.safe_dump(root_level_metadata, default_flow_style=False).splitlines()) if header: header = ["---"] + header + ["---"] if fmt.get("hide_notebook_metadata", False) and text_format.format_name == "markdown": header = [""] return ( comment_lines(header, text_format.header_prefix, text_format.header_suffix), lines_to_next_cell, ) def recursive_update(target, update, overwrite=True): """Update recursively a (nested) dictionary with the content of another. Inspired from https://stackoverflow.com/questions/3232943/update-value-of-a-nested-dictionary-of-varying-depth """ for key in update: value = update[key] if value is None: del target[key] elif isinstance(value, dict): target[key] = recursive_update( target.get(key, {}), value, overwrite=overwrite, ) elif overwrite: target[key] = value else: target.setdefault(key, value) return target def header_to_metadata_and_cell(lines, header_prefix, header_suffix, ext=None, root_level_metadata_as_raw_cell=True): """ Return the metadata, a boolean to indicate if a jupyter section was found, the first cell of notebook if some metadata is found outside the jupyter section, and next loc in text """ header = [] jupyter = [] in_jupyter = False in_html_div = False start = 0 started = False ended = False metadata = {} i = -1 comment = "#" if header_prefix == "#'" else header_prefix encoding_re = re.compile(rf"^[ \t\f]*{re.escape(comment)}.*?coding[:=][ \t]*([-_.a-zA-Z0-9]+)") for i, line in enumerate(lines): if i == 0 and line.startswith("#!"): metadata.setdefault("jupytext", {})["executable"] = line[2:] start = i + 1 continue if i == 0 or (i == 1 and not encoding_re.match(lines[0])): encoding = encoding_re.match(line) if encoding: if encoding.group(1) != "utf-8": raise ValueError("Encodings other than utf-8 are not supported") metadata.setdefault("jupytext", {})["encoding"] = line start = i + 1 continue if not line.startswith(header_prefix): break if not comment: if line.strip().startswith("" in line: break if not started and not line.strip(): continue line = uncomment_line(line, header_prefix, header_suffix) if _HEADER_RE.match(line): if not started: started = True continue ended = True if in_html_div: continue break # Stop if there is something else than a YAML header if not started and line.strip(): break if _JUPYTER_RE.match(line): in_jupyter = True elif line and not _LEFTSPACE_RE.match(line): in_jupyter = False if in_jupyter: jupyter.append(line) else: header.append(line) if ended: if jupyter: extra_metadata = metadata metadata = yaml.safe_load("\n".join(jupyter))["jupyter"] recursive_update(metadata, extra_metadata) lines_to_next_cell = 1 if len(lines) > i + 1: line = uncomment_line(lines[i + 1], header_prefix) if not _BLANK_RE.match(line): lines_to_next_cell = 0 else: i = i + 1 else: lines_to_next_cell = 0 if header: if root_level_metadata_as_raw_cell: cell = new_raw_cell( source="\n".join(["---"] + header + ["---"]), metadata=( {} if lines_to_next_cell == pep8_lines_between_cells(["---"], lines[i + 1 :], ext) else {"lines_to_next_cell": lines_to_next_cell} ), ) else: cell = None root_level_metadata = yaml.safe_load("\n".join(header)) metadata.setdefault("jupytext", {})["root_level_metadata"] = root_level_metadata else: cell = None return metadata, jupyter, cell, i + 1 return metadata, False, None, start def default_root_level_metadata_filter(fmt): """Return defaults for settings that promote or demote root level metadata.""" if fmt and fmt.get("format_name") == MYST_FORMAT_NAME: from .myst import _DEFAULT_ROOT_LEVEL_METADATA as default_filter else: default_filter = _DEFAULT_ROOT_LEVEL_METADATA return default_filter def metadata_to_metadata_and_cell(nb, metadata, fmt, unsupported_keys=None): # stash notebook metadata, including keys promoted to the root level metadata = recursive_update( metadata, filter_metadata( nb.metadata, fmt.get("root_level_metadata_filter", ""), default_root_level_metadata_filter(fmt), unsupported_keys=unsupported_keys, remove=True, ), ) # move remaining metadata (i.e. frontmatter) to the first notebook cell if nb.metadata and fmt.get("root_level_metadata_as_raw_cell", True): frontmatter = yaml.safe_dump(nb.metadata, sort_keys=False) nb.cells.insert(0, new_raw_cell("---\n" + frontmatter + "---")) # attach the stashed metadata to notebook nb.metadata = metadata return nb def metadata_and_cell_to_metadata(nb, fmt, unsupported_keys=None): # new metadata from filtered nb.metadata metadata = filter_metadata( nb.metadata, fmt.get("root_level_metadata_filter", ""), default_root_level_metadata_filter(fmt), unsupported_keys=unsupported_keys, remove=True, ) # remaining nb.metadata moved under namespace key for jupyter metadata if nb.metadata: metadata[_JUPYTER_METADATA_NAMESPACE] = nb.metadata # move first cell frontmatter to the root level of nb.metadata (overwrites) if nb.cells and fmt.get("root_level_metadata_as_raw_cell", True): cell = nb.cells[0] if cell.cell_type == "raw": lines = cell.source.strip("\n\t ").splitlines() if len(lines) >= 2 and _HEADER_RE.match(lines[0]) and _HEADER_RE.match(lines[-1]): try: frontmatter = next(yaml.safe_load_all(cell.source)) except (yaml.parser.ParserError, yaml.scanner.ScannerError): logging.warning("[jupytext] failed to parse YAML in raw cell") else: if not isinstance(frontmatter, dict): logging.warning("[jupytext] YAML header in raw cell is not a dictionary") else: nb.cells = nb.cells[1:] if "root_level_metadata_filter" not in fmt and default_root_level_metadata_filter(fmt) == "all": metadata.setdefault("jupytext", {})["root_level_metadata_filter"] = "-" + ",-".join(frontmatter) metadata = recursive_update(frontmatter, metadata, overwrite=False) nb.metadata = metadata return nb ================================================ FILE: src/jupytext/jupytext.py ================================================ """Read and write Jupyter notebooks as text files""" import logging import os import sys import warnings from copy import copy, deepcopy import nbformat from nbformat.v4.nbbase import NotebookNode, new_code_cell, new_notebook from nbformat.v4.rwbase import NotebookReader, NotebookWriter from .cell_metadata import _IGNORE_CELL_METADATA from .config import get_formats_from_notebook_and_config, load_jupytext_config from .formats import ( _VALID_FORMAT_OPTIONS, divine_format, format_name_for_ext, get_format_implementation, guess_format, long_form_one_format, read_format_from_metadata, rearrange_jupytext_metadata, update_jupytext_formats_metadata, ) from .header import ( _JUPYTER_METADATA_NAMESPACE, encoding_and_executable, header_to_metadata_and_cell, insert_jupytext_info_and_filter_metadata, insert_or_test_version_number, metadata_and_cell_to_header, metadata_and_cell_to_metadata, metadata_to_metadata_and_cell, ) from .languages import ( _SCRIPT_EXTENSIONS, default_language_from_metadata_and_ext, set_main_and_cell_language, ) from .metadata_filter import filter_metadata, update_metadata_filters from .myst import MYST_FORMAT_NAME, myst_extensions, myst_to_notebook, notebook_to_myst from .pandoc import md_to_notebook, notebook_to_md from .pep8 import pep8_lines_between_cells from .quarto import notebook_to_qmd, qmd_to_notebook from .marimo import notebook_to_marimo_py, marimo_py_to_notebook from .version import __version__ class NotSupportedNBFormatVersion(NotImplementedError): """An error issued when the current notebook format is not supported by this version of Jupytext""" class TextNotebookConverter(NotebookReader, NotebookWriter): """A class that can read or write a Jupyter notebook as text""" def __init__(self, fmt, config): self.fmt = copy(long_form_one_format(fmt)) self.config = config self.ext = self.fmt["extension"] self.implementation = get_format_implementation(self.ext, self.fmt.get("format_name")) def update_fmt_with_notebook_options(self, metadata, read=False): """Update format options with the values in the notebook metadata, and record those options in the notebook metadata""" # The settings in the Jupytext configuration file have precedence over the metadata in the notebook # when the notebook is saved. This is because the metadata in the notebook might not be visible # in the text representation when e.g. notebook_metadata_filter="-all", which makes them hard to edit. if not read and self.config is not None: self.config.set_default_format_options(self.fmt, read) # Use format options from the notebook if not already set by the config for opt in _VALID_FORMAT_OPTIONS: if opt in metadata.get("jupytext", {}): self.fmt.setdefault(opt, metadata["jupytext"][opt]) # When we read the notebook we use the values of the config as defaults, as again the text representation # of the notebook might not store the format options when notebook_metadata_filter="-all" if read and self.config is not None: self.config.set_default_format_options(self.fmt, read=read) # We save the format options in the notebook metadata for opt in _VALID_FORMAT_OPTIONS: if opt in self.fmt: metadata.setdefault("jupytext", {})[opt] = self.fmt[opt] # Is this format the same as that documented in the YAML header? If so, we want to know the format version file_fmt = metadata.get("jupytext", {}).get("text_representation", {}) if self.fmt.get("extension") == file_fmt.get("extension") and self.fmt.get("format_name") == file_fmt.get( "format_name" ): self.fmt.update(file_fmt) # rST to md conversion should happen only once if metadata.get("jupytext", {}).get("rst2md") is True: metadata["jupytext"]["rst2md"] = False def reads(self, s, **_): """Read a notebook represented as text""" if self.fmt.get("format_name") == "pandoc": return md_to_notebook(s) if self.fmt.get("format_name") == "quarto": return qmd_to_notebook(s) if self.fmt.get("format_name") == "marimo": return marimo_py_to_notebook(s) if self.fmt.get("format_name") == MYST_FORMAT_NAME: nb = myst_to_notebook(s) return self.split_frontmatter(nb) lines = s.splitlines() cells = [] metadata, jupyter_md, header_cell, pos = header_to_metadata_and_cell( lines, self.implementation.header_prefix, self.implementation.header_suffix, self.implementation.extension, self.fmt.get( "root_level_metadata_as_raw_cell", (self.config.root_level_metadata_as_raw_cell if self.config is not None else True), ), ) default_language = default_language_from_metadata_and_ext(metadata, self.implementation.extension) self.update_fmt_with_notebook_options(metadata, read=True) if header_cell: cells.append(header_cell) lines = lines[pos:] if self.implementation.format_name and self.implementation.format_name.startswith("sphinx"): cells.append(new_code_cell(source="%matplotlib inline")) cell_metadata_json = False while lines: reader = self.implementation.cell_reader_class(self.fmt, default_language) cell, pos = reader.read(lines) cells.append(cell) cell_metadata_json = cell_metadata_json or reader.cell_metadata_json if pos <= 0: raise Exception("Blocked at lines " + "\n".join(lines[:6])) # pragma: no cover lines = lines[pos:] custom_cell_magics = self.fmt.get("custom_cell_magics", "").split(",") set_main_and_cell_language(metadata, cells, self.implementation.extension, custom_cell_magics) cell_metadata = set() for cell in cells: cell_metadata.update(cell.metadata.keys()) update_metadata_filters(metadata, jupyter_md, cell_metadata) if cell_metadata_json: metadata.setdefault("jupytext", {}).setdefault("cell_metadata_json", True) if self.implementation.format_name and self.implementation.format_name.startswith("sphinx"): filtered_cells = [] for i, cell in enumerate(cells): if ( cell.source == "" and i > 0 and i + 1 < len(cells) and cells[i - 1].cell_type != "markdown" and cells[i + 1].cell_type != "markdown" ): continue filtered_cells.append(cell) cells = filtered_cells return new_notebook(cells=cells, metadata=metadata) def filter_notebook(self, nb, metadata, preserve_cell_ids=True): self.update_fmt_with_notebook_options(nb.metadata) unsupported_keys = set() metadata = insert_jupytext_info_and_filter_metadata( metadata, self.fmt, self.implementation, unsupported_keys=unsupported_keys ) # We sort the notebook metadata for consistency with v1.16 metadata = dict(sorted(metadata.items())) cells = [] for cell in nb.cells: cell_kwargs = dict(cell) cell_kwargs["metadata"] = filter_metadata( cell.metadata, self.fmt.get("cell_metadata_filter"), _IGNORE_CELL_METADATA, unsupported_keys=unsupported_keys, ) if not preserve_cell_ids: cell_kwargs.pop("id", None) elif hasattr(cell, "id"): cell_kwargs["id"] = cell.id if cell.cell_type == "code": # Drop outputs and execution count cell_kwargs["outputs"] = [] cell_kwargs["execution_count"] = None cells.append(NotebookNode(**cell_kwargs)) _warn_on_unsupported_keys(unsupported_keys) return NotebookNode( nbformat=nb.nbformat, nbformat_minor=nb.nbformat_minor, metadata=metadata, cells=cells, ) def writes(self, nb, metadata=None, **kwargs): """Return the text representation of the notebook""" if self.fmt.get("format_name") == "pandoc": return notebook_to_md(self.filter_notebook(nb, metadata)) if self.fmt.get("format_name") == "quarto" or self.ext == ".qmd": return notebook_to_qmd(self.filter_notebook(nb, metadata)) if self.fmt.get("format_name") == "marimo": return notebook_to_marimo_py(self.filter_notebook(nb, metadata)) if self.fmt.get("format_name") == MYST_FORMAT_NAME or self.ext in myst_extensions(no_md=True): default_lexer_from_language_info = metadata.get("language_info", {}).get("pygments_lexer", None) default_lexer_from_jupytext_metadata = metadata.get("jupytext", {}).pop("default_lexer", None) default_lexer = default_lexer_from_language_info or default_lexer_from_jupytext_metadata nb = self.filter_notebook(nb, metadata) nb = self.merge_frontmatter(nb) return notebook_to_myst(nb, default_lexer=default_lexer) # Copy the notebook, in order to be sure we do not modify the original notebook nb = NotebookNode( nbformat=nb.nbformat, nbformat_minor=nb.nbformat_minor, metadata=deepcopy(metadata or nb.metadata), cells=nb.cells, ) metadata = nb.metadata default_language = default_language_from_metadata_and_ext(metadata, self.implementation.extension, True) or "python" self.update_fmt_with_notebook_options(nb.metadata) if "use_runtools" not in self.fmt: for cell in nb.cells: if cell.metadata.get("hide_input", False) or cell.metadata.get("hide_output", False): self.fmt["use_runtools"] = True break header = encoding_and_executable(nb, metadata, self.ext) unsupported_keys = set() header_content, header_lines_to_next_cell = metadata_and_cell_to_header( nb, metadata, self.implementation, self.fmt, unsupported_keys=unsupported_keys, ) header.extend(header_content) cell_exporters = [] looking_for_first_markdown_cell = self.implementation.format_name and self.implementation.format_name.startswith( "sphinx" ) split_at_heading = self.fmt.get("split_at_heading", False) for cell in nb.cells: if looking_for_first_markdown_cell and cell.cell_type == "markdown": cell.metadata.setdefault("cell_marker", '"""') looking_for_first_markdown_cell = False cell_exporters.append( self.implementation.cell_exporter_class(cell, default_language, self.fmt, unsupported_keys=unsupported_keys) ) _warn_on_unsupported_keys(unsupported_keys) texts = [cell.cell_to_text() for cell in cell_exporters] lines = [] # concatenate cells in reverse order to determine how many blank lines (pep8) for i, cell in reversed(list(enumerate(cell_exporters))): text = cell.remove_eoc_marker(texts[i], lines) if ( i == 0 and self.implementation.format_name and self.implementation.format_name.startswith("sphinx") and (text in [["%matplotlib inline"], ["# %matplotlib inline"]]) ): continue lines_to_next_cell = cell.lines_to_next_cell if lines_to_next_cell is None: lines_to_next_cell = pep8_lines_between_cells(text, lines, self.implementation.extension) text.extend([""] * lines_to_next_cell) # two blank lines between markdown cells in Rmd when those do not have explicit region markers if self.ext in [".md", ".markdown", ".Rmd"] and not cell.is_code(): if ( i + 1 < len(cell_exporters) and not cell_exporters[i + 1].is_code() and not texts[i][0].startswith(" 1\u001b[1;33m \u001b[0mundefined_variable\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m", "\u001b[1;31mNameError\u001b[0m: name 'undefined_variable' is not defined" ] } ], "source": [ "undefined_variable" ] } ], "metadata": { "kernelspec": { "display_name": "Python 3", "language": "python", "name": "python3" }, "language_info": { "codemirror_mode": { "name": "ipython", "version": 3 }, "file_extension": ".py", "mimetype": "text/x-python", "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", "version": "3.7.4" } }, "nbformat": 4, "nbformat_minor": 2 } ================================================ FILE: tests/data/notebooks/inputs/ipynb_q/kalman_filter_and_visualization.ipynb ================================================ { "cells": [ { "cell_type": "code", "execution_count": 32, "metadata": {}, "outputs": [], "source": [ "plt: .p.import`matplotlib.pyplot" ] }, { "cell_type": "code", "execution_count": 33, "metadata": {}, "outputs": [], "source": [ "filter: {\n", " t: ([] x: `float $ x; xh: `float $ x; p: (count x) # R: var x);\n", " (first t), iterate[R; R]\\[first t; 1 _ t] \n", " }\n", "\n", "iterate: {[Q; R; x; y]\n", " x[`p]+: Q;\n", " k: x[`p] % R + x[`p];\n", " `x`xh`p ! (y[`x]; x[`xh] + k * y[`x] - x[`xh]; (1 - k) * x[`p])\n", " }" ] }, { "cell_type": "code", "execution_count": 36, "metadata": {}, "outputs": [], "source": [ "price: 100 + sums 0.5 - (n:50)?1." ] }, { "cell_type": "code", "execution_count": 37, "metadata": {}, "outputs": [], "source": [ "output:filter price" ] }, { "cell_type": "code", "execution_count": 38, "metadata": {}, "outputs": [ { "data": { "image/png": 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", "text/plain": [ "
" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "plt[`:plot][til n; output`x; `label pykw \"price\"];\n", "plt[`:plot][til n; output`xh;`label pykw \"forecast\"];\n", "plt[`:legend][];\n", "plt[`:show][];" ] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": [] } ], "metadata": { "kernelspec": { "display_name": "Q 3.5", "language": "q", "name": "qpk" }, "language_info": { "file_extension": ".q", "mimetype": "text/x-q", "name": "q", "version": "3.6.0" }, "toc": { "base_numbering": 1, "nav_menu": {}, "number_sections": true, "sideBar": true, "skip_h1_title": false, "title_cell": "Table of Contents", "title_sidebar": "Contents", "toc_cell": false, "toc_position": {}, "toc_section_display": true, "toc_window_display": false } }, "nbformat": 4, "nbformat_minor": 2 } ================================================ FILE: tests/data/notebooks/inputs/ipynb_robot/simple_robot_notebook.ipynb ================================================ { "cells": [ { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": [ "*** Settings ***\n", "\n", "Library Collections" ] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": [ "*** Keywords ***\n", "\n", "Head\n", " [Arguments] ${list}\n", " ${value}= Get from list ${list} 0\n", " [Return] ${value}" ] }, { "cell_type": "code", "execution_count": null, "metadata": { "lines_to_next_cell": 0 }, "outputs": [], "source": [ "*** Tasks ***\n", "\n", "Get head\n", " ${array}= Create list 1 2 3 4 5\n", " ${head}= Head ${array}\n", " Should be equal ${head} 1" ] } ], "metadata": { "kernelspec": { "display_name": "Robot Framework", "language": "robotframework", "name": "robotkernel" }, "language_info": { "codemirror_mode": "robotframework", "file_extension": ".robot", "mimetype": "text/plain", "name": "robotframework", "pygments_lexer": "robotframework" }, "pycharm": { "stem_cell": { "cell_type": "raw", "metadata": { "collapsed": false }, "source": [] } } }, "nbformat": 4, "nbformat_minor": 2 } ================================================ FILE: tests/data/notebooks/inputs/ipynb_rust/evcxr_jupyter_tour.ipynb ================================================ { "cells": [ { "cell_type": "markdown", "metadata": {}, "source": [ "# Tour of the EvCxR Jupyter Kernel\n", "For those not already familiar with Jupyter notebook, it lets you write code into \"cells\" like the box below. Cells can alternatively contain markdown, like this text here. Each code cell is compiled and executed separately, but variables, defined functions etc persist between cells.\n", "\n", "## Printing to outputs and evaluating expressions\n", "Lets print something to stdout and stderr then return a final expression to see how that's presented. Note that stdout and stderr are separate streams, so may not appear in the same order is their respective print statements." ] }, { "cell_type": "code", "execution_count": 2, "metadata": {}, "outputs": [ { "name": "stderr", "output_type": "stream", "text": [ "Hello error\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ "Hello world\n" ] }, { "data": { "text/plain": [ "\"Hello world\"" ] }, "execution_count": 2, "metadata": {}, "output_type": "execute_result" } ], "source": [ "println!(\"Hello world\");\n", "eprintln!(\"Hello error\");\n", "format!(\"Hello {}\", \"world\")" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "## Assigning and making use of variables\n", "We define a variable `message`, then in the subsequent cell, modify the string and finally print it out. We could also do all this in the one cell if we wanted." ] }, { "cell_type": "code", "execution_count": 3, "metadata": {}, "outputs": [], "source": [ "let mut message = \"Hello \".to_owned();" ] }, { "cell_type": "code", "execution_count": 4, "metadata": {}, "outputs": [], "source": [ "message.push_str(\"world!\");" ] }, { "cell_type": "code", "execution_count": 5, "metadata": {}, "outputs": [ { "data": { "text/plain": [ "\"Hello world!\"" ] }, "execution_count": 5, "metadata": {}, "output_type": "execute_result" } ], "source": [ "message" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "## Defining and redefining functions\n", "Next we'll define a function" ] }, { "cell_type": "code", "execution_count": 6, "metadata": {}, "outputs": [], "source": [ "pub fn fib(x: i32) -> i32 {\n", " if x <= 2 {0} else {fib(x - 2) + fib(x - 1)}\n", "}" ] }, { "cell_type": "code", "execution_count": 7, "metadata": {}, "outputs": [ { "data": { "text/plain": [ "[0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0]" ] }, "execution_count": 7, "metadata": {}, "output_type": "execute_result" } ], "source": [ "(1..13).map(fib).collect::>()" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Hmm, that doesn't look right. Lets redefine the function. In practice, we'd go back and edit the function above and reevaluate it, but here, lets redefine it in a separate cell." ] }, { "cell_type": "code", "execution_count": 8, "metadata": {}, "outputs": [], "source": [ "pub fn fib(x: i32) -> i32 {\n", " if x <= 2 {2} else {fib(x - 2) + fib(x - 1)}\n", "}" ] }, { "cell_type": "code", "execution_count": 9, "metadata": {}, "outputs": [ { "data": { "text/plain": [ "[2, 2, 4, 6, 10, 16, 26, 42, 68, 110, 178, 288]" ] }, "execution_count": 9, "metadata": {}, "output_type": "execute_result" } ], "source": [ "let values = (1..13).map(fib).collect::>();\n", "values" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "## Spawning a separate thread and communicating with it\n", "We can spawn a thread to do stuff in the background, then continue executing code in other cells." ] }, { "cell_type": "code", "execution_count": 10, "metadata": {}, "outputs": [], "source": [ "use std::sync::{Mutex, Arc};\n", "let counter = Arc::new(Mutex::new(0i32));\n", "std::thread::spawn({\n", " let counter = Arc::clone(&counter);\n", " move || {\n", " for i in 1..300 {\n", " *counter.lock().unwrap() += 1;\n", " std::thread::sleep(std::time::Duration::from_millis(100));\n", " }\n", "}});" ] }, { "cell_type": "code", "execution_count": 11, "metadata": {}, "outputs": [ { "data": { "text/plain": [ "17" ] }, "execution_count": 11, "metadata": {}, "output_type": "execute_result" } ], "source": [ "*counter.lock().unwrap()" ] }, { "cell_type": "code", "execution_count": 12, "metadata": {}, "outputs": [ { "data": { "text/plain": [ "29" ] }, "execution_count": 12, "metadata": {}, "output_type": "execute_result" } ], "source": [ "*counter.lock().unwrap()" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "## Loading external crates\n", "We can load external crates. This one takes a while to compile, but once it's compiled, subsequent cells shouldn't need to recompile it, so it should be much quicker." ] }, { "cell_type": "code", "execution_count": 14, "metadata": {}, "outputs": [ { "data": { "text/plain": [ "\"AQIDBA==\"" ] }, "execution_count": 14, "metadata": {}, "output_type": "execute_result" } ], "source": [ ":dep base64 = \"0.10.1\"\n", "base64::encode(&vec![1, 2, 3, 4])" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "## Customizing how types are displayed\n", "We can also customize how our types are displayed, including presenting them as HTML. Here's an example where we define a custom display function for a type `Matrix`." ] }, { "cell_type": "code", "execution_count": 2, "metadata": {}, "outputs": [], "source": [ "use std::fmt::Debug;\n", "pub struct Matrix {pub values: Vec, pub row_size: usize}\n", "impl Matrix {\n", " pub fn evcxr_display(&self) {\n", " let mut html = String::new();\n", " html.push_str(\"\");\n", " for r in 0..(self.values.len() / self.row_size) {\n", " html.push_str(\"\");\n", " for c in 0..self.row_size {\n", " html.push_str(\"\");\n", " }\n", " html.push_str(\"\"); \n", " }\n", " html.push_str(\"
\");\n", " html.push_str(&format!(\"{:?}\", self.values[r * self.row_size + c]));\n", " html.push_str(\"
\");\n", " println!(\"EVCXR_BEGIN_CONTENT text/html\\n{}\\nEVCXR_END_CONTENT\", html);\n", " }\n", "}" ] }, { "cell_type": "code", "execution_count": 3, "metadata": {}, "outputs": [ { "data": { "text/html": [ "
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" ] }, "execution_count": 3, "metadata": {}, "output_type": "execute_result" } ], "source": [ "let m = Matrix {values: vec![1,2,3,4,5,6,7,8,9], row_size: 3};\n", "m" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "We can also return images, we just need to base64 encode them. First, we set up code for displaying RGB and grayscale images." ] }, { "cell_type": "code", "execution_count": 4, "metadata": {}, "outputs": [], "source": [ "extern crate image;\n", "extern crate base64;\n", "pub trait EvcxrResult {fn evcxr_display(&self);}\n", "impl EvcxrResult for image::RgbImage {\n", " fn evcxr_display(&self) {\n", " let mut buffer = Vec::new();\n", " image::png::PNGEncoder::new(&mut buffer).encode(&**self, self.width(), self.height(),\n", " image::ColorType::RGB(8)).unwrap();\n", " let img = base64::encode(&buffer);\n", " println!(\"EVCXR_BEGIN_CONTENT image/png\\n{}\\nEVCXR_END_CONTENT\", img); \n", " }\n", "}\n", "impl EvcxrResult for image::GrayImage {\n", " fn evcxr_display(&self) {\n", " let mut buffer = Vec::new();\n", " image::png::PNGEncoder::new(&mut buffer).encode(&**self, self.width(), self.height(),\n", " image::ColorType::Gray(8)).unwrap();\n", " let img = base64::encode(&buffer);\n", " println!(\"EVCXR_BEGIN_CONTENT image/png\\n{}\\nEVCXR_END_CONTENT\", img); \n", " }\n", "}" ] }, { "cell_type": "code", "execution_count": 5, "metadata": {}, "outputs": [ { "data": { "image/png": "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" }, "execution_count": 5, "metadata": {}, "output_type": "execute_result" } ], "source": [ "image::ImageBuffer::from_fn(256, 256, |x, y| {\n", " if (x as i32 - y as i32).abs() < 3 {\n", " image::Rgb([0, 0, 255])\n", " } else {\n", " image::Rgb([0, 0, 0])\n", " }\n", "})" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "## Display of compilation errors\n", "Here's how compilation errors are presented. Here we forgot an & and passed a String instead of an &str." ] }, { "cell_type": "code", "execution_count": 17, "metadata": {}, "outputs": [ { "ename": "Error", "evalue": "mismatched types", "output_type": "error", "traceback": [ "s.push_str(format!(\"foo {}\", 42));", "\u001b[91m ^^^^^^^^^^^^^^^^^^^^^\u001b[0m \u001b[94mexpected &str, found struct `std::string::String`\u001b[0m", "mismatched types" ] } ], "source": [ "let mut s = String::new();\n", "s.push_str(format!(\"foo {}\", 42));" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "## Seeing what variables have been defined\n", "We can print a table of defined variables and their types with the :vars command." ] }, { "cell_type": "code", "execution_count": 19, "metadata": {}, "outputs": [ { "data": { "text/html": [ "
VariableType
counterstd::sync::Arc<std::sync::Mutex<i32>>
messageString
muser_code_13::Matrix<i32>
valuesstd::vec::Vec<i32>
" ], "text/plain": [ "counter: std::sync::Arc>\n", "message: String\n", "m: user_code_13::Matrix\n", "values: std::vec::Vec\n" ] }, "execution_count": 19, "metadata": {}, "output_type": "execute_result" } ], "source": [ ":vars" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Other built-in commands can be found via :help" ] }, { "cell_type": "code", "execution_count": 3, "metadata": {}, "outputs": [ { "data": { "text/plain": [ ":vars List bound variables and their types\n", ":opt [level] Toggle/set optimization level\n", ":explain Print explanation of last error\n", ":clear Clear all state, keeping compilation cache\n", ":dep Add dependency. e.g. :dep regex = \"1.0\"\n", ":version Print Evcxr version\n", ":preserve_vars_on_panic [0|1] Try to keep vars on panic\n", "\n", "Mostly for development / debugging purposes:\n", ":last_compile_dir Print the directory in which we last compiled\n", ":timing Toggle printing of how long evaluations take\n", ":last_error_json Print the last compilation error as JSON (for debugging)\n", ":time_passes Toggle printing of rustc pass times (requires nightly)\n", ":internal_debug Toggle various internal debugging code\n" ] }, "execution_count": 3, "metadata": {}, "output_type": "execute_result" } ], "source": [ ":help" ] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": [] } ], "metadata": { "kernelspec": { "display_name": "Rust", "language": "rust", "name": "rust" }, "language_info": { "codemirror_mode": "rust", "file_extension": ".rs", "mimetype": "text/rust", "name": "Rust", "pygment_lexer": "rust", "version": "" } }, "nbformat": 4, "nbformat_minor": 2 } ================================================ FILE: tests/data/notebooks/inputs/ipynb_sage/sage_print_hello.ipynb ================================================ { "cells": [ { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": [ "print(\"Hello world\")" ] } ], "metadata": { "kernelspec": { "display_name": "SageMath 9.2", "language": "sage", "name": "sagemath" }, "language_info": { "codemirror_mode": { "name": "ipython", "version": 3 }, "file_extension": ".py", "mimetype": "text/x-python", "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", "version": "3.9.1" } }, "nbformat": 4, "nbformat_minor": 4 } ================================================ FILE: tests/data/notebooks/inputs/ipynb_sas/sas.ipynb ================================================ { "cells": [ { "cell_type": "markdown", "id": "14a71cf0-4339-4ae6-982d-7dda15f3810e", "metadata": {}, "source": [ "# SAS Notebooks with jupytext" ] }, { "cell_type": "code", "execution_count": null, "id": "47346888-e79f-4205-82fd-3a5fdfde9b4d", "metadata": {}, "outputs": [], "source": [ "proc sql;\n", " select *\n", " from sashelp.cars (obs=10)\n", " ;\n", "quit; " ] }, { "cell_type": "code", "execution_count": null, "id": "c96b0faf-26fe-4245-a1d9-78dee30b19c3", "metadata": {}, "outputs": [], "source": [ "%let name = \"Jupytext\";" ] }, { "cell_type": "code", "execution_count": null, "id": "56cafffb-e397-4c3b-97ab-c6970149b6bc", "metadata": {}, "outputs": [], "source": [ "%put &name;" ] }, { "cell_type": "code", "execution_count": null, "id": "bbc273c9-8690-450d-bd9b-2d075d512437", "metadata": {}, "outputs": [], "source": [ "/* Note when defining macros \"%macro\" cannot be the first line of text in the cell */\n", "%macro test;\n", " data temp;\n", " set sashelp.cars;\n", " name = \"testx\";\n", " run; \n", " proc print data = temp (obs=10);\n", " run; \n", "%mend test;\n", "\n", "%test" ] } ], "metadata": { "kernelspec": { "display_name": "SAS", "language": "sas", "name": "sas" }, "language_info": { "codemirror_mode": "sas", "file_extension": ".sas", "mimetype": "text/x-sas", "name": "sas" } }, "nbformat": 4, "nbformat_minor": 5 } ================================================ FILE: tests/data/notebooks/inputs/ipynb_scala/simple_scala_notebook.ipynb ================================================ { "cells": [ { "cell_type": "code", "execution_count": 5, "metadata": {}, "outputs": [ { "data": { "text/plain": [ "defined object SampleObject\n", "result = 3\n" ] }, "metadata": {}, "output_type": "display_data" }, { "data": { "text/plain": [ "3" ] }, "execution_count": 5, "metadata": {}, "output_type": "execute_result" } ], "source": [ "// This is just a simple scala notebook\n", "\n", "object SampleObject {\n", " def calculation(x: Int, y: Int): Int = x + y\n", "}\n", "\n", "val result = SampleObject.calculation(1, 2)" ] }, { "cell_type": "code", "execution_count": 6, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "30\n" ] } ], "source": [ "println(result * 10)" ] } ], "metadata": { "kernelspec": { "display_name": "Apache Toree - Scala", "language": "scala", "name": "apache_toree_scala" }, "language_info": { "codemirror_mode": "text/x-scala", "file_extension": ".scala", "mimetype": "text/x-scala", "name": "scala", "pygments_lexer": "scala", "version": "2.11.12" } }, "nbformat": 4, "nbformat_minor": 2 } ================================================ FILE: tests/data/notebooks/inputs/ipynb_scheme/Reference Guide for Calysto Scheme.ipynb ================================================ { "cells": [ { "cell_type": "markdown", "metadata": {}, "source": [ "\n", "

Reference Guide for Calysto Scheme

\n", "\n", "[Calysto Scheme](https://github.com/Calysto/calysto_scheme) is a real Scheme programming language, with full support for continuations, including call/cc. It can also use all Python libraries. Also has some extensions that make it more useful (stepper-debugger, choose/fail, stack traces), or make it better integrated with Python.\n", "\n", "In Jupyter notebooks, because Calysto Scheme uses [MetaKernel](https://github.com/Calysto/metakernel/blob/master/README.rst), it has a fully-supported set of \"magics\"---meta-commands for additional functionality. This includes running Scheme in parallel. See all of the [MetaKernel Magics](https://github.com/Calysto/metakernel/blob/master/metakernel/magics/README.md).\n", "\n", "Calysto Scheme is written in Scheme, and then translated into Python (and other backends). The entire functionality lies in a single Python file: https://github.com/Calysto/calysto_scheme/blob/master/calysto_scheme/scheme.py However, you can easily install it (see below).\n", "\n", "Please see [Calysto Scheme Language](Calysto%20Scheme%20Language.ipynb) for more details on the Calysto Scheme language.\n", "\n", "## Installation\n", "\n", "You can install Calysto Scheme with Python3:\n", "\n", "```\n", "pip3 install --upgrade calysto-scheme --user -U\n", "python3 -m calysto_kernel install --user\n", "```\n", "\n", "or in the system kernel folder with:\n", "\n", "```\n", "sudo pip3 install --upgrade calysto-scheme -U\n", "sudo python3 -m calysto_kernel install\n", "```\n", "\n", "Change pip3/python3 to use a different pip or Python. The version of Python used will determine how Calysto Scheme is run.\n", "\n", "Use it in the console, qtconsole, or notebook with IPython 3:\n", "\n", "```\n", "ipython console --kernel calysto_scheme\n", "ipython qtconsole --kernel calysto_scheme\n", "ipython notebook --kernel calysto_scheme\n", "```\n", "\n", "In addition to all of the following items, Calysto Scheme also has access to all of Python's builtin functions, and all of Python's libraries. For example, you can use `(complex 3 2)` to create a complex number by calling Python's complex function.\n", "\n", "## Jupyter Enhancements\n", "\n", "When you run Calysto Scheme in Jupyter (console, notebook, qtconsole, etc.) you get:\n", "\n", "* TAB completions of Scheme functions and variable names\n", "* display of rich media\n", "* stepper/debugger\n", "* magics (% macros)\n", "* shell commands (! command)\n", "* LaTeX equations\n", "* LaTeX-style variables\n", "* Python integration" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "### LaTeX-style variables\n", "\n", "Calysto Scheme allows you to use LaTeX-style variables in code. For example, if you type:\n", "\n", "```\n", "\\beta\n", "```\n", "\n", "with the cursor right after the 'a' in beta, and then press TAB, it will turn into the unicode character:\n", "\n", "```\n", "β\n", "```\n", "\n", "There are nearly 1300 different symbols defined (thanks to the Julia language) and documented here:\n", "\n", "http://docs.julialang.org/en/release-0.4/manual/unicode-input/#man-unicode-input\n", "\n", "Calysto Scheme may not implement all of those. Some useful and suggestive ones:\n", "\n", "* \\pi - π\n", "* \\Pi - Π\n", "* \\Sigma - Σ\n", "* \\_i - subscript i, such as vectorᵢ" ] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": [ "(define α 67)" ] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": [ "α" ] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": [ "(define i 2)\n", "(define vectorᵢ (vector-ref (vector 0 6 3 2) i))\n", "vectorᵢ" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "### Rich media" ] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": [ "(import \"calysto.display\")" ] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": [ "(calysto.display.HTML \"This is bold, italics, underlined.\")" ] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": [ "(import \"calysto.graphics\")" ] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": [ "(define canvas (calysto.graphics.Canvas))" ] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": [ "(define ball (calysto.graphics.Circle '(150 150) 100))" ] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": [ "(ball.draw canvas)" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "### Shell commands" ] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": [ "! ls /tmp" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "### Stepper/Debugger\n", "\n", "Here is what the debugger looks like:\n", "\n", "\n", "\n", "It has breakpoints (click in left margin). You must press Stop to exit the debugger." ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "```scheme\n", "%%debug\n", "\n", "(begin\n", " (define x 1)\n", " (set! x 2)\n", ")\n", "```" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "### Python Integration\n", "\n", "You can import and use any Python library in Calysto Scheme.\n", "\n", "In addition, if you wish, you can execute expressions and statements in a Python environment:" ] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": [ "(python-eval \"1 + 2\")" ] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": [ "(python-exec \n", "\"\n", "def mypyfunc(a, b):\n", " return a * b\n", "\")" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "This is a shared environment with Scheme:" ] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": [ "(mypyfunc 4 5)" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "You can use `func` to turn a Scheme procedure into a Python function, and `define!` to put it into the shared environment with Python:" ] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": [ "(define! mypyfunc2 (func (lambda (n) n)))" ] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": [ "(python-eval \"mypyfunc2(34)\")" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "# Differences Between Languages\n", "\n", "## Major differences between Scheme and Python\n", "\n", "1. In Scheme, double quotes are used for strings and may contain newlines\n", "1. In Scheme, a single quote is short for (quote ...) and means \"literal\"\n", "1. In Scheme, everything is an expression and has a return value\n", "1. Python does not support macros (e.g., extending syntax)\n", "1. In Python, \"if X\" is false if X is None, False, [], (,) or 0. In Scheme, \"if X\" is only false if X is #f or 0\n", "1. Calysto Scheme uses continuations, not the call stack. However, for debugging there is a pseudo-stack when an error is raised. You can turn that off with (use-stack-trace #f)\n", "1. Scheme procedures are not Python functions, but there are means to use one as the other.\n", "\n", "## Major Differences Between Calysto Scheme and other Schemes\n", "\n", "1. define-syntax works slightly differently\n", "1. In Calysto Scheme, #(...) is short for '#(...)\n", "1. Calysto Scheme is missing many standard functions (see list at bottom)\n", "1. Calysto Scheme has a built-in amb operator called `choose`\n", "1. For debugging there is a pseudo-stack when errors are raised in Calysto Scheme. You can turn that off with (use-stack-trace #f)\n", "\n", "### Stack Trace\n", "\n", "Calysto Scheme acts as if it has a call stack, for easier debugging. For example:" ] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": [ "(define fact\n", " (lambda (n)\n", " (if (= n 1)\n", " q\n", " (* n (fact (- n 1))))))" ] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": [ "(fact 5)" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "To turn off the stack trace on error:\n", "\n", "```scheme\n", "(use-stack-trace #f)\n", "```\n", "That will allow infinite recursive loops without keeping track of the \"stack\"." ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "# Calysto Scheme Variables\n", "\n", "## SCHEMEPATH\n", "SCHEMEPATH is a list of search directories used with (load NAME). This is a reference, so you should append to it rather than attempting to redefine it." ] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": [ "SCHEMEPATH" ] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": [ "(set-cdr! (cdr SCHEMEPATH) (list \"/var/modules\"))" ] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": [ "SCHEMEPATH" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "## Getting Started\n", "\n", "Note that you can use the word `lambda` or \\lambda and then press [TAB]" ] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": [ "(define factorial\n", " (λ (n)\n", " (cond\n", " ((zero? n) 1)\n", " (else (* n (factorial (- n 1)))))))" ] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": [ "(factorial 5)" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "## define-syntax\n", "(define-syntax NAME RULES): a method for creating macros" ] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": [ "(define-syntax time \n", " [(time ?exp) (let ((start (current-time)))\n", " ?exp\n", " (- (current-time) start))])" ] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": [ "(time (car '(1 2 3 4)))" ] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": [ ";;---------------------------------------------------------------------\n", ";; collect is like list comprehension in Python\n", "\n", "(define-syntax collect\n", " [(collect ?exp for ?var in ?list)\n", " (filter-map (lambda (?var) ?exp) (lambda (?var) #t) ?list)]\n", " [(collect ?exp for ?var in ?list if ?condition)\n", " (filter-map (lambda (?var) ?exp) (lambda (?var) ?condition) ?list)])\n", "\n", "(define filter-map\n", " (lambda (f pred? values)\n", " (if (null? values)\n", " '()\n", " (if (pred? (car values))\n", " (cons (f (car values)) (filter-map f pred? (cdr values)))\n", " (filter-map f pred? (cdr values))))))" ] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": [ "(collect (* n n) for n in (range 10))" ] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": [ "(collect (* n n) for n in (range 5 20 3))" ] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": [ "(collect (* n n) for n in (range 10) if (> n 5))" ] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": [ ";;---------------------------------------------------------------------\n", ";; for loops\n", "\n", "(define-syntax for\n", " [(for ?exp times do . ?bodies)\n", " (for-repeat ?exp (lambda () . ?bodies))]\n", " [(for ?var in ?exp do . ?bodies)\n", " (for-iterate1 ?exp (lambda (?var) . ?bodies))]\n", " [(for ?var at (?i) in ?exp do . ?bodies)\n", " (for-iterate2 0 ?exp (lambda (?var ?i) . ?bodies))]\n", " [(for ?var at (?i ?j . ?rest) in ?exp do . ?bodies)\n", " (for ?var at (?i) in ?exp do\n", " (for ?var at (?j . ?rest) in ?var do . ?bodies))])\n", "\n", "(define for-repeat\n", " (lambda (n f)\n", " (if (< n 1)\n", " 'done\n", " (begin\n", " (f)\n", " (for-repeat (- n 1) f)))))\n", "\n", "(define for-iterate1\n", " (lambda (values f)\n", " (if (null? values)\n", " 'done\n", " (begin\n", " (f (car values))\n", " (for-iterate1 (cdr values) f)))))\n", "\n", "(define for-iterate2\n", " (lambda (i values f)\n", " (if (null? values)\n", " 'done\n", " (begin\n", " (f (car values) i)\n", " (for-iterate2 (+ i 1) (cdr values) f)))))" ] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": [ "(define matrix2d\n", " '((10 20)\n", " (30 40)\n", " (50 60)\n", " (70 80)))\n", "\n", "(define matrix3d\n", " '(((10 20 30) (40 50 60))\n", " ((70 80 90) (100 110 120))\n", " ((130 140 150) (160 170 180))\n", " ((190 200 210) (220 230 240))))" ] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": [ "(begin \n", " (define hello 0)\n", " (for 5 times do (set! hello (+ hello 1)))\n", " hello\n", " )" ] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": [ "(for sym in '(a b c d) do (define x 1) (set! x sym) (print x))" ] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": [ "(for n in (range 10 20 2) do (print n))" ] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": [ "(for n at (i j) in matrix2d do (print (list n 'coords: i j)))" ] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": [ "(for n at (i j k) in matrix3d do (print (list n 'coords: i j k)))" ] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": [ "(define-syntax scons\n", " [(scons ?x ?y) (cons ?x (lambda () ?y))])\n", "\n", "(define scar car)\n", "\n", "(define scdr\n", " (lambda (s)\n", " (let ((result ((cdr s))))\n", " (set-cdr! s (lambda () result))\n", " result)))\n", "\n", "(define first\n", " (lambda (n s)\n", " (if (= n 0)\n", " '()\n", " (cons (scar s) (first (- n 1) (scdr s))))))\n", "\n", "(define nth\n", " (lambda (n s)\n", " (if (= n 0)\n", " (scar s)\n", " (nth (- n 1) (scdr s)))))\n", "\n", "(define smap\n", " (lambda (f s)\n", " (scons (f (scar s)) (smap f (scdr s)))))\n", "\n", "(define ones (scons 1 ones))\n", "\n", "(define nats (scons 0 (combine nats + ones)))\n", "\n", "(define combine\n", " (lambda (s1 op s2)\n", " (scons (op (scar s1) (scar s2)) (combine (scdr s1) op (scdr s2)))))\n", "\n", "(define fibs (scons 1 (scons 1 (combine fibs + (scdr fibs)))))\n", "\n", "(define facts (scons 1 (combine facts * (scdr nats))))\n", "\n", "(define ! (lambda (n) (nth n facts)))" ] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": [ "(! 5)" ] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": [ "(nth 10 facts)" ] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": [ "(nth 20 fibs)" ] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": [ "(first 30 fibs)" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "## for-each\n", "(for-each PROCEDURE LIST): apply PROCEDURE to each item in LIST; like `map` but don't return results" ] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": [ "(for-each (lambda (n) (print n)) '(3 4 5))" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "## format\n", "(format STRING ITEM ...): format the string with ITEMS as arguments" ] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": [ "(format \"This uses formatting ~a ~s ~%\" 'apple 'apple)" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "## func\n", "\n", "Turns a lambda into a Python function.\n", "\n", "(func (lambda ...))" ] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": [ "(func (lambda (n) n))" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "## There's more!\n", "\n", "Please see [Calysto Scheme Language](Calysto%20Scheme%20Language.ipynb) for more details on the Calysto Scheme language." ] } ], "metadata": { "kernelspec": { "display_name": "Calysto Scheme (Python)", "language": "scheme", "name": "calysto_scheme" }, "language_info": { "codemirror_mode": { "name": "scheme" }, "mimetype": "text/x-scheme", "name": "scheme", "pygments_lexer": "scheme" } }, "nbformat": 4, "nbformat_minor": 2 } ================================================ FILE: tests/data/notebooks/inputs/ipynb_sos/jupytext_replication.ipynb ================================================ { "cells": [ { "cell_type": "markdown", "metadata": { "Collapsed": "false", "kernel": "SoS" }, "source": [ "# Text SOS-kernel with Jupytext\n", "\n", "## What is SOS kernel\n", "\n", "SoS consists of a ployglot notebook that allows the use of multiple kernels in one Jupyter notebook, and a workflow system that is designed for daily computational research. Basically,\n", "\n", "- SoS Polyglot Notebook is a Jupyter Notebook with a SoS kernel.\n", "- SoS Notebook serves as a super kernel to all other Jupyter kernels and allows the use of multiple kernels in one Jupyter notebook.\n", "- SoS Workflow System is a Python based workflow system that is designed to be readable, shareable, and suitable for daily data analysis.\n", "- SoS Workflow System can be used from command line or use SoS Notebook as its IDE.\n", "\n", "![](https://vatlab.github.io/sos-docs/doc/media/SoS_Notebook_and_Workflow.png)\n", "\n", "### How to install SOS-kernel\n", "\n", "Please follow this [link](https://vatlab.github.io/sos-docs/running.html#Conda-installation) to setup SOS\n", "\n", "I run some issue with the latest version of R on my Mac, so I had to install an earlier version of R\n", "\n", "```\n", "conda install -c r r=3.5.1\n", "conda install sos-notebook jupyterlab-sos sos-papermill -c conda-forge\n", "```\n", "\n", "## Related issue with Jupytext\n", "\n", "Jupytext works fine with Python/R kernel but converts code cells into markdown cells when using the SOS kernel.\n", "\n", "cf the image below. It is a code cell. After saving the notebook and restart it, it converted the code cell into markdown\n", "\n", "\"Screenshot" ] }, { "cell_type": "markdown", "metadata": { "Collapsed": "false", "kernel": "SoS" }, "source": [ "## Step 1\n", "\n", "Please, choose SOS Kernel and then, in the cell code, choose SOS (or any other kernel available), the outcome is the same.\n", "\n", "![](https://drive.google.com/uc?export=view&id=1OtyxfwoRyVK23XHnmd9JR-crBgHBL5mt)" ] }, { "cell_type": "code", "execution_count": null, "metadata": { "Collapsed": "false", "kernel": "SoS" }, "outputs": [], "source": [ "import pandas as pd \n", "import numpy as np\n", "\n", "pd.DataFrame({\n", " 'x': np.random.random(10),\n", " 'y': np.random.random(10),\n", "})" ] }, { "cell_type": "markdown", "metadata": { "Collapsed": "false", "kernel": "python3" }, "source": [ "## Step 2\n", "\n", "Now, pair it with Jupytex\n", "\n", "![](https://drive.google.com/uc?export=view&id=1Wtx-YPAXY8HWHqzCcy4iIgHpzt_9emEn)" ] }, { "cell_type": "markdown", "metadata": { "Collapsed": "false", "kernel": "python3" }, "source": [ "### Step 3\n", "\n", "Save the notebook, restart and clear all, **save**, then Shut down kernel. Close the notebook and reopen" ] }, { "cell_type": "markdown", "metadata": { "Collapsed": "false", "kernel": "python3" }, "source": [ "### Step 4\n", "\n", "Reopen the notebook. Here is the outcome\n", "\n", "![](https://drive.google.com/uc?export=view&id=12C70unbSPv0gHCZaCICEUy7kO7wM93JH)\n", "\n" ] } ], "metadata": { "kernelspec": { "display_name": "SoS", "language": "sos", "name": "sos" }, "language_info": { "codemirror_mode": "sos", "file_extension": ".sos", "mimetype": "text/x-sos", "name": "sos", "nbconvert_exporter": "sos_notebook.converter.SoS_Exporter", "pygments_lexer": "sos" }, "sos": { "kernels": [ [ "python3", "python3", "python3", "", "" ] ], "version": "0.20.6" } }, "nbformat": 4, "nbformat_minor": 4 } ================================================ FILE: tests/data/notebooks/inputs/ipynb_stata/stata_notebook.ipynb ================================================ { "cells": [ { "cell_type": "code", "execution_count": 1, "id": "a4033377", "metadata": {}, "outputs": [], "source": [ "// This notebook uses the stata_kernel: https://github.com/kylebarron/stata_kernel" ] }, { "cell_type": "code", "execution_count": 2, "id": "5f4a41aa-92fb-4344-accf-fca4df13d0b1", "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "(1978 Automobile Data)\n" ] } ], "source": [ "use http://www.stata-press.com/data/r13/auto" ] }, { "cell_type": "code", "execution_count": 3, "id": "3f8bc0a3-2e04-4025-97b6-fe07b341d359", "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "\n", " Variable | Obs Mean Std. dev. Min Max\n", "-------------+---------------------------------------------------------\n", " make | 0\n", " price | 74 6165.257 2949.496 3291 15906\n", " mpg | 74 21.2973 5.785503 12 41\n", " rep78 | 69 3.405797 .9899323 1 5\n", " headroom | 74 2.993243 .8459948 1.5 5\n", "-------------+---------------------------------------------------------\n", " trunk | 74 13.75676 4.277404 5 23\n", " weight | 74 3019.459 777.1936 1760 4840\n", " length | 74 187.9324 22.26634 142 233\n", " turn | 74 39.64865 4.399354 31 51\n", "displacement | 74 197.2973 91.83722 79 425\n", "-------------+---------------------------------------------------------\n", " gear_ratio | 74 3.014865 .4562871 2.19 3.89\n", " foreign | 74 .2972973 .4601885 0 1\n" ] } ], "source": [ "summarize" ] }, { "cell_type": "code", "execution_count": 4, "id": "ce932414-a959-40e7-ab27-b59f9dc2a5af", "metadata": {}, "outputs": [ { "data": { "text/plain": [ "This front-end cannot display the desired image type." ] }, "metadata": { "image/svg+xml": { "height": 436, "width": 600 }, "text/html": { "height": 436, "width": 600 } }, "output_type": "display_data" }, { "name": "stdout", "output_type": "stream", "text": [ "\n", " format\n" ] }, { "data": { "text/plain": [ "This front-end cannot display the desired image type." ] }, "metadata": {}, "output_type": "display_data" }, { "name": "stdout", "output_type": "stream", "text": [ " format\n" ] } ], "source": [ "scatter weight length" ] } ], "metadata": { "kernelspec": { "display_name": "Stata", "language": "stata", "name": "stata" }, "language_info": { "codemirror_mode": "stata", "file_extension": ".do", "mimetype": "text/x-stata", "name": "stata", "version": "15.1" }, "widgets": { "application/vnd.jupyter.widget-state+json": { "state": {}, "version_major": 2, "version_minor": 0 } } }, "nbformat": 4, "nbformat_minor": 5 } ================================================ FILE: tests/data/notebooks/inputs/ipynb_tcl/tcl_test.ipynb ================================================ { "cells": [ { "cell_type": "markdown", "metadata": {}, "source": [ "# Assign Values" ] }, { "cell_type": "code", "execution_count": 2, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "a = 1\n" ] } ], "source": [ "set a 1\n", "puts \"a = $a\"" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "# Loop" ] }, { "cell_type": "code", "execution_count": 3, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "I inside first loop: 0\n", "I inside first loop: 1\n", "I inside first loop: 2\n", "I inside first loop: 3\n", "I inside first loop: 4\n", "I inside first loop: 5\n", "I inside first loop: 6\n", "I inside first loop: 7\n", "I inside first loop: 8\n", "I inside first loop: 9\n" ] } ], "source": [ "for {set i 0} {$i < 10} {incr i} {\n", " puts \"I inside first loop: $i\"\n", "}" ] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": [] } ], "metadata": { "kernelspec": { "display_name": "Tcl", "language": "tcl", "name": "tcljupyter" }, "language_info": { "file_extension": ".tcl", "mimetype": "txt/x-tcl", "name": "tcl", "version": "8.6.11" } }, "nbformat": 4, "nbformat_minor": 4 } ================================================ FILE: tests/data/notebooks/inputs/ipynb_ts/itypescript.ipynb ================================================ { "cells": [ { "cell_type": "code", "execution_count": 1, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "hi\n" ] }, { "data": { "text/plain": [ "11" ] }, "execution_count": 1, "metadata": {}, "output_type": "execute_result" } ], "source": [ "let x: number = 5;\n", "const y: number = 6;\n", "var z: string = \"hi\";\n", "console.log(z);\n", "x + y;" ] }, { "cell_type": "code", "execution_count": 2, "metadata": {}, "outputs": [ { "data": { "text/plain": [ "11" ] }, "execution_count": 2, "metadata": {}, "output_type": "execute_result" } ], "source": [ "function add(num1: number, num2: number): number {\n", " return num1 + num2\n", "}\n", "add(x, y);" ] }, { "cell_type": "code", "execution_count": 3, "metadata": {}, "outputs": [ { "data": { "text/plain": [ "11" ] }, "execution_count": 3, "metadata": {}, "output_type": "execute_result" } ], "source": [ "const arrowAdd = (num1: number, num2: number) => num1 + num2;\n", "arrowAdd(x, y);" ] }, { "cell_type": "code", "execution_count": 4, "metadata": {}, "outputs": [ { "data": { "text/plain": [ "\"Hello, I'm John\"" ] }, "execution_count": 4, "metadata": {}, "output_type": "execute_result" } ], "source": [ "class User {\n", " constructor(private name: string) {\n", " this.name = name;\n", " }\n", " sayHello(): string {\n", " return \"Hello, I'm \" + this.name;\n", " }\n", "}\n", "let John: User;\n", "John = new User(\"John\");\n", "John.sayHello();" ] } ], "metadata": { "kernelspec": { "display_name": "Typescript 3.5", "language": "typescript", "name": "typescript" }, "language_info": { "file_extension": ".ts", "mimetype": "application/x-typescript", "name": "typescript", "version": "3.5.1" } }, "nbformat": 4, "nbformat_minor": 2 } ================================================ FILE: tests/data/notebooks/inputs/ipynb_wolfram/wolfram.ipynb ================================================ { "cells": [ { "cell_type": "markdown", "id": "f48fe6fa", "metadata": {}, "source": [ "**Note:** The `language_info` `file_extension` in this notebook should be `.m`, but it was deliberately changed to `.wolfram` to avoid conflicts with Matlab which is using the same extension." ] }, { "cell_type": "markdown", "id": "19ffc137", "metadata": {}, "source": [ "We start with..." ] }, { "cell_type": "code", "execution_count": null, "id": "17c5b20c", "metadata": {}, "outputs": [], "source": [ "Print[\"Hello, World!\"];" ] }, { "cell_type": "markdown", "id": "2b9e8c46", "metadata": {}, "source": [ "Then we draw the first example plot from the [ListPlot](https://reference.wolfram.com/language/ref/ListPlot.html) reference:" ] }, { "cell_type": "code", "execution_count": 2, "id": "7c4dfdc2", "metadata": {}, "outputs": [ { "data": { "text/html": [ "
\"Output\"
" ], "text/plain": [ "-Graphics-" ] }, "execution_count": 2, "metadata": { "text/html": [], "text/plain": [] }, "output_type": "execute_result" } ], "source": [ "ListPlot[Prime[Range[25]]]" ] }, { "cell_type": "markdown", "id": "0e549b21", "metadata": {}, "source": [ "We also test the math outputs as in the [Simplify](https://reference.wolfram.com/language/ref/Simplify.html) example:" ] }, { "cell_type": "code", "execution_count": 3, "id": "5c2010aa", "metadata": {}, "outputs": [ { "data": { "text/html": [ "
\"Output\"
" ], "text/plain": [ " 1 -1 + 2 x 2\n", "--------- - -------------- + -------------------\n", "3 (1 + x) 2 2\n", " 6 (1 - x + x ) (-1 + 2 x)\n", " 3 (1 + -----------)\n", " 3" ] }, "execution_count": 3, "metadata": { "text/html": [], "text/plain": [] }, "output_type": "execute_result" } ], "source": [ "D[Integrate[1/(x^3 + 1), x], x]" ] } ], "metadata": { "kernelspec": { "display_name": "Wolfram Language 13.1", "language": "Wolfram Language", "name": "wolframlanguage13.1" }, "language_info": { "codemirror_mode": "mathematica", "file_extension": ".wolfram", "mimetype": "application/vnd.wolfram.m", "name": "Wolfram Language", "pygments_lexer": "mathematica", "version": "12.0" } }, "nbformat": 4, "nbformat_minor": 5 } ================================================ FILE: tests/data/notebooks/inputs/ipynb_xonsh/xonsh_example.ipynb ================================================ { "cells": [ { "cell_type": "code", "execution_count": 3, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "35196\n" ] } ], "source": [ "len($(curl -L https://xon.sh))" ] }, { "cell_type": "code", "execution_count": 4, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "xonsh_example.ipynb\n", "\n" ] } ], "source": [ "for filename in `.*`:\n", " print(filename)\n", " du -sh @(filename)" ] } ], "metadata": { "kernelspec": { "display_name": "Xonsh", "language": "xonsh", "name": "xonsh" }, "language_info": { "codemirror_mode": "shell", "file_extension": ".xsh", "mimetype": "text/x-sh", "name": "xonsh", "pygments_lexer": "xonsh", "version": "0.14.4" } }, "nbformat": 4, "nbformat_minor": 2 } ================================================ FILE: tests/data/notebooks/inputs/julia/julia_sample_script.jl ================================================ # -*- coding: utf-8 -*- # From https://juliabyexample.helpmanual.io/ # function to calculate the volume of a sphere function sphere_vol(r) # julia allows Unicode names (in UTF-8 encoding) # so either "pi" or the symbol π can be used return 4/3*pi*r^3 end # functions can also be defined more succinctly quadratic(a, sqr_term, b) = (-b + sqr_term) / 2a # calculates x for 0 = a*x^2+b*x+c, arguments types can be defined in function definitions function quadratic2(a::Float64, b::Float64, c::Float64) # unlike other languages 2a is equivalent to 2*a # a^2 is used instead of a**2 or pow(a,2) sqr_term = sqrt(b^2-4a*c) r1 = quadratic(a, sqr_term, b) r2 = quadratic(a, -sqr_term, b) # multiple values can be returned from a function using tuples # if the return keyword is omitted, the last term is returned r1, r2 end vol = sphere_vol(3) # @printf allows number formatting but does not automatically append the \n to statements, see below @printf "volume = %0.3f\n" vol #> volume = 113.097 quad1, quad2 = quadratic2(2.0, -2.0, -12.0) println("result 1: ", quad1) #> result 1: 3.0 println("result 2: ", quad2) #> result 2: -2.0 ================================================ FILE: tests/data/notebooks/inputs/marimo/basic_marimo_example.py ================================================ import marimo __generated_with = "0.17.8" app = marimo.App() @app.cell(hide_code=True) def _(mo): mo.md(r""" This is a simple marimo notebook """) return @app.cell def _(): x = 1 return (x,) @app.cell def _(x): y = x+1 y return @app.cell def _(): import marimo as mo return (mo,) if __name__ == "__main__": app.run() ================================================ FILE: tests/data/notebooks/inputs/md/jupytext_markdown.md ================================================ --- jupyter: kernelspec: display_name: Python 3 language: python name: python3 --- # Markdown, code and raw cells ## Markdown cells This is a Markdown cell. Markdown cells end with either a code cell, or two consecutive blank lines in the text. If you prefer that Markdown headings define new cells, have a look at the `split_at_heading` option. Indented code is accepted, and consecutive blank lines there do not break Markdown cells: def f(x): return 1 def h(x): return f(x)+2 ## Code cells ```python """This code cell starts with ` ```python`""" 1 + 1 ``` ## Raw cells Raw cells are delimited with `` and , like here: this is a raw cell # Protected Markdown cells If you want to include code blocks (or two consecutive blank lines) in a Markdown cell, use explicit Markdown cell delimiters `` and ``. This Markdown cell has two consecutive blank lines And then a code block which is not a Jupyter code cell: ```python 2 + 2 ``` # Metadata Metadata are supported for all cell types. ## Markdown cells A cell with a title and additional metadata. ## Code cells ```python tags=["parameters"] a = 2 ``` ================================================ FILE: tests/data/notebooks/inputs/md/plain_markdown.md ================================================ --- title: A sample document --- This document is a plain Markdown document that was not created from a notebook. We use this document to test that inputing a Markdown file into Jupytext, and then converting the resulting notebook to a Markdown file using nbconvert, is the identity Another paragraph # A header Indented code def f(x): return 1 def h(x): return f(x)+2 A Python code snippet ```python """This code cell starts with ` ```python`""" 1 + 1 ``` Code snippet without an explicit language ``` echo 'Hello world' ``` Markdown comments VS Code region markers This Markdown cell has two consecutive blank lines And continues here ================================================ FILE: tests/data/notebooks/inputs/myst/fenced_code_vs_code_cells.md ================================================ # Fenced code ## No language ``` # a generic code instruction 1 + 1 ``` ## Python ```python 1 + 1 ``` ## Bash ```python echo Hi ``` # Code cells ```{code-cell} ipython3 # This code gets executed in notebooks 1 + 1 ``` ================================================ FILE: tests/data/notebooks/inputs/myst/reference_link.md ================================================ This documents contains a code cell to make sure it is recognized as a MyST document. ```{code-cell} ipython3 1 + 1 ``` This is a [reference-link to the issue][]. :::{note} This note is key... not sure why. ::: [reference-link to the issue]: ================================================ FILE: tests/data/notebooks/inputs/percent/hydrogen.py ================================================ # %% import pandas as pd # %% Display a data frame df = pd.DataFrame({'A': [1, 2], 'B': [3, 4]}, index=pd.Index(['x0', 'x1'], name='x')) df # %% Pandas plot {"tags": ["parameters"]} df.plot(kind='bar') ================================================ FILE: tests/data/notebooks/inputs/ps1/build.ps1 ================================================ # This file originates from # https://github.com/MicrosoftDocs/PowerShell-Docs/blob/staging/build.ps1 param( [switch]$SkipCabs, [switch]$ShowProgress ) # Turning off the progress display, by default $global:ProgressPreference = 'SilentlyContinue' if ($ShowProgress) { $ProgressPreference = 'Continue' } [Net.ServicePointManager]::SecurityProtocol = [Net.ServicePointManager]::SecurityProtocol -bor [Net.SecurityProtocolType]::Tls12 $tempDir = [System.IO.Path]::GetTempPath() # Pandoc source URL $panDocVersion = "2.7.3" $pandocSourceURL = "https://github.com/jgm/pandoc/releases/download/$panDocVersion/pandoc-$panDocVersion-windows-x86_64.zip" $pandocDestinationPath = New-Item (Join-Path $tempDir "pandoc") -ItemType Directory -Force $pandocZipPath = Join-Path $pandocDestinationPath "pandoc-$panDocVersion-windows-x86_64.zip" Invoke-WebRequest -Uri $pandocSourceURL -OutFile $pandocZipPath Expand-Archive -Path $pandocZipPath -DestinationPath $pandocDestinationPath -Force $pandocExePath = Join-Path (Join-Path $pandocDestinationPath "pandoc-$panDocVersion-windows-x86_64") "pandoc.exe" # Install ThreadJob if not available $threadJob = Get-Module ThreadJob -ListAvailable if ($null -eq $threadjob) { Install-Module ThreadJob -RequiredVersion 1.1.2 -Scope CurrentUser -Force } # Find the reference folder path w.r.t the script $ReferenceDocset = Join-Path $PSScriptRoot 'reference' # Go through all the directories in the reference folder $jobs = [System.Collections.Generic.List[object]]::new() $excludeList = 'module', 'media', 'docs-conceptual', 'mapping', 'bread', '7' Get-ChildItem $ReferenceDocset -Directory -Exclude $excludeList | ForEach-Object -Process { $job = Start-ThreadJob -Name $_.Name -ArgumentList @($SkipCabs,$pandocExePath,$PSScriptRoot,$_) -ScriptBlock { param($SkipCabs, $pandocExePath, $WorkingDirectory, $DocSet) $tempDir = [System.IO.Path]::GetTempPath() $workingDir = Join-Path $tempDir $DocSet.Name $workingDir = New-Item -ItemType Directory -Path $workingDir -Force Set-Location $WorkingDir function Get-ContentWithoutHeader { param( $path ) $doc = Get-Content $path -Encoding UTF8 $start = $end = -1 # search the first 30 lines for the Yaml header # no yaml header in our docset will ever be that long for ($x = 0; $x -lt 30; $x++) { if ($doc[$x] -eq '---') { if ($start -eq -1) { $start = $x } else { if ($end -eq -1) { $end = $x + 1 break } } } } if ($end -gt $start) { Write-Output ($doc[$end..$($doc.count)] -join "`r`n") } else { Write-Output ($doc -join "`r`n") } } $Version = $DocSet.Name Write-Verbose -Verbose "Version = $Version" $VersionFolder = $DocSet.FullName Write-Verbose -Verbose "VersionFolder = $VersionFolder" # For each of the directories, go through each module folder Get-ChildItem $VersionFolder -Directory | ForEach-Object -Process { $ModuleName = $_.Name Write-Verbose -Verbose "ModuleName = $ModuleName" $ModulePath = Join-Path $VersionFolder $ModuleName Write-Verbose -Verbose "ModulePath = $ModulePath" $LandingPage = Join-Path $ModulePath "$ModuleName.md" Write-Verbose -Verbose "LandingPage = $LandingPage" $MamlOutputFolder = Join-Path "$WorkingDirectory\maml" "$Version\$ModuleName" Write-Verbose -Verbose "MamlOutputFolder = $MamlOutputFolder" $CabOutputFolder = Join-Path "$WorkingDirectory\updatablehelp" "$Version\$ModuleName" Write-Verbose -Verbose "CabOutputFolder = $CabOutputFolder" if (-not (Test-Path $MamlOutputFolder)) { New-Item $MamlOutputFolder -ItemType Directory -Force > $null } # Process the about topics if any $AboutFolder = Join-Path $ModulePath "About" if (Test-Path $AboutFolder) { Write-Verbose -Verbose "AboutFolder = $AboutFolder" Get-ChildItem "$aboutfolder/about_*.md" | ForEach-Object { $aboutFileFullName = $_.FullName $aboutFileOutputName = "$($_.BaseName).help.txt" $aboutFileOutputFullName = Join-Path $MamlOutputFolder $aboutFileOutputName $pandocArgs = @( "--from=gfm", "--to=plain+multiline_tables", "--columns=75", "--output=$aboutFileOutputFullName", "--quiet" ) Get-ContentWithoutHeader $aboutFileFullName | & $pandocExePath $pandocArgs } } try { # For each module, create a single maml help file # Adding warningaction=stop to throw errors for all warnings, erroraction=stop to make them terminating errors New-ExternalHelp -Path $ModulePath -OutputPath $MamlOutputFolder -Force -WarningAction Stop -ErrorAction Stop # For each module, create update-help help files (cab and helpinfo.xml files) if (-not $SkipCabs) { $cabInfo = New-ExternalHelpCab -CabFilesFolder $MamlOutputFolder -LandingPagePath $LandingPage -OutputFolder $CabOutputFolder # Only output the cab fileinfo object if ($cabInfo.Count -eq 8) { $cabInfo[-1].FullName } } } catch { Write-Error -Message "PlatyPS failure: $ModuleName -- $Version" -Exception $_ } } Remove-Item $workingDir -Force -ErrorAction SilentlyContinue } Write-Verbose -Verbose "Started job for $($_.Name)" $jobs += $job } $null = $jobs | Wait-Job # Variable to collect any errors in during processing $allErrors = [System.Collections.Generic.List[string]]::new() foreach ($job in $jobs) { Write-Verbose -Verbose "$($job.Name) output:" if ($job.Verbose.Count -gt 0) { foreach ($verboseMessage in $job.Verbose) { Write-Verbose -Verbose $verboseMessage } } if ($job.State -eq "Failed") { $allErrors += "$($job.Name) failed due to unhandled exception" } if ($job.Error.Count -gt 0) { $allErrors += "$($job.Name) failed with errors:" $allErrors += $job.Error.ReadAll() } } # If the above block, produced any errors, throw and fail the job if ($allErrors.Count -gt 0) { $allErrors throw "There are errors during platyPS run!`nPlease fix your markdown to comply with the schema: https://github.com/PowerShell/platyPS/blob/master/platyPS.schema.md" } ================================================ FILE: tests/data/notebooks/inputs/python/light_sample.py ================================================ # --- # jupyter: # jupytext: # formats: ipynb,py:light # --- # # Sample notebook a = 1 b = 2 a + b ================================================ FILE: tests/data/notebooks/inputs/python/python_notebook_sample.py ================================================ # # Specifications for Jupyter notebooks as python scripts # ## Markdown cells # Markdown cells are escaped with a single quote. Two consecutive # cells are separated with a blank line. # ## Code cells # Python code and adjacent comments are mapped to cell codes. # For instance, this is a code cell that starts with a # code comment, where we define a variable a = 1 # A cell with another variable b = 2 # In this cell we define a function def f(x): return x + 1 # Now simple function calls c = f(b) a * b + c # Line breaks in code cells are supported but then the cell need to have # metadata and an end-of-cell marker. Metadata information in json format, # escaped with '#+' or '# +' # + def g(x): return x + 2 d = 4 # - # One more cell a * b + g(c) + d # ## Raw cells, and cells active in py or ipynb only # Raw cells are commented code cells with metadata "active": "". # + {"active": ""} # This is a raw cell # - # Actually, using the "active" key you can have cells active in Jupyter # and inactive in python scripts # + {"active": "py"} 1 + 1 # done only in py script, inactive (raw) in ipynb # + {"active": "ipynb"} # 2 + 2 # active in ipynb only ================================================ FILE: tests/data/notebooks/inputs/sphinx/plot_notebook.py ================================================ # -*- coding: utf-8 -*- """ Notebook styled examples ======================== The gallery is capable of transforming Python files into reStructuredText files with a notebook structure. For this to be used you need to respect some syntax rules. It makes a lot of sense to contrast this output rst file with the :download:`original Python script ` to get better feeling of the necessary file structure. Anything before the Python script docstring is ignored by sphinx-gallery and will not appear in the rst file, nor will it be executed. This Python docstring requires an reStructuredText title to name the file and correctly build the reference links. Once you close the docstring you would be writing Python code. This code gets executed by sphinx gallery shows the plots and attaches the generating code. Nevertheless you can break your code into blocks and give the rendered file a notebook style. In this case you have to include a code comment breaker a line of at least 20 hashes and then every comment start with the a new hash. As in this example we start by first writing this module style docstring, then for the first code block we write the example file author and script license continued by the import modules instructions. Original script from: https://sphinx-gallery.readthedocs.io/en/latest/tutorials/plot_notebook.html """ # Code source: Óscar Nájera # License: BSD 3 clause import numpy as np import matplotlib.pyplot as plt ############################################################################## # This code block is executed, although it produces no output. Lines starting # with a simple hash are code comment and get treated as part of the code # block. To include this new comment string we started the new block with a # long line of hashes. # # The sphinx-gallery parser will assume everything after this splitter and that # continues to start with a **comment hash and space** (respecting code style) # is text that has to be rendered in # html format. Keep in mind to always keep your comments always together by # comment hashes. That means to break a paragraph you still need to comment # that line break. # # In this example the next block of code produces some plotable data. Code is # executed, figure is saved and then code is presented next, followed by the # inlined figure. x = np.linspace(-np.pi, np.pi, 300) xx, yy = np.meshgrid(x, x) z = np.cos(xx) + np.cos(yy) plt.figure() plt.imshow(z) plt.colorbar() plt.xlabel('$x$') plt.ylabel('$y$') ########################################################################### # Again it is possible to continue the discussion with a new Python string. This # time to introduce the next code block generates 2 separate figures. plt.figure() plt.imshow(z, cmap=plt.cm.get_cmap('hot')) plt.figure() plt.imshow(z, cmap=plt.cm.get_cmap('Spectral'), interpolation='none') ########################################################################## # There's some subtle differences between rendered html rendered comment # strings and code comment strings which I'll demonstrate below. (Some of this # only makes sense if you look at the # :download:`raw Python script `) # # Comments in comment blocks remain nested in the text. def dummy(): """Dummy function to make sure docstrings don't get rendered as text""" pass # Code comments not preceded by the hash splitter are left in code blocks. string = """ Triple-quoted string which tries to break parser but doesn't. """ ############################################################################ # Output of the script is captured: print('Some output from Python') ############################################################################ # Finally, I'll call ``show`` at the end just so someone running the Python # code directly will see the plots; this is not necessary for creating the docs plt.show() ############################################################################ # You can also include :math:`math` inline, or as separate equations: # # .. math:: # # \exp(j\pi) = -1 # # You can also insert images: # # .. image:: http://www.sphinx-doc.org/en/stable/_static/sphinxheader.png # :alt: Sphinx header # ================================================ FILE: tests/data/notebooks/outputs/Rmd_to_ipynb/R_sample.ipynb ================================================ { "cells": [ { "cell_type": "raw", "metadata": {}, "source": [ "---\n", "title: \"R Notebook\"\n", "output: html_notebook\n", "---" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "This is an [R Markdown](http://rmarkdown.rstudio.com) Notebook. When you execute code within the notebook, the results appear beneath the code. \n", "\n", "Try executing this chunk by clicking the *Run* button within the chunk or by placing your cursor inside it and pressing *Ctrl+Shift+Enter*. " ] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": [ "plot(cars)" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Add a new chunk by clicking the *Insert Chunk* button on the toolbar or by pressing *Ctrl+Alt+I*.\n", "\n", "When you save the notebook, an HTML file containing the code and output will be saved alongside it (click the *Preview* button or press *Ctrl+Shift+K* to preview the HTML file).\n", "\n", "The preview shows you a rendered HTML copy of the contents of the editor. Consequently, unlike *Knit*, *Preview* does not run any R code chunks. Instead, the output of the chunk when it was last run in the editor is displayed." ] } ], "metadata": { "jupytext": { "cell_metadata_filter": "-all", "main_language": "R", "notebook_metadata_filter": "-all" } }, "nbformat": 4, "nbformat_minor": 2 } ================================================ FILE: tests/data/notebooks/outputs/Rmd_to_ipynb/chunk_options.ipynb ================================================ { "cells": [ { "cell_type": "raw", "metadata": {}, "source": [ "---\n", "title: \"Test chunk options in Rmd/Jupyter conversion\"\n", "author: \"Marc Wouts\"\n", "date: \"June 16, 2018\"\n", "---" ] }, { "cell_type": "code", "execution_count": null, "metadata": { "lines_to_next_cell": 2, "name": "knitr_setup", "tags": [ "remove_cell" ] }, "outputs": [], "source": [ "%%R\n", "knitr::opts_chunk$set(echo = FALSE, fig.width = 10, fig.height = 5)" ] }, { "cell_type": "code", "execution_count": null, "metadata": { "echo": true }, "outputs": [], "source": [ "import pandas as pd\n", "x = pd.Series({'A':1, 'B':3, 'C':2})" ] }, { "cell_type": "code", "execution_count": null, "metadata": { "fig.height": 5, "fig.width": 8, "lines_to_next_cell": 0, "name": "bar_plot", "tags": [ "remove_input" ] }, "outputs": [], "source": [ "x.plot(kind='bar', title='Sample plot')" ] }, { "cell_type": "markdown", "metadata": {}, "source": [] } ], "metadata": { "kernelspec": { "display_name": "Python", "language": "python", "name": "python3" } }, "nbformat": 4, "nbformat_minor": 2 } ================================================ FILE: tests/data/notebooks/outputs/Rmd_to_ipynb/ioslides.ipynb ================================================ { "cells": [ { "cell_type": "raw", "metadata": {}, "source": [ "---\n", "title: \"Quick ioslides\"\n", "subtitle: \"Slides generated using R, python and ioslides\"\n", "author: \"Marc Wouts\"\n", "date: \"June 15, 2018\"\n", "output:\n", " ioslides_presentation:\n", " widescreen: true\n", " smaller: true\n", "editor_options:\n", " chunk_output_type: console\n", "---" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "## What is ioslides?\n", "\n", "This is the default format in rstudio for building interactive HTML presentations.\n", "\n", "Enjoy the [manual](https://rmarkdown.rstudio.com/ioslides_presentation_format.html)!\n", "\n", "These slides can be turned to a single HTML file with either a click on 'knitr' in rstudio, or, command line:\n", "```bash\n", "R -e 'rmarkdown::render(\"ioslides.Rmd\")'\n", "```\n", "\n", "## A sample plot\n", "\n", "
\n", "Here we create a sample data set for plotting." ] }, { "cell_type": "code", "execution_count": null, "metadata": { "echo": true }, "outputs": [], "source": [ "import pandas as pd\n", "x = pd.Series({'A':1, 'B':3, 'C':2})" ] }, { "cell_type": "markdown", "metadata": { "lines_to_next_cell": 0 }, "source": [ "Then, in another column we plot. The R notebook code chunks have many [options](https://yihui.name/knitr/options/).\n", "For this plot I chose not to display the source code.\n", "
\n", "\n", "
" ] }, { "cell_type": "code", "execution_count": null, "metadata": { "fig.height": 5, "fig.width": 8, "lines_to_next_cell": 0, "tags": [ "remove_input" ] }, "outputs": [], "source": [ "x.plot(kind='bar', title='Sample plot')" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "
" ] } ], "metadata": { "jupytext": { "cell_metadata_filter": "echo,tags,fig.width,fig.height,-all", "main_language": "python", "notebook_metadata_filter": "-all" } }, "nbformat": 4, "nbformat_minor": 2 } ================================================ FILE: tests/data/notebooks/outputs/Rmd_to_ipynb/knitr-spin.ipynb ================================================ { "cells": [ { "cell_type": "markdown", "metadata": {}, "source": [ "The below derives from\n", "https://github.com/yihui/knitr/blob/master/inst/examples/knitr-spin.R\n", "\n", "This is a special R script which can be used to generate a report. You can\n", "write normal text in roxygen comments.\n", "\n", "First we set up some options (you do not have to do this):" ] }, { "cell_type": "code", "execution_count": null, "metadata": { "name": "setup", "tags": [ "remove_cell" ] }, "outputs": [], "source": [ "library(knitr)\n", "opts_chunk$set(fig.path = 'figure/silk-')" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "The report begins here." ] }, { "cell_type": "code", "execution_count": null, "metadata": { "cache": false, "name": "test-a" }, "outputs": [], "source": [ "# boring examples as usual\n", "set.seed(123)\n", "x = rnorm(5)\n", "mean(x)" ] }, { "cell_type": "markdown", "metadata": { "lines_to_next_cell": 0 }, "source": [ "You can not use here the special syntax {{code}} to embed inline expressions, e.g." ] }, { "cell_type": "code", "execution_count": null, "metadata": { "lines_to_next_cell": 0 }, "outputs": [], "source": [ "{{mean(x) + 2}}" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "is the mean of x plus 2.\n", "The code itself may contain braces, but these are not checked. Thus,\n", "perfectly valid (though very strange) R code such as `{{2 + 3}} - {{4 - 5}}`\n", "can lead to errors because `2 + 3}} - {{4 - 5` will be treated as inline code.\n", "\n", "Now we continue writing the report. We can draw plots as well." ] }, { "cell_type": "code", "execution_count": null, "metadata": { "fig.height": 5, "fig.width": 5, "name": "test-b" }, "outputs": [], "source": [ "par(mar = c(4, 4, .1, .1)); plot(x)" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Actually you do not have to write chunk options, in which case knitr will use\n", "default options. For example, the code below has no options attached:" ] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": [ "var(x)\n", "quantile(x)" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "And you can also write two chunks successively like this:" ] }, { "cell_type": "code", "execution_count": null, "metadata": { "lines_to_next_cell": 0, "name": "test-chisq5" }, "outputs": [], "source": [ "sum(x^2) # chi-square distribution with df 5" ] }, { "cell_type": "code", "execution_count": null, "metadata": { "name": "test-chisq4" }, "outputs": [], "source": [ "sum((x - mean(x))^2) # df is 4 now" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Done. Call spin('knitr-spin.R') to make silk from sow's ear now and knit a\n", "lovely purse." ] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": [ "# /* you can write comments between /* and */ like C comments (the preceding #\n", "# is optional)\n", "Sys.sleep(60)\n", "# */" ] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": [ "# /* there is no inline comment; you have to write block comments */" ] } ], "metadata": { "jupytext": { "cell_metadata_filter": "tags,name,fig.width,cache,fig.height,-all", "main_language": "R", "notebook_metadata_filter": "-all" } }, "nbformat": 4, "nbformat_minor": 2 } ================================================ FILE: tests/data/notebooks/outputs/Rmd_to_ipynb/markdown.ipynb ================================================ { "cells": [ { "cell_type": "markdown", "metadata": {}, "source": [ "# This is a plain markdown file\n", "\n", "```python\n", "1+1\n", "```\n", "\n", "And more comments\n", "\n", "Another comment separated by one line" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "This is another cell, separated by two or more lines from the previous one." ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "And a last markdown cell, followed by a code cell\n", "```python\n", "1+1\n", "```" ] } ], "metadata": { "jupytext": { "cell_metadata_filter": "-all", "main_language": "python", "notebook_metadata_filter": "-all" } }, "nbformat": 4, "nbformat_minor": 2 } ================================================ FILE: tests/data/notebooks/outputs/ipynb_to_Rmd/Line_breaks_in_LateX_305.Rmd ================================================ --- jupyter: kernelspec: display_name: Python 3 language: python name: python3 --- This cell uses no particular cell marker $$ \begin{align} \dot{x} & = \sigma(y-x)\\ \dot{y} & = \rho x - y - xz \\ \dot{z} & = -\beta z + xy \end{align} $$ This cell uses no particular cell marker, and a single slash in the $\LaTeX$ equation $$ \begin{align} \dot{x} & = \sigma(y-x) \ \dot{y} & = \rho x - y - xz \ \dot{z} & = -\beta z + xy \end{align} $$ This cell uses the triple quote cell markers introduced at https://github.com/mwouts/jupytext/issues/305 $$ \begin{align} \dot{x} & = \sigma(y-x)\\ \dot{y} & = \rho x - y - xz \\ \dot{z} & = -\beta z + xy \end{align} $$ ================================================ FILE: tests/data/notebooks/outputs/ipynb_to_Rmd/Notebook with function and cell metadata 164.Rmd ================================================ --- jupyter: kernelspec: display_name: Python 3 language: python name: python3 --- ```{python} 1 + 1 ``` A markdown cell And below, the cell for function f has non trivial cell metadata. And the next cell as well. ```{python attributes={'classes': [], 'id': '', 'n': '10'}} def f(x): return x ``` ```{python attributes={'classes': [], 'id': '', 'n': '10'}} f(5) ``` More text ```{python} 2 + 2 ``` ================================================ FILE: tests/data/notebooks/outputs/ipynb_to_Rmd/Notebook with html and latex cells.Rmd ================================================ --- jupyter: kernelspec: display_name: Python 3 language: python name: python3 --- ```{html}

Jupytext on GitHub

``` ```{latex} $\frac{\pi}{2}$ ``` ```{python} # %load_ext rpy2.ipython ``` ```{r} library(ggplot2) ggplot(data=data.frame(x=c('A', 'B'), y=c(5, 2)), aes(x,weight=y)) + geom_bar() ``` ```{python} # %matplotlib inline import pandas as pd pd.Series({'A':5, 'B':2}).plot(figsize=(3,2), kind='bar') ``` ================================================ FILE: tests/data/notebooks/outputs/ipynb_to_Rmd/Notebook with many hash signs.Rmd ================================================ --- jupyter: kernelspec: display_name: Python 3 language: python name: python3 --- ################################################################## This is a notebook that contains many hash signs. Hopefully its python representation is not recognized as a Sphinx Gallery script... ################################################################## ```{python} some = 1 code = 2 some+code ################################################################## # A comment ################################################################## # Another comment ``` ################################################################## This is a notebook that contains many hash signs. Hopefully its python representation is not recognized as a Sphinx Gallery script... ################################################################## ================================================ FILE: tests/data/notebooks/outputs/ipynb_to_Rmd/Notebook with metadata and long cells.Rmd ================================================ --- jupyter: kernelspec: display_name: Python 3 language: python name: python3 --- # Part one - various cells Here we have a markdown cell with two blank lines Now we have a markdown cell with a code block inside it ```python 1 + 1 ``` After that cell we'll have a code cell ```{python} 2 + 2 3 + 3 ``` Followed by a raw cell ```{python active="", eval=FALSE} This is the content of the raw cell ``` # Part two - cell metadata This is a markdown cell with cell metadata `{"key": "value"}` ```{python .class=None, tags=c("parameters")} """This is a code cell with metadata `{"tags":["parameters"], ".class":null}`""" ``` ```{python key="value", active="", eval=FALSE} This is a raw cell with cell metadata `{"key": "value"}` ``` ================================================ FILE: tests/data/notebooks/outputs/ipynb_to_Rmd/Notebook_with_R_magic.Rmd ================================================ --- jupyter: kernelspec: display_name: Python 2 language: python name: python2 --- # A notebook with R cells This notebook shows the use of R cells to generate plots ```{python} # %load_ext rpy2.ipython ``` ```{r} suppressMessages(require(tidyverse)) ``` ```{r} ggplot(iris, aes(x = Sepal.Length, y = Petal.Length, color=Species)) + geom_point() ``` The default plot dimensions are not good for us, so we use the -w and -h parameters in %%R magic to set the plot size ```{r magic_args="-w 400 -h 240"} ggplot(iris, aes(x = Sepal.Length, y = Petal.Length, color=Species)) + geom_point() ``` ================================================ FILE: tests/data/notebooks/outputs/ipynb_to_Rmd/Notebook_with_more_R_magic_111.Rmd ================================================ --- jupyter: kernelspec: display_name: Python 3 language: python name: python3 --- ```{python} # %load_ext rpy2.ipython import pandas as pd df = pd.DataFrame( { "Letter": ["a", "a", "a", "b", "b", "b", "c", "c", "c"], "X": [4, 3, 5, 2, 1, 7, 7, 5, 9], "Y": [0, 4, 3, 6, 7, 10, 11, 9, 13], "Z": [1, 2, 3, 1, 2, 3, 1, 2, 3], } ) ``` ```{r magic_args="-i df"} library("ggplot2") ggplot(data = df) + geom_point(aes(x = X, y = Y, color = Letter, size = Z)) ``` ================================================ FILE: tests/data/notebooks/outputs/ipynb_to_Rmd/R notebook with invalid cell keys.Rmd ================================================ --- jupyter: kernelspec: display_name: R language: R name: ir --- This notebook was created with IRKernel 0.8.12, and is not completely valid, as the code cell below contains an unexpected 'source' entry. This did cause https://github.com/mwouts/jupytext/issues/234. Note that the problem is solved when one upgrades to IRKernel 1.0.0. ```{r} library("ggplot2") ggplot(mtcars, aes(mpg)) + stat_ecdf() ``` ================================================ FILE: tests/data/notebooks/outputs/ipynb_to_Rmd/Reference Guide for Calysto Scheme.Rmd ================================================ --- jupyter: kernelspec: display_name: Calysto Scheme (Python) language: scheme name: calysto_scheme ---

Reference Guide for Calysto Scheme

[Calysto Scheme](https://github.com/Calysto/calysto_scheme) is a real Scheme programming language, with full support for continuations, including call/cc. It can also use all Python libraries. Also has some extensions that make it more useful (stepper-debugger, choose/fail, stack traces), or make it better integrated with Python. In Jupyter notebooks, because Calysto Scheme uses [MetaKernel](https://github.com/Calysto/metakernel/blob/master/README.rst), it has a fully-supported set of "magics"---meta-commands for additional functionality. This includes running Scheme in parallel. See all of the [MetaKernel Magics](https://github.com/Calysto/metakernel/blob/master/metakernel/magics/README.md). Calysto Scheme is written in Scheme, and then translated into Python (and other backends). The entire functionality lies in a single Python file: https://github.com/Calysto/calysto_scheme/blob/master/calysto_scheme/scheme.py However, you can easily install it (see below). Please see [Calysto Scheme Language](Calysto%20Scheme%20Language.ipynb) for more details on the Calysto Scheme language. ## Installation You can install Calysto Scheme with Python3: ``` pip3 install --upgrade calysto-scheme --user -U python3 -m calysto_kernel install --user ``` or in the system kernel folder with: ``` sudo pip3 install --upgrade calysto-scheme -U sudo python3 -m calysto_kernel install ``` Change pip3/python3 to use a different pip or Python. The version of Python used will determine how Calysto Scheme is run. Use it in the console, qtconsole, or notebook with IPython 3: ``` ipython console --kernel calysto_scheme ipython qtconsole --kernel calysto_scheme ipython notebook --kernel calysto_scheme ``` In addition to all of the following items, Calysto Scheme also has access to all of Python's builtin functions, and all of Python's libraries. For example, you can use `(complex 3 2)` to create a complex number by calling Python's complex function. ## Jupyter Enhancements When you run Calysto Scheme in Jupyter (console, notebook, qtconsole, etc.) you get: * TAB completions of Scheme functions and variable names * display of rich media * stepper/debugger * magics (% macros) * shell commands (! command) * LaTeX equations * LaTeX-style variables * Python integration ### LaTeX-style variables Calysto Scheme allows you to use LaTeX-style variables in code. For example, if you type: ``` \beta ``` with the cursor right after the 'a' in beta, and then press TAB, it will turn into the unicode character: ``` β ``` There are nearly 1300 different symbols defined (thanks to the Julia language) and documented here: http://docs.julialang.org/en/release-0.4/manual/unicode-input/#man-unicode-input Calysto Scheme may not implement all of those. Some useful and suggestive ones: * \pi - π * \Pi - Π * \Sigma - Σ * \_i - subscript i, such as vectorᵢ ```{scheme} (define α 67) ``` ```{scheme} α ``` ```{scheme} (define i 2) (define vectorᵢ (vector-ref (vector 0 6 3 2) i)) vectorᵢ ``` ### Rich media ```{scheme} (import "calysto.display") ``` ```{scheme} (calysto.display.HTML "This is bold, italics, underlined.") ``` ```{scheme} (import "calysto.graphics") ``` ```{scheme} (define canvas (calysto.graphics.Canvas)) ``` ```{scheme} (define ball (calysto.graphics.Circle '(150 150) 100)) ``` ```{scheme} (ball.draw canvas) ``` ### Shell commands ```{scheme} ! ls /tmp ``` ### Stepper/Debugger Here is what the debugger looks like: It has breakpoints (click in left margin). You must press Stop to exit the debugger. ```scheme %%debug (begin (define x 1) (set! x 2) ) ``` ### Python Integration You can import and use any Python library in Calysto Scheme. In addition, if you wish, you can execute expressions and statements in a Python environment: ```{scheme} (python-eval "1 + 2") ``` ```{scheme} (python-exec " def mypyfunc(a, b): return a * b ") ``` This is a shared environment with Scheme: ```{scheme} (mypyfunc 4 5) ``` You can use `func` to turn a Scheme procedure into a Python function, and `define!` to put it into the shared environment with Python: ```{scheme} (define! mypyfunc2 (func (lambda (n) n))) ``` ```{scheme} (python-eval "mypyfunc2(34)") ``` # Differences Between Languages ## Major differences between Scheme and Python 1. In Scheme, double quotes are used for strings and may contain newlines 1. In Scheme, a single quote is short for (quote ...) and means "literal" 1. In Scheme, everything is an expression and has a return value 1. Python does not support macros (e.g., extending syntax) 1. In Python, "if X" is false if X is None, False, [], (,) or 0. In Scheme, "if X" is only false if X is #f or 0 1. Calysto Scheme uses continuations, not the call stack. However, for debugging there is a pseudo-stack when an error is raised. You can turn that off with (use-stack-trace #f) 1. Scheme procedures are not Python functions, but there are means to use one as the other. ## Major Differences Between Calysto Scheme and other Schemes 1. define-syntax works slightly differently 1. In Calysto Scheme, #(...) is short for '#(...) 1. Calysto Scheme is missing many standard functions (see list at bottom) 1. Calysto Scheme has a built-in amb operator called `choose` 1. For debugging there is a pseudo-stack when errors are raised in Calysto Scheme. You can turn that off with (use-stack-trace #f) ### Stack Trace Calysto Scheme acts as if it has a call stack, for easier debugging. For example: ```{scheme} (define fact (lambda (n) (if (= n 1) q (* n (fact (- n 1)))))) ``` ```{scheme} (fact 5) ``` To turn off the stack trace on error: ```scheme (use-stack-trace #f) ``` That will allow infinite recursive loops without keeping track of the "stack". # Calysto Scheme Variables ## SCHEMEPATH SCHEMEPATH is a list of search directories used with (load NAME). This is a reference, so you should append to it rather than attempting to redefine it. ```{scheme} SCHEMEPATH ``` ```{scheme} (set-cdr! (cdr SCHEMEPATH) (list "/var/modules")) ``` ```{scheme} SCHEMEPATH ``` ## Getting Started Note that you can use the word `lambda` or \lambda and then press [TAB] ```{scheme} (define factorial (λ (n) (cond ((zero? n) 1) (else (* n (factorial (- n 1))))))) ``` ```{scheme} (factorial 5) ``` ## define-syntax (define-syntax NAME RULES): a method for creating macros ```{scheme} (define-syntax time [(time ?exp) (let ((start (current-time))) ?exp (- (current-time) start))]) ``` ```{scheme} (time (car '(1 2 3 4))) ``` ```{scheme} ;;--------------------------------------------------------------------- ;; collect is like list comprehension in Python (define-syntax collect [(collect ?exp for ?var in ?list) (filter-map (lambda (?var) ?exp) (lambda (?var) #t) ?list)] [(collect ?exp for ?var in ?list if ?condition) (filter-map (lambda (?var) ?exp) (lambda (?var) ?condition) ?list)]) (define filter-map (lambda (f pred? values) (if (null? values) '() (if (pred? (car values)) (cons (f (car values)) (filter-map f pred? (cdr values))) (filter-map f pred? (cdr values)))))) ``` ```{scheme} (collect (* n n) for n in (range 10)) ``` ```{scheme} (collect (* n n) for n in (range 5 20 3)) ``` ```{scheme} (collect (* n n) for n in (range 10) if (> n 5)) ``` ```{scheme} ;;--------------------------------------------------------------------- ;; for loops (define-syntax for [(for ?exp times do . ?bodies) (for-repeat ?exp (lambda () . ?bodies))] [(for ?var in ?exp do . ?bodies) (for-iterate1 ?exp (lambda (?var) . ?bodies))] [(for ?var at (?i) in ?exp do . ?bodies) (for-iterate2 0 ?exp (lambda (?var ?i) . ?bodies))] [(for ?var at (?i ?j . ?rest) in ?exp do . ?bodies) (for ?var at (?i) in ?exp do (for ?var at (?j . ?rest) in ?var do . ?bodies))]) (define for-repeat (lambda (n f) (if (< n 1) 'done (begin (f) (for-repeat (- n 1) f))))) (define for-iterate1 (lambda (values f) (if (null? values) 'done (begin (f (car values)) (for-iterate1 (cdr values) f))))) (define for-iterate2 (lambda (i values f) (if (null? values) 'done (begin (f (car values) i) (for-iterate2 (+ i 1) (cdr values) f))))) ``` ```{scheme} (define matrix2d '((10 20) (30 40) (50 60) (70 80))) (define matrix3d '(((10 20 30) (40 50 60)) ((70 80 90) (100 110 120)) ((130 140 150) (160 170 180)) ((190 200 210) (220 230 240)))) ``` ```{scheme} (begin (define hello 0) (for 5 times do (set! hello (+ hello 1))) hello ) ``` ```{scheme} (for sym in '(a b c d) do (define x 1) (set! x sym) (print x)) ``` ```{scheme} (for n in (range 10 20 2) do (print n)) ``` ```{scheme} (for n at (i j) in matrix2d do (print (list n 'coords: i j))) ``` ```{scheme} (for n at (i j k) in matrix3d do (print (list n 'coords: i j k))) ``` ```{scheme} (define-syntax scons [(scons ?x ?y) (cons ?x (lambda () ?y))]) (define scar car) (define scdr (lambda (s) (let ((result ((cdr s)))) (set-cdr! s (lambda () result)) result))) (define first (lambda (n s) (if (= n 0) '() (cons (scar s) (first (- n 1) (scdr s)))))) (define nth (lambda (n s) (if (= n 0) (scar s) (nth (- n 1) (scdr s))))) (define smap (lambda (f s) (scons (f (scar s)) (smap f (scdr s))))) (define ones (scons 1 ones)) (define nats (scons 0 (combine nats + ones))) (define combine (lambda (s1 op s2) (scons (op (scar s1) (scar s2)) (combine (scdr s1) op (scdr s2))))) (define fibs (scons 1 (scons 1 (combine fibs + (scdr fibs))))) (define facts (scons 1 (combine facts * (scdr nats)))) (define ! (lambda (n) (nth n facts))) ``` ```{scheme} (! 5) ``` ```{scheme} (nth 10 facts) ``` ```{scheme} (nth 20 fibs) ``` ```{scheme} (first 30 fibs) ``` ## for-each (for-each PROCEDURE LIST): apply PROCEDURE to each item in LIST; like `map` but don't return results ```{scheme} (for-each (lambda (n) (print n)) '(3 4 5)) ``` ## format (format STRING ITEM ...): format the string with ITEMS as arguments ```{scheme} (format "This uses formatting ~a ~s ~%" 'apple 'apple) ``` ## func Turns a lambda into a Python function. (func (lambda ...)) ```{scheme} (func (lambda (n) n)) ``` ## There's more! Please see [Calysto Scheme Language](Calysto%20Scheme%20Language.ipynb) for more details on the Calysto Scheme language. ================================================ FILE: tests/data/notebooks/outputs/ipynb_to_Rmd/The flavors of raw cells.Rmd ================================================ --- jupyter: kernelspec: display_name: Python 3 language: python name: python3 --- ```{python raw_mimetype="text/latex", active="", eval=FALSE} $1+1$ ``` ```{python raw_mimetype="text/restructuredtext", active="", eval=FALSE} :math:`1+1` ``` ```{python raw_mimetype="text/html", active="", eval=FALSE} Bold text ``` ```{python raw_mimetype="text/markdown", active="", eval=FALSE} **Bold text** ``` ```{python raw_mimetype="text/x-python", active="", eval=FALSE} 1 + 1 ``` ```{python active="", eval=FALSE} Not formatted ``` ================================================ FILE: tests/data/notebooks/outputs/ipynb_to_Rmd/cat_variable.Rmd ================================================ --- jupyter: kernelspec: display_name: Python 3 language: python name: python3 --- ```{python} cat = 42 ``` ================================================ FILE: tests/data/notebooks/outputs/ipynb_to_Rmd/coconut_homepage_demo.Rmd ================================================ --- jupyter: kernelspec: display_name: Coconut language: coconut name: coconut --- Taken from [coconut-lang.org](coconut-lang.org) pipeline-style programming ```{coconut} "hello, world!" |> print ``` prettier lambdas ```{coconut} x -> x ** 2 ``` partial application ```{coconut} range(10) |> map$(pow$(?, 2)) |> list ``` pattern-matching ```{coconut} match [head] + tail in [0, 1, 2, 3]: print(head, tail) ``` destructuring assignment ```{coconut} {"list": [0] + rest} = {"list": [0, 1, 2, 3]} ``` infix notation ```{coconut} # 5 `mod` 3 == 2 ``` operator functions ```{coconut} product = reduce$(*) ``` function composition ```{coconut} # (f..g..h)(x, y, z) ``` lazy lists ```{coconut} # (| first_elem() |) :: rest_elems() ``` parallel programming ```{coconut} range(100) |> parallel_map$(pow$(2)) |> list ``` tail call optimization ```{coconut} def factorial(n, acc=1): case n: match 0: return acc match _ is int if n > 0: return factorial(n-1, acc*n) ``` algebraic data types ```{coconut} data Empty() data Leaf(n) data Node(l, r) def size(Empty()) = 0 addpattern def size(Leaf(n)) = 1 addpattern def size(Node(l, r)) = size(l) + size(r) ``` and much more! Like what you see? Don't forget to star Coconut on GitHub! ```{coconut} ``` ================================================ FILE: tests/data/notebooks/outputs/ipynb_to_Rmd/convert_to_py_then_test_with_update83.Rmd ================================================ --- jupyter: kernelspec: display_name: Python 3 language: python name: python3 --- ```{python} # %%time print('asdf') ``` Thanks for jupytext! ```{python} ``` ================================================ FILE: tests/data/notebooks/outputs/ipynb_to_Rmd/csharp.Rmd ================================================ --- jupyter: kernelspec: display_name: .NET (C#) language: C# name: .net-csharp --- We start with... ```{csharp} Console.WriteLine("Hello World!"); ``` Then we do a plot with Plotly, following the [Plotting with XPlot](https://github.com/dotnet/interactive/blob/master/NotebookExamples/csharp/Docs/Plotting%20with%20Xplot.ipynb) example from `dotnet/interactive`: ```{csharp} using XPlot.Plotly; var bar = new Graph.Bar { name = "Bar", x = new[] {'A', 'B', 'C'}, y = new[] {1, 3, 2} }; var chart = Chart.Plot(new[] {bar}); chart.WithTitle("A bar plot"); display(chart); ``` We also test the math outputs as in the [Math and Latex](https://github.com/dotnet/interactive/blob/master/NotebookExamples/csharp/Docs/Math%20and%20LaTeX.ipynb) example: ```{csharp} (LaTeXString)@"\begin{align} e^{i \pi} = -1\end{align}" ``` ```{csharp} (MathString)@"e^{i \pi} = -1" ``` ================================================ FILE: tests/data/notebooks/outputs/ipynb_to_Rmd/demo_gdl_fbp.Rmd ================================================ --- jupyter: kernelspec: display_name: IDL [conda env:gdl] * language: IDL name: conda-env-gdl-idl --- ## GDL demo notebook Demonstration of GDL [(gnudatalanguage)](https://github.com/gnudatalanguage/gdl) This notebook creates a Shepp-Logan phantom, projects it and then performs an FBP reconstruction. ```{idl} ;; L.A. Shepp and B.F. Logan, “The Fourier reconstruction of a head section,” ;; IEEE Trans. Nucl. Sci. 21(3), 21–43 (1974). function shepplogan, size = size if NOT keyword_set(size) then size = 256 phantom = fltarr(size,size) tmp = (findgen(size)-((size-1)/2.0)) / (size/2.0) xcor = rebin(tmp,size,size) ycor = rebin(transpose(tmp),size,size) tmp = fltarr(size,size) aa={cx: 0.0, cy: 0.0, maj:0.69, min:0.92, theta: 0.0, val: 2.0 } bb={cx: 0.0, cy:-0.0184, maj:0.6624, min:0.874, theta: 0.0, val:-0.98} cc={cx: 0.22, cy: 0.0, maj:0.11, min:0.31, theta:-18.0, val:-0.02} dd={cx:-0.22, cy: 0.0, maj:0.16, min:0.41, theta: 18.0, val:-0.02} ee={cx: 0.0, cy: 0.35, maj:0.21, min:0.25, theta: 0.0, val:-0.01} ff={cx: 0.0, cy: 0.1, maj:0.046, min:0.046, theta: 0.0, val:-0.01} gg={cx: 0.0, cy:-0.1, maj:0.046, min:0.046, theta: 0.0, val:-0.01} hh={cx:-0.08, cy:-0.605, maj:0.046, min:0.023, theta: 0.0, val:-0.01} ii={cx: 0.0, cy:-0.605, maj:0.023, min:0.023, theta: 0.0, val:-0.01} jj={cx: 0.06, cy:-0.605, maj:0.023, min:0.046, theta: 0.0, val:-0.01} list = [aa,bb,cc,dd,ee,ff,gg,hh,ii,jj] for n = 0, n_elements(list)-1 do begin tmp = ((xcor-list[n].cx) / list[n].maj)^2 $ + ((ycor-list[n].cy) / list[n].min)^2 if list[n].theta NE 0 then begin nx = (size-1) * (list[n].cx + 1) / 2 ny = (size-1) * (list[n].cy + 1) / 2 tmp = rot(tmp, -list[n].theta, 1, nx, ny, /interp, /pivot) endif phantom[where(tmp LE 1.0)] += list[n].val endfor return, phantom < 1.1 end ``` ```{idl} ;; Enable inline plotting !inline=1 ``` ```{idl} phantom = shepplogan() window, 0, xsize=256, ysize=256 tvscl, phantom > 0.95 ``` Now we define simple forward and backprojection functions: ```{idl} function proj, image, angle sino_size_x = max(size(image,/dim)) sino_size_y = n_elements(angle) sino = fltarr(sino_size_x, sino_size_y) for aa=0, n_elements(angle)-1 do begin sino[*,aa] = total(rot(image, angle[aa], /interp), 2) endfor return, sino end ``` ```{idl} function back, sino, angle image_size = n_elements(sino[*,0]) image = fltarr(image_size,image_size) for aa=0, n_elements(angle)-1 do begin image += rot(rebin(sino[*,aa],[image_size,image_size]), -angle[aa], /interp) endfor return, image / n_elements(angle) end ``` This allows us to create a sinogram: ```{idl} angles = findgen(360) sino = proj(phantom, angles) window, 0, xsize=256, ysize=360 tvscl, sino ``` On this we can apply a simple FBP reconstruction: ```{idl} ;; G.L. Zeng, “Revisit of the Ramp Filter,” ;; IEEE Trans. Nucl. Sci. 62(1), 131–136 (2015). function fbp, sino, angles ntot = n_elements(sino[*,0]) nang = n_elements(sino[0,*]) npos = ntot / 2 + 1 ; integer division needed ! nneg = ntot - npos freq = findgen(ntot) freq[npos:ntot-1] = REVERSE(freq[1:nneg]) freq[0] = 1 filter = -1 / (!pi * freq)^2 filter[where(freq mod 2 EQ 0)] *= -0.0 filter[0] = 0.25 filter = abs(fft(filter)) * ntot filter[ntot/4:ntot/4+ntot/2-1] *= 0.0 filter = rebin(filter,ntot,nang) ;; apply filter to the sinogram fsino = fft(sino, dim=1) fsino *= filter fsino = fft(fsino, dim=1, /overwrite, /inverse) fsino = !pi * real_part(fsino) ;; backproject the filtered sinogram return, back(fsino, angles) end ``` ```{idl} reconstruction = fbp(sino, angles) window, 0, xsize=512, ysize=256 tvscl, [phantom, reconstruction] > 0.8 ``` ### The end ================================================ FILE: tests/data/notebooks/outputs/ipynb_to_Rmd/evcxr_jupyter_tour.Rmd ================================================ --- jupyter: kernelspec: display_name: Rust language: rust name: rust --- # Tour of the EvCxR Jupyter Kernel For those not already familiar with Jupyter notebook, it lets you write code into "cells" like the box below. Cells can alternatively contain markdown, like this text here. Each code cell is compiled and executed separately, but variables, defined functions etc persist between cells. ## Printing to outputs and evaluating expressions Lets print something to stdout and stderr then return a final expression to see how that's presented. Note that stdout and stderr are separate streams, so may not appear in the same order is their respective print statements. ```{rust} println!("Hello world"); eprintln!("Hello error"); format!("Hello {}", "world") ``` ## Assigning and making use of variables We define a variable `message`, then in the subsequent cell, modify the string and finally print it out. We could also do all this in the one cell if we wanted. ```{rust} let mut message = "Hello ".to_owned(); ``` ```{rust} message.push_str("world!"); ``` ```{rust} message ``` ## Defining and redefining functions Next we'll define a function ```{rust} pub fn fib(x: i32) -> i32 { if x <= 2 {0} else {fib(x - 2) + fib(x - 1)} } ``` ```{rust} (1..13).map(fib).collect::>() ``` Hmm, that doesn't look right. Lets redefine the function. In practice, we'd go back and edit the function above and reevaluate it, but here, lets redefine it in a separate cell. ```{rust} pub fn fib(x: i32) -> i32 { if x <= 2 {2} else {fib(x - 2) + fib(x - 1)} } ``` ```{rust} let values = (1..13).map(fib).collect::>(); values ``` ## Spawning a separate thread and communicating with it We can spawn a thread to do stuff in the background, then continue executing code in other cells. ```{rust} use std::sync::{Mutex, Arc}; let counter = Arc::new(Mutex::new(0i32)); std::thread::spawn({ let counter = Arc::clone(&counter); move || { for i in 1..300 { *counter.lock().unwrap() += 1; std::thread::sleep(std::time::Duration::from_millis(100)); } }}); ``` ```{rust} *counter.lock().unwrap() ``` ```{rust} *counter.lock().unwrap() ``` ## Loading external crates We can load external crates. This one takes a while to compile, but once it's compiled, subsequent cells shouldn't need to recompile it, so it should be much quicker. ```{rust} // :dep base64 = "0.10.1" base64::encode(&vec![1, 2, 3, 4]) ``` ## Customizing how types are displayed We can also customize how our types are displayed, including presenting them as HTML. Here's an example where we define a custom display function for a type `Matrix`. ```{rust} use std::fmt::Debug; pub struct Matrix {pub values: Vec, pub row_size: usize} impl Matrix { pub fn evcxr_display(&self) { let mut html = String::new(); html.push_str(""); for r in 0..(self.values.len() / self.row_size) { html.push_str(""); for c in 0..self.row_size { html.push_str(""); } html.push_str(""); } html.push_str("
"); html.push_str(&format!("{:?}", self.values[r * self.row_size + c])); html.push_str("
"); println!("EVCXR_BEGIN_CONTENT text/html\n{}\nEVCXR_END_CONTENT", html); } } ``` ```{rust} let m = Matrix {values: vec![1,2,3,4,5,6,7,8,9], row_size: 3}; m ``` We can also return images, we just need to base64 encode them. First, we set up code for displaying RGB and grayscale images. ```{rust} extern crate image; extern crate base64; pub trait EvcxrResult {fn evcxr_display(&self);} impl EvcxrResult for image::RgbImage { fn evcxr_display(&self) { let mut buffer = Vec::new(); image::png::PNGEncoder::new(&mut buffer).encode(&**self, self.width(), self.height(), image::ColorType::RGB(8)).unwrap(); let img = base64::encode(&buffer); println!("EVCXR_BEGIN_CONTENT image/png\n{}\nEVCXR_END_CONTENT", img); } } impl EvcxrResult for image::GrayImage { fn evcxr_display(&self) { let mut buffer = Vec::new(); image::png::PNGEncoder::new(&mut buffer).encode(&**self, self.width(), self.height(), image::ColorType::Gray(8)).unwrap(); let img = base64::encode(&buffer); println!("EVCXR_BEGIN_CONTENT image/png\n{}\nEVCXR_END_CONTENT", img); } } ``` ```{rust} image::ImageBuffer::from_fn(256, 256, |x, y| { if (x as i32 - y as i32).abs() < 3 { image::Rgb([0, 0, 255]) } else { image::Rgb([0, 0, 0]) } }) ``` ## Display of compilation errors Here's how compilation errors are presented. Here we forgot an & and passed a String instead of an &str. ```{rust} let mut s = String::new(); s.push_str(format!("foo {}", 42)); ``` ## Seeing what variables have been defined We can print a table of defined variables and their types with the :vars command. ```{rust} // :vars ``` Other built-in commands can be found via :help ```{rust} // :help ``` ```{rust} ``` ================================================ FILE: tests/data/notebooks/outputs/ipynb_to_Rmd/frozen_cell.Rmd ================================================ --- jupyter: kernelspec: display_name: Python 3 language: python name: python3 --- ```{python} # This is an unfrozen cell. Works as usual. print("I'm a regular cell so I run and print!") ``` ```{python deletable=FALSE, editable=FALSE, run_control={'frozen': True}, eval=FALSE} # This is an frozen cell print("I'm frozen so Im not executed :(") ``` ================================================ FILE: tests/data/notebooks/outputs/ipynb_to_Rmd/fsharp.Rmd ================================================ --- jupyter: kernelspec: display_name: .NET (F#) language: F# name: .net-fsharp --- This notebook was inspired by [Plottting with XPlot](https://github.com/dotnet/interactive/blob/master/NotebookExamples/fsharp/Docs/Plotting%20with%20Xplot.ipynb). ```{fsharp} open XPlot.Plotly ``` ```{fsharp} let bar = Bar( name = "Bar 1", x = ["A"; "B"; "C"], y = [1; 3; 2]) [bar] |> Chart.Plot |> Chart.WithTitle "A sample bar plot" ``` ================================================ FILE: tests/data/notebooks/outputs/ipynb_to_Rmd/gnuplot_notebook.Rmd ================================================ --- jupyter: kernelspec: display_name: gnuplot language: gnuplot name: gnuplot --- # Sample gnuplot notebook ## Simple plotting ```{gnuplot} # Plot sin and cos with different linetypes f(x) = sin(x) g(x) = cos(x) set xrange[0:2*pi] set xtics(0, "{/Symbol p}" pi , "2{/Symbol p}" 2*pi) set ytics 1 plot f(x) linewidth 2 title "sin(x)", \ g(x) linewidth 2 dashtype "--" title "cos(x)" ``` ## Example of line magic ```{gnuplot} # %gnuplot inline pngcairo enhanced background rgb "#EEEEEE" size 600, 600 # Parametric plot without border reset set parametric set size ratio -1 unset border unset tics plot f(t), g(t) linewidth 2 notitle ``` ================================================ FILE: tests/data/notebooks/outputs/ipynb_to_Rmd/haskell_notebook.Rmd ================================================ --- jupyter: kernelspec: display_name: Haskell language: haskell name: haskell --- # Example Haskell Notebook Define a function to add two numbers. ```{haskell} f :: Num a => a -> a -> a f x y = x + y ``` Try to use the function ```{haskell} f 1 2 ``` ================================================ FILE: tests/data/notebooks/outputs/ipynb_to_Rmd/hello_world_gonb.Rmd ================================================ --- jupyter: kernelspec: display_name: Go (gonb) language: go name: gonb --- A notebook that use [GoNB](https://github.com/janpfeifer/gonb) the code below comes from [tutorial.ipynb](https://github.com/janpfeifer/gonb/blob/main/examples/tutorial.ipynb) ```{go} func main() { fmt.Printf("Hello World!") } ``` ```{go} %% fmt.Printf("Hello World!") ``` %% --who=world can pass flags to main func ```{go} import ( "flag" "fmt" ) var flagWho = flag.String("who", "", "Your name!") %% --who=world fmt.Printf("Hello %s!\n", *flagWho) ``` %args also can pass flags ```{go} // %args --who=Wally func main() { flag.Parse() fmt.Printf("Where is %s?", *flagWho) } ``` ```{go} import "github.com/janpfeifer/gonb/gonbui" %% gonbui.DisplayHtml(`I 🧡 GoNB!`) ``` ```{go} %% gonbui.DisplayMarkdown("#### Objective\n\n1. Have fun coding **Go**;\n1. Profit...\n"+ `$$f(x) = \int_{-\infty}^{\infty} e^{-x^2} dx$$`) ``` ```{go} func init_a() { fmt.Println("init_a") } %% fmt.Println("main") ``` ================================================ FILE: tests/data/notebooks/outputs/ipynb_to_Rmd/html-demo.Rmd ================================================ --- jupyter: kernelspec: display_name: Clojure language: clojure name: clojure --- # Clojupyter Demo This example notebook is from the [Clojupyter](https://github.com/clojupyter/clojupyter/blob/1637f6b2557f01db1e35bae5389bc38522eefe9a/examples/html-demo.ipynb) project. This notebook demonstrates some of the more advanced features of Clojupyter. ## Displaying HTML To display HTML, you'll need to require a clojupyter helper function to change the cell output ```{clojure} (require '[clojupyter.misc.display :as display]) ``` ```{clojure} (println ">> should print some text") ;; displaying html (display/hiccup-html [:ul [:li "a " [:i "emphatic"] " idea"] [:li "a " [:b "bold"] " idea"] [:li "an " [:span {:style "text-decoration: underline;"} "important"] " idea"]]) ``` We can also use this to render SVG: ```{clojure} (display/hiccup-html [:svg {:height 100 :width 100 :xmlns "http://www.w3.org/2000/svg"} [:circle {:cx 50 :cy 40 :r 40 :fill "red"}]]) ``` ## Adding External Clojure Dependencies You can fetch external Clojure dependencies using the `clojupyter.misc.helper` namespace. ```{clojure} (require '[clojupyter.misc.helper :as helper]) ``` ```{clojure} (helper/add-dependencies '[org.clojure/data.json "0.2.6"]) (require '[clojure.data.json :as json]) ``` ```{clojure} (json/write-str {:a 1 :b [2, 3] :c "c"}) ``` ## Adding External Javascript Dependency Since you can render arbitrary HTML using `display/hiccup-html`, it's pretty easy to use external Javascript libraries to do things like generate charts. Here's an example using [Highcharts](https://www.highcharts.com/). First, we use a cell to add javascript to the running notebook: ```{clojure} (helper/add-javascript "https://code.highcharts.com/highcharts.js") ``` Now we define a function which takes Clojure data and returns hiccup HTML to display: ```{clojure} (defn plot-highchart [highchart-json] (let [id (str (java.util.UUID/randomUUID)) code (format "Highcharts.chart('%s', %s );" id, (json/write-str highchart-json))] (display/hiccup-html [:div [:div {:id id :style {:background-color "red"}}] [:script code]]))) ``` Now we can make generate interactive plots (try hovering over plot): ```{clojure} (def raw-data (map #(+ (* 22 (+ % (Math/random)) 78)) (range))) (def data-1 (take 500 raw-data)) (def data-2 (take 500 (drop 500 raw-data))) (plot-highchart {:chart {:type "line"} :title {:text "Plot of random data"} :series [{:data data-1} {:data data-2}]}) ``` ```{clojure} ``` ================================================ FILE: tests/data/notebooks/outputs/ipynb_to_Rmd/ijavascript.Rmd ================================================ --- jupyter: kernelspec: display_name: Javascript (Node.js) language: javascript name: javascript --- ## A notebook that uses IJavascript kernel ```{javascript} let x = 5; const y = 6; var z = 10; ``` ```{javascript} x + y; ``` ```{javascript} function add(num1, num2) { return num1 + num2 } ``` ```{javascript} add(x, y); ``` ```{javascript} const arrowAdd = (num1, num2) => num1 + num2; ``` ```{javascript} arrowAdd(x, y); ``` ```{javascript} const myCar = { color: "blue", weight: 850, model: "fiat", start: () => "car started!", doors: [1,2,3,4] } ``` ```{javascript} console.log("color:", myCar.color); ``` ```{javascript} console.log("start:", myCar.start()); ``` ```{javascript} for (let door of myCar.doors) { console.log("I'm door", door) } ``` ```{javascript} myCar; ``` ```{javascript} class User { constructor(name){ this.name = name; } sayHello(){ return "Hello, I'm " + this.name; } } ``` ```{javascript} let John = new User("John"); John.sayHello(); ``` ================================================ FILE: tests/data/notebooks/outputs/ipynb_to_Rmd/ir_notebook.Rmd ================================================ --- jupyter: kernelspec: display_name: R language: R name: ir --- This is a jupyter notebook that uses the IR kernel. ```{r} sum(1:10) ``` ```{r} plot(cars) ``` ```{r} ``` ================================================ FILE: tests/data/notebooks/outputs/ipynb_to_Rmd/itypescript.Rmd ================================================ --- jupyter: kernelspec: display_name: Typescript 3.5 language: typescript name: typescript --- ```{typescript} let x: number = 5; const y: number = 6; var z: string = "hi"; console.log(z); x + y; ``` ```{typescript} function add(num1: number, num2: number): number { return num1 + num2 } add(x, y); ``` ```{typescript} const arrowAdd = (num1: number, num2: number) => num1 + num2; arrowAdd(x, y); ``` ```{typescript} class User { constructor(private name: string) { this.name = name; } sayHello(): string { return "Hello, I'm " + this.name; } } let John: User; John = new User("John"); John.sayHello(); ``` ================================================ FILE: tests/data/notebooks/outputs/ipynb_to_Rmd/julia_benchmark_plotly_barchart.Rmd ================================================ --- jupyter: kernelspec: display_name: Julia 1.1.1 language: julia name: julia-1.1 --- ```{julia} # IJulia rocks! So does Plotly. Check it out using Plotly api_key = "" # visit https://plot.ly/api to generate an API username and password username = "" Plotly.signin(username, api_key) ``` ```{julia} # Following data taken from http://julialang.org/ frontpage benchmarks = ["fib", "parse_int", "quicksort3", "mandel", "pi_sum", "rand_mat_stat", "rand_mat_mul"] platforms = ["Fortran", "Julia", "Python", "R", "Matlab", "Mathematica", "Javascript", "Go"] data = { platforms[1] => [0.26, 5.03, 1.11, 0.86, 0.80, 0.64, 0.96], platforms[2] => [0.91, 1.60, 1.14, 0.85, 1.00, 1.66, 1.01], platforms[3] => [30.37, 13.95, 31.98, 14.19, 16.33, 13.52, 3.41 ], platforms[4] => [411.36, 59.40, 524.29, 106.97, 15.42, 10.84, 3.98 ], platforms[5] => [1992.00, 1463.16, 101.84, 64.58, 1.29, 6.61, 1.10 ], platforms[6] => [64.46, 29.54, 35.74, 6.07, 1.32, 4.52, 1.16 ], platforms[7] => [2.18, 2.43, 3.51, 3.49, 0.84, 3.28, 14.60], platforms[8] => [1.03, 4.79, 1.25, 2.36, 1.41, 8.12, 8.51] } pdata = [ {"x"=>benchmarks,"y"=>data[k],"bardir"=>"h","type"=>"bar","name"=>k} for k = platforms ] layout = { "title"=> "Julia benchmark comparison (smaller is better, C performance = 1.0)", "barmode"=> "group", "autosize"=> false, "width"=> 900, "height"=> 900, "titlefont"=> { "family"=> "Open Sans", "size"=> 18, "color"=> "rgb(84, 39, 143)" }, "margin"=> {"l"=>160, "pad"=>0}, "xaxis"=> { "title"=> "Benchmark log-time", "type"=> "log" }, "yaxis"=> {"title"=> "Benchmark Name"} } response = Plotly.plot(pdata,["layout"=>layout]) # Embed in an iframe within IJulia s = string("") display("text/html", s) ``` ```{julia} # checkout https://plot.ly/api/ for more Julia examples! # But to show off some other Plotly features: x = 1:1500 y1 = sin(2*pi*x/1500.) + rand(1500)-0.5 y2 = sin(2*pi*x/1500.) fish = {"x"=>x,"y"=> y1, "type"=>"scatter","mode"=>"markers", "marker"=>{"color"=>"rgb(0, 0, 255)","opacity"=>0.5 } } fit = {"x"=> x,"y"=> y2, "type"=>"scatter", "mode"=>"markers", "opacity"=>0.8, "marker"=>{"color"=>"rgb(255, 0, 0)"} } layout = {"autosize"=> false, "width"=> 650, "height"=> 550, "title"=>"Fish School", "xaxis"=>{ "ticks"=> "", "gridcolor"=> "white", "zerolinecolor"=> "white", "linecolor"=> "white", "autorange"=> false, "range"=>[0,1500] }, "yaxis"=>{ "ticks"=> "", "gridcolor"=> "white", "zerolinecolor"=> "white", "linecolor"=> "white", "autorange"=> false, "range"=>[-2.2,2.2] }, "plot_bgcolor"=> "rgb(245,245,247)", "showlegend"=> false, "hovermode"=> "closest"} response = Plotly.plot([fish, fit],["layout"=>layout]) s = string("") display("text/html", s) ``` ================================================ FILE: tests/data/notebooks/outputs/ipynb_to_Rmd/julia_functional_geometry.Rmd ================================================ --- jupyter: kernelspec: display_name: Julia 1.1.1 language: julia name: julia-1.1 --- ```{julia} # This notebook is a semi top-down explanation. This cell needs to be # executed first so that the operators and helper functions are defined # All of this is explained in the later half of the notebook using Compose, Interact Compose.set_default_graphic_size(2inch, 2inch) points_f = [ (.1, .1), (.9, .1), (.9, .2), (.2, .2), (.2, .4), (.6, .4), (.6, .5), (.2, .5), (.2, .9), (.1, .9), (.1, .1) ] f = compose(context(), stroke("black"), line(points_f)) rot(pic) = compose(context(rotation=Rotation(-deg2rad(90))), pic) flip(pic) = compose(context(mirror=Mirror(deg2rad(90), 0.5w, 0.5h)), pic) above(m, n, p, q) = compose(context(), (context(0, 0, 1, m/(m+n)), p), (context(0, m/(m+n), 1, n/(m+n)), q)) above(p, q) = above(1, 1, p, q) beside(m, n, p, q) = compose(context(), (context(0, 0, m/(m+n), 1), p), (context(m/(m+n), 0, n/(m+n), 1), q)) beside(p, q) = beside(1, 1, p, q) over(p, q) = compose(context(), (context(), p), (context(), q)) rot45(pic) = compose(context(0, 0, 1/sqrt(2), 1/sqrt(2), rotation=Rotation(-deg2rad(45), 0w, 0h)), pic) # Utility function to zoom out and look at the context zoomout(pic) = compose(context(), (context(0.2, 0.2, 0.6, 0.6), pic), (context(0.2, 0.2, 0.6, 0.6), fill(nothing), stroke("black"), strokedash([0.5mm, 0.5mm]), polygon([(0, 0), (1, 0), (1, 1), (0, 1)]))) function read_path(p_str) tokens = [try parsefloat(x) catch symbol(x) end for x in split(p_str, r"[\s,]+")] path(tokens) end fish = compose(context(units=UnitBox(260, 260)), stroke("black"), read_path(strip(readall("fish.path")))) rotatable(pic) = @manipulate for θ=0:0.001:2π compose(context(rotation=Rotation(θ)), pic) end blank = compose(context()) fliprot45(pic) = rot45(compose(context(mirror=Mirror(deg2rad(-45))),pic)) # Hide this cell. display(MIME("text/html"), """""") ``` # Functional Geometry *Functional Geometry* is a paper by Peter Henderson ([original (1982)](users.ecs.soton.ac.uk/peter/funcgeo.pdf), [revisited (2002)](https://cs.au.dk/~hosc/local/HOSC-15-4-pp349-365.pdf)) which deconstructs the MC Escher woodcut *Square Limit* ![Square Limit](http://i.imgur.com/LjRzmNM.png) > A picture is an example of a complex object that can be described in terms of its parts. Yet a picture needs to be rendered on a printer or a screen by a device that expects to be given a sequence of commands. Programming that sequence of commands directly is much harder than having an application generate the commands automatically from the simpler, denotational description. A `picture` is a *denotation* of something to draw. e.g. The value of f here denotes the picture of the letter F Original at http://nbviewer.jupyter.org/github/shashi/ijulia-notebooks/blob/master/funcgeo/Functional%20Geometry.ipynb ## In conclusion We described Escher's *Square Limit* from the description of its smaller parts, which in turn were described in terms of their smaller parts. This seemed simple because we chose to talk in terms of an *algebra* to describe pictures. The primitives `rot`, `flip`, `fliprot45`, `above`, `beside` and `over` fit the job perfectly. We were able to describe these primitives in terms of `compose` `contexts`, which the Compose library knows how to render. Denotation can be an easy way to describe a system as well as a practical implementation method. [Abstraction barriers](https://mitpress.mit.edu/sicp/full-text/sicp/book/node29.html) are useful tools that can reduce the cognitive overhead on the programmer. It entails creating layers consisting of functions which only use functions in the same layer or layers below in their own implementation. The layers in our language were: ------------------[ squarelimit ]------------------ -------------[ quartet, cycle, nonet ]------------- ---[ rot, flip, fliprot45, above, beside, over ]--- -------[ compose, context, line, path,... ]-------- Drawing this diagram out is a useful way to begin building any library. ================================================ FILE: tests/data/notebooks/outputs/ipynb_to_Rmd/jupyter.Rmd ================================================ --- jupyter: kernelspec: display_name: Python 3 language: python name: python3 --- # Jupyter notebook This notebook is a simple jupyter notebook. It only has markdown and code cells. And it does not contain consecutive markdown cells. We start with an addition: ```{python} a = 1 b = 2 a + b ``` Now we return a few tuples ```{python} a, b ``` ```{python} a, b, a+b ``` And this is already the end of the notebook ================================================ FILE: tests/data/notebooks/outputs/ipynb_to_Rmd/jupyter_again.Rmd ================================================ --- jupyter: kernelspec: display_name: Python 3 language: python name: python3 --- ```{python} c = ''' title: "Quick test" output: ioslides_presentation: widescreen: true smaller: true editor_options: chunk_output_type console ''' ``` ```{python} import yaml print(yaml.dump(yaml.load(c))) ``` ```{python} # ?next ``` ================================================ FILE: tests/data/notebooks/outputs/ipynb_to_Rmd/jupyter_with_raw_cell_in_body.Rmd ================================================ --- jupyter: kernelspec: display_name: Python 3 language: python name: python3 --- ```{python} 1+2+3 ``` ```{python active="", eval=FALSE} This is a raw cell ``` This is a markdown cell ================================================ FILE: tests/data/notebooks/outputs/ipynb_to_Rmd/jupyter_with_raw_cell_on_top.Rmd ================================================ --- title: Quick test output: ioslides_presentation: widescreen: true smaller: true editor_options: chunk_output_type: console jupyter: kernelspec: display_name: Python 3 language: python name: python3 --- ```{python} 1+2+3 ``` ```{python} ``` ================================================ FILE: tests/data/notebooks/outputs/ipynb_to_Rmd/jupyter_with_raw_cell_with_invalid_yaml.Rmd ================================================ --- title: Exception: Test jupyter: kernelspec: display_name: Python 3 (ipykernel) language: python name: python3 --- ```{python} 1 + 2 + 3 ``` ================================================ FILE: tests/data/notebooks/outputs/ipynb_to_Rmd/jupyterlab-slideshow_1441.Rmd ================================================ --- jupyter: kernelspec: display_name: Python 3 (ipykernel) language: python name: python3 --- > **Note** > > `slide` layer with a `top` of `30%` ================================================ FILE: tests/data/notebooks/outputs/ipynb_to_Rmd/jupytext_replication.Rmd ================================================ --- jupyter: kernelspec: display_name: SoS language: sos name: sos --- # Text SOS-kernel with Jupytext ## What is SOS kernel SoS consists of a ployglot notebook that allows the use of multiple kernels in one Jupyter notebook, and a workflow system that is designed for daily computational research. Basically, - SoS Polyglot Notebook is a Jupyter Notebook with a SoS kernel. - SoS Notebook serves as a super kernel to all other Jupyter kernels and allows the use of multiple kernels in one Jupyter notebook. - SoS Workflow System is a Python based workflow system that is designed to be readable, shareable, and suitable for daily data analysis. - SoS Workflow System can be used from command line or use SoS Notebook as its IDE. ![](https://vatlab.github.io/sos-docs/doc/media/SoS_Notebook_and_Workflow.png) ### How to install SOS-kernel Please follow this [link](https://vatlab.github.io/sos-docs/running.html#Conda-installation) to setup SOS I run some issue with the latest version of R on my Mac, so I had to install an earlier version of R ``` conda install -c r r=3.5.1 conda install sos-notebook jupyterlab-sos sos-papermill -c conda-forge ``` ## Related issue with Jupytext Jupytext works fine with Python/R kernel but converts code cells into markdown cells when using the SOS kernel. cf the image below. It is a code cell. After saving the notebook and restart it, it converted the code cell into markdown Screenshot 2020-03-13 at 10 51 18 ## Step 1 Please, choose SOS Kernel and then, in the cell code, choose SOS (or any other kernel available), the outcome is the same. ![](https://drive.google.com/uc?export=view&id=1OtyxfwoRyVK23XHnmd9JR-crBgHBL5mt) ```{sos Collapsed="false", kernel="SoS"} import pandas as pd import numpy as np pd.DataFrame({ 'x': np.random.random(10), 'y': np.random.random(10), }) ``` ## Step 2 Now, pair it with Jupytex ![](https://drive.google.com/uc?export=view&id=1Wtx-YPAXY8HWHqzCcy4iIgHpzt_9emEn) ### Step 3 Save the notebook, restart and clear all, **save**, then Shut down kernel. Close the notebook and reopen ### Step 4 Reopen the notebook. Here is the outcome ![](https://drive.google.com/uc?export=view&id=12C70unbSPv0gHCZaCICEUy7kO7wM93JH) ================================================ FILE: tests/data/notebooks/outputs/ipynb_to_Rmd/kalman_filter_and_visualization.Rmd ================================================ --- jupyter: kernelspec: display_name: Q 3.5 language: q name: qpk --- ```{q} plt: .p.import`matplotlib.pyplot ``` ```{q} filter: { t: ([] x: `float $ x; xh: `float $ x; p: (count x) # R: var x); (first t), iterate[R; R]\[first t; 1 _ t] } iterate: {[Q; R; x; y] x[`p]+: Q; k: x[`p] % R + x[`p]; `x`xh`p ! (y[`x]; x[`xh] + k * y[`x] - x[`xh]; (1 - k) * x[`p]) } ``` ```{q} price: 100 + sums 0.5 - (n:50)?1. ``` ```{q} output:filter price ``` ```{q} plt[`:plot][til n; output`x; `label pykw "price"]; plt[`:plot][til n; output`xh;`label pykw "forecast"]; plt[`:legend][]; plt[`:show][]; ``` ```{q} ``` ================================================ FILE: tests/data/notebooks/outputs/ipynb_to_Rmd/logtalk_notebook.Rmd ================================================ --- jupyter: kernelspec: display_name: Logtalk language: logtalk name: logtalk_kernel --- # An implementation of the Ackermann function ```{logtalk vscode={'languageId': 'logtalk'}} %%load ack.lgt :- object(ack). :- info([ version is 1:0:0, author is 'Paulo Moura', date is 2008-3-31, comment is 'Ackermann function (general recursive function).' ]). :- public(ack/3). :- mode(ack(+integer, +integer, -integer), one). :- info(ack/3, [ comment is 'Ackermann function.', argnames is ['M', 'N', 'V'] ]). ack(0, N, V) :- !, V is N + 1. ack(M, 0, V) :- !, M2 is M - 1, ack(M2, 1, V). ack(M, N, V) :- M2 is M - 1, N2 is N - 1, ack(M, N2, V2), ack(M2, V2, V). :- end_object. ``` ## Sample query ```{logtalk vscode={'languageId': 'logtalk'}} ack::ack(2, 4, V). ``` ================================================ FILE: tests/data/notebooks/outputs/ipynb_to_Rmd/lua_example.Rmd ================================================ --- jupyter: kernelspec: display_name: Lua language: lua name: lua --- Source: https://www.lua.org/pil/19.3.html # Sort Another useful function on arrays is table.sort, which we have seen before. It receives the array to be sorted, plus an optional order function. This order function receives two arguments and must return true if the first argument should come first in the sorted array. If this function is not provided, sort uses the default less-than operation (corresponding to the `<´ operator). A common mistake is to try to order the indices of a table. In a table, the indices form a set, and have no order whatsoever. If you want to order them, you have to copy them to an array and then sort the array. Let us see an example. Suppose that you read a source file and build a table that gives, for each function name, the line where that function is defined; something like this: ```{lua} lines = { luaH_set = 10, luaH_get = 24, luaH_present = 48, } ``` Now you want to print these function names in alphabetical order. If you traverse this table with pairs, the names appear in an arbitrary order. However, you cannot sort them directly, because these names are keys of the table. However, when you put these names into an array, then you can sort them. First, you must create an array with those names, then sort it, and finally print the result: ```{lua} a = {} for n in pairs(lines) do table.insert(a, n) end table.sort(a) for i,n in ipairs(a) do print(n) end ``` Note that, for Lua, arrays also have no order. But we know how to count, so we get ordered values as long as we access the array with ordered indices. That is why you should always traverse arrays with ipairs, rather than pairs. The first imposes the key order 1, 2, ..., whereas the latter uses the natural arbitrary order of the table. As a more advanced solution, we can write an iterator that traverses a table following the order of its keys. An optional parameter f allows the specification of an alternative order. It first sorts the keys into an array, and then iterates on the array. At each step, it returns the key and value from the original table: ```{lua} function pairsByKeys (t, f) local a = {} for n in pairs(t) do table.insert(a, n) end table.sort(a, f) local i = 0 -- iterator variable local iter = function () -- iterator function i = i + 1 if a[i] == nil then return nil else return a[i], t[a[i]] end end return iter end ``` With this function, it is easy to print those function names in alphabetical order. The loop ```{lua} for name, line in pairsByKeys(lines) do print(name, line) end ``` ================================================ FILE: tests/data/notebooks/outputs/ipynb_to_Rmd/maxima_example.Rmd ================================================ --- jupyter: kernelspec: display_name: Maxima language: maxima name: maxima --- ## maxima misc ```{maxima} kill(all)$ ``` ```{maxima} f(x) := 1/(x^2+l^2)^(3/2); ``` ```{maxima} integrate(f(x), x); ``` ```{maxima} tex(%)$ ``` ```{maxima} ``` ================================================ FILE: tests/data/notebooks/outputs/ipynb_to_Rmd/notebook_with_complex_metadata.Rmd ================================================ --- jupyter: kernelspec: display_name: Python 3 language: python name: python3 --- ```{python} ``` ================================================ FILE: tests/data/notebooks/outputs/ipynb_to_Rmd/nteract_with_parameter.Rmd ================================================ --- jupyter: kernel_info: name: python3 kernelspec: display_name: Python 3 language: python name: python3 --- ```{python inputHidden=FALSE, outputHidden=FALSE, tags=c("parameters")} param = 4 ``` ```{python inputHidden=FALSE, outputHidden=FALSE} import pandas as pd ``` ```{python inputHidden=FALSE, outputHidden=FALSE} df = pd.DataFrame({'A': [1, 2], 'B': [3 + param, 4]}, index=pd.Index(['x0', 'x1'], name='x')) df ``` ```{python inputHidden=FALSE, outputHidden=FALSE} # %matplotlib inline df.plot(kind='bar') ``` ================================================ FILE: tests/data/notebooks/outputs/ipynb_to_Rmd/ocaml_notebook.Rmd ================================================ --- jupyter: jupytext: formats: ipynb:markdown,md kernelspec: display_name: OCaml default language: OCaml name: ocaml-jupyter --- # Example of an OCaml notebook ```{ocaml} let sum x y = x + y ``` Let's try our function: ```{ocaml} sum 3 4 = 7 + 0 ``` ================================================ FILE: tests/data/notebooks/outputs/ipynb_to_Rmd/octave_notebook.Rmd ================================================ --- jupyter: kernelspec: display_name: Octave language: octave name: octave --- A markdown cell ```{octave} 1 + 1 ``` ```{octave} % a code cell with comments 2 + 2 ``` ```{octave} % a simple plot x = -10:0.1:10; plot (x, sin (x)); ``` ```{octave} %plot -w 800 % a simple plot with a magic instruction x = -10:0.1:10; plot (x, sin (x)); ``` And to finish with, a Python cell ```{python} a = 1 ``` ```{python} a + 1 ``` ================================================ FILE: tests/data/notebooks/outputs/ipynb_to_Rmd/plotly_graphs.Rmd ================================================ --- jupyter: kernelspec: display_name: Python 3 language: python name: python3 --- This notebook contains complex outputs, including plotly javascript graphs. # Interactive plots We use Plotly's connected mode to make the notebook lighter - when connected, the notebook downloads the `plotly.js` library from the web. ```{python} import plotly.offline as offline offline.init_notebook_mode(connected=True) ``` ```{python} import plotly.graph_objects as go fig = go.Figure( data=[go.Bar(y=[2, 3, 1])], layout=go.Layout(title="bar plot")) fig.show() fig.data[0].marker = dict(color='purple') fig ``` ================================================ FILE: tests/data/notebooks/outputs/ipynb_to_Rmd/powershell.Rmd ================================================ --- jupyter: kernelspec: display_name: PowerShell language: PowerShell name: powershell --- This is an extract from https://github.com/Jaykul/Jupyter-PowerShell/blob/master/LiterateDevOps.ipynb ```{powershell} $imageUrl = 'https://upload.wikimedia.org/wikipedia/commons/2/2f/PowerShell_5.0_icon.png' $ImageData = @{ "png" = (Invoke-WebRequest $imageUrl -UseBasicParsing).RawContentStream.GetBuffer() } # $ImageData Write-Jupyter -InputObject $ImageData -Metadata @{ "image/png" = @{ 'width' = 32 } } Write-Jupyter -InputObject $ImageData -Metadata @{ "image/png" = @{ 'width' = 64 } } ``` ================================================ FILE: tests/data/notebooks/outputs/ipynb_to_Rmd/raw_cell_with_complex_yaml_like_content.Rmd ================================================ --- This is a complex paragraph that is split over multiple lines. It also includes blank lines. jupyter: kernelspec: display_name: Python 3 language: python name: python3 --- ```{python} print("Hello, World!") ``` ================================================ FILE: tests/data/notebooks/outputs/ipynb_to_Rmd/raw_cell_with_non_dict_yaml_content.Rmd ================================================ --- Content. jupyter: kernelspec: display_name: Python 3 language: python name: python3 --- ```{python} print("Hello, World!") ``` ================================================ FILE: tests/data/notebooks/outputs/ipynb_to_Rmd/root_cpp.Rmd ================================================ --- jupyter: kernelspec: display_name: ROOT C++ language: c++ name: root --- ```{c++} #include #include ``` ```{c++} int k = 4; std::string foo = "This string says \"foo\""; ``` ```{c++} std::cout << "k = " << k << '\n' << foo << '\n'; ``` ================================================ FILE: tests/data/notebooks/outputs/ipynb_to_Rmd/sage_print_hello.Rmd ================================================ --- jupyter: kernelspec: display_name: SageMath 9.2 language: sage name: sagemath --- ```{sage} print("Hello world") ``` ================================================ FILE: tests/data/notebooks/outputs/ipynb_to_Rmd/sample_bash_notebook.Rmd ================================================ --- jupyter: kernelspec: display_name: Bash language: bash name: bash --- ```{bash} ls ``` ```{bash} # https://coderwall.com/p/euwpig/a-better-git-log git config --global alias.lg "log --color --graph --pretty=format:'%Cred%h%Creset -%C(yellow)%d%Creset %s %Cgreen(%cr) %C(bold blue)<%an>%Creset' --abbrev-commit" ``` ```{bash} git lg ``` ================================================ FILE: tests/data/notebooks/outputs/ipynb_to_Rmd/sample_rise_notebook_66.Rmd ================================================ --- jupyter: kernelspec: display_name: Python 3 language: python name: python3 --- A markdown cell ```{python slideshow={'slide_type': ''}} 1+1 ``` Markdown cell two ================================================ FILE: tests/data/notebooks/outputs/ipynb_to_Rmd/sas.Rmd ================================================ --- jupyter: kernelspec: display_name: SAS language: sas name: sas --- # SAS Notebooks with jupytext ```{sas} proc sql; select * from sashelp.cars (obs=10) ; quit; ``` ```{sas} %let name = "Jupytext"; ``` ```{sas} %put &name; ``` ```{sas} /* Note when defining macros "%macro" cannot be the first line of text in the cell */ %macro test; data temp; set sashelp.cars; name = "testx"; run; proc print data = temp (obs=10); run; %mend test; %test ``` ================================================ FILE: tests/data/notebooks/outputs/ipynb_to_Rmd/simple-helloworld.Rmd ================================================ --- jupyter: jupytext: encoding: '// -*- coding: utf-8 -*-' formats: ipynb,java:light kernelspec: display_name: Java language: java name: java --- Let's define some class. ```{java} class A { public void hello() { System.out.println("Hello World"); } } ``` And now we call its method. ```{java} new A().hello(); ``` You can run it e.g. with `jshell` * from command line, as `jshell simple-helloworld.java` * from jshell's shell with `/open simple-helloworld.java` ================================================ FILE: tests/data/notebooks/outputs/ipynb_to_Rmd/simple_robot_notebook.Rmd ================================================ --- jupyter: kernelspec: display_name: Robot Framework language: robotframework name: robotkernel --- ```{robotframework} *** Settings *** Library Collections ``` ```{robotframework} *** Keywords *** Head [Arguments] ${list} ${value}= Get from list ${list} 0 [Return] ${value} ``` ```{robotframework} *** Tasks *** Get head ${array}= Create list 1 2 3 4 5 ${head}= Head ${array} Should be equal ${head} 1 ``` ================================================ FILE: tests/data/notebooks/outputs/ipynb_to_Rmd/simple_scala_notebook.Rmd ================================================ --- jupyter: kernelspec: display_name: Apache Toree - Scala language: scala name: apache_toree_scala --- ```{scala} // This is just a simple scala notebook object SampleObject { def calculation(x: Int, y: Int): Int = x + y } val result = SampleObject.calculation(1, 2) ``` ```{scala} println(result * 10) ``` ================================================ FILE: tests/data/notebooks/outputs/ipynb_to_Rmd/stata_notebook.Rmd ================================================ --- jupyter: kernelspec: display_name: Stata language: stata name: stata --- ```{stata} // This notebook uses the stata_kernel: https://github.com/kylebarron/stata_kernel ``` ```{stata} use http://www.stata-press.com/data/r13/auto ``` ```{stata} summarize ``` ```{stata} scatter weight length ``` ================================================ FILE: tests/data/notebooks/outputs/ipynb_to_Rmd/tailrecursive-factorial.Rmd ================================================ --- jupyter: jupytext: encoding: '// -*- coding: utf-8 -*-' formats: ipynb,groovy:light kernelspec: display_name: Groovy language: groovy name: groovy --- # TailRecursive annotation Let's check what is the effect of `@TailRecursive` annotation on the simple recursive definition of factorial function. ```{groovy} import groovy.transform.CompileStatic import groovy.transform.TailRecursive import groovy.transform.TypeChecked @CompileStatic @TypeChecked class X { static final BigInteger factorial0(int n) { (n <= 1) ? 1G : factorial0(n-1).multiply(BigInteger.valueOf(n)) } static final BigInteger factorial1(int n, BigInteger acc = 1G) { (n <= 1) ? acc : factorial1(n-1, acc.multiply(BigInteger.valueOf(n))) } @TailRecursive static final BigInteger factorial2(int n, BigInteger acc = 1G) { (n <= 1) ? acc : factorial2(n-1, acc.multiply(BigInteger.valueOf(n))) } } x = new X() ``` Although we can time the execution of the calls, it is not very accurate; such micro benchmarks should be performed in more controlled environment, such us under [JMH](https://openjdk.java.net/projects/code-tools/jmh/). For example, see [blog posts of Szymon Stępniak](https://e.printstacktrace.blog/tail-recursive-methods-in-groovy/). ```{groovy} // %%timeit x.factorial0(19_000).toString().length() ``` ```{groovy} // %%timeit x.factorial1(19_000).toString().length() ``` ```{groovy} // %%timeit x.factorial2(19_000).toString().length() ``` The real difference is the use of stack. Non-tail recursive calls exhaust the stack space at some point, whereas tail recursive calls don't add frames to the stack. ```{groovy} factSize = { n, cl -> println "Factorial of ${n} has ${cl(n).toString().length()} digits" } factSize 2_000, x.&factorial0 factSize 2_000, x.&factorial1 factSize 2_000, x.&factorial2 factSize 100_000, x.&factorial2 ``` ```{groovy} try { factSize 100_000, x.&factorial1 } catch (Throwable e) { assert e instanceof StackOverflowError println e } ``` ================================================ FILE: tests/data/notebooks/outputs/ipynb_to_Rmd/tcl_test.Rmd ================================================ --- jupyter: kernelspec: display_name: Tcl language: tcl name: tcljupyter --- # Assign Values ```{tcl} set a 1 puts "a = $a" ``` # Loop ```{tcl} for {set i 0} {$i < 10} {incr i} { puts "I inside first loop: $i" } ``` ```{tcl} ``` ================================================ FILE: tests/data/notebooks/outputs/ipynb_to_Rmd/text_outputs_and_images.Rmd ================================================ --- jupyter: kernelspec: display_name: Python 3 language: python name: python3 --- This notebook contains outputs of many different types: text, HTML, plots and errors. # Text outputs Using `print`, `sys.stdout` and `sys.stderr` ```{python} import sys print('using print') sys.stdout.write('using sys.stdout.write') sys.stderr.write('using sys.stderr.write') ``` ```{python} import logging logging.debug('Debug') logging.info('Info') logging.warning('Warning') logging.error('Error') ``` # HTML outputs Using `pandas`. Here we find two representations: both text and HTML. ```{python} import pandas as pd pd.DataFrame([4]) ``` ```{python} from IPython.display import display display(pd.DataFrame([5])) display(pd.DataFrame([6])) ``` # Images ```{python} # %matplotlib inline ``` ```{python} # First plot from matplotlib import pyplot as plt import numpy as np w, h = 3, 3 data = np.zeros((h, w, 3), dtype=np.uint8) data[0,:] = [0,255,0] data[1,:] = [0,0,255] data[2,:] = [0,255,0] data[1:3,1:3] = [255, 0, 0] plt.imshow(data) plt.axis('off') plt.show() # Second plot data[1:3,1:3] = [255, 255, 0] plt.imshow(data) plt.axis('off') plt.show() ``` # Errors ```{python} undefined_variable ``` ================================================ FILE: tests/data/notebooks/outputs/ipynb_to_Rmd/wolfram.Rmd ================================================ --- jupyter: kernelspec: display_name: Wolfram Language 13.1 language: Wolfram Language name: wolframlanguage13.1 --- **Note:** The `language_info` `file_extension` in this notebook should be `.m`, but it was deliberately changed to `.wolfram` to avoid conflicts with Matlab which is using the same extension. We start with... ```{wolfram language} Print["Hello, World!"]; ``` Then we draw the first example plot from the [ListPlot](https://reference.wolfram.com/language/ref/ListPlot.html) reference: ```{wolfram language} ListPlot[Prime[Range[25]]] ``` We also test the math outputs as in the [Simplify](https://reference.wolfram.com/language/ref/Simplify.html) example: ```{wolfram language} D[Integrate[1/(x^3 + 1), x], x] ``` ================================================ FILE: tests/data/notebooks/outputs/ipynb_to_Rmd/xcpp_by_quantstack.Rmd ================================================ --- jupyter: kernelspec: display_name: C++14 language: C++14 name: xeus-cling-cpp14 --- [![xeus-cling](images/xeus-cling.png)](https://github.com/QuantStack/xeus-cling/) A Jupyter kernel for C++ based on the `cling` C++ interpreter and the `xeus` native implementation of the Jupyter protocol, xeus. - GitHub repository: https://github.com/QuantStack/xeus-cling/ - Online documentation: https://xeus-cling.readthedocs.io/ ## Usage
To run the selected code cell, hit 
Shift + Enter
## Output and error streams `std::cout` and `std::cerr` are redirected to the notebook frontend. ```{c++} #include std::cout << "some output" << std::endl; ``` ```{c++} std::cerr << "some error" << std::endl; ``` ```{c++} #include ``` ```{c++} throw std::runtime_error("Unknown exception"); ``` Omitting the `;` in the last statement of a cell results in an output being printed ```{c++} int j = 5; ``` ```{c++} j ``` # Interpreting the C++ programming language `cling` has a broad support of the features of C++. You can define functions, classes, templates, etc ... ## Functions ```{c++} double sqr(double a) { return a * a; } ``` ```{c++} double a = 2.5; double asqr = sqr(a); asqr ``` ## Classes ```{c++} class Foo { public: virtual ~Foo() {} virtual void print(double value) const { std::cout << "Foo value = " << value << std::endl; } }; ``` ```{c++} Foo bar; bar.print(1.2); ``` ## Polymorphism ```{c++} class Bar : public Foo { public: virtual ~Bar() {} virtual void print(double value) const { std::cout << "Bar value = " << 2 * value << std::endl; } }; ``` ```{c++} Foo* bar2 = new Bar; bar2->print(1.2); delete bar2; ``` ## Templates ```{c++} #include template class FooT { public: explicit FooT(const T& t) : m_t(t) {} void print() const { std::cout << typeid(T).name() << " m_t = " << m_t << std::endl; } private: T m_t; }; template <> class FooT { public: explicit FooT(const int& t) : m_t(t) {} void print() const { std::cout << "m_t = " << m_t << std::endl; } private: int m_t; }; ``` ```{c++} FooT foot1(1.2); foot1.print(); ``` ```{c++} FooT foot2(4); foot2.print(); ``` ## C++11 / C++14 support ```{c++} class Foo11 { public: Foo11() { std::cout << "Foo11 default constructor" << std::endl; } Foo11(const Foo11&) { std::cout << "Foo11 copy constructor" << std::endl; } Foo11(Foo11&&) { std::cout << "Foo11 move constructor" << std::endl; } }; ``` ```{c++} Foo11 f1; Foo11 f2(f1); Foo11 f3(std::move(f1)); ``` ```{c++} #include std::vector v = { 1, 2, 3}; auto iter = ++v.begin(); v ``` ```{c++} *iter ``` ... and also lambda, universal references, `decltype`, etc ... ## Documentation and completion - Documentation for types of the standard library is retrieved on cppreference.com. - The quick-help feature can also be enabled for user-defined types and third-party libraries. More documentation on this feature is available at https://xeus-cling.readthedocs.io/en/latest/inline_help.html. ```{c++} ?std::vector ``` ## Using the `display_data` mechanism For a user-defined type `T`, the rich rendering in the notebook and JupyterLab can be enabled by by implementing the function `xeus::xjson mime_bundle_repr(const T& im)`, which returns the JSON mime bundle for that type. More documentation on the rich display system of Jupyter and Xeus-cling is available at https://xeus-cling.readthedocs.io/en/latest/rich_display.html ### Image example ```{c++} #include #include #include "xtl/xbase64.hpp" #include "xeus/xjson.hpp" namespace im { struct image { inline image(const std::string& filename) { std::ifstream fin(filename, std::ios::binary); m_buffer << fin.rdbuf(); } std::stringstream m_buffer; }; xeus::xjson mime_bundle_repr(const image& i) { auto bundle = xeus::xjson::object(); bundle["image/png"] = xtl::base64encode(i.m_buffer.str()); return bundle; } } ``` ```{c++} im::image marie("images/marie.png"); marie ``` ### Audio example ```{c++} #include #include #include "xtl/xbase64.hpp" #include "xeus/xjson.hpp" namespace au { struct audio { inline audio(const std::string& filename) { std::ifstream fin(filename, std::ios::binary); m_buffer << fin.rdbuf(); } std::stringstream m_buffer; }; xeus::xjson mime_bundle_repr(const audio& a) { auto bundle = xeus::xjson::object(); bundle["text/html"] = std::string(""; return bundle; } } ``` ```{c++} au::audio drums("audio/audio.wav"); drums ``` ### Display ```{c++} #include "xcpp/xdisplay.hpp" ``` ```{c++} xcpp::display(drums); ``` ### Update-display ```{c++} #include #include "xcpp/xdisplay.hpp" namespace ht { struct html { inline html(const std::string& content) { m_content = content; } std::string m_content; }; xeus::xjson mime_bundle_repr(const html& a) { auto bundle = xeus::xjson::object(); bundle["text/html"] = a.m_content; return bundle; } } // A red rectangle ht::html rect(R"(
Original
)"); ``` ```{c++} xcpp::display(rect, "some_display_id"); ``` ```{c++} // Update the rectangle to be blue rect.m_content = R"(
Updated
)"; xcpp::display(rect, "some_display_id", true); ``` ## Magics Magics are special commands for the kernel that are not part of the C++ language. They are defined with the symbol `%` for a line magic and `%%` for a cell magic. More documentation for magics is available at https://xeus-cling.readthedocs.io/en/latest/magics.html. ```{c++} #include #include ``` ```{c++} std::vector to_shuffle = {1, 2, 3, 4}; ``` ```{c++} // %timeit std::random_shuffle(to_shuffle.begin(), to_shuffle.end()); ``` [![xtensor](images/xtensor.png)](https://github.com/QuantStack/xtensor/) - GitHub repository: https://github.com/QuantStack/xtensor/ - Online documentation: https://xtensor.readthedocs.io/ - NumPy to xtensor cheat sheet: http://xtensor.readthedocs.io/en/latest/numpy.html `xtensor` is a C++ library for manipulating N-D arrays with an API very similar to that of numpy. ```{c++} #include #include "xtensor/xarray.hpp" #include "xtensor/xio.hpp" #include "xtensor/xview.hpp" xt::xarray arr1 {{1.0, 2.0, 3.0}, {2.0, 5.0, 7.0}, {2.0, 5.0, 7.0}}; xt::xarray arr2 {5.0, 6.0, 7.0}; xt::view(arr1, 1) + arr2 ``` Together with the C++ Jupyter kernel, `xtensor` offers a similar experience as `NumPy` in the Python Jupyter kernel, including broadcasting and universal functions. ```{c++} #include #include "xtensor/xarray.hpp" #include "xtensor/xio.hpp" ``` ```{c++} xt::xarray arr {1, 2, 3, 4, 5, 6, 7, 8, 9}; arr.reshape({3, 3}); std::cout << arr; ``` ```{c++} #include "xtensor-blas/xlinalg.hpp" ``` ```{c++} xt::xtensor m = {{1.5, 0.5}, {0.7, 1.0}}; std::cout << "Matrix rank: " << std::endl << xt::linalg::matrix_rank(m) << std::endl; std::cout << "Matrix inverse: " << std::endl << xt::linalg::inv(m) << std::endl; std::cout << "Eigen values: " << std::endl << xt::linalg::eigvals(m) << std::endl; ``` ```{c++} xt::xarray arg1 = xt::arange(9); xt::xarray arg2 = xt::arange(18); arg1.reshape({3, 3}); arg2.reshape({2, 3, 3}); std::cout << xt::linalg::dot(arg1, arg2) << std::endl; ``` ```{c++} ``` ================================================ FILE: tests/data/notebooks/outputs/ipynb_to_Rmd/xonsh_example.Rmd ================================================ --- jupyter: kernelspec: display_name: Xonsh language: xonsh name: xonsh --- ```{xonsh} len($(curl -L https://xon.sh)) ``` ```{xonsh} for filename in `.*`: print(filename) du -sh @(filename) ``` ================================================ FILE: tests/data/notebooks/outputs/ipynb_to_hydrogen/Line_breaks_in_LateX_305.py ================================================ # --- # jupyter: # kernelspec: # display_name: Python 3 # language: python # name: python3 # --- # %% [markdown] # This cell uses no particular cell marker # # $$ # \begin{align} # \dot{x} & = \sigma(y-x)\\ # \dot{y} & = \rho x - y - xz \\ # \dot{z} & = -\beta z + xy # \end{align} # $$ # %% [markdown] # This cell uses no particular cell marker, and a single slash in the $\LaTeX$ equation # # $$ # \begin{align} # \dot{x} & = \sigma(y-x) \ # \dot{y} & = \rho x - y - xz \ # \dot{z} & = -\beta z + xy # \end{align} # $$ # %% [markdown] ''' This cell uses the triple quote cell markers introduced at https://github.com/mwouts/jupytext/issues/305 $$ \begin{align} \dot{x} & = \sigma(y-x)\\ \dot{y} & = \rho x - y - xz \\ \dot{z} & = -\beta z + xy \end{align} $$ ''' ================================================ FILE: tests/data/notebooks/outputs/ipynb_to_hydrogen/Notebook with function and cell metadata 164.py ================================================ # --- # jupyter: # kernelspec: # display_name: Python 3 # language: python # name: python3 # --- # %% 1 + 1 # %% [markdown] # A markdown cell # And below, the cell for function f has non trivial cell metadata. And the next cell as well. # %% attributes={"classes": [], "id": "", "n": "10"} def f(x): return x # %% attributes={"classes": [], "id": "", "n": "10"} f(5) # %% [markdown] # More text # %% 2 + 2 ================================================ FILE: tests/data/notebooks/outputs/ipynb_to_hydrogen/Notebook with html and latex cells.py ================================================ # --- # jupyter: # kernelspec: # display_name: Python 3 # language: python # name: python3 # --- # %% %%html

Jupytext on GitHub

# %% %%latex $\frac{\pi}{2}$ # %% %load_ext rpy2.ipython # %% %%R library(ggplot2) ggplot(data=data.frame(x=c('A', 'B'), y=c(5, 2)), aes(x,weight=y)) + geom_bar() # %% %matplotlib inline import pandas as pd pd.Series({'A':5, 'B':2}).plot(figsize=(3,2), kind='bar') ================================================ FILE: tests/data/notebooks/outputs/ipynb_to_hydrogen/Notebook with many hash signs.py ================================================ # --- # jupyter: # kernelspec: # display_name: Python 3 # language: python # name: python3 # --- # %% [markdown] # ################################################################## # This is a notebook that contains many hash signs. # Hopefully its python representation is not recognized as a Sphinx Gallery script... # ################################################################## # %% some = 1 code = 2 some+code ################################################################## # A comment ################################################################## # Another comment # %% [markdown] # ################################################################## # This is a notebook that contains many hash signs. # Hopefully its python representation is not recognized as a Sphinx Gallery script... # ################################################################## ================================================ FILE: tests/data/notebooks/outputs/ipynb_to_hydrogen/Notebook with metadata and long cells.py ================================================ # --- # jupyter: # kernelspec: # display_name: Python 3 # language: python # name: python3 # --- # %% [markdown] # # Part one - various cells # %% [markdown] # Here we have a markdown cell # # # with two blank lines # %% [markdown] # Now we have a markdown cell # with a code block inside it # # ```python # 1 + 1 # ``` # # After that cell we'll have a code cell # %% 2 + 2 3 + 3 # %% [markdown] # Followed by a raw cell # %% [raw] # This is # the content # of the raw cell # %% [markdown] # # Part two - cell metadata # %% [markdown] key="value" # This is a markdown cell with cell metadata `{"key": "value"}` # %% .class tags=["parameters"] """This is a code cell with metadata `{"tags":["parameters"], ".class":null}`""" # %% [raw] key="value" # This is a raw cell with cell metadata `{"key": "value"}` ================================================ FILE: tests/data/notebooks/outputs/ipynb_to_hydrogen/Notebook_with_R_magic.py ================================================ # --- # jupyter: # kernelspec: # display_name: Python 2 # language: python # name: python2 # --- # %% [markdown] # # A notebook with R cells # # This notebook shows the use of R cells to generate plots # %% %load_ext rpy2.ipython # %% %%R suppressMessages(require(tidyverse)) # %% %%R ggplot(iris, aes(x = Sepal.Length, y = Petal.Length, color=Species)) + geom_point() # %% [markdown] # The default plot dimensions are not good for us, so we use the -w and -h parameters in %%R magic to set the plot size # %% %%R -w 400 -h 240 ggplot(iris, aes(x = Sepal.Length, y = Petal.Length, color=Species)) + geom_point() ================================================ FILE: tests/data/notebooks/outputs/ipynb_to_hydrogen/Notebook_with_more_R_magic_111.py ================================================ # --- # jupyter: # kernelspec: # display_name: Python 3 # language: python # name: python3 # --- # %% %load_ext rpy2.ipython import pandas as pd df = pd.DataFrame( { "Letter": ["a", "a", "a", "b", "b", "b", "c", "c", "c"], "X": [4, 3, 5, 2, 1, 7, 7, 5, 9], "Y": [0, 4, 3, 6, 7, 10, 11, 9, 13], "Z": [1, 2, 3, 1, 2, 3, 1, 2, 3], } ) # %% %%R -i df library("ggplot2") ggplot(data = df) + geom_point(aes(x = X, y = Y, color = Letter, size = Z)) ================================================ FILE: tests/data/notebooks/outputs/ipynb_to_hydrogen/R notebook with invalid cell keys.R ================================================ # --- # jupyter: # kernelspec: # display_name: R # language: R # name: ir # --- # %% [markdown] # This notebook was created with IRKernel 0.8.12, and is not completely valid, as the code cell below contains an unexpected 'source' entry. This did cause https://github.com/mwouts/jupytext/issues/234. Note that the problem is solved when one upgrades to IRKernel 1.0.0. # %% library("ggplot2") ggplot(mtcars, aes(mpg)) + stat_ecdf() ================================================ FILE: tests/data/notebooks/outputs/ipynb_to_hydrogen/Reference Guide for Calysto Scheme.ss ================================================ ;; -*- coding: utf-8 -*- ;; --- ;; jupyter: ;; kernelspec: ;; display_name: Calysto Scheme (Python) ;; language: scheme ;; name: calysto_scheme ;; --- ;; %% [markdown] ;; ;;

Reference Guide for Calysto Scheme

;; ;; [Calysto Scheme](https://github.com/Calysto/calysto_scheme) is a real Scheme programming language, with full support for continuations, including call/cc. It can also use all Python libraries. Also has some extensions that make it more useful (stepper-debugger, choose/fail, stack traces), or make it better integrated with Python. ;; ;; In Jupyter notebooks, because Calysto Scheme uses [MetaKernel](https://github.com/Calysto/metakernel/blob/master/README.rst), it has a fully-supported set of "magics"---meta-commands for additional functionality. This includes running Scheme in parallel. See all of the [MetaKernel Magics](https://github.com/Calysto/metakernel/blob/master/metakernel/magics/README.md). ;; ;; Calysto Scheme is written in Scheme, and then translated into Python (and other backends). The entire functionality lies in a single Python file: https://github.com/Calysto/calysto_scheme/blob/master/calysto_scheme/scheme.py However, you can easily install it (see below). ;; ;; Please see [Calysto Scheme Language](Calysto%20Scheme%20Language.ipynb) for more details on the Calysto Scheme language. ;; ;; ## Installation ;; ;; You can install Calysto Scheme with Python3: ;; ;; ``` ;; pip3 install --upgrade calysto-scheme --user -U ;; python3 -m calysto_kernel install --user ;; ``` ;; ;; or in the system kernel folder with: ;; ;; ``` ;; sudo pip3 install --upgrade calysto-scheme -U ;; sudo python3 -m calysto_kernel install ;; ``` ;; ;; Change pip3/python3 to use a different pip or Python. The version of Python used will determine how Calysto Scheme is run. ;; ;; Use it in the console, qtconsole, or notebook with IPython 3: ;; ;; ``` ;; ipython console --kernel calysto_scheme ;; ipython qtconsole --kernel calysto_scheme ;; ipython notebook --kernel calysto_scheme ;; ``` ;; ;; In addition to all of the following items, Calysto Scheme also has access to all of Python's builtin functions, and all of Python's libraries. For example, you can use `(complex 3 2)` to create a complex number by calling Python's complex function. ;; ;; ## Jupyter Enhancements ;; ;; When you run Calysto Scheme in Jupyter (console, notebook, qtconsole, etc.) you get: ;; ;; * TAB completions of Scheme functions and variable names ;; * display of rich media ;; * stepper/debugger ;; * magics (% macros) ;; * shell commands (! command) ;; * LaTeX equations ;; * LaTeX-style variables ;; * Python integration ;; %% [markdown] ;; ### LaTeX-style variables ;; ;; Calysto Scheme allows you to use LaTeX-style variables in code. For example, if you type: ;; ;; ``` ;; \beta ;; ``` ;; ;; with the cursor right after the 'a' in beta, and then press TAB, it will turn into the unicode character: ;; ;; ``` ;; β ;; ``` ;; ;; There are nearly 1300 different symbols defined (thanks to the Julia language) and documented here: ;; ;; http://docs.julialang.org/en/release-0.4/manual/unicode-input/#man-unicode-input ;; ;; Calysto Scheme may not implement all of those. Some useful and suggestive ones: ;; ;; * \pi - π ;; * \Pi - Π ;; * \Sigma - Σ ;; * \_i - subscript i, such as vectorᵢ ;; %% (define α 67) ;; %% α ;; %% (define i 2) (define vectorᵢ (vector-ref (vector 0 6 3 2) i)) vectorᵢ ;; %% [markdown] ;; ### Rich media ;; %% (import "calysto.display") ;; %% (calysto.display.HTML "This is bold, italics, underlined.") ;; %% (import "calysto.graphics") ;; %% (define canvas (calysto.graphics.Canvas)) ;; %% (define ball (calysto.graphics.Circle '(150 150) 100)) ;; %% (ball.draw canvas) ;; %% [markdown] ;; ### Shell commands ;; %% ! ls /tmp ;; %% [markdown] ;; ### Stepper/Debugger ;; ;; Here is what the debugger looks like: ;; ;; ;; ;; It has breakpoints (click in left margin). You must press Stop to exit the debugger. ;; %% [markdown] ;; ```scheme ;; %%debug ;; ;; (begin ;; (define x 1) ;; (set! x 2) ;; ) ;; ``` ;; %% [markdown] ;; ### Python Integration ;; ;; You can import and use any Python library in Calysto Scheme. ;; ;; In addition, if you wish, you can execute expressions and statements in a Python environment: ;; %% (python-eval "1 + 2") ;; %% (python-exec " def mypyfunc(a, b): return a * b ") ;; %% [markdown] ;; This is a shared environment with Scheme: ;; %% (mypyfunc 4 5) ;; %% [markdown] ;; You can use `func` to turn a Scheme procedure into a Python function, and `define!` to put it into the shared environment with Python: ;; %% (define! mypyfunc2 (func (lambda (n) n))) ;; %% (python-eval "mypyfunc2(34)") ;; %% [markdown] ;; # Differences Between Languages ;; ;; ## Major differences between Scheme and Python ;; ;; 1. In Scheme, double quotes are used for strings and may contain newlines ;; 1. In Scheme, a single quote is short for (quote ...) and means "literal" ;; 1. In Scheme, everything is an expression and has a return value ;; 1. Python does not support macros (e.g., extending syntax) ;; 1. In Python, "if X" is false if X is None, False, [], (,) or 0. In Scheme, "if X" is only false if X is #f or 0 ;; 1. Calysto Scheme uses continuations, not the call stack. However, for debugging there is a pseudo-stack when an error is raised. You can turn that off with (use-stack-trace #f) ;; 1. Scheme procedures are not Python functions, but there are means to use one as the other. ;; ;; ## Major Differences Between Calysto Scheme and other Schemes ;; ;; 1. define-syntax works slightly differently ;; 1. In Calysto Scheme, #(...) is short for '#(...) ;; 1. Calysto Scheme is missing many standard functions (see list at bottom) ;; 1. Calysto Scheme has a built-in amb operator called `choose` ;; 1. For debugging there is a pseudo-stack when errors are raised in Calysto Scheme. You can turn that off with (use-stack-trace #f) ;; ;; ### Stack Trace ;; ;; Calysto Scheme acts as if it has a call stack, for easier debugging. For example: ;; %% (define fact (lambda (n) (if (= n 1) q (* n (fact (- n 1)))))) ;; %% (fact 5) ;; %% [markdown] ;; To turn off the stack trace on error: ;; ;; ```scheme ;; (use-stack-trace #f) ;; ``` ;; That will allow infinite recursive loops without keeping track of the "stack". ;; %% [markdown] ;; # Calysto Scheme Variables ;; ;; ## SCHEMEPATH ;; SCHEMEPATH is a list of search directories used with (load NAME). This is a reference, so you should append to it rather than attempting to redefine it. ;; %% SCHEMEPATH ;; %% (set-cdr! (cdr SCHEMEPATH) (list "/var/modules")) ;; %% SCHEMEPATH ;; %% [markdown] ;; ## Getting Started ;; ;; Note that you can use the word `lambda` or \lambda and then press [TAB] ;; %% (define factorial (λ (n) (cond ((zero? n) 1) (else (* n (factorial (- n 1))))))) ;; %% (factorial 5) ;; %% [markdown] ;; ## define-syntax ;; (define-syntax NAME RULES): a method for creating macros ;; %% (define-syntax time [(time ?exp) (let ((start (current-time))) ?exp (- (current-time) start))]) ;; %% (time (car '(1 2 3 4))) ;; %% ;;--------------------------------------------------------------------- ;; collect is like list comprehension in Python (define-syntax collect [(collect ?exp for ?var in ?list) (filter-map (lambda (?var) ?exp) (lambda (?var) #t) ?list)] [(collect ?exp for ?var in ?list if ?condition) (filter-map (lambda (?var) ?exp) (lambda (?var) ?condition) ?list)]) (define filter-map (lambda (f pred? values) (if (null? values) '() (if (pred? (car values)) (cons (f (car values)) (filter-map f pred? (cdr values))) (filter-map f pred? (cdr values)))))) ;; %% (collect (* n n) for n in (range 10)) ;; %% (collect (* n n) for n in (range 5 20 3)) ;; %% (collect (* n n) for n in (range 10) if (> n 5)) ;; %% ;;--------------------------------------------------------------------- ;; for loops (define-syntax for [(for ?exp times do . ?bodies) (for-repeat ?exp (lambda () . ?bodies))] [(for ?var in ?exp do . ?bodies) (for-iterate1 ?exp (lambda (?var) . ?bodies))] [(for ?var at (?i) in ?exp do . ?bodies) (for-iterate2 0 ?exp (lambda (?var ?i) . ?bodies))] [(for ?var at (?i ?j . ?rest) in ?exp do . ?bodies) (for ?var at (?i) in ?exp do (for ?var at (?j . ?rest) in ?var do . ?bodies))]) (define for-repeat (lambda (n f) (if (< n 1) 'done (begin (f) (for-repeat (- n 1) f))))) (define for-iterate1 (lambda (values f) (if (null? values) 'done (begin (f (car values)) (for-iterate1 (cdr values) f))))) (define for-iterate2 (lambda (i values f) (if (null? values) 'done (begin (f (car values) i) (for-iterate2 (+ i 1) (cdr values) f))))) ;; %% (define matrix2d '((10 20) (30 40) (50 60) (70 80))) (define matrix3d '(((10 20 30) (40 50 60)) ((70 80 90) (100 110 120)) ((130 140 150) (160 170 180)) ((190 200 210) (220 230 240)))) ;; %% (begin (define hello 0) (for 5 times do (set! hello (+ hello 1))) hello ) ;; %% (for sym in '(a b c d) do (define x 1) (set! x sym) (print x)) ;; %% (for n in (range 10 20 2) do (print n)) ;; %% (for n at (i j) in matrix2d do (print (list n 'coords: i j))) ;; %% (for n at (i j k) in matrix3d do (print (list n 'coords: i j k))) ;; %% (define-syntax scons [(scons ?x ?y) (cons ?x (lambda () ?y))]) (define scar car) (define scdr (lambda (s) (let ((result ((cdr s)))) (set-cdr! s (lambda () result)) result))) (define first (lambda (n s) (if (= n 0) '() (cons (scar s) (first (- n 1) (scdr s)))))) (define nth (lambda (n s) (if (= n 0) (scar s) (nth (- n 1) (scdr s))))) (define smap (lambda (f s) (scons (f (scar s)) (smap f (scdr s))))) (define ones (scons 1 ones)) (define nats (scons 0 (combine nats + ones))) (define combine (lambda (s1 op s2) (scons (op (scar s1) (scar s2)) (combine (scdr s1) op (scdr s2))))) (define fibs (scons 1 (scons 1 (combine fibs + (scdr fibs))))) (define facts (scons 1 (combine facts * (scdr nats)))) (define ! (lambda (n) (nth n facts))) ;; %% (! 5) ;; %% (nth 10 facts) ;; %% (nth 20 fibs) ;; %% (first 30 fibs) ;; %% [markdown] ;; ## for-each ;; (for-each PROCEDURE LIST): apply PROCEDURE to each item in LIST; like `map` but don't return results ;; %% (for-each (lambda (n) (print n)) '(3 4 5)) ;; %% [markdown] ;; ## format ;; (format STRING ITEM ...): format the string with ITEMS as arguments ;; %% (format "This uses formatting ~a ~s ~%" 'apple 'apple) ;; %% [markdown] ;; ## func ;; ;; Turns a lambda into a Python function. ;; ;; (func (lambda ...)) ;; %% (func (lambda (n) n)) ;; %% [markdown] ;; ## There's more! ;; ;; Please see [Calysto Scheme Language](Calysto%20Scheme%20Language.ipynb) for more details on the Calysto Scheme language. ================================================ FILE: tests/data/notebooks/outputs/ipynb_to_hydrogen/The flavors of raw cells.py ================================================ # --- # jupyter: # kernelspec: # display_name: Python 3 # language: python # name: python3 # --- # %% [raw] raw_mimetype="text/latex" # $1+1$ # %% [raw] raw_mimetype="text/restructuredtext" # :math:`1+1` # %% [raw] raw_mimetype="text/html" # Bold text # %% [raw] raw_mimetype="text/markdown" # **Bold text** # %% [raw] raw_mimetype="text/x-python" # 1 + 1 # %% [raw] # Not formatted ================================================ FILE: tests/data/notebooks/outputs/ipynb_to_hydrogen/cat_variable.py ================================================ # --- # jupyter: # kernelspec: # display_name: Python 3 # language: python # name: python3 # --- # %% cat = 42 ================================================ FILE: tests/data/notebooks/outputs/ipynb_to_hydrogen/coconut_homepage_demo.coco ================================================ # --- # jupyter: # kernelspec: # display_name: Coconut # language: coconut # name: coconut # --- # %% [markdown] # Taken from [coconut-lang.org](coconut-lang.org) # %% [markdown] # pipeline-style programming # %% "hello, world!" |> print # %% [markdown] # prettier lambdas # %% x -> x ** 2 # %% [markdown] # partial application # %% range(10) |> map$(pow$(?, 2)) |> list # %% [markdown] # pattern-matching # %% match [head] + tail in [0, 1, 2, 3]: print(head, tail) # %% [markdown] # destructuring assignment # %% {"list": [0] + rest} = {"list": [0, 1, 2, 3]} # %% [markdown] # infix notation # %% # 5 `mod` 3 == 2 # %% [markdown] # operator functions # %% product = reduce$(*) # %% [markdown] # function composition # %% # (f..g..h)(x, y, z) # %% [markdown] # lazy lists # %% # (| first_elem() |) :: rest_elems() # %% [markdown] # parallel programming # %% range(100) |> parallel_map$(pow$(2)) |> list # %% [markdown] # tail call optimization # %% def factorial(n, acc=1): case n: match 0: return acc match _ is int if n > 0: return factorial(n-1, acc*n) # %% [markdown] # algebraic data types # %% data Empty() data Leaf(n) data Node(l, r) def size(Empty()) = 0 addpattern def size(Leaf(n)) = 1 addpattern def size(Node(l, r)) = size(l) + size(r) # %% [markdown] # and much more! # # Like what you see? Don't forget to star Coconut on GitHub! # %% ================================================ FILE: tests/data/notebooks/outputs/ipynb_to_hydrogen/convert_to_py_then_test_with_update83.py ================================================ # --- # jupyter: # kernelspec: # display_name: Python 3 # language: python # name: python3 # --- # %% %%time print('asdf') # %% [markdown] # Thanks for jupytext! # %% ================================================ FILE: tests/data/notebooks/outputs/ipynb_to_hydrogen/csharp.cs ================================================ // --- // jupyter: // kernelspec: // display_name: .NET (C#) // language: C# // name: .net-csharp // --- // %% [markdown] // We start with... // %% Console.WriteLine("Hello World!"); // %% [markdown] // Then we do a plot with Plotly, following the [Plotting with XPlot](https://github.com/dotnet/interactive/blob/master/NotebookExamples/csharp/Docs/Plotting%20with%20Xplot.ipynb) example from `dotnet/interactive`: // %% using XPlot.Plotly; var bar = new Graph.Bar { name = "Bar", x = new[] {'A', 'B', 'C'}, y = new[] {1, 3, 2} }; var chart = Chart.Plot(new[] {bar}); chart.WithTitle("A bar plot"); display(chart); // %% [markdown] // We also test the math outputs as in the [Math and Latex](https://github.com/dotnet/interactive/blob/master/NotebookExamples/csharp/Docs/Math%20and%20LaTeX.ipynb) example: // %% (LaTeXString)@"\begin{align} e^{i \pi} = -1\end{align}" // %% (MathString)@"e^{i \pi} = -1" ================================================ FILE: tests/data/notebooks/outputs/ipynb_to_hydrogen/demo_gdl_fbp.pro ================================================ ; -*- coding: utf-8 -*- ; --- ; jupyter: ; kernelspec: ; display_name: IDL [conda env:gdl] * ; language: IDL ; name: conda-env-gdl-idl ; --- ; %% [markdown] ; ## GDL demo notebook ; %% [markdown] ; Demonstration of GDL [(gnudatalanguage)](https://github.com/gnudatalanguage/gdl) ; ; This notebook creates a Shepp-Logan phantom, projects it and then performs an FBP reconstruction. ; %% ;; L.A. Shepp and B.F. Logan, “The Fourier reconstruction of a head section,” ;; IEEE Trans. Nucl. Sci. 21(3), 21–43 (1974). function shepplogan, size = size if NOT keyword_set(size) then size = 256 phantom = fltarr(size,size) tmp = (findgen(size)-((size-1)/2.0)) / (size/2.0) xcor = rebin(tmp,size,size) ycor = rebin(transpose(tmp),size,size) tmp = fltarr(size,size) aa={cx: 0.0, cy: 0.0, maj:0.69, min:0.92, theta: 0.0, val: 2.0 } bb={cx: 0.0, cy:-0.0184, maj:0.6624, min:0.874, theta: 0.0, val:-0.98} cc={cx: 0.22, cy: 0.0, maj:0.11, min:0.31, theta:-18.0, val:-0.02} dd={cx:-0.22, cy: 0.0, maj:0.16, min:0.41, theta: 18.0, val:-0.02} ee={cx: 0.0, cy: 0.35, maj:0.21, min:0.25, theta: 0.0, val:-0.01} ff={cx: 0.0, cy: 0.1, maj:0.046, min:0.046, theta: 0.0, val:-0.01} gg={cx: 0.0, cy:-0.1, maj:0.046, min:0.046, theta: 0.0, val:-0.01} hh={cx:-0.08, cy:-0.605, maj:0.046, min:0.023, theta: 0.0, val:-0.01} ii={cx: 0.0, cy:-0.605, maj:0.023, min:0.023, theta: 0.0, val:-0.01} jj={cx: 0.06, cy:-0.605, maj:0.023, min:0.046, theta: 0.0, val:-0.01} list = [aa,bb,cc,dd,ee,ff,gg,hh,ii,jj] for n = 0, n_elements(list)-1 do begin tmp = ((xcor-list[n].cx) / list[n].maj)^2 $ + ((ycor-list[n].cy) / list[n].min)^2 if list[n].theta NE 0 then begin nx = (size-1) * (list[n].cx + 1) / 2 ny = (size-1) * (list[n].cy + 1) / 2 tmp = rot(tmp, -list[n].theta, 1, nx, ny, /interp, /pivot) endif phantom[where(tmp LE 1.0)] += list[n].val endfor return, phantom < 1.1 end ; %% ;; Enable inline plotting !inline=1 ; %% phantom = shepplogan() window, 0, xsize=256, ysize=256 tvscl, phantom > 0.95 ; %% [markdown] ; Now we define simple forward and backprojection functions: ; %% function proj, image, angle sino_size_x = max(size(image,/dim)) sino_size_y = n_elements(angle) sino = fltarr(sino_size_x, sino_size_y) for aa=0, n_elements(angle)-1 do begin sino[*,aa] = total(rot(image, angle[aa], /interp), 2) endfor return, sino end ; %% function back, sino, angle image_size = n_elements(sino[*,0]) image = fltarr(image_size,image_size) for aa=0, n_elements(angle)-1 do begin image += rot(rebin(sino[*,aa],[image_size,image_size]), -angle[aa], /interp) endfor return, image / n_elements(angle) end ; %% [markdown] ; This allows us to create a sinogram: ; %% angles = findgen(360) sino = proj(phantom, angles) window, 0, xsize=256, ysize=360 tvscl, sino ; %% [markdown] ; On this we can apply a simple FBP reconstruction: ; %% ;; G.L. Zeng, “Revisit of the Ramp Filter,” ;; IEEE Trans. Nucl. Sci. 62(1), 131–136 (2015). function fbp, sino, angles ntot = n_elements(sino[*,0]) nang = n_elements(sino[0,*]) npos = ntot / 2 + 1 ; integer division needed ! nneg = ntot - npos freq = findgen(ntot) freq[npos:ntot-1] = REVERSE(freq[1:nneg]) freq[0] = 1 filter = -1 / (!pi * freq)^2 filter[where(freq mod 2 EQ 0)] *= -0.0 filter[0] = 0.25 filter = abs(fft(filter)) * ntot filter[ntot/4:ntot/4+ntot/2-1] *= 0.0 filter = rebin(filter,ntot,nang) ;; apply filter to the sinogram fsino = fft(sino, dim=1) fsino *= filter fsino = fft(fsino, dim=1, /overwrite, /inverse) fsino = !pi * real_part(fsino) ;; backproject the filtered sinogram return, back(fsino, angles) end ; %% reconstruction = fbp(sino, angles) window, 0, xsize=512, ysize=256 tvscl, [phantom, reconstruction] > 0.8 ; %% [markdown] ; ### The end ================================================ FILE: tests/data/notebooks/outputs/ipynb_to_hydrogen/evcxr_jupyter_tour.rs ================================================ // --- // jupyter: // kernelspec: // display_name: Rust // language: rust // name: rust // --- // %% [markdown] // # Tour of the EvCxR Jupyter Kernel // For those not already familiar with Jupyter notebook, it lets you write code into "cells" like the box below. Cells can alternatively contain markdown, like this text here. Each code cell is compiled and executed separately, but variables, defined functions etc persist between cells. // // ## Printing to outputs and evaluating expressions // Lets print something to stdout and stderr then return a final expression to see how that's presented. Note that stdout and stderr are separate streams, so may not appear in the same order is their respective print statements. // %% println!("Hello world"); eprintln!("Hello error"); format!("Hello {}", "world") // %% [markdown] // ## Assigning and making use of variables // We define a variable `message`, then in the subsequent cell, modify the string and finally print it out. We could also do all this in the one cell if we wanted. // %% let mut message = "Hello ".to_owned(); // %% message.push_str("world!"); // %% message // %% [markdown] // ## Defining and redefining functions // Next we'll define a function // %% pub fn fib(x: i32) -> i32 { if x <= 2 {0} else {fib(x - 2) + fib(x - 1)} } // %% (1..13).map(fib).collect::>() // %% [markdown] // Hmm, that doesn't look right. Lets redefine the function. In practice, we'd go back and edit the function above and reevaluate it, but here, lets redefine it in a separate cell. // %% pub fn fib(x: i32) -> i32 { if x <= 2 {2} else {fib(x - 2) + fib(x - 1)} } // %% let values = (1..13).map(fib).collect::>(); values // %% [markdown] // ## Spawning a separate thread and communicating with it // We can spawn a thread to do stuff in the background, then continue executing code in other cells. // %% use std::sync::{Mutex, Arc}; let counter = Arc::new(Mutex::new(0i32)); std::thread::spawn({ let counter = Arc::clone(&counter); move || { for i in 1..300 { *counter.lock().unwrap() += 1; std::thread::sleep(std::time::Duration::from_millis(100)); } }}); // %% *counter.lock().unwrap() // %% *counter.lock().unwrap() // %% [markdown] // ## Loading external crates // We can load external crates. This one takes a while to compile, but once it's compiled, subsequent cells shouldn't need to recompile it, so it should be much quicker. // %% :dep base64 = "0.10.1" base64::encode(&vec![1, 2, 3, 4]) // %% [markdown] // ## Customizing how types are displayed // We can also customize how our types are displayed, including presenting them as HTML. Here's an example where we define a custom display function for a type `Matrix`. // %% use std::fmt::Debug; pub struct Matrix {pub values: Vec, pub row_size: usize} impl Matrix { pub fn evcxr_display(&self) { let mut html = String::new(); html.push_str(""); for r in 0..(self.values.len() / self.row_size) { html.push_str(""); for c in 0..self.row_size { html.push_str(""); } html.push_str(""); } html.push_str("
"); html.push_str(&format!("{:?}", self.values[r * self.row_size + c])); html.push_str("
"); println!("EVCXR_BEGIN_CONTENT text/html\n{}\nEVCXR_END_CONTENT", html); } } // %% let m = Matrix {values: vec![1,2,3,4,5,6,7,8,9], row_size: 3}; m // %% [markdown] // We can also return images, we just need to base64 encode them. First, we set up code for displaying RGB and grayscale images. // %% extern crate image; extern crate base64; pub trait EvcxrResult {fn evcxr_display(&self);} impl EvcxrResult for image::RgbImage { fn evcxr_display(&self) { let mut buffer = Vec::new(); image::png::PNGEncoder::new(&mut buffer).encode(&**self, self.width(), self.height(), image::ColorType::RGB(8)).unwrap(); let img = base64::encode(&buffer); println!("EVCXR_BEGIN_CONTENT image/png\n{}\nEVCXR_END_CONTENT", img); } } impl EvcxrResult for image::GrayImage { fn evcxr_display(&self) { let mut buffer = Vec::new(); image::png::PNGEncoder::new(&mut buffer).encode(&**self, self.width(), self.height(), image::ColorType::Gray(8)).unwrap(); let img = base64::encode(&buffer); println!("EVCXR_BEGIN_CONTENT image/png\n{}\nEVCXR_END_CONTENT", img); } } // %% image::ImageBuffer::from_fn(256, 256, |x, y| { if (x as i32 - y as i32).abs() < 3 { image::Rgb([0, 0, 255]) } else { image::Rgb([0, 0, 0]) } }) // %% [markdown] // ## Display of compilation errors // Here's how compilation errors are presented. Here we forgot an & and passed a String instead of an &str. // %% let mut s = String::new(); s.push_str(format!("foo {}", 42)); // %% [markdown] // ## Seeing what variables have been defined // We can print a table of defined variables and their types with the :vars command. // %% :vars // %% [markdown] // Other built-in commands can be found via :help // %% :help // %% ================================================ FILE: tests/data/notebooks/outputs/ipynb_to_hydrogen/frozen_cell.py ================================================ # --- # jupyter: # kernelspec: # display_name: Python 3 # language: python # name: python3 # --- # %% # This is an unfrozen cell. Works as usual. print("I'm a regular cell so I run and print!") # %% deletable=false editable=false run_control={"frozen": true} # # This is an frozen cell # print("I'm frozen so Im not executed :(") ================================================ FILE: tests/data/notebooks/outputs/ipynb_to_hydrogen/fsharp.fsx ================================================ // --- // jupyter: // kernelspec: // display_name: .NET (F#) // language: F# // name: .net-fsharp // --- // %% [markdown] // This notebook was inspired by [Plottting with XPlot](https://github.com/dotnet/interactive/blob/master/NotebookExamples/fsharp/Docs/Plotting%20with%20Xplot.ipynb). // %% open XPlot.Plotly // %% let bar = Bar( name = "Bar 1", x = ["A"; "B"; "C"], y = [1; 3; 2]) [bar] |> Chart.Plot |> Chart.WithTitle "A sample bar plot" ================================================ FILE: tests/data/notebooks/outputs/ipynb_to_hydrogen/gnuplot_notebook.gp ================================================ # --- # jupyter: # kernelspec: # display_name: gnuplot # language: gnuplot # name: gnuplot # --- # %% [markdown] # # Sample gnuplot notebook # %% [markdown] # ## Simple plotting # %% # Plot sin and cos with different linetypes f(x) = sin(x) g(x) = cos(x) set xrange[0:2*pi] set xtics(0, "{/Symbol p}" pi , "2{/Symbol p}" 2*pi) set ytics 1 plot f(x) linewidth 2 title "sin(x)", \ g(x) linewidth 2 dashtype "--" title "cos(x)" # %% [markdown] # ## Example of line magic # %% %gnuplot inline pngcairo enhanced background rgb "#EEEEEE" size 600, 600 # Parametric plot without border reset set parametric set size ratio -1 unset border unset tics plot f(t), g(t) linewidth 2 notitle ================================================ FILE: tests/data/notebooks/outputs/ipynb_to_hydrogen/haskell_notebook.hs ================================================ -- --- -- jupyter: -- kernelspec: -- display_name: Haskell -- language: haskell -- name: haskell -- --- -- %% [markdown] -- # Example Haskell Notebook -- %% [markdown] -- Define a function to add two numbers. -- %% f :: Num a => a -> a -> a f x y = x + y -- %% [markdown] -- Try to use the function -- %% f 1 2 ================================================ FILE: tests/data/notebooks/outputs/ipynb_to_hydrogen/hello_world_gonb.go ================================================ // -*- coding: utf-8 -*- // --- // jupyter: // kernelspec: // display_name: Go (gonb) // language: go // name: gonb // --- // %% [markdown] // A notebook that use [GoNB](https://github.com/janpfeifer/gonb) // %% [markdown] // the code below comes from [tutorial.ipynb](https://github.com/janpfeifer/gonb/blob/main/examples/tutorial.ipynb) // %% func main() { fmt.Printf("Hello World!") } // %% //gonb:%% fmt.Printf("Hello World!") // %% [markdown] // //gonb:%% --who=world can pass flags to main func // %% import ( "flag" "fmt" ) var flagWho = flag.String("who", "", "Your name!") //gonb:%% --who=world fmt.Printf("Hello %s!\n", *flagWho) // %% [markdown] // %args also can pass flags // %% %args --who=Wally func main() { flag.Parse() fmt.Printf("Where is %s?", *flagWho) } // %% import "github.com/janpfeifer/gonb/gonbui" //gonb:%% gonbui.DisplayHtml(`I 🧡 GoNB!`) // %% //gonb:%% gonbui.DisplayMarkdown("#### Objective\n\n1. Have fun coding **Go**;\n1. Profit...\n"+ `$$f(x) = \int_{-\infty}^{\infty} e^{-x^2} dx$$`) // %% func init_a() { fmt.Println("init_a") } //gonb:%% fmt.Println("main") ================================================ FILE: tests/data/notebooks/outputs/ipynb_to_hydrogen/html-demo.clj ================================================ ;; --- ;; jupyter: ;; kernelspec: ;; display_name: Clojure ;; language: clojure ;; name: clojure ;; --- ;; %% [markdown] ;; # Clojupyter Demo ;; ;; This example notebook is from the [Clojupyter](https://github.com/clojupyter/clojupyter/blob/1637f6b2557f01db1e35bae5389bc38522eefe9a/examples/html-demo.ipynb) project. ;; This notebook demonstrates some of the more advanced features of Clojupyter. ;; %% [markdown] ;; ## Displaying HTML ;; ;; To display HTML, you'll need to require a clojupyter helper function to change the cell output ;; %% (require '[clojupyter.misc.display :as display]) ;; %% (println ">> should print some text") ;; displaying html (display/hiccup-html [:ul [:li "a " [:i "emphatic"] " idea"] [:li "a " [:b "bold"] " idea"] [:li "an " [:span {:style "text-decoration: underline;"} "important"] " idea"]]) ;; %% [markdown] ;; We can also use this to render SVG: ;; %% (display/hiccup-html [:svg {:height 100 :width 100 :xmlns "http://www.w3.org/2000/svg"} [:circle {:cx 50 :cy 40 :r 40 :fill "red"}]]) ;; %% [markdown] ;; ## Adding External Clojure Dependencies ;; ;; You can fetch external Clojure dependencies using the `clojupyter.misc.helper` namespace. ;; %% (require '[clojupyter.misc.helper :as helper]) ;; %% (helper/add-dependencies '[org.clojure/data.json "0.2.6"]) (require '[clojure.data.json :as json]) ;; %% (json/write-str {:a 1 :b [2, 3] :c "c"}) ;; %% [markdown] ;; ## Adding External Javascript Dependency ;; ;; Since you can render arbitrary HTML using `display/hiccup-html`, it's pretty easy to use external Javascript libraries to do things like generate charts. Here's an example using [Highcharts](https://www.highcharts.com/). ;; ;; First, we use a cell to add javascript to the running notebook: ;; %% (helper/add-javascript "https://code.highcharts.com/highcharts.js") ;; %% [markdown] ;; Now we define a function which takes Clojure data and returns hiccup HTML to display: ;; %% (defn plot-highchart [highchart-json] (let [id (str (java.util.UUID/randomUUID)) code (format "Highcharts.chart('%s', %s );" id, (json/write-str highchart-json))] (display/hiccup-html [:div [:div {:id id :style {:background-color "red"}}] [:script code]]))) ;; %% [markdown] ;; Now we can make generate interactive plots (try hovering over plot): ;; %% (def raw-data (map #(+ (* 22 (+ % (Math/random)) 78)) (range))) (def data-1 (take 500 raw-data)) (def data-2 (take 500 (drop 500 raw-data))) (plot-highchart {:chart {:type "line"} :title {:text "Plot of random data"} :series [{:data data-1} {:data data-2}]}) ;; %% ================================================ FILE: tests/data/notebooks/outputs/ipynb_to_hydrogen/ijavascript.js ================================================ // --- // jupyter: // kernelspec: // display_name: Javascript (Node.js) // language: javascript // name: javascript // --- // %% [markdown] // ## A notebook that uses IJavascript kernel // %% let x = 5; const y = 6; var z = 10; // %% x + y; // %% function add(num1, num2) { return num1 + num2 } // %% add(x, y); // %% const arrowAdd = (num1, num2) => num1 + num2; // %% arrowAdd(x, y); // %% const myCar = { color: "blue", weight: 850, model: "fiat", start: () => "car started!", doors: [1,2,3,4] } // %% console.log("color:", myCar.color); // %% console.log("start:", myCar.start()); // %% for (let door of myCar.doors) { console.log("I'm door", door) } // %% myCar; // %% class User { constructor(name){ this.name = name; } sayHello(){ return "Hello, I'm " + this.name; } } // %% let John = new User("John"); John.sayHello(); ================================================ FILE: tests/data/notebooks/outputs/ipynb_to_hydrogen/ir_notebook.R ================================================ # --- # jupyter: # kernelspec: # display_name: R # language: R # name: ir # --- # %% [markdown] # This is a jupyter notebook that uses the IR kernel. # %% sum(1:10) # %% plot(cars) # %% ================================================ FILE: tests/data/notebooks/outputs/ipynb_to_hydrogen/itypescript.ts ================================================ // --- // jupyter: // kernelspec: // display_name: Typescript 3.5 // language: typescript // name: typescript // --- // %% let x: number = 5; const y: number = 6; var z: string = "hi"; console.log(z); x + y; // %% function add(num1: number, num2: number): number { return num1 + num2 } add(x, y); // %% const arrowAdd = (num1: number, num2: number) => num1 + num2; arrowAdd(x, y); // %% class User { constructor(private name: string) { this.name = name; } sayHello(): string { return "Hello, I'm " + this.name; } } let John: User; John = new User("John"); John.sayHello(); ================================================ FILE: tests/data/notebooks/outputs/ipynb_to_hydrogen/julia_benchmark_plotly_barchart.jl ================================================ # --- # jupyter: # kernelspec: # display_name: Julia 1.1.1 # language: julia # name: julia-1.1 # --- # %% # IJulia rocks! So does Plotly. Check it out using Plotly api_key = "" # visit https://plot.ly/api to generate an API username and password username = "" Plotly.signin(username, api_key) # %% # Following data taken from http://julialang.org/ frontpage benchmarks = ["fib", "parse_int", "quicksort3", "mandel", "pi_sum", "rand_mat_stat", "rand_mat_mul"] platforms = ["Fortran", "Julia", "Python", "R", "Matlab", "Mathematica", "Javascript", "Go"] data = { platforms[1] => [0.26, 5.03, 1.11, 0.86, 0.80, 0.64, 0.96], platforms[2] => [0.91, 1.60, 1.14, 0.85, 1.00, 1.66, 1.01], platforms[3] => [30.37, 13.95, 31.98, 14.19, 16.33, 13.52, 3.41 ], platforms[4] => [411.36, 59.40, 524.29, 106.97, 15.42, 10.84, 3.98 ], platforms[5] => [1992.00, 1463.16, 101.84, 64.58, 1.29, 6.61, 1.10 ], platforms[6] => [64.46, 29.54, 35.74, 6.07, 1.32, 4.52, 1.16 ], platforms[7] => [2.18, 2.43, 3.51, 3.49, 0.84, 3.28, 14.60], platforms[8] => [1.03, 4.79, 1.25, 2.36, 1.41, 8.12, 8.51] } pdata = [ {"x"=>benchmarks,"y"=>data[k],"bardir"=>"h","type"=>"bar","name"=>k} for k = platforms ] layout = { "title"=> "Julia benchmark comparison (smaller is better, C performance = 1.0)", "barmode"=> "group", "autosize"=> false, "width"=> 900, "height"=> 900, "titlefont"=> { "family"=> "Open Sans", "size"=> 18, "color"=> "rgb(84, 39, 143)" }, "margin"=> {"l"=>160, "pad"=>0}, "xaxis"=> { "title"=> "Benchmark log-time", "type"=> "log" }, "yaxis"=> {"title"=> "Benchmark Name"} } response = Plotly.plot(pdata,["layout"=>layout]) # Embed in an iframe within IJulia s = string("") display("text/html", s) # %% # checkout https://plot.ly/api/ for more Julia examples! # But to show off some other Plotly features: x = 1:1500 y1 = sin(2*pi*x/1500.) + rand(1500)-0.5 y2 = sin(2*pi*x/1500.) fish = {"x"=>x,"y"=> y1, "type"=>"scatter","mode"=>"markers", "marker"=>{"color"=>"rgb(0, 0, 255)","opacity"=>0.5 } } fit = {"x"=> x,"y"=> y2, "type"=>"scatter", "mode"=>"markers", "opacity"=>0.8, "marker"=>{"color"=>"rgb(255, 0, 0)"} } layout = {"autosize"=> false, "width"=> 650, "height"=> 550, "title"=>"Fish School", "xaxis"=>{ "ticks"=> "", "gridcolor"=> "white", "zerolinecolor"=> "white", "linecolor"=> "white", "autorange"=> false, "range"=>[0,1500] }, "yaxis"=>{ "ticks"=> "", "gridcolor"=> "white", "zerolinecolor"=> "white", "linecolor"=> "white", "autorange"=> false, "range"=>[-2.2,2.2] }, "plot_bgcolor"=> "rgb(245,245,247)", "showlegend"=> false, "hovermode"=> "closest"} response = Plotly.plot([fish, fit],["layout"=>layout]) s = string("") display("text/html", s) ================================================ FILE: tests/data/notebooks/outputs/ipynb_to_hydrogen/julia_functional_geometry.jl ================================================ # -*- coding: utf-8 -*- # --- # jupyter: # kernelspec: # display_name: Julia 1.1.1 # language: julia # name: julia-1.1 # --- # %% # This notebook is a semi top-down explanation. This cell needs to be # executed first so that the operators and helper functions are defined # All of this is explained in the later half of the notebook using Compose, Interact Compose.set_default_graphic_size(2inch, 2inch) points_f = [ (.1, .1), (.9, .1), (.9, .2), (.2, .2), (.2, .4), (.6, .4), (.6, .5), (.2, .5), (.2, .9), (.1, .9), (.1, .1) ] f = compose(context(), stroke("black"), line(points_f)) rot(pic) = compose(context(rotation=Rotation(-deg2rad(90))), pic) flip(pic) = compose(context(mirror=Mirror(deg2rad(90), 0.5w, 0.5h)), pic) above(m, n, p, q) = compose(context(), (context(0, 0, 1, m/(m+n)), p), (context(0, m/(m+n), 1, n/(m+n)), q)) above(p, q) = above(1, 1, p, q) beside(m, n, p, q) = compose(context(), (context(0, 0, m/(m+n), 1), p), (context(m/(m+n), 0, n/(m+n), 1), q)) beside(p, q) = beside(1, 1, p, q) over(p, q) = compose(context(), (context(), p), (context(), q)) rot45(pic) = compose(context(0, 0, 1/sqrt(2), 1/sqrt(2), rotation=Rotation(-deg2rad(45), 0w, 0h)), pic) # Utility function to zoom out and look at the context zoomout(pic) = compose(context(), (context(0.2, 0.2, 0.6, 0.6), pic), (context(0.2, 0.2, 0.6, 0.6), fill(nothing), stroke("black"), strokedash([0.5mm, 0.5mm]), polygon([(0, 0), (1, 0), (1, 1), (0, 1)]))) function read_path(p_str) tokens = [try parsefloat(x) catch symbol(x) end for x in split(p_str, r"[\s,]+")] path(tokens) end fish = compose(context(units=UnitBox(260, 260)), stroke("black"), read_path(strip(readall("fish.path")))) rotatable(pic) = @manipulate for θ=0:0.001:2π compose(context(rotation=Rotation(θ)), pic) end blank = compose(context()) fliprot45(pic) = rot45(compose(context(mirror=Mirror(deg2rad(-45))),pic)) # Hide this cell. display(MIME("text/html"), """""") # %% [markdown] # # Functional Geometry # *Functional Geometry* is a paper by Peter Henderson ([original (1982)](users.ecs.soton.ac.uk/peter/funcgeo.pdf), [revisited (2002)](https://cs.au.dk/~hosc/local/HOSC-15-4-pp349-365.pdf)) which deconstructs the MC Escher woodcut *Square Limit* # # ![Square Limit](http://i.imgur.com/LjRzmNM.png) # %% [markdown] # > A picture is an example of a complex object that can be described in terms of its parts. # Yet a picture needs to be rendered on a printer or a screen by a device that expects to # be given a sequence of commands. Programming that sequence of commands directly is # much harder than having an application generate the commands automatically from the # simpler, denotational description. # %% [markdown] # A `picture` is a *denotation* of something to draw. # # e.g. The value of f here denotes the picture of the letter F # %% [markdown] # Original at http://nbviewer.jupyter.org/github/shashi/ijulia-notebooks/blob/master/funcgeo/Functional%20Geometry.ipynb # %% [markdown] # ## In conclusion # # We described Escher's *Square Limit* from the description of its smaller parts, which in turn were described in terms of their smaller parts. # # This seemed simple because we chose to talk in terms of an *algebra* to describe pictures. The primitives `rot`, `flip`, `fliprot45`, `above`, `beside` and `over` fit the job perfectly. # # We were able to describe these primitives in terms of `compose` `contexts`, which the Compose library knows how to render. # # Denotation can be an easy way to describe a system as well as a practical implementation method. # # [Abstraction barriers](https://mitpress.mit.edu/sicp/full-text/sicp/book/node29.html) are useful tools that can reduce the cognitive overhead on the programmer. It entails creating layers consisting of functions which only use functions in the same layer or layers below in their own implementation. The layers in our language were: # # ------------------[ squarelimit ]------------------ # -------------[ quartet, cycle, nonet ]------------- # ---[ rot, flip, fliprot45, above, beside, over ]--- # -------[ compose, context, line, path,... ]-------- # # Drawing this diagram out is a useful way to begin building any library. # ================================================ FILE: tests/data/notebooks/outputs/ipynb_to_hydrogen/jupyter.py ================================================ # --- # jupyter: # kernelspec: # display_name: Python 3 # language: python # name: python3 # --- # %% [markdown] # # Jupyter notebook # # This notebook is a simple jupyter notebook. It only has markdown and code cells. And it does not contain consecutive markdown cells. We start with an addition: # %% a = 1 b = 2 a + b # %% [markdown] # Now we return a few tuples # %% a, b # %% a, b, a+b # %% [markdown] # And this is already the end of the notebook ================================================ FILE: tests/data/notebooks/outputs/ipynb_to_hydrogen/jupyter_again.py ================================================ # --- # jupyter: # kernelspec: # display_name: Python 3 # language: python # name: python3 # --- # %% c = ''' title: "Quick test" output: ioslides_presentation: widescreen: true smaller: true editor_options: chunk_output_type console ''' # %% import yaml print(yaml.dump(yaml.load(c))) # %% ?next ================================================ FILE: tests/data/notebooks/outputs/ipynb_to_hydrogen/jupyter_with_raw_cell_in_body.py ================================================ # --- # jupyter: # kernelspec: # display_name: Python 3 # language: python # name: python3 # --- # %% 1+2+3 # %% [raw] # This is a raw cell # %% [markdown] # This is a markdown cell ================================================ FILE: tests/data/notebooks/outputs/ipynb_to_hydrogen/jupyter_with_raw_cell_on_top.py ================================================ # --- # title: Quick test # output: # ioslides_presentation: # widescreen: true # smaller: true # editor_options: # chunk_output_type: console # jupyter: # kernelspec: # display_name: Python 3 # language: python # name: python3 # --- # %% 1+2+3 # %% ================================================ FILE: tests/data/notebooks/outputs/ipynb_to_hydrogen/jupyter_with_raw_cell_with_invalid_yaml.py ================================================ # --- # title: Exception: Test # jupyter: # kernelspec: # display_name: Python 3 (ipykernel) # language: python # name: python3 # --- # %% 1 + 2 + 3 ================================================ FILE: tests/data/notebooks/outputs/ipynb_to_hydrogen/jupyterlab-slideshow_1441.py ================================================ # --- # jupyter: # kernelspec: # display_name: Python 3 (ipykernel) # language: python # name: python3 # --- # %% [markdown] @deathbeds/jupyterlab-fonts={"styles": {"": {"body[data-jp-deck-mode='presenting'] &": {"right": "0", "top": "30%", "width": "25%", "z-index": 1}}}} jupyterlab-slideshow={"layer": "slide"} # > **Note** # > # > `slide` layer with a `top` of `30%` ================================================ FILE: tests/data/notebooks/outputs/ipynb_to_hydrogen/jupytext_replication.sos ================================================ # --- # jupyter: # kernelspec: # display_name: SoS # language: sos # name: sos # --- # %% [markdown] Collapsed="false" kernel="SoS" # # Text SOS-kernel with Jupytext # # ## What is SOS kernel # # SoS consists of a ployglot notebook that allows the use of multiple kernels in one Jupyter notebook, and a workflow system that is designed for daily computational research. Basically, # # - SoS Polyglot Notebook is a Jupyter Notebook with a SoS kernel. # - SoS Notebook serves as a super kernel to all other Jupyter kernels and allows the use of multiple kernels in one Jupyter notebook. # - SoS Workflow System is a Python based workflow system that is designed to be readable, shareable, and suitable for daily data analysis. # - SoS Workflow System can be used from command line or use SoS Notebook as its IDE. # # ![](https://vatlab.github.io/sos-docs/doc/media/SoS_Notebook_and_Workflow.png) # # ### How to install SOS-kernel # # Please follow this [link](https://vatlab.github.io/sos-docs/running.html#Conda-installation) to setup SOS # # I run some issue with the latest version of R on my Mac, so I had to install an earlier version of R # # ``` # conda install -c r r=3.5.1 # conda install sos-notebook jupyterlab-sos sos-papermill -c conda-forge # ``` # # ## Related issue with Jupytext # # Jupytext works fine with Python/R kernel but converts code cells into markdown cells when using the SOS kernel. # # cf the image below. It is a code cell. After saving the notebook and restart it, it converted the code cell into markdown # # Screenshot 2020-03-13 at 10 51 18 # %% [markdown] Collapsed="false" kernel="SoS" # ## Step 1 # # Please, choose SOS Kernel and then, in the cell code, choose SOS (or any other kernel available), the outcome is the same. # # ![](https://drive.google.com/uc?export=view&id=1OtyxfwoRyVK23XHnmd9JR-crBgHBL5mt) # %% Collapsed="false" kernel="SoS" import pandas as pd import numpy as np pd.DataFrame({ 'x': np.random.random(10), 'y': np.random.random(10), }) # %% [markdown] Collapsed="false" kernel="python3" # ## Step 2 # # Now, pair it with Jupytex # # ![](https://drive.google.com/uc?export=view&id=1Wtx-YPAXY8HWHqzCcy4iIgHpzt_9emEn) # %% [markdown] Collapsed="false" kernel="python3" # ### Step 3 # # Save the notebook, restart and clear all, **save**, then Shut down kernel. Close the notebook and reopen # %% [markdown] Collapsed="false" kernel="python3" # ### Step 4 # # Reopen the notebook. Here is the outcome # # ![](https://drive.google.com/uc?export=view&id=12C70unbSPv0gHCZaCICEUy7kO7wM93JH) # # ================================================ FILE: tests/data/notebooks/outputs/ipynb_to_hydrogen/kalman_filter_and_visualization.q ================================================ / --- / jupyter: / kernelspec: / display_name: Q 3.5 / language: q / name: qpk / --- / %% plt: .p.import`matplotlib.pyplot / %% filter: { t: ([] x: `float $ x; xh: `float $ x; p: (count x) # R: var x); (first t), iterate[R; R]\[first t; 1 _ t] } iterate: {[Q; R; x; y] x[`p]+: Q; k: x[`p] % R + x[`p]; `x`xh`p ! (y[`x]; x[`xh] + k * y[`x] - x[`xh]; (1 - k) * x[`p]) } / %% price: 100 + sums 0.5 - (n:50)?1. / %% output:filter price / %% plt[`:plot][til n; output`x; `label pykw "price"]; plt[`:plot][til n; output`xh;`label pykw "forecast"]; plt[`:legend][]; plt[`:show][]; / %% ================================================ FILE: tests/data/notebooks/outputs/ipynb_to_hydrogen/logtalk_notebook.lgt ================================================ % --- % jupyter: % kernelspec: % display_name: Logtalk % language: logtalk % name: logtalk_kernel % --- % %% [markdown] % # An implementation of the Ackermann function % %% vscode={"languageId": "logtalk"} %%load ack.lgt :- object(ack). :- info([ version is 1:0:0, author is 'Paulo Moura', date is 2008-3-31, comment is 'Ackermann function (general recursive function).' ]). :- public(ack/3). :- mode(ack(+integer, +integer, -integer), one). :- info(ack/3, [ comment is 'Ackermann function.', argnames is ['M', 'N', 'V'] ]). ack(0, N, V) :- !, V is N + 1. ack(M, 0, V) :- !, M2 is M - 1, ack(M2, 1, V). ack(M, N, V) :- M2 is M - 1, N2 is N - 1, ack(M, N2, V2), ack(M2, V2, V). :- end_object. % %% [markdown] % ## Sample query % %% vscode={"languageId": "logtalk"} ack::ack(2, 4, V). ================================================ FILE: tests/data/notebooks/outputs/ipynb_to_hydrogen/lua_example.lua ================================================ -- -*- coding: utf-8 -*- -- --- -- jupyter: -- kernelspec: -- display_name: Lua -- language: lua -- name: lua -- --- -- %% [markdown] -- Source: https://www.lua.org/pil/19.3.html -- %% [markdown] -- # Sort -- %% [markdown] -- Another useful function on arrays is table.sort, which we have seen before. It receives the array to be sorted, plus an optional order function. This order function receives two arguments and must return true if the first argument should come first in the sorted array. If this function is not provided, sort uses the default less-than operation (corresponding to the `<´ operator). -- %% [markdown] -- A common mistake is to try to order the indices of a table. In a table, the indices form a set, and have no order whatsoever. If you want to order them, you have to copy them to an array and then sort the array. Let us see an example. Suppose that you read a source file and build a table that gives, for each function name, the line where that function is defined; something like this: -- %% lines = { luaH_set = 10, luaH_get = 24, luaH_present = 48, } -- %% [markdown] -- Now you want to print these function names in alphabetical order. If you traverse this table with pairs, the names appear in an arbitrary order. However, you cannot sort them directly, because these names are keys of the table. However, when you put these names into an array, then you can sort them. First, you must create an array with those names, then sort it, and finally print the result: -- %% a = {} for n in pairs(lines) do table.insert(a, n) end table.sort(a) for i,n in ipairs(a) do print(n) end -- %% [markdown] -- Note that, for Lua, arrays also have no order. But we know how to count, so we get ordered values as long as we access the array with ordered indices. That is why you should always traverse arrays with ipairs, rather than pairs. The first imposes the key order 1, 2, ..., whereas the latter uses the natural arbitrary order of the table. -- %% [markdown] -- As a more advanced solution, we can write an iterator that traverses a table following the order of its keys. An optional parameter f allows the specification of an alternative order. It first sorts the keys into an array, and then iterates on the array. At each step, it returns the key and value from the original table: -- %% function pairsByKeys (t, f) local a = {} for n in pairs(t) do table.insert(a, n) end table.sort(a, f) local i = 0 -- iterator variable local iter = function () -- iterator function i = i + 1 if a[i] == nil then return nil else return a[i], t[a[i]] end end return iter end -- %% [markdown] -- With this function, it is easy to print those function names in alphabetical order. The loop -- %% for name, line in pairsByKeys(lines) do print(name, line) end ================================================ FILE: tests/data/notebooks/outputs/ipynb_to_hydrogen/maxima_example.mac ================================================ /* --- */ /* jupyter: */ /* kernelspec: */ /* display_name: Maxima */ /* language: maxima */ /* name: maxima */ /* --- */ /* %% [markdown] */ /* ## maxima misc */ /* %% */ kill(all)$ /* %% */ f(x) := 1/(x^2+l^2)^(3/2); /* %% */ integrate(f(x), x); /* %% */ tex(%)$ /* %% */ ================================================ FILE: tests/data/notebooks/outputs/ipynb_to_hydrogen/notebook_with_complex_metadata.py ================================================ # --- # jupyter: # kernelspec: # display_name: Python 3 # language: python # name: python3 # --- # %% ================================================ FILE: tests/data/notebooks/outputs/ipynb_to_hydrogen/nteract_with_parameter.py ================================================ # --- # jupyter: # kernel_info: # name: python3 # kernelspec: # display_name: Python 3 # language: python # name: python3 # --- # %% inputHidden=false outputHidden=false tags=["parameters"] param = 4 # %% inputHidden=false outputHidden=false import pandas as pd # %% inputHidden=false outputHidden=false df = pd.DataFrame({'A': [1, 2], 'B': [3 + param, 4]}, index=pd.Index(['x0', 'x1'], name='x')) df # %% inputHidden=false outputHidden=false %matplotlib inline df.plot(kind='bar') ================================================ FILE: tests/data/notebooks/outputs/ipynb_to_hydrogen/ocaml_notebook.ml ================================================ (* --- *) (* jupyter: *) (* jupytext: *) (* formats: ipynb:markdown,md *) (* kernelspec: *) (* display_name: OCaml default *) (* language: OCaml *) (* name: ocaml-jupyter *) (* --- *) (* %% [markdown] *) (* # Example of an OCaml notebook *) (* %% *) let sum x y = x + y (* %% [markdown] *) (* Let's try our function: *) (* %% *) sum 3 4 = 7 + 0 ================================================ FILE: tests/data/notebooks/outputs/ipynb_to_hydrogen/octave_notebook.m ================================================ % --- % jupyter: % kernelspec: % display_name: Octave % language: octave % name: octave % --- % %% [markdown] % A markdown cell % %% 1 + 1 % %% % a code cell with comments 2 + 2 % %% % a simple plot x = -10:0.1:10; plot (x, sin (x)); % %% %plot -w 800 % a simple plot with a magic instruction x = -10:0.1:10; plot (x, sin (x)); % %% [markdown] % And to finish with, a Python cell % %% %%python a = 1 % %% %%python a + 1 ================================================ FILE: tests/data/notebooks/outputs/ipynb_to_hydrogen/plotly_graphs.py ================================================ # --- # jupyter: # kernelspec: # display_name: Python 3 # language: python # name: python3 # --- # %% [markdown] # This notebook contains complex outputs, including plotly javascript graphs. # %% [markdown] # # Interactive plots # %% [markdown] # We use Plotly's connected mode to make the notebook lighter - when connected, the notebook downloads the `plotly.js` library from the web. # %% import plotly.offline as offline offline.init_notebook_mode(connected=True) # %% import plotly.graph_objects as go fig = go.Figure( data=[go.Bar(y=[2, 3, 1])], layout=go.Layout(title="bar plot")) fig.show() fig.data[0].marker = dict(color='purple') fig ================================================ FILE: tests/data/notebooks/outputs/ipynb_to_hydrogen/powershell.ps1 ================================================ # --- # jupyter: # kernelspec: # display_name: PowerShell # language: PowerShell # name: powershell # --- # %% [markdown] # This is an extract from # https://github.com/Jaykul/Jupyter-PowerShell/blob/master/LiterateDevOps.ipynb # %% $imageUrl = 'https://upload.wikimedia.org/wikipedia/commons/2/2f/PowerShell_5.0_icon.png' $ImageData = @{ "png" = (Invoke-WebRequest $imageUrl -UseBasicParsing).RawContentStream.GetBuffer() } # $ImageData Write-Jupyter -InputObject $ImageData -Metadata @{ "image/png" = @{ 'width' = 32 } } Write-Jupyter -InputObject $ImageData -Metadata @{ "image/png" = @{ 'width' = 64 } } ================================================ FILE: tests/data/notebooks/outputs/ipynb_to_hydrogen/raw_cell_with_complex_yaml_like_content.py ================================================ # --- # # This is a complex paragraph # that is split over multiple lines. # # It also includes blank lines. # # # jupyter: # kernelspec: # display_name: Python 3 # language: python # name: python3 # --- # %% print("Hello, World!") ================================================ FILE: tests/data/notebooks/outputs/ipynb_to_hydrogen/raw_cell_with_non_dict_yaml_content.py ================================================ # --- # Content. # jupyter: # kernelspec: # display_name: Python 3 # language: python # name: python3 # --- # %% print("Hello, World!") ================================================ FILE: tests/data/notebooks/outputs/ipynb_to_hydrogen/root_cpp.cpp ================================================ // --- // jupyter: // kernelspec: // display_name: ROOT C++ // language: c++ // name: root // --- // %% #include #include // %% int k = 4; std::string foo = "This string says \"foo\""; // %% std::cout << "k = " << k << '\n' << foo << '\n'; ================================================ FILE: tests/data/notebooks/outputs/ipynb_to_hydrogen/sage_print_hello.sage ================================================ # --- # jupyter: # kernelspec: # display_name: SageMath 9.2 # language: sage # name: sagemath # --- # %% print("Hello world") ================================================ FILE: tests/data/notebooks/outputs/ipynb_to_hydrogen/sample_bash_notebook.sh ================================================ # --- # jupyter: # kernelspec: # display_name: Bash # language: bash # name: bash # --- # %% ls # %% # https://coderwall.com/p/euwpig/a-better-git-log git config --global alias.lg "log --color --graph --pretty=format:'%Cred%h%Creset -%C(yellow)%d%Creset %s %Cgreen(%cr) %C(bold blue)<%an>%Creset' --abbrev-commit" # %% git lg ================================================ FILE: tests/data/notebooks/outputs/ipynb_to_hydrogen/sample_rise_notebook_66.py ================================================ # --- # jupyter: # kernelspec: # display_name: Python 3 # language: python # name: python3 # --- # %% [markdown] slideshow={"slide_type": "slide"} # A markdown cell # %% slideshow={"slide_type": ""} 1+1 # %% [markdown] cell_style="center" slideshow={"slide_type": "fragment"} # Markdown cell two ================================================ FILE: tests/data/notebooks/outputs/ipynb_to_hydrogen/sas.sas ================================================ /* --- */ /* jupyter: */ /* kernelspec: */ /* display_name: SAS */ /* language: sas */ /* name: sas */ /* --- */ /* %% [markdown] */ /* # SAS Notebooks with jupytext */ /* %% */ proc sql; select * from sashelp.cars (obs=10) ; quit; /* %% */ %let name = "Jupytext"; /* %% */ %put &name; /* %% */ /* Note when defining macros "%macro" cannot be the first line of text in the cell */ %macro test; data temp; set sashelp.cars; name = "testx"; run; proc print data = temp (obs=10); run; %mend test; %test ================================================ FILE: tests/data/notebooks/outputs/ipynb_to_hydrogen/simple-helloworld.java ================================================ // -*- coding: utf-8 -*- // --- // jupyter: // jupytext: // formats: ipynb,java:hydrogen // kernelspec: // display_name: Java // language: java // name: java // --- // %% [markdown] // Let's define some class. // %% class A { public void hello() { System.out.println("Hello World"); } } // %% [markdown] // And now we call its method. // %% new A().hello(); // %% [markdown] // You can run it e.g. with `jshell` // // * from command line, as `jshell simple-helloworld.java` // * from jshell's shell with `/open simple-helloworld.java` ================================================ FILE: tests/data/notebooks/outputs/ipynb_to_hydrogen/simple_robot_notebook.robot ================================================ # --- # jupyter: # kernelspec: # display_name: Robot Framework # language: robotframework # name: robotkernel # --- # %% *** Settings *** Library Collections # %% *** Keywords *** Head [Arguments] ${list} ${value}= Get from list ${list} 0 [Return] ${value} # %% *** Tasks *** Get head ${array}= Create list 1 2 3 4 5 ${head}= Head ${array} Should be equal ${head} 1 ================================================ FILE: tests/data/notebooks/outputs/ipynb_to_hydrogen/simple_scala_notebook.scala ================================================ // --- // jupyter: // kernelspec: // display_name: Apache Toree - Scala // language: scala // name: apache_toree_scala // --- // %% // This is just a simple scala notebook object SampleObject { def calculation(x: Int, y: Int): Int = x + y } val result = SampleObject.calculation(1, 2) // %% println(result * 10) ================================================ FILE: tests/data/notebooks/outputs/ipynb_to_hydrogen/stata_notebook.do ================================================ // --- // jupyter: // kernelspec: // display_name: Stata // language: stata // name: stata // --- // %% // This notebook uses the stata_kernel: https://github.com/kylebarron/stata_kernel // %% use http://www.stata-press.com/data/r13/auto // %% summarize // %% scatter weight length ================================================ FILE: tests/data/notebooks/outputs/ipynb_to_hydrogen/tailrecursive-factorial.groovy ================================================ // -*- coding: utf-8 -*- // --- // jupyter: // jupytext: // formats: ipynb,groovy:hydrogen // kernelspec: // display_name: Groovy // language: groovy // name: groovy // --- // %% [markdown] // # TailRecursive annotation // // Let's check what is the effect of `@TailRecursive` annotation on the simple recursive definition of factorial function. // %% import groovy.transform.CompileStatic import groovy.transform.TailRecursive import groovy.transform.TypeChecked @CompileStatic @TypeChecked class X { static final BigInteger factorial0(int n) { (n <= 1) ? 1G : factorial0(n-1).multiply(BigInteger.valueOf(n)) } static final BigInteger factorial1(int n, BigInteger acc = 1G) { (n <= 1) ? acc : factorial1(n-1, acc.multiply(BigInteger.valueOf(n))) } @TailRecursive static final BigInteger factorial2(int n, BigInteger acc = 1G) { (n <= 1) ? acc : factorial2(n-1, acc.multiply(BigInteger.valueOf(n))) } } x = new X() // %% [markdown] // Although we can time the execution of the calls, it is not very accurate; such micro benchmarks should be performed in more controlled environment, such us under [JMH](https://openjdk.java.net/projects/code-tools/jmh/). // // For example, see [blog posts of Szymon Stępniak](https://e.printstacktrace.blog/tail-recursive-methods-in-groovy/). // %% %%timeit x.factorial0(19_000).toString().length() // %% %%timeit x.factorial1(19_000).toString().length() // %% %%timeit x.factorial2(19_000).toString().length() // %% [markdown] // The real difference is the use of stack. Non-tail recursive calls exhaust the stack space at some point, whereas tail recursive calls don't add frames to the stack. // %% factSize = { n, cl -> println "Factorial of ${n} has ${cl(n).toString().length()} digits" } factSize 2_000, x.&factorial0 factSize 2_000, x.&factorial1 factSize 2_000, x.&factorial2 factSize 100_000, x.&factorial2 // %% try { factSize 100_000, x.&factorial1 } catch (Throwable e) { assert e instanceof StackOverflowError println e } ================================================ FILE: tests/data/notebooks/outputs/ipynb_to_hydrogen/tcl_test.tcl ================================================ # --- # jupyter: # kernelspec: # display_name: Tcl # language: tcl # name: tcljupyter # --- # %% [markdown] # # Assign Values # %% set a 1 puts "a = $a" # %% [markdown] # # Loop # %% for {set i 0} {$i < 10} {incr i} { puts "I inside first loop: $i" } # %% ================================================ FILE: tests/data/notebooks/outputs/ipynb_to_hydrogen/text_outputs_and_images.py ================================================ # --- # jupyter: # kernelspec: # display_name: Python 3 # language: python # name: python3 # --- # %% [markdown] # This notebook contains outputs of many different types: text, HTML, plots and errors. # %% [markdown] # # Text outputs # # Using `print`, `sys.stdout` and `sys.stderr` # %% import sys print('using print') sys.stdout.write('using sys.stdout.write') sys.stderr.write('using sys.stderr.write') # %% import logging logging.debug('Debug') logging.info('Info') logging.warning('Warning') logging.error('Error') # %% [markdown] # # HTML outputs # # Using `pandas`. Here we find two representations: both text and HTML. # %% import pandas as pd pd.DataFrame([4]) # %% from IPython.display import display display(pd.DataFrame([5])) display(pd.DataFrame([6])) # %% [markdown] # # Images # %% %matplotlib inline # %% # First plot from matplotlib import pyplot as plt import numpy as np w, h = 3, 3 data = np.zeros((h, w, 3), dtype=np.uint8) data[0,:] = [0,255,0] data[1,:] = [0,0,255] data[2,:] = [0,255,0] data[1:3,1:3] = [255, 0, 0] plt.imshow(data) plt.axis('off') plt.show() # Second plot data[1:3,1:3] = [255, 255, 0] plt.imshow(data) plt.axis('off') plt.show() # %% [markdown] # # Errors # %% undefined_variable ================================================ FILE: tests/data/notebooks/outputs/ipynb_to_hydrogen/wolfram.wolfram ================================================ (* --- *) (* jupyter: *) (* kernelspec: *) (* display_name: Wolfram Language 13.1 *) (* language: Wolfram Language *) (* name: wolframlanguage13.1 *) (* --- *) (* %% [markdown] *) (* **Note:** The `language_info` `file_extension` in this notebook should be `.m`, but it was deliberately changed to `.wolfram` to avoid conflicts with Matlab which is using the same extension. *) (* %% [markdown] *) (* We start with... *) (* %% *) Print["Hello, World!"]; (* %% [markdown] *) (* Then we draw the first example plot from the [ListPlot](https://reference.wolfram.com/language/ref/ListPlot.html) reference: *) (* %% *) ListPlot[Prime[Range[25]]] (* %% [markdown] *) (* We also test the math outputs as in the [Simplify](https://reference.wolfram.com/language/ref/Simplify.html) example: *) (* %% *) D[Integrate[1/(x^3 + 1), x], x] ================================================ FILE: tests/data/notebooks/outputs/ipynb_to_hydrogen/xcpp_by_quantstack.cpp ================================================ // --- // jupyter: // kernelspec: // display_name: C++14 // language: C++14 // name: xeus-cling-cpp14 // --- // %% [markdown] // [![xeus-cling](images/xeus-cling.png)](https://github.com/QuantStack/xeus-cling/) // // A Jupyter kernel for C++ based on the `cling` C++ interpreter and the `xeus` native implementation of the Jupyter protocol, xeus. // // - GitHub repository: https://github.com/QuantStack/xeus-cling/ // - Online documentation: https://xeus-cling.readthedocs.io/ // %% [markdown] // ## Usage // //
// // //
// To run the selected code cell, hit 
Shift + Enter
//
//
// %% [markdown] // ## Output and error streams // // `std::cout` and `std::cerr` are redirected to the notebook frontend. // %% #include std::cout << "some output" << std::endl; // %% std::cerr << "some error" << std::endl; // %% #include // %% throw std::runtime_error("Unknown exception"); // %% [markdown] // Omitting the `;` in the last statement of a cell results in an output being printed // %% int j = 5; // %% j // %% [markdown] // # Interpreting the C++ programming language // // `cling` has a broad support of the features of C++. You can define functions, classes, templates, etc ... // %% [markdown] // ## Functions // %% double sqr(double a) { return a * a; } // %% double a = 2.5; double asqr = sqr(a); asqr // %% [markdown] // ## Classes // %% class Foo { public: virtual ~Foo() {} virtual void print(double value) const { std::cout << "Foo value = " << value << std::endl; } }; // %% Foo bar; bar.print(1.2); // %% [markdown] // ## Polymorphism // %% class Bar : public Foo { public: virtual ~Bar() {} virtual void print(double value) const { std::cout << "Bar value = " << 2 * value << std::endl; } }; // %% Foo* bar2 = new Bar; bar2->print(1.2); delete bar2; // %% [markdown] // ## Templates // %% #include template class FooT { public: explicit FooT(const T& t) : m_t(t) {} void print() const { std::cout << typeid(T).name() << " m_t = " << m_t << std::endl; } private: T m_t; }; template <> class FooT { public: explicit FooT(const int& t) : m_t(t) {} void print() const { std::cout << "m_t = " << m_t << std::endl; } private: int m_t; }; // %% FooT foot1(1.2); foot1.print(); // %% FooT foot2(4); foot2.print(); // %% [markdown] // ## C++11 / C++14 support // %% class Foo11 { public: Foo11() { std::cout << "Foo11 default constructor" << std::endl; } Foo11(const Foo11&) { std::cout << "Foo11 copy constructor" << std::endl; } Foo11(Foo11&&) { std::cout << "Foo11 move constructor" << std::endl; } }; // %% Foo11 f1; Foo11 f2(f1); Foo11 f3(std::move(f1)); // %% #include std::vector v = { 1, 2, 3}; auto iter = ++v.begin(); v // %% *iter // %% [markdown] // ... and also lambda, universal references, `decltype`, etc ... // %% [markdown] // ## Documentation and completion // // - Documentation for types of the standard library is retrieved on cppreference.com. // - The quick-help feature can also be enabled for user-defined types and third-party libraries. More documentation on this feature is available at https://xeus-cling.readthedocs.io/en/latest/inline_help.html. // // %% ?std::vector // %% [markdown] // ## Using the `display_data` mechanism // %% [markdown] // For a user-defined type `T`, the rich rendering in the notebook and JupyterLab can be enabled by by implementing the function `xeus::xjson mime_bundle_repr(const T& im)`, which returns the JSON mime bundle for that type. // // More documentation on the rich display system of Jupyter and Xeus-cling is available at https://xeus-cling.readthedocs.io/en/latest/rich_display.html // %% [markdown] // ### Image example // %% #include #include #include "xtl/xbase64.hpp" #include "xeus/xjson.hpp" namespace im { struct image { inline image(const std::string& filename) { std::ifstream fin(filename, std::ios::binary); m_buffer << fin.rdbuf(); } std::stringstream m_buffer; }; xeus::xjson mime_bundle_repr(const image& i) { auto bundle = xeus::xjson::object(); bundle["image/png"] = xtl::base64encode(i.m_buffer.str()); return bundle; } } // %% im::image marie("images/marie.png"); marie // %% [markdown] // ### Audio example // %% #include #include #include "xtl/xbase64.hpp" #include "xeus/xjson.hpp" namespace au { struct audio { inline audio(const std::string& filename) { std::ifstream fin(filename, std::ios::binary); m_buffer << fin.rdbuf(); } std::stringstream m_buffer; }; xeus::xjson mime_bundle_repr(const audio& a) { auto bundle = xeus::xjson::object(); bundle["text/html"] = std::string(""; return bundle; } } // %% au::audio drums("audio/audio.wav"); drums // %% [markdown] // ### Display // %% #include "xcpp/xdisplay.hpp" // %% xcpp::display(drums); // %% [markdown] // ### Update-display // %% #include #include "xcpp/xdisplay.hpp" namespace ht { struct html { inline html(const std::string& content) { m_content = content; } std::string m_content; }; xeus::xjson mime_bundle_repr(const html& a) { auto bundle = xeus::xjson::object(); bundle["text/html"] = a.m_content; return bundle; } } // A red rectangle ht::html rect(R"(
Original
)"); // %% xcpp::display(rect, "some_display_id"); // %% // Update the rectangle to be blue rect.m_content = R"(
Updated
)"; xcpp::display(rect, "some_display_id", true); // %% [markdown] // ## Magics // // Magics are special commands for the kernel that are not part of the C++ language. // // They are defined with the symbol `%` for a line magic and `%%` for a cell magic. // // More documentation for magics is available at https://xeus-cling.readthedocs.io/en/latest/magics.html. // %% #include #include // %% std::vector to_shuffle = {1, 2, 3, 4}; // %% %timeit std::random_shuffle(to_shuffle.begin(), to_shuffle.end()); // %% [markdown] // [![xtensor](images/xtensor.png)](https://github.com/QuantStack/xtensor/) // // - GitHub repository: https://github.com/QuantStack/xtensor/ // - Online documentation: https://xtensor.readthedocs.io/ // - NumPy to xtensor cheat sheet: http://xtensor.readthedocs.io/en/latest/numpy.html // // `xtensor` is a C++ library for manipulating N-D arrays with an API very similar to that of numpy. // %% #include #include "xtensor/xarray.hpp" #include "xtensor/xio.hpp" #include "xtensor/xview.hpp" xt::xarray arr1 {{1.0, 2.0, 3.0}, {2.0, 5.0, 7.0}, {2.0, 5.0, 7.0}}; xt::xarray arr2 {5.0, 6.0, 7.0}; xt::view(arr1, 1) + arr2 // %% [markdown] // Together with the C++ Jupyter kernel, `xtensor` offers a similar experience as `NumPy` in the Python Jupyter kernel, including broadcasting and universal functions. // %% #include #include "xtensor/xarray.hpp" #include "xtensor/xio.hpp" // %% xt::xarray arr {1, 2, 3, 4, 5, 6, 7, 8, 9}; arr.reshape({3, 3}); std::cout << arr; // %% #include "xtensor-blas/xlinalg.hpp" // %% xt::xtensor m = {{1.5, 0.5}, {0.7, 1.0}}; std::cout << "Matrix rank: " << std::endl << xt::linalg::matrix_rank(m) << std::endl; std::cout << "Matrix inverse: " << std::endl << xt::linalg::inv(m) << std::endl; std::cout << "Eigen values: " << std::endl << xt::linalg::eigvals(m) << std::endl; // %% xt::xarray arg1 = xt::arange(9); xt::xarray arg2 = xt::arange(18); arg1.reshape({3, 3}); arg2.reshape({2, 3, 3}); std::cout << xt::linalg::dot(arg1, arg2) << std::endl; // %% ================================================ FILE: tests/data/notebooks/outputs/ipynb_to_hydrogen/xonsh_example.xsh ================================================ # --- # jupyter: # kernelspec: # display_name: Xonsh # language: xonsh # name: xonsh # --- # %% len($(curl -L https://xon.sh)) # %% for filename in `.*`: print(filename) du -sh @(filename) ================================================ FILE: tests/data/notebooks/outputs/ipynb_to_marimo/Line_breaks_in_LateX_305.py ================================================ import marimo __generated_with = "0.17.8" app = marimo.App() @app.cell(hide_code=True) def _(mo): mo.md(r""" This cell uses no particular cell marker $$ \begin{align} \dot{x} & = \sigma(y-x)\\ \dot{y} & = \rho x - y - xz \\ \dot{z} & = -\beta z + xy \end{align} $$ """) return @app.cell(hide_code=True) def _(mo): mo.md(r""" This cell uses no particular cell marker, and a single slash in the $\LaTeX$ equation $$ \begin{align} \dot{x} & = \sigma(y-x) \ \dot{y} & = \rho x - y - xz \ \dot{z} & = -\beta z + xy \end{align} $$ """) return @app.cell(hide_code=True) def _(mo): mo.md(r""" This cell uses the triple quote cell markers introduced at https://github.com/mwouts/jupytext/issues/305 $$ \begin{align} \dot{x} & = \sigma(y-x)\\ \dot{y} & = \rho x - y - xz \\ \dot{z} & = -\beta z + xy \end{align} $$ """) return @app.cell def _(): import marimo as mo return (mo,) if __name__ == "__main__": app.run() ================================================ FILE: tests/data/notebooks/outputs/ipynb_to_marimo/Notebook with function and cell metadata 164.py ================================================ import marimo __generated_with = "0.17.8" app = marimo.App() @app.cell def _(): 1 + 1 return @app.cell(hide_code=True) def _(mo): mo.md(r""" A markdown cell And below, the cell for function f has non trivial cell metadata. And the next cell as well. """) return @app.function def f(x): return x @app.cell def _(): f(5) return @app.cell(hide_code=True) def _(mo): mo.md(r""" More text """) return @app.cell def _(): 2 + 2 return @app.cell def _(): import marimo as mo return (mo,) if __name__ == "__main__": app.run() ================================================ FILE: tests/data/notebooks/outputs/ipynb_to_marimo/Notebook with many hash signs.py ================================================ import marimo __generated_with = "0.17.8" app = marimo.App() @app.cell(hide_code=True) def _(mo): mo.md(r""" ################################################################## This is a notebook that contains many hash signs. Hopefully its python representation is not recognized as a Sphinx Gallery script... ################################################################## """) return @app.cell def _(): some = 1 code = 2 some+code ################################################################## # A comment ################################################################## # Another comment return @app.cell(hide_code=True) def _(mo): mo.md(r""" ################################################################## This is a notebook that contains many hash signs. Hopefully its python representation is not recognized as a Sphinx Gallery script... ################################################################## """) return @app.cell def _(): import marimo as mo return (mo,) if __name__ == "__main__": app.run() ================================================ FILE: tests/data/notebooks/outputs/ipynb_to_marimo/cat_variable.py ================================================ import marimo __generated_with = "0.17.8" app = marimo.App() @app.cell def _(): cat = 42 return if __name__ == "__main__": app.run() ================================================ FILE: tests/data/notebooks/outputs/ipynb_to_marimo/frozen_cell.py ================================================ import marimo __generated_with = "0.17.8" app = marimo.App() @app.cell def _(): # This is an unfrozen cell. Works as usual. print("I'm a regular cell so I run and print!") return @app.cell def _(): # This is an frozen cell print("I'm frozen so Im not executed :(") return if __name__ == "__main__": app.run() ================================================ FILE: tests/data/notebooks/outputs/ipynb_to_marimo/jupyter.py ================================================ import marimo __generated_with = "0.17.8" app = marimo.App() @app.cell(hide_code=True) def _(mo): mo.md(r""" # Jupyter notebook This notebook is a simple jupyter notebook. It only has markdown and code cells. And it does not contain consecutive markdown cells. We start with an addition: """) return @app.cell def _(): a = 1 b = 2 a + b return a, b @app.cell(hide_code=True) def _(mo): mo.md(r""" Now we return a few tuples """) return @app.cell def _(a, b): a, b return @app.cell def _(a, b): a, b, a+b return @app.cell(hide_code=True) def _(mo): mo.md(r""" And this is already the end of the notebook """) return @app.cell def _(): import marimo as mo return (mo,) if __name__ == "__main__": app.run() ================================================ FILE: tests/data/notebooks/outputs/ipynb_to_marimo/notebook_with_complex_metadata.py ================================================ import marimo __generated_with = "0.17.8" app = marimo.App() @app.cell def _(): return if __name__ == "__main__": app.run() ================================================ FILE: tests/data/notebooks/outputs/ipynb_to_marimo/plotly_graphs.py ================================================ import marimo __generated_with = "0.17.8" app = marimo.App() @app.cell(hide_code=True) def _(mo): mo.md(r""" This notebook contains complex outputs, including plotly javascript graphs. """) return @app.cell(hide_code=True) def _(mo): mo.md(r""" # Interactive plots """) return @app.cell(hide_code=True) def _(mo): mo.md(r""" We use Plotly's connected mode to make the notebook lighter - when connected, the notebook downloads the `plotly.js` library from the web. """) return @app.cell def _(): import plotly.offline as offline offline.init_notebook_mode(connected=True) return @app.cell def _(): import plotly.graph_objects as go fig = go.Figure( data=[go.Bar(y=[2, 3, 1])], layout=go.Layout(title="bar plot")) fig.show() fig.data[0].marker = dict(color='purple') fig return @app.cell def _(): import marimo as mo return (mo,) if __name__ == "__main__": app.run() ================================================ FILE: tests/data/notebooks/outputs/ipynb_to_marimo/sample_rise_notebook_66.py ================================================ import marimo __generated_with = "0.17.8" app = marimo.App() @app.cell(hide_code=True) def _(mo): mo.md(r""" A markdown cell """) return @app.cell def _(): 1+1 return @app.cell(hide_code=True) def _(mo): mo.md(r""" Markdown cell two """) return @app.cell def _(): import marimo as mo return (mo,) if __name__ == "__main__": app.run() ================================================ FILE: tests/data/notebooks/outputs/ipynb_to_marimo/text_outputs_and_images.py ================================================ import marimo __generated_with = "0.17.8" app = marimo.App() @app.cell(hide_code=True) def _(mo): mo.md(r""" This notebook contains outputs of many different types: text, HTML, plots and errors. """) return @app.cell(hide_code=True) def _(mo): mo.md(r""" # Text outputs Using `print`, `sys.stdout` and `sys.stderr` """) return @app.cell def _(): import sys print('using print') sys.stdout.write('using sys.stdout.write') sys.stderr.write('using sys.stderr.write') return @app.cell def _(): import logging logging.debug('Debug') logging.info('Info') logging.warning('Warning') logging.error('Error') return @app.cell(hide_code=True) def _(mo): mo.md(r""" # HTML outputs Using `pandas`. Here we find two representations: both text and HTML. """) return @app.cell def _(): import pandas as pd pd.DataFrame([4]) return (pd,) @app.cell def _(pd): from IPython.display import display display(pd.DataFrame([5])) display(pd.DataFrame([6])) return @app.cell(hide_code=True) def _(mo): mo.md(r""" # Images """) return @app.cell def _(): # '%matplotlib inline' command supported automatically in marimo return @app.cell def _(): # First plot from matplotlib import pyplot as plt import numpy as np w, h = 3, 3 data = np.zeros((h, w, 3), dtype=np.uint8) data[0,:] = [0,255,0] data[1,:] = [0,0,255] data[2,:] = [0,255,0] data[1:3,1:3] = [255, 0, 0] plt.imshow(data) plt.axis('off') plt.show() # Second plot data[1:3,1:3] = [255, 255, 0] plt.imshow(data) plt.axis('off') plt.show() return @app.cell(hide_code=True) def _(mo): mo.md(r""" # Errors """) return @app.cell def _(undefined_variable): undefined_variable return @app.cell def _(): import marimo as mo return (mo,) if __name__ == "__main__": app.run() ================================================ FILE: tests/data/notebooks/outputs/ipynb_to_md/Line_breaks_in_LateX_305.md ================================================ --- jupyter: kernelspec: display_name: Python 3 language: python name: python3 --- This cell uses no particular cell marker $$ \begin{align} \dot{x} & = \sigma(y-x)\\ \dot{y} & = \rho x - y - xz \\ \dot{z} & = -\beta z + xy \end{align} $$ This cell uses no particular cell marker, and a single slash in the $\LaTeX$ equation $$ \begin{align} \dot{x} & = \sigma(y-x) \ \dot{y} & = \rho x - y - xz \ \dot{z} & = -\beta z + xy \end{align} $$ This cell uses the triple quote cell markers introduced at https://github.com/mwouts/jupytext/issues/305 $$ \begin{align} \dot{x} & = \sigma(y-x)\\ \dot{y} & = \rho x - y - xz \\ \dot{z} & = -\beta z + xy \end{align} $$ ================================================ FILE: tests/data/notebooks/outputs/ipynb_to_md/Notebook with function and cell metadata 164.md ================================================ --- jupyter: kernelspec: display_name: Python 3 language: python name: python3 --- ```python 1 + 1 ``` A markdown cell And below, the cell for function f has non trivial cell metadata. And the next cell as well. ```python attributes={"classes": [], "id": "", "n": "10"} def f(x): return x ``` ```python attributes={"classes": [], "id": "", "n": "10"} f(5) ``` More text ```python 2 + 2 ``` ================================================ FILE: tests/data/notebooks/outputs/ipynb_to_md/Notebook with html and latex cells.md ================================================ --- jupyter: kernelspec: display_name: Python 3 language: python name: python3 --- ```html

Jupytext on GitHub

``` ```latex $\frac{\pi}{2}$ ``` ```python %load_ext rpy2.ipython ``` ```R library(ggplot2) ggplot(data=data.frame(x=c('A', 'B'), y=c(5, 2)), aes(x,weight=y)) + geom_bar() ``` ```python %matplotlib inline import pandas as pd pd.Series({'A':5, 'B':2}).plot(figsize=(3,2), kind='bar') ``` ================================================ FILE: tests/data/notebooks/outputs/ipynb_to_md/Notebook with many hash signs.md ================================================ --- jupyter: kernelspec: display_name: Python 3 language: python name: python3 --- ################################################################## This is a notebook that contains many hash signs. Hopefully its python representation is not recognized as a Sphinx Gallery script... ################################################################## ```python some = 1 code = 2 some+code ################################################################## # A comment ################################################################## # Another comment ``` ################################################################## This is a notebook that contains many hash signs. Hopefully its python representation is not recognized as a Sphinx Gallery script... ################################################################## ================================================ FILE: tests/data/notebooks/outputs/ipynb_to_md/Notebook with metadata and long cells.md ================================================ --- jupyter: kernelspec: display_name: Python 3 language: python name: python3 --- # Part one - various cells Here we have a markdown cell with two blank lines Now we have a markdown cell with a code block inside it ```python 1 + 1 ``` After that cell we'll have a code cell ```python 2 + 2 3 + 3 ``` Followed by a raw cell This is the content of the raw cell # Part two - cell metadata This is a markdown cell with cell metadata `{"key": "value"}` ```python .class tags=["parameters"] """This is a code cell with metadata `{"tags":["parameters"], ".class":null}`""" ``` This is a raw cell with cell metadata `{"key": "value"}` ================================================ FILE: tests/data/notebooks/outputs/ipynb_to_md/Notebook_with_R_magic.md ================================================ --- jupyter: kernelspec: display_name: Python 2 language: python name: python2 --- # A notebook with R cells This notebook shows the use of R cells to generate plots ```python %load_ext rpy2.ipython ``` ```R suppressMessages(require(tidyverse)) ``` ```R ggplot(iris, aes(x = Sepal.Length, y = Petal.Length, color=Species)) + geom_point() ``` The default plot dimensions are not good for us, so we use the -w and -h parameters in %%R magic to set the plot size ```R magic_args="-w 400 -h 240" ggplot(iris, aes(x = Sepal.Length, y = Petal.Length, color=Species)) + geom_point() ``` ================================================ FILE: tests/data/notebooks/outputs/ipynb_to_md/Notebook_with_more_R_magic_111.md ================================================ --- jupyter: kernelspec: display_name: Python 3 language: python name: python3 --- ```python %load_ext rpy2.ipython import pandas as pd df = pd.DataFrame( { "Letter": ["a", "a", "a", "b", "b", "b", "c", "c", "c"], "X": [4, 3, 5, 2, 1, 7, 7, 5, 9], "Y": [0, 4, 3, 6, 7, 10, 11, 9, 13], "Z": [1, 2, 3, 1, 2, 3, 1, 2, 3], } ) ``` ```R magic_args="-i df" library("ggplot2") ggplot(data = df) + geom_point(aes(x = X, y = Y, color = Letter, size = Z)) ``` ================================================ FILE: tests/data/notebooks/outputs/ipynb_to_md/R notebook with invalid cell keys.md ================================================ --- jupyter: kernelspec: display_name: R language: R name: ir --- This notebook was created with IRKernel 0.8.12, and is not completely valid, as the code cell below contains an unexpected 'source' entry. This did cause https://github.com/mwouts/jupytext/issues/234. Note that the problem is solved when one upgrades to IRKernel 1.0.0. ```R library("ggplot2") ggplot(mtcars, aes(mpg)) + stat_ecdf() ``` ================================================ FILE: tests/data/notebooks/outputs/ipynb_to_md/Reference Guide for Calysto Scheme.md ================================================ --- jupyter: kernelspec: display_name: Calysto Scheme (Python) language: scheme name: calysto_scheme ---

Reference Guide for Calysto Scheme

[Calysto Scheme](https://github.com/Calysto/calysto_scheme) is a real Scheme programming language, with full support for continuations, including call/cc. It can also use all Python libraries. Also has some extensions that make it more useful (stepper-debugger, choose/fail, stack traces), or make it better integrated with Python. In Jupyter notebooks, because Calysto Scheme uses [MetaKernel](https://github.com/Calysto/metakernel/blob/master/README.rst), it has a fully-supported set of "magics"---meta-commands for additional functionality. This includes running Scheme in parallel. See all of the [MetaKernel Magics](https://github.com/Calysto/metakernel/blob/master/metakernel/magics/README.md). Calysto Scheme is written in Scheme, and then translated into Python (and other backends). The entire functionality lies in a single Python file: https://github.com/Calysto/calysto_scheme/blob/master/calysto_scheme/scheme.py However, you can easily install it (see below). Please see [Calysto Scheme Language](Calysto%20Scheme%20Language.ipynb) for more details on the Calysto Scheme language. ## Installation You can install Calysto Scheme with Python3: ``` pip3 install --upgrade calysto-scheme --user -U python3 -m calysto_kernel install --user ``` or in the system kernel folder with: ``` sudo pip3 install --upgrade calysto-scheme -U sudo python3 -m calysto_kernel install ``` Change pip3/python3 to use a different pip or Python. The version of Python used will determine how Calysto Scheme is run. Use it in the console, qtconsole, or notebook with IPython 3: ``` ipython console --kernel calysto_scheme ipython qtconsole --kernel calysto_scheme ipython notebook --kernel calysto_scheme ``` In addition to all of the following items, Calysto Scheme also has access to all of Python's builtin functions, and all of Python's libraries. For example, you can use `(complex 3 2)` to create a complex number by calling Python's complex function. ## Jupyter Enhancements When you run Calysto Scheme in Jupyter (console, notebook, qtconsole, etc.) you get: * TAB completions of Scheme functions and variable names * display of rich media * stepper/debugger * magics (% macros) * shell commands (! command) * LaTeX equations * LaTeX-style variables * Python integration ### LaTeX-style variables Calysto Scheme allows you to use LaTeX-style variables in code. For example, if you type: ``` \beta ``` with the cursor right after the 'a' in beta, and then press TAB, it will turn into the unicode character: ``` β ``` There are nearly 1300 different symbols defined (thanks to the Julia language) and documented here: http://docs.julialang.org/en/release-0.4/manual/unicode-input/#man-unicode-input Calysto Scheme may not implement all of those. Some useful and suggestive ones: * \pi - π * \Pi - Π * \Sigma - Σ * \_i - subscript i, such as vectorᵢ ```scheme (define α 67) ``` ```scheme α ``` ```scheme (define i 2) (define vectorᵢ (vector-ref (vector 0 6 3 2) i)) vectorᵢ ``` ### Rich media ```scheme (import "calysto.display") ``` ```scheme (calysto.display.HTML "This is bold, italics, underlined.") ``` ```scheme (import "calysto.graphics") ``` ```scheme (define canvas (calysto.graphics.Canvas)) ``` ```scheme (define ball (calysto.graphics.Circle '(150 150) 100)) ``` ```scheme (ball.draw canvas) ``` ### Shell commands ```scheme ! ls /tmp ``` ### Stepper/Debugger Here is what the debugger looks like: It has breakpoints (click in left margin). You must press Stop to exit the debugger. ```scheme %%debug (begin (define x 1) (set! x 2) ) ``` ### Python Integration You can import and use any Python library in Calysto Scheme. In addition, if you wish, you can execute expressions and statements in a Python environment: ```scheme (python-eval "1 + 2") ``` ```scheme (python-exec " def mypyfunc(a, b): return a * b ") ``` This is a shared environment with Scheme: ```scheme (mypyfunc 4 5) ``` You can use `func` to turn a Scheme procedure into a Python function, and `define!` to put it into the shared environment with Python: ```scheme (define! mypyfunc2 (func (lambda (n) n))) ``` ```scheme (python-eval "mypyfunc2(34)") ``` # Differences Between Languages ## Major differences between Scheme and Python 1. In Scheme, double quotes are used for strings and may contain newlines 1. In Scheme, a single quote is short for (quote ...) and means "literal" 1. In Scheme, everything is an expression and has a return value 1. Python does not support macros (e.g., extending syntax) 1. In Python, "if X" is false if X is None, False, [], (,) or 0. In Scheme, "if X" is only false if X is #f or 0 1. Calysto Scheme uses continuations, not the call stack. However, for debugging there is a pseudo-stack when an error is raised. You can turn that off with (use-stack-trace #f) 1. Scheme procedures are not Python functions, but there are means to use one as the other. ## Major Differences Between Calysto Scheme and other Schemes 1. define-syntax works slightly differently 1. In Calysto Scheme, #(...) is short for '#(...) 1. Calysto Scheme is missing many standard functions (see list at bottom) 1. Calysto Scheme has a built-in amb operator called `choose` 1. For debugging there is a pseudo-stack when errors are raised in Calysto Scheme. You can turn that off with (use-stack-trace #f) ### Stack Trace Calysto Scheme acts as if it has a call stack, for easier debugging. For example: ```scheme (define fact (lambda (n) (if (= n 1) q (* n (fact (- n 1)))))) ``` ```scheme (fact 5) ``` To turn off the stack trace on error: ```scheme (use-stack-trace #f) ``` That will allow infinite recursive loops without keeping track of the "stack". # Calysto Scheme Variables ## SCHEMEPATH SCHEMEPATH is a list of search directories used with (load NAME). This is a reference, so you should append to it rather than attempting to redefine it. ```scheme SCHEMEPATH ``` ```scheme (set-cdr! (cdr SCHEMEPATH) (list "/var/modules")) ``` ```scheme SCHEMEPATH ``` ## Getting Started Note that you can use the word `lambda` or \lambda and then press [TAB] ```scheme (define factorial (λ (n) (cond ((zero? n) 1) (else (* n (factorial (- n 1))))))) ``` ```scheme (factorial 5) ``` ## define-syntax (define-syntax NAME RULES): a method for creating macros ```scheme (define-syntax time [(time ?exp) (let ((start (current-time))) ?exp (- (current-time) start))]) ``` ```scheme (time (car '(1 2 3 4))) ``` ```scheme ;;--------------------------------------------------------------------- ;; collect is like list comprehension in Python (define-syntax collect [(collect ?exp for ?var in ?list) (filter-map (lambda (?var) ?exp) (lambda (?var) #t) ?list)] [(collect ?exp for ?var in ?list if ?condition) (filter-map (lambda (?var) ?exp) (lambda (?var) ?condition) ?list)]) (define filter-map (lambda (f pred? values) (if (null? values) '() (if (pred? (car values)) (cons (f (car values)) (filter-map f pred? (cdr values))) (filter-map f pred? (cdr values)))))) ``` ```scheme (collect (* n n) for n in (range 10)) ``` ```scheme (collect (* n n) for n in (range 5 20 3)) ``` ```scheme (collect (* n n) for n in (range 10) if (> n 5)) ``` ```scheme ;;--------------------------------------------------------------------- ;; for loops (define-syntax for [(for ?exp times do . ?bodies) (for-repeat ?exp (lambda () . ?bodies))] [(for ?var in ?exp do . ?bodies) (for-iterate1 ?exp (lambda (?var) . ?bodies))] [(for ?var at (?i) in ?exp do . ?bodies) (for-iterate2 0 ?exp (lambda (?var ?i) . ?bodies))] [(for ?var at (?i ?j . ?rest) in ?exp do . ?bodies) (for ?var at (?i) in ?exp do (for ?var at (?j . ?rest) in ?var do . ?bodies))]) (define for-repeat (lambda (n f) (if (< n 1) 'done (begin (f) (for-repeat (- n 1) f))))) (define for-iterate1 (lambda (values f) (if (null? values) 'done (begin (f (car values)) (for-iterate1 (cdr values) f))))) (define for-iterate2 (lambda (i values f) (if (null? values) 'done (begin (f (car values) i) (for-iterate2 (+ i 1) (cdr values) f))))) ``` ```scheme (define matrix2d '((10 20) (30 40) (50 60) (70 80))) (define matrix3d '(((10 20 30) (40 50 60)) ((70 80 90) (100 110 120)) ((130 140 150) (160 170 180)) ((190 200 210) (220 230 240)))) ``` ```scheme (begin (define hello 0) (for 5 times do (set! hello (+ hello 1))) hello ) ``` ```scheme (for sym in '(a b c d) do (define x 1) (set! x sym) (print x)) ``` ```scheme (for n in (range 10 20 2) do (print n)) ``` ```scheme (for n at (i j) in matrix2d do (print (list n 'coords: i j))) ``` ```scheme (for n at (i j k) in matrix3d do (print (list n 'coords: i j k))) ``` ```scheme (define-syntax scons [(scons ?x ?y) (cons ?x (lambda () ?y))]) (define scar car) (define scdr (lambda (s) (let ((result ((cdr s)))) (set-cdr! s (lambda () result)) result))) (define first (lambda (n s) (if (= n 0) '() (cons (scar s) (first (- n 1) (scdr s)))))) (define nth (lambda (n s) (if (= n 0) (scar s) (nth (- n 1) (scdr s))))) (define smap (lambda (f s) (scons (f (scar s)) (smap f (scdr s))))) (define ones (scons 1 ones)) (define nats (scons 0 (combine nats + ones))) (define combine (lambda (s1 op s2) (scons (op (scar s1) (scar s2)) (combine (scdr s1) op (scdr s2))))) (define fibs (scons 1 (scons 1 (combine fibs + (scdr fibs))))) (define facts (scons 1 (combine facts * (scdr nats)))) (define ! (lambda (n) (nth n facts))) ``` ```scheme (! 5) ``` ```scheme (nth 10 facts) ``` ```scheme (nth 20 fibs) ``` ```scheme (first 30 fibs) ``` ## for-each (for-each PROCEDURE LIST): apply PROCEDURE to each item in LIST; like `map` but don't return results ```scheme (for-each (lambda (n) (print n)) '(3 4 5)) ``` ## format (format STRING ITEM ...): format the string with ITEMS as arguments ```scheme (format "This uses formatting ~a ~s ~%" 'apple 'apple) ``` ## func Turns a lambda into a Python function. (func (lambda ...)) ```scheme (func (lambda (n) n)) ``` ## There's more! Please see [Calysto Scheme Language](Calysto%20Scheme%20Language.ipynb) for more details on the Calysto Scheme language. ================================================ FILE: tests/data/notebooks/outputs/ipynb_to_md/The flavors of raw cells.md ================================================ --- jupyter: kernelspec: display_name: Python 3 language: python name: python3 --- $1+1$ :math:`1+1` Bold text **Bold text** 1 + 1 Not formatted ================================================ FILE: tests/data/notebooks/outputs/ipynb_to_md/cat_variable.md ================================================ --- jupyter: kernelspec: display_name: Python 3 language: python name: python3 --- ```python cat = 42 ``` ================================================ FILE: tests/data/notebooks/outputs/ipynb_to_md/coconut_homepage_demo.md ================================================ --- jupyter: kernelspec: display_name: Coconut language: coconut name: coconut --- Taken from [coconut-lang.org](coconut-lang.org) pipeline-style programming ```coconut "hello, world!" |> print ``` prettier lambdas ```coconut x -> x ** 2 ``` partial application ```coconut range(10) |> map$(pow$(?, 2)) |> list ``` pattern-matching ```coconut match [head] + tail in [0, 1, 2, 3]: print(head, tail) ``` destructuring assignment ```coconut {"list": [0] + rest} = {"list": [0, 1, 2, 3]} ``` infix notation ```coconut # 5 `mod` 3 == 2 ``` operator functions ```coconut product = reduce$(*) ``` function composition ```coconut # (f..g..h)(x, y, z) ``` lazy lists ```coconut # (| first_elem() |) :: rest_elems() ``` parallel programming ```coconut range(100) |> parallel_map$(pow$(2)) |> list ``` tail call optimization ```coconut def factorial(n, acc=1): case n: match 0: return acc match _ is int if n > 0: return factorial(n-1, acc*n) ``` algebraic data types ```coconut data Empty() data Leaf(n) data Node(l, r) def size(Empty()) = 0 addpattern def size(Leaf(n)) = 1 addpattern def size(Node(l, r)) = size(l) + size(r) ``` and much more! Like what you see? Don't forget to star Coconut on GitHub! ```coconut ``` ================================================ FILE: tests/data/notebooks/outputs/ipynb_to_md/convert_to_py_then_test_with_update83.md ================================================ --- jupyter: kernelspec: display_name: Python 3 language: python name: python3 --- ```python %%time print('asdf') ``` Thanks for jupytext! ```python ``` ================================================ FILE: tests/data/notebooks/outputs/ipynb_to_md/csharp.md ================================================ --- jupyter: kernelspec: display_name: .NET (C#) language: C# name: .net-csharp --- We start with... ```csharp Console.WriteLine("Hello World!"); ``` Then we do a plot with Plotly, following the [Plotting with XPlot](https://github.com/dotnet/interactive/blob/master/NotebookExamples/csharp/Docs/Plotting%20with%20Xplot.ipynb) example from `dotnet/interactive`: ```csharp using XPlot.Plotly; var bar = new Graph.Bar { name = "Bar", x = new[] {'A', 'B', 'C'}, y = new[] {1, 3, 2} }; var chart = Chart.Plot(new[] {bar}); chart.WithTitle("A bar plot"); display(chart); ``` We also test the math outputs as in the [Math and Latex](https://github.com/dotnet/interactive/blob/master/NotebookExamples/csharp/Docs/Math%20and%20LaTeX.ipynb) example: ```csharp (LaTeXString)@"\begin{align} e^{i \pi} = -1\end{align}" ``` ```csharp (MathString)@"e^{i \pi} = -1" ``` ================================================ FILE: tests/data/notebooks/outputs/ipynb_to_md/demo_gdl_fbp.md ================================================ --- jupyter: kernelspec: display_name: IDL [conda env:gdl] * language: IDL name: conda-env-gdl-idl --- ## GDL demo notebook Demonstration of GDL [(gnudatalanguage)](https://github.com/gnudatalanguage/gdl) This notebook creates a Shepp-Logan phantom, projects it and then performs an FBP reconstruction. ```idl ;; L.A. Shepp and B.F. Logan, “The Fourier reconstruction of a head section,” ;; IEEE Trans. Nucl. Sci. 21(3), 21–43 (1974). function shepplogan, size = size if NOT keyword_set(size) then size = 256 phantom = fltarr(size,size) tmp = (findgen(size)-((size-1)/2.0)) / (size/2.0) xcor = rebin(tmp,size,size) ycor = rebin(transpose(tmp),size,size) tmp = fltarr(size,size) aa={cx: 0.0, cy: 0.0, maj:0.69, min:0.92, theta: 0.0, val: 2.0 } bb={cx: 0.0, cy:-0.0184, maj:0.6624, min:0.874, theta: 0.0, val:-0.98} cc={cx: 0.22, cy: 0.0, maj:0.11, min:0.31, theta:-18.0, val:-0.02} dd={cx:-0.22, cy: 0.0, maj:0.16, min:0.41, theta: 18.0, val:-0.02} ee={cx: 0.0, cy: 0.35, maj:0.21, min:0.25, theta: 0.0, val:-0.01} ff={cx: 0.0, cy: 0.1, maj:0.046, min:0.046, theta: 0.0, val:-0.01} gg={cx: 0.0, cy:-0.1, maj:0.046, min:0.046, theta: 0.0, val:-0.01} hh={cx:-0.08, cy:-0.605, maj:0.046, min:0.023, theta: 0.0, val:-0.01} ii={cx: 0.0, cy:-0.605, maj:0.023, min:0.023, theta: 0.0, val:-0.01} jj={cx: 0.06, cy:-0.605, maj:0.023, min:0.046, theta: 0.0, val:-0.01} list = [aa,bb,cc,dd,ee,ff,gg,hh,ii,jj] for n = 0, n_elements(list)-1 do begin tmp = ((xcor-list[n].cx) / list[n].maj)^2 $ + ((ycor-list[n].cy) / list[n].min)^2 if list[n].theta NE 0 then begin nx = (size-1) * (list[n].cx + 1) / 2 ny = (size-1) * (list[n].cy + 1) / 2 tmp = rot(tmp, -list[n].theta, 1, nx, ny, /interp, /pivot) endif phantom[where(tmp LE 1.0)] += list[n].val endfor return, phantom < 1.1 end ``` ```idl ;; Enable inline plotting !inline=1 ``` ```idl phantom = shepplogan() window, 0, xsize=256, ysize=256 tvscl, phantom > 0.95 ``` Now we define simple forward and backprojection functions: ```idl function proj, image, angle sino_size_x = max(size(image,/dim)) sino_size_y = n_elements(angle) sino = fltarr(sino_size_x, sino_size_y) for aa=0, n_elements(angle)-1 do begin sino[*,aa] = total(rot(image, angle[aa], /interp), 2) endfor return, sino end ``` ```idl function back, sino, angle image_size = n_elements(sino[*,0]) image = fltarr(image_size,image_size) for aa=0, n_elements(angle)-1 do begin image += rot(rebin(sino[*,aa],[image_size,image_size]), -angle[aa], /interp) endfor return, image / n_elements(angle) end ``` This allows us to create a sinogram: ```idl angles = findgen(360) sino = proj(phantom, angles) window, 0, xsize=256, ysize=360 tvscl, sino ``` On this we can apply a simple FBP reconstruction: ```idl ;; G.L. Zeng, “Revisit of the Ramp Filter,” ;; IEEE Trans. Nucl. Sci. 62(1), 131–136 (2015). function fbp, sino, angles ntot = n_elements(sino[*,0]) nang = n_elements(sino[0,*]) npos = ntot / 2 + 1 ; integer division needed ! nneg = ntot - npos freq = findgen(ntot) freq[npos:ntot-1] = REVERSE(freq[1:nneg]) freq[0] = 1 filter = -1 / (!pi * freq)^2 filter[where(freq mod 2 EQ 0)] *= -0.0 filter[0] = 0.25 filter = abs(fft(filter)) * ntot filter[ntot/4:ntot/4+ntot/2-1] *= 0.0 filter = rebin(filter,ntot,nang) ;; apply filter to the sinogram fsino = fft(sino, dim=1) fsino *= filter fsino = fft(fsino, dim=1, /overwrite, /inverse) fsino = !pi * real_part(fsino) ;; backproject the filtered sinogram return, back(fsino, angles) end ``` ```idl reconstruction = fbp(sino, angles) window, 0, xsize=512, ysize=256 tvscl, [phantom, reconstruction] > 0.8 ``` ### The end ================================================ FILE: tests/data/notebooks/outputs/ipynb_to_md/evcxr_jupyter_tour.md ================================================ --- jupyter: kernelspec: display_name: Rust language: rust name: rust --- # Tour of the EvCxR Jupyter Kernel For those not already familiar with Jupyter notebook, it lets you write code into "cells" like the box below. Cells can alternatively contain markdown, like this text here. Each code cell is compiled and executed separately, but variables, defined functions etc persist between cells. ## Printing to outputs and evaluating expressions Lets print something to stdout and stderr then return a final expression to see how that's presented. Note that stdout and stderr are separate streams, so may not appear in the same order is their respective print statements. ```rust println!("Hello world"); eprintln!("Hello error"); format!("Hello {}", "world") ``` ## Assigning and making use of variables We define a variable `message`, then in the subsequent cell, modify the string and finally print it out. We could also do all this in the one cell if we wanted. ```rust let mut message = "Hello ".to_owned(); ``` ```rust message.push_str("world!"); ``` ```rust message ``` ## Defining and redefining functions Next we'll define a function ```rust pub fn fib(x: i32) -> i32 { if x <= 2 {0} else {fib(x - 2) + fib(x - 1)} } ``` ```rust (1..13).map(fib).collect::>() ``` Hmm, that doesn't look right. Lets redefine the function. In practice, we'd go back and edit the function above and reevaluate it, but here, lets redefine it in a separate cell. ```rust pub fn fib(x: i32) -> i32 { if x <= 2 {2} else {fib(x - 2) + fib(x - 1)} } ``` ```rust let values = (1..13).map(fib).collect::>(); values ``` ## Spawning a separate thread and communicating with it We can spawn a thread to do stuff in the background, then continue executing code in other cells. ```rust use std::sync::{Mutex, Arc}; let counter = Arc::new(Mutex::new(0i32)); std::thread::spawn({ let counter = Arc::clone(&counter); move || { for i in 1..300 { *counter.lock().unwrap() += 1; std::thread::sleep(std::time::Duration::from_millis(100)); } }}); ``` ```rust *counter.lock().unwrap() ``` ```rust *counter.lock().unwrap() ``` ## Loading external crates We can load external crates. This one takes a while to compile, but once it's compiled, subsequent cells shouldn't need to recompile it, so it should be much quicker. ```rust :dep base64 = "0.10.1" base64::encode(&vec![1, 2, 3, 4]) ``` ## Customizing how types are displayed We can also customize how our types are displayed, including presenting them as HTML. Here's an example where we define a custom display function for a type `Matrix`. ```rust use std::fmt::Debug; pub struct Matrix {pub values: Vec, pub row_size: usize} impl Matrix { pub fn evcxr_display(&self) { let mut html = String::new(); html.push_str(""); for r in 0..(self.values.len() / self.row_size) { html.push_str(""); for c in 0..self.row_size { html.push_str(""); } html.push_str(""); } html.push_str("
"); html.push_str(&format!("{:?}", self.values[r * self.row_size + c])); html.push_str("
"); println!("EVCXR_BEGIN_CONTENT text/html\n{}\nEVCXR_END_CONTENT", html); } } ``` ```rust let m = Matrix {values: vec![1,2,3,4,5,6,7,8,9], row_size: 3}; m ``` We can also return images, we just need to base64 encode them. First, we set up code for displaying RGB and grayscale images. ```rust extern crate image; extern crate base64; pub trait EvcxrResult {fn evcxr_display(&self);} impl EvcxrResult for image::RgbImage { fn evcxr_display(&self) { let mut buffer = Vec::new(); image::png::PNGEncoder::new(&mut buffer).encode(&**self, self.width(), self.height(), image::ColorType::RGB(8)).unwrap(); let img = base64::encode(&buffer); println!("EVCXR_BEGIN_CONTENT image/png\n{}\nEVCXR_END_CONTENT", img); } } impl EvcxrResult for image::GrayImage { fn evcxr_display(&self) { let mut buffer = Vec::new(); image::png::PNGEncoder::new(&mut buffer).encode(&**self, self.width(), self.height(), image::ColorType::Gray(8)).unwrap(); let img = base64::encode(&buffer); println!("EVCXR_BEGIN_CONTENT image/png\n{}\nEVCXR_END_CONTENT", img); } } ``` ```rust image::ImageBuffer::from_fn(256, 256, |x, y| { if (x as i32 - y as i32).abs() < 3 { image::Rgb([0, 0, 255]) } else { image::Rgb([0, 0, 0]) } }) ``` ## Display of compilation errors Here's how compilation errors are presented. Here we forgot an & and passed a String instead of an &str. ```rust let mut s = String::new(); s.push_str(format!("foo {}", 42)); ``` ## Seeing what variables have been defined We can print a table of defined variables and their types with the :vars command. ```rust :vars ``` Other built-in commands can be found via :help ```rust :help ``` ```rust ``` ================================================ FILE: tests/data/notebooks/outputs/ipynb_to_md/frozen_cell.md ================================================ --- jupyter: kernelspec: display_name: Python 3 language: python name: python3 --- ```python # This is an unfrozen cell. Works as usual. print("I'm a regular cell so I run and print!") ``` ```python deletable=false editable=false run_control={"frozen": true} # This is an frozen cell print("I'm frozen so Im not executed :(") ``` ================================================ FILE: tests/data/notebooks/outputs/ipynb_to_md/fsharp.md ================================================ --- jupyter: kernelspec: display_name: .NET (F#) language: F# name: .net-fsharp --- This notebook was inspired by [Plottting with XPlot](https://github.com/dotnet/interactive/blob/master/NotebookExamples/fsharp/Docs/Plotting%20with%20Xplot.ipynb). ```fsharp open XPlot.Plotly ``` ```fsharp let bar = Bar( name = "Bar 1", x = ["A"; "B"; "C"], y = [1; 3; 2]) [bar] |> Chart.Plot |> Chart.WithTitle "A sample bar plot" ``` ================================================ FILE: tests/data/notebooks/outputs/ipynb_to_md/gnuplot_notebook.md ================================================ --- jupyter: kernelspec: display_name: gnuplot language: gnuplot name: gnuplot --- # Sample gnuplot notebook ## Simple plotting ```gnuplot # Plot sin and cos with different linetypes f(x) = sin(x) g(x) = cos(x) set xrange[0:2*pi] set xtics(0, "{/Symbol p}" pi , "2{/Symbol p}" 2*pi) set ytics 1 plot f(x) linewidth 2 title "sin(x)", \ g(x) linewidth 2 dashtype "--" title "cos(x)" ``` ## Example of line magic ```gnuplot %gnuplot inline pngcairo enhanced background rgb "#EEEEEE" size 600, 600 # Parametric plot without border reset set parametric set size ratio -1 unset border unset tics plot f(t), g(t) linewidth 2 notitle ``` ================================================ FILE: tests/data/notebooks/outputs/ipynb_to_md/haskell_notebook.md ================================================ --- jupyter: kernelspec: display_name: Haskell language: haskell name: haskell --- # Example Haskell Notebook Define a function to add two numbers. ```haskell f :: Num a => a -> a -> a f x y = x + y ``` Try to use the function ```haskell f 1 2 ``` ================================================ FILE: tests/data/notebooks/outputs/ipynb_to_md/hello_world_gonb.md ================================================ --- jupyter: kernelspec: display_name: Go (gonb) language: go name: gonb --- A notebook that use [GoNB](https://github.com/janpfeifer/gonb) the code below comes from [tutorial.ipynb](https://github.com/janpfeifer/gonb/blob/main/examples/tutorial.ipynb) ```go func main() { fmt.Printf("Hello World!") } ``` ```go %% fmt.Printf("Hello World!") ``` %% --who=world can pass flags to main func ```go import ( "flag" "fmt" ) var flagWho = flag.String("who", "", "Your name!") %% --who=world fmt.Printf("Hello %s!\n", *flagWho) ``` %args also can pass flags ```go %args --who=Wally func main() { flag.Parse() fmt.Printf("Where is %s?", *flagWho) } ``` ```go import "github.com/janpfeifer/gonb/gonbui" %% gonbui.DisplayHtml(`I 🧡 GoNB!`) ``` ```go %% gonbui.DisplayMarkdown("#### Objective\n\n1. Have fun coding **Go**;\n1. Profit...\n"+ `$$f(x) = \int_{-\infty}^{\infty} e^{-x^2} dx$$`) ``` ```go func init_a() { fmt.Println("init_a") } %% fmt.Println("main") ``` ================================================ FILE: tests/data/notebooks/outputs/ipynb_to_md/html-demo.md ================================================ --- jupyter: kernelspec: display_name: Clojure language: clojure name: clojure --- # Clojupyter Demo This example notebook is from the [Clojupyter](https://github.com/clojupyter/clojupyter/blob/1637f6b2557f01db1e35bae5389bc38522eefe9a/examples/html-demo.ipynb) project. This notebook demonstrates some of the more advanced features of Clojupyter. ## Displaying HTML To display HTML, you'll need to require a clojupyter helper function to change the cell output ```clojure (require '[clojupyter.misc.display :as display]) ``` ```clojure (println ">> should print some text") ;; displaying html (display/hiccup-html [:ul [:li "a " [:i "emphatic"] " idea"] [:li "a " [:b "bold"] " idea"] [:li "an " [:span {:style "text-decoration: underline;"} "important"] " idea"]]) ``` We can also use this to render SVG: ```clojure (display/hiccup-html [:svg {:height 100 :width 100 :xmlns "http://www.w3.org/2000/svg"} [:circle {:cx 50 :cy 40 :r 40 :fill "red"}]]) ``` ## Adding External Clojure Dependencies You can fetch external Clojure dependencies using the `clojupyter.misc.helper` namespace. ```clojure (require '[clojupyter.misc.helper :as helper]) ``` ```clojure (helper/add-dependencies '[org.clojure/data.json "0.2.6"]) (require '[clojure.data.json :as json]) ``` ```clojure (json/write-str {:a 1 :b [2, 3] :c "c"}) ``` ## Adding External Javascript Dependency Since you can render arbitrary HTML using `display/hiccup-html`, it's pretty easy to use external Javascript libraries to do things like generate charts. Here's an example using [Highcharts](https://www.highcharts.com/). First, we use a cell to add javascript to the running notebook: ```clojure (helper/add-javascript "https://code.highcharts.com/highcharts.js") ``` Now we define a function which takes Clojure data and returns hiccup HTML to display: ```clojure (defn plot-highchart [highchart-json] (let [id (str (java.util.UUID/randomUUID)) code (format "Highcharts.chart('%s', %s );" id, (json/write-str highchart-json))] (display/hiccup-html [:div [:div {:id id :style {:background-color "red"}}] [:script code]]))) ``` Now we can make generate interactive plots (try hovering over plot): ```clojure (def raw-data (map #(+ (* 22 (+ % (Math/random)) 78)) (range))) (def data-1 (take 500 raw-data)) (def data-2 (take 500 (drop 500 raw-data))) (plot-highchart {:chart {:type "line"} :title {:text "Plot of random data"} :series [{:data data-1} {:data data-2}]}) ``` ```clojure ``` ================================================ FILE: tests/data/notebooks/outputs/ipynb_to_md/ijavascript.md ================================================ --- jupyter: kernelspec: display_name: Javascript (Node.js) language: javascript name: javascript --- ## A notebook that uses IJavascript kernel ```javascript let x = 5; const y = 6; var z = 10; ``` ```javascript x + y; ``` ```javascript function add(num1, num2) { return num1 + num2 } ``` ```javascript add(x, y); ``` ```javascript const arrowAdd = (num1, num2) => num1 + num2; ``` ```javascript arrowAdd(x, y); ``` ```javascript const myCar = { color: "blue", weight: 850, model: "fiat", start: () => "car started!", doors: [1,2,3,4] } ``` ```javascript console.log("color:", myCar.color); ``` ```javascript console.log("start:", myCar.start()); ``` ```javascript for (let door of myCar.doors) { console.log("I'm door", door) } ``` ```javascript myCar; ``` ```javascript class User { constructor(name){ this.name = name; } sayHello(){ return "Hello, I'm " + this.name; } } ``` ```javascript let John = new User("John"); John.sayHello(); ``` ================================================ FILE: tests/data/notebooks/outputs/ipynb_to_md/ir_notebook.md ================================================ --- jupyter: kernelspec: display_name: R language: R name: ir --- This is a jupyter notebook that uses the IR kernel. ```R sum(1:10) ``` ```R plot(cars) ``` ```R ``` ================================================ FILE: tests/data/notebooks/outputs/ipynb_to_md/itypescript.md ================================================ --- jupyter: kernelspec: display_name: Typescript 3.5 language: typescript name: typescript --- ```typescript let x: number = 5; const y: number = 6; var z: string = "hi"; console.log(z); x + y; ``` ```typescript function add(num1: number, num2: number): number { return num1 + num2 } add(x, y); ``` ```typescript const arrowAdd = (num1: number, num2: number) => num1 + num2; arrowAdd(x, y); ``` ```typescript class User { constructor(private name: string) { this.name = name; } sayHello(): string { return "Hello, I'm " + this.name; } } let John: User; John = new User("John"); John.sayHello(); ``` ================================================ FILE: tests/data/notebooks/outputs/ipynb_to_md/julia_benchmark_plotly_barchart.md ================================================ --- jupyter: kernelspec: display_name: Julia 1.1.1 language: julia name: julia-1.1 --- ```julia # IJulia rocks! So does Plotly. Check it out using Plotly api_key = "" # visit https://plot.ly/api to generate an API username and password username = "" Plotly.signin(username, api_key) ``` ```julia # Following data taken from http://julialang.org/ frontpage benchmarks = ["fib", "parse_int", "quicksort3", "mandel", "pi_sum", "rand_mat_stat", "rand_mat_mul"] platforms = ["Fortran", "Julia", "Python", "R", "Matlab", "Mathematica", "Javascript", "Go"] data = { platforms[1] => [0.26, 5.03, 1.11, 0.86, 0.80, 0.64, 0.96], platforms[2] => [0.91, 1.60, 1.14, 0.85, 1.00, 1.66, 1.01], platforms[3] => [30.37, 13.95, 31.98, 14.19, 16.33, 13.52, 3.41 ], platforms[4] => [411.36, 59.40, 524.29, 106.97, 15.42, 10.84, 3.98 ], platforms[5] => [1992.00, 1463.16, 101.84, 64.58, 1.29, 6.61, 1.10 ], platforms[6] => [64.46, 29.54, 35.74, 6.07, 1.32, 4.52, 1.16 ], platforms[7] => [2.18, 2.43, 3.51, 3.49, 0.84, 3.28, 14.60], platforms[8] => [1.03, 4.79, 1.25, 2.36, 1.41, 8.12, 8.51] } pdata = [ {"x"=>benchmarks,"y"=>data[k],"bardir"=>"h","type"=>"bar","name"=>k} for k = platforms ] layout = { "title"=> "Julia benchmark comparison (smaller is better, C performance = 1.0)", "barmode"=> "group", "autosize"=> false, "width"=> 900, "height"=> 900, "titlefont"=> { "family"=> "Open Sans", "size"=> 18, "color"=> "rgb(84, 39, 143)" }, "margin"=> {"l"=>160, "pad"=>0}, "xaxis"=> { "title"=> "Benchmark log-time", "type"=> "log" }, "yaxis"=> {"title"=> "Benchmark Name"} } response = Plotly.plot(pdata,["layout"=>layout]) # Embed in an iframe within IJulia s = string("") display("text/html", s) ``` ```julia # checkout https://plot.ly/api/ for more Julia examples! # But to show off some other Plotly features: x = 1:1500 y1 = sin(2*pi*x/1500.) + rand(1500)-0.5 y2 = sin(2*pi*x/1500.) fish = {"x"=>x,"y"=> y1, "type"=>"scatter","mode"=>"markers", "marker"=>{"color"=>"rgb(0, 0, 255)","opacity"=>0.5 } } fit = {"x"=> x,"y"=> y2, "type"=>"scatter", "mode"=>"markers", "opacity"=>0.8, "marker"=>{"color"=>"rgb(255, 0, 0)"} } layout = {"autosize"=> false, "width"=> 650, "height"=> 550, "title"=>"Fish School", "xaxis"=>{ "ticks"=> "", "gridcolor"=> "white", "zerolinecolor"=> "white", "linecolor"=> "white", "autorange"=> false, "range"=>[0,1500] }, "yaxis"=>{ "ticks"=> "", "gridcolor"=> "white", "zerolinecolor"=> "white", "linecolor"=> "white", "autorange"=> false, "range"=>[-2.2,2.2] }, "plot_bgcolor"=> "rgb(245,245,247)", "showlegend"=> false, "hovermode"=> "closest"} response = Plotly.plot([fish, fit],["layout"=>layout]) s = string("") display("text/html", s) ``` ================================================ FILE: tests/data/notebooks/outputs/ipynb_to_md/julia_functional_geometry.md ================================================ --- jupyter: kernelspec: display_name: Julia 1.1.1 language: julia name: julia-1.1 --- ```julia # This notebook is a semi top-down explanation. This cell needs to be # executed first so that the operators and helper functions are defined # All of this is explained in the later half of the notebook using Compose, Interact Compose.set_default_graphic_size(2inch, 2inch) points_f = [ (.1, .1), (.9, .1), (.9, .2), (.2, .2), (.2, .4), (.6, .4), (.6, .5), (.2, .5), (.2, .9), (.1, .9), (.1, .1) ] f = compose(context(), stroke("black"), line(points_f)) rot(pic) = compose(context(rotation=Rotation(-deg2rad(90))), pic) flip(pic) = compose(context(mirror=Mirror(deg2rad(90), 0.5w, 0.5h)), pic) above(m, n, p, q) = compose(context(), (context(0, 0, 1, m/(m+n)), p), (context(0, m/(m+n), 1, n/(m+n)), q)) above(p, q) = above(1, 1, p, q) beside(m, n, p, q) = compose(context(), (context(0, 0, m/(m+n), 1), p), (context(m/(m+n), 0, n/(m+n), 1), q)) beside(p, q) = beside(1, 1, p, q) over(p, q) = compose(context(), (context(), p), (context(), q)) rot45(pic) = compose(context(0, 0, 1/sqrt(2), 1/sqrt(2), rotation=Rotation(-deg2rad(45), 0w, 0h)), pic) # Utility function to zoom out and look at the context zoomout(pic) = compose(context(), (context(0.2, 0.2, 0.6, 0.6), pic), (context(0.2, 0.2, 0.6, 0.6), fill(nothing), stroke("black"), strokedash([0.5mm, 0.5mm]), polygon([(0, 0), (1, 0), (1, 1), (0, 1)]))) function read_path(p_str) tokens = [try parsefloat(x) catch symbol(x) end for x in split(p_str, r"[\s,]+")] path(tokens) end fish = compose(context(units=UnitBox(260, 260)), stroke("black"), read_path(strip(readall("fish.path")))) rotatable(pic) = @manipulate for θ=0:0.001:2π compose(context(rotation=Rotation(θ)), pic) end blank = compose(context()) fliprot45(pic) = rot45(compose(context(mirror=Mirror(deg2rad(-45))),pic)) # Hide this cell. display(MIME("text/html"), """""") ``` # Functional Geometry *Functional Geometry* is a paper by Peter Henderson ([original (1982)](users.ecs.soton.ac.uk/peter/funcgeo.pdf), [revisited (2002)](https://cs.au.dk/~hosc/local/HOSC-15-4-pp349-365.pdf)) which deconstructs the MC Escher woodcut *Square Limit* ![Square Limit](http://i.imgur.com/LjRzmNM.png) > A picture is an example of a complex object that can be described in terms of its parts. Yet a picture needs to be rendered on a printer or a screen by a device that expects to be given a sequence of commands. Programming that sequence of commands directly is much harder than having an application generate the commands automatically from the simpler, denotational description. A `picture` is a *denotation* of something to draw. e.g. The value of f here denotes the picture of the letter F Original at http://nbviewer.jupyter.org/github/shashi/ijulia-notebooks/blob/master/funcgeo/Functional%20Geometry.ipynb ## In conclusion We described Escher's *Square Limit* from the description of its smaller parts, which in turn were described in terms of their smaller parts. This seemed simple because we chose to talk in terms of an *algebra* to describe pictures. The primitives `rot`, `flip`, `fliprot45`, `above`, `beside` and `over` fit the job perfectly. We were able to describe these primitives in terms of `compose` `contexts`, which the Compose library knows how to render. Denotation can be an easy way to describe a system as well as a practical implementation method. [Abstraction barriers](https://mitpress.mit.edu/sicp/full-text/sicp/book/node29.html) are useful tools that can reduce the cognitive overhead on the programmer. It entails creating layers consisting of functions which only use functions in the same layer or layers below in their own implementation. The layers in our language were: ------------------[ squarelimit ]------------------ -------------[ quartet, cycle, nonet ]------------- ---[ rot, flip, fliprot45, above, beside, over ]--- -------[ compose, context, line, path,... ]-------- Drawing this diagram out is a useful way to begin building any library. ================================================ FILE: tests/data/notebooks/outputs/ipynb_to_md/jupyter.md ================================================ --- jupyter: kernelspec: display_name: Python 3 language: python name: python3 --- # Jupyter notebook This notebook is a simple jupyter notebook. It only has markdown and code cells. And it does not contain consecutive markdown cells. We start with an addition: ```python a = 1 b = 2 a + b ``` Now we return a few tuples ```python a, b ``` ```python a, b, a+b ``` And this is already the end of the notebook ================================================ FILE: tests/data/notebooks/outputs/ipynb_to_md/jupyter_again.md ================================================ --- jupyter: kernelspec: display_name: Python 3 language: python name: python3 --- ```python c = ''' title: "Quick test" output: ioslides_presentation: widescreen: true smaller: true editor_options: chunk_output_type console ''' ``` ```python import yaml print(yaml.dump(yaml.load(c))) ``` ```python ?next ``` ================================================ FILE: tests/data/notebooks/outputs/ipynb_to_md/jupyter_with_raw_cell_in_body.md ================================================ --- jupyter: kernelspec: display_name: Python 3 language: python name: python3 --- ```python 1+2+3 ``` This is a raw cell This is a markdown cell ================================================ FILE: tests/data/notebooks/outputs/ipynb_to_md/jupyter_with_raw_cell_on_top.md ================================================ --- title: Quick test output: ioslides_presentation: widescreen: true smaller: true editor_options: chunk_output_type: console jupyter: kernelspec: display_name: Python 3 language: python name: python3 --- ```python 1+2+3 ``` ```python ``` ================================================ FILE: tests/data/notebooks/outputs/ipynb_to_md/jupyter_with_raw_cell_with_invalid_yaml.md ================================================ --- title: Exception: Test jupyter: kernelspec: display_name: Python 3 (ipykernel) language: python name: python3 --- ```python 1 + 2 + 3 ``` ================================================ FILE: tests/data/notebooks/outputs/ipynb_to_md/jupyterlab-slideshow_1441.md ================================================ --- jupyter: kernelspec: display_name: Python 3 (ipykernel) language: python name: python3 --- > **Note** > > `slide` layer with a `top` of `30%` ================================================ FILE: tests/data/notebooks/outputs/ipynb_to_md/jupytext_replication.md ================================================ --- jupyter: kernelspec: display_name: SoS language: sos name: sos --- # Text SOS-kernel with Jupytext ## What is SOS kernel SoS consists of a ployglot notebook that allows the use of multiple kernels in one Jupyter notebook, and a workflow system that is designed for daily computational research. Basically, - SoS Polyglot Notebook is a Jupyter Notebook with a SoS kernel. - SoS Notebook serves as a super kernel to all other Jupyter kernels and allows the use of multiple kernels in one Jupyter notebook. - SoS Workflow System is a Python based workflow system that is designed to be readable, shareable, and suitable for daily data analysis. - SoS Workflow System can be used from command line or use SoS Notebook as its IDE. ![](https://vatlab.github.io/sos-docs/doc/media/SoS_Notebook_and_Workflow.png) ### How to install SOS-kernel Please follow this [link](https://vatlab.github.io/sos-docs/running.html#Conda-installation) to setup SOS I run some issue with the latest version of R on my Mac, so I had to install an earlier version of R ``` conda install -c r r=3.5.1 conda install sos-notebook jupyterlab-sos sos-papermill -c conda-forge ``` ## Related issue with Jupytext Jupytext works fine with Python/R kernel but converts code cells into markdown cells when using the SOS kernel. cf the image below. It is a code cell. After saving the notebook and restart it, it converted the code cell into markdown Screenshot 2020-03-13 at 10 51 18 ## Step 1 Please, choose SOS Kernel and then, in the cell code, choose SOS (or any other kernel available), the outcome is the same. ![](https://drive.google.com/uc?export=view&id=1OtyxfwoRyVK23XHnmd9JR-crBgHBL5mt) ```sos Collapsed="false" kernel="SoS" import pandas as pd import numpy as np pd.DataFrame({ 'x': np.random.random(10), 'y': np.random.random(10), }) ``` ## Step 2 Now, pair it with Jupytex ![](https://drive.google.com/uc?export=view&id=1Wtx-YPAXY8HWHqzCcy4iIgHpzt_9emEn) ### Step 3 Save the notebook, restart and clear all, **save**, then Shut down kernel. Close the notebook and reopen ### Step 4 Reopen the notebook. Here is the outcome ![](https://drive.google.com/uc?export=view&id=12C70unbSPv0gHCZaCICEUy7kO7wM93JH) ================================================ FILE: tests/data/notebooks/outputs/ipynb_to_md/kalman_filter_and_visualization.md ================================================ --- jupyter: kernelspec: display_name: Q 3.5 language: q name: qpk --- ```q plt: .p.import`matplotlib.pyplot ``` ```q filter: { t: ([] x: `float $ x; xh: `float $ x; p: (count x) # R: var x); (first t), iterate[R; R]\[first t; 1 _ t] } iterate: {[Q; R; x; y] x[`p]+: Q; k: x[`p] % R + x[`p]; `x`xh`p ! (y[`x]; x[`xh] + k * y[`x] - x[`xh]; (1 - k) * x[`p]) } ``` ```q price: 100 + sums 0.5 - (n:50)?1. ``` ```q output:filter price ``` ```q plt[`:plot][til n; output`x; `label pykw "price"]; plt[`:plot][til n; output`xh;`label pykw "forecast"]; plt[`:legend][]; plt[`:show][]; ``` ```q ``` ================================================ FILE: tests/data/notebooks/outputs/ipynb_to_md/logtalk_notebook.md ================================================ --- jupyter: kernelspec: display_name: Logtalk language: logtalk name: logtalk_kernel --- # An implementation of the Ackermann function ```logtalk vscode={"languageId": "logtalk"} %%load ack.lgt :- object(ack). :- info([ version is 1:0:0, author is 'Paulo Moura', date is 2008-3-31, comment is 'Ackermann function (general recursive function).' ]). :- public(ack/3). :- mode(ack(+integer, +integer, -integer), one). :- info(ack/3, [ comment is 'Ackermann function.', argnames is ['M', 'N', 'V'] ]). ack(0, N, V) :- !, V is N + 1. ack(M, 0, V) :- !, M2 is M - 1, ack(M2, 1, V). ack(M, N, V) :- M2 is M - 1, N2 is N - 1, ack(M, N2, V2), ack(M2, V2, V). :- end_object. ``` ## Sample query ```logtalk vscode={"languageId": "logtalk"} ack::ack(2, 4, V). ``` ================================================ FILE: tests/data/notebooks/outputs/ipynb_to_md/lua_example.md ================================================ --- jupyter: kernelspec: display_name: Lua language: lua name: lua --- Source: https://www.lua.org/pil/19.3.html # Sort Another useful function on arrays is table.sort, which we have seen before. It receives the array to be sorted, plus an optional order function. This order function receives two arguments and must return true if the first argument should come first in the sorted array. If this function is not provided, sort uses the default less-than operation (corresponding to the `<´ operator). A common mistake is to try to order the indices of a table. In a table, the indices form a set, and have no order whatsoever. If you want to order them, you have to copy them to an array and then sort the array. Let us see an example. Suppose that you read a source file and build a table that gives, for each function name, the line where that function is defined; something like this: ```lua lines = { luaH_set = 10, luaH_get = 24, luaH_present = 48, } ``` Now you want to print these function names in alphabetical order. If you traverse this table with pairs, the names appear in an arbitrary order. However, you cannot sort them directly, because these names are keys of the table. However, when you put these names into an array, then you can sort them. First, you must create an array with those names, then sort it, and finally print the result: ```lua a = {} for n in pairs(lines) do table.insert(a, n) end table.sort(a) for i,n in ipairs(a) do print(n) end ``` Note that, for Lua, arrays also have no order. But we know how to count, so we get ordered values as long as we access the array with ordered indices. That is why you should always traverse arrays with ipairs, rather than pairs. The first imposes the key order 1, 2, ..., whereas the latter uses the natural arbitrary order of the table. As a more advanced solution, we can write an iterator that traverses a table following the order of its keys. An optional parameter f allows the specification of an alternative order. It first sorts the keys into an array, and then iterates on the array. At each step, it returns the key and value from the original table: ```lua function pairsByKeys (t, f) local a = {} for n in pairs(t) do table.insert(a, n) end table.sort(a, f) local i = 0 -- iterator variable local iter = function () -- iterator function i = i + 1 if a[i] == nil then return nil else return a[i], t[a[i]] end end return iter end ``` With this function, it is easy to print those function names in alphabetical order. The loop ```lua for name, line in pairsByKeys(lines) do print(name, line) end ``` ================================================ FILE: tests/data/notebooks/outputs/ipynb_to_md/maxima_example.md ================================================ --- jupyter: kernelspec: display_name: Maxima language: maxima name: maxima --- ## maxima misc ```maxima kill(all)$ ``` ```maxima f(x) := 1/(x^2+l^2)^(3/2); ``` ```maxima integrate(f(x), x); ``` ```maxima tex(%)$ ``` ```maxima ``` ================================================ FILE: tests/data/notebooks/outputs/ipynb_to_md/notebook_with_complex_metadata.md ================================================ --- jupyter: kernelspec: display_name: Python 3 language: python name: python3 --- ```python ``` ================================================ FILE: tests/data/notebooks/outputs/ipynb_to_md/nteract_with_parameter.md ================================================ --- jupyter: kernel_info: name: python3 kernelspec: display_name: Python 3 language: python name: python3 --- ```python inputHidden=false outputHidden=false tags=["parameters"] param = 4 ``` ```python inputHidden=false outputHidden=false import pandas as pd ``` ```python inputHidden=false outputHidden=false df = pd.DataFrame({'A': [1, 2], 'B': [3 + param, 4]}, index=pd.Index(['x0', 'x1'], name='x')) df ``` ```python inputHidden=false outputHidden=false %matplotlib inline df.plot(kind='bar') ``` ================================================ FILE: tests/data/notebooks/outputs/ipynb_to_md/ocaml_notebook.md ================================================ --- jupyter: jupytext: formats: ipynb:markdown,md kernelspec: display_name: OCaml default language: OCaml name: ocaml-jupyter --- # Example of an OCaml notebook ```ocaml let sum x y = x + y ``` Let's try our function: ```ocaml sum 3 4 = 7 + 0 ``` ================================================ FILE: tests/data/notebooks/outputs/ipynb_to_md/octave_notebook.md ================================================ --- jupyter: kernelspec: display_name: Octave language: octave name: octave --- A markdown cell ```octave 1 + 1 ``` ```octave % a code cell with comments 2 + 2 ``` ```octave % a simple plot x = -10:0.1:10; plot (x, sin (x)); ``` ```octave %plot -w 800 % a simple plot with a magic instruction x = -10:0.1:10; plot (x, sin (x)); ``` And to finish with, a Python cell ```python a = 1 ``` ```python a + 1 ``` ================================================ FILE: tests/data/notebooks/outputs/ipynb_to_md/plotly_graphs.md ================================================ --- jupyter: kernelspec: display_name: Python 3 language: python name: python3 --- This notebook contains complex outputs, including plotly javascript graphs. # Interactive plots We use Plotly's connected mode to make the notebook lighter - when connected, the notebook downloads the `plotly.js` library from the web. ```python import plotly.offline as offline offline.init_notebook_mode(connected=True) ``` ```python import plotly.graph_objects as go fig = go.Figure( data=[go.Bar(y=[2, 3, 1])], layout=go.Layout(title="bar plot")) fig.show() fig.data[0].marker = dict(color='purple') fig ``` ================================================ FILE: tests/data/notebooks/outputs/ipynb_to_md/powershell.md ================================================ --- jupyter: kernelspec: display_name: PowerShell language: PowerShell name: powershell --- This is an extract from https://github.com/Jaykul/Jupyter-PowerShell/blob/master/LiterateDevOps.ipynb ```powershell $imageUrl = 'https://upload.wikimedia.org/wikipedia/commons/2/2f/PowerShell_5.0_icon.png' $ImageData = @{ "png" = (Invoke-WebRequest $imageUrl -UseBasicParsing).RawContentStream.GetBuffer() } # $ImageData Write-Jupyter -InputObject $ImageData -Metadata @{ "image/png" = @{ 'width' = 32 } } Write-Jupyter -InputObject $ImageData -Metadata @{ "image/png" = @{ 'width' = 64 } } ``` ================================================ FILE: tests/data/notebooks/outputs/ipynb_to_md/raw_cell_with_complex_yaml_like_content.md ================================================ --- This is a complex paragraph that is split over multiple lines. It also includes blank lines. jupyter: kernelspec: display_name: Python 3 language: python name: python3 --- ```python print("Hello, World!") ``` ================================================ FILE: tests/data/notebooks/outputs/ipynb_to_md/raw_cell_with_non_dict_yaml_content.md ================================================ --- Content. jupyter: kernelspec: display_name: Python 3 language: python name: python3 --- ```python print("Hello, World!") ``` ================================================ FILE: tests/data/notebooks/outputs/ipynb_to_md/root_cpp.md ================================================ --- jupyter: kernelspec: display_name: ROOT C++ language: c++ name: root --- ```c++ #include #include ``` ```c++ int k = 4; std::string foo = "This string says \"foo\""; ``` ```c++ std::cout << "k = " << k << '\n' << foo << '\n'; ``` ================================================ FILE: tests/data/notebooks/outputs/ipynb_to_md/sage_print_hello.md ================================================ --- jupyter: kernelspec: display_name: SageMath 9.2 language: sage name: sagemath --- ```sage print("Hello world") ``` ================================================ FILE: tests/data/notebooks/outputs/ipynb_to_md/sample_bash_notebook.md ================================================ --- jupyter: kernelspec: display_name: Bash language: bash name: bash --- ```bash ls ``` ```bash # https://coderwall.com/p/euwpig/a-better-git-log git config --global alias.lg "log --color --graph --pretty=format:'%Cred%h%Creset -%C(yellow)%d%Creset %s %Cgreen(%cr) %C(bold blue)<%an>%Creset' --abbrev-commit" ``` ```bash git lg ``` ================================================ FILE: tests/data/notebooks/outputs/ipynb_to_md/sample_rise_notebook_66.md ================================================ --- jupyter: kernelspec: display_name: Python 3 language: python name: python3 --- A markdown cell ```python slideshow={"slide_type": ""} 1+1 ``` Markdown cell two ================================================ FILE: tests/data/notebooks/outputs/ipynb_to_md/sas.md ================================================ --- jupyter: kernelspec: display_name: SAS language: sas name: sas --- # SAS Notebooks with jupytext ```sas proc sql; select * from sashelp.cars (obs=10) ; quit; ``` ```sas %let name = "Jupytext"; ``` ```sas %put &name; ``` ```sas /* Note when defining macros "%macro" cannot be the first line of text in the cell */ %macro test; data temp; set sashelp.cars; name = "testx"; run; proc print data = temp (obs=10); run; %mend test; %test ``` ================================================ FILE: tests/data/notebooks/outputs/ipynb_to_md/simple-helloworld.md ================================================ --- jupyter: jupytext: encoding: '// -*- coding: utf-8 -*-' formats: ipynb,java:light kernelspec: display_name: Java language: java name: java --- Let's define some class. ```java class A { public void hello() { System.out.println("Hello World"); } } ``` And now we call its method. ```java new A().hello(); ``` You can run it e.g. with `jshell` * from command line, as `jshell simple-helloworld.java` * from jshell's shell with `/open simple-helloworld.java` ================================================ FILE: tests/data/notebooks/outputs/ipynb_to_md/simple_robot_notebook.md ================================================ --- jupyter: kernelspec: display_name: Robot Framework language: robotframework name: robotkernel --- ```robotframework *** Settings *** Library Collections ``` ```robotframework *** Keywords *** Head [Arguments] ${list} ${value}= Get from list ${list} 0 [Return] ${value} ``` ```robotframework *** Tasks *** Get head ${array}= Create list 1 2 3 4 5 ${head}= Head ${array} Should be equal ${head} 1 ``` ================================================ FILE: tests/data/notebooks/outputs/ipynb_to_md/simple_scala_notebook.md ================================================ --- jupyter: kernelspec: display_name: Apache Toree - Scala language: scala name: apache_toree_scala --- ```scala // This is just a simple scala notebook object SampleObject { def calculation(x: Int, y: Int): Int = x + y } val result = SampleObject.calculation(1, 2) ``` ```scala println(result * 10) ``` ================================================ FILE: tests/data/notebooks/outputs/ipynb_to_md/stata_notebook.md ================================================ --- jupyter: kernelspec: display_name: Stata language: stata name: stata --- ```stata // This notebook uses the stata_kernel: https://github.com/kylebarron/stata_kernel ``` ```stata use http://www.stata-press.com/data/r13/auto ``` ```stata summarize ``` ```stata scatter weight length ``` ================================================ FILE: tests/data/notebooks/outputs/ipynb_to_md/tailrecursive-factorial.md ================================================ --- jupyter: jupytext: encoding: '// -*- coding: utf-8 -*-' formats: ipynb,groovy:light kernelspec: display_name: Groovy language: groovy name: groovy --- # TailRecursive annotation Let's check what is the effect of `@TailRecursive` annotation on the simple recursive definition of factorial function. ```groovy import groovy.transform.CompileStatic import groovy.transform.TailRecursive import groovy.transform.TypeChecked @CompileStatic @TypeChecked class X { static final BigInteger factorial0(int n) { (n <= 1) ? 1G : factorial0(n-1).multiply(BigInteger.valueOf(n)) } static final BigInteger factorial1(int n, BigInteger acc = 1G) { (n <= 1) ? acc : factorial1(n-1, acc.multiply(BigInteger.valueOf(n))) } @TailRecursive static final BigInteger factorial2(int n, BigInteger acc = 1G) { (n <= 1) ? acc : factorial2(n-1, acc.multiply(BigInteger.valueOf(n))) } } x = new X() ``` Although we can time the execution of the calls, it is not very accurate; such micro benchmarks should be performed in more controlled environment, such us under [JMH](https://openjdk.java.net/projects/code-tools/jmh/). For example, see [blog posts of Szymon Stępniak](https://e.printstacktrace.blog/tail-recursive-methods-in-groovy/). ```groovy %%timeit x.factorial0(19_000).toString().length() ``` ```groovy %%timeit x.factorial1(19_000).toString().length() ``` ```groovy %%timeit x.factorial2(19_000).toString().length() ``` The real difference is the use of stack. Non-tail recursive calls exhaust the stack space at some point, whereas tail recursive calls don't add frames to the stack. ```groovy factSize = { n, cl -> println "Factorial of ${n} has ${cl(n).toString().length()} digits" } factSize 2_000, x.&factorial0 factSize 2_000, x.&factorial1 factSize 2_000, x.&factorial2 factSize 100_000, x.&factorial2 ``` ```groovy try { factSize 100_000, x.&factorial1 } catch (Throwable e) { assert e instanceof StackOverflowError println e } ``` ================================================ FILE: tests/data/notebooks/outputs/ipynb_to_md/tcl_test.md ================================================ --- jupyter: kernelspec: display_name: Tcl language: tcl name: tcljupyter --- # Assign Values ```tcl set a 1 puts "a = $a" ``` # Loop ```tcl for {set i 0} {$i < 10} {incr i} { puts "I inside first loop: $i" } ``` ```tcl ``` ================================================ FILE: tests/data/notebooks/outputs/ipynb_to_md/text_outputs_and_images.md ================================================ --- jupyter: kernelspec: display_name: Python 3 language: python name: python3 --- This notebook contains outputs of many different types: text, HTML, plots and errors. # Text outputs Using `print`, `sys.stdout` and `sys.stderr` ```python import sys print('using print') sys.stdout.write('using sys.stdout.write') sys.stderr.write('using sys.stderr.write') ``` ```python import logging logging.debug('Debug') logging.info('Info') logging.warning('Warning') logging.error('Error') ``` # HTML outputs Using `pandas`. Here we find two representations: both text and HTML. ```python import pandas as pd pd.DataFrame([4]) ``` ```python from IPython.display import display display(pd.DataFrame([5])) display(pd.DataFrame([6])) ``` # Images ```python %matplotlib inline ``` ```python # First plot from matplotlib import pyplot as plt import numpy as np w, h = 3, 3 data = np.zeros((h, w, 3), dtype=np.uint8) data[0,:] = [0,255,0] data[1,:] = [0,0,255] data[2,:] = [0,255,0] data[1:3,1:3] = [255, 0, 0] plt.imshow(data) plt.axis('off') plt.show() # Second plot data[1:3,1:3] = [255, 255, 0] plt.imshow(data) plt.axis('off') plt.show() ``` # Errors ```python undefined_variable ``` ================================================ FILE: tests/data/notebooks/outputs/ipynb_to_md/wolfram.md ================================================ --- jupyter: kernelspec: display_name: Wolfram Language 13.1 language: Wolfram Language name: wolframlanguage13.1 --- **Note:** The `language_info` `file_extension` in this notebook should be `.m`, but it was deliberately changed to `.wolfram` to avoid conflicts with Matlab which is using the same extension. We start with... ```wolfram language Print["Hello, World!"]; ``` Then we draw the first example plot from the [ListPlot](https://reference.wolfram.com/language/ref/ListPlot.html) reference: ```wolfram language ListPlot[Prime[Range[25]]] ``` We also test the math outputs as in the [Simplify](https://reference.wolfram.com/language/ref/Simplify.html) example: ```wolfram language D[Integrate[1/(x^3 + 1), x], x] ``` ================================================ FILE: tests/data/notebooks/outputs/ipynb_to_md/xcpp_by_quantstack.md ================================================ --- jupyter: kernelspec: display_name: C++14 language: C++14 name: xeus-cling-cpp14 --- [![xeus-cling](images/xeus-cling.png)](https://github.com/QuantStack/xeus-cling/) A Jupyter kernel for C++ based on the `cling` C++ interpreter and the `xeus` native implementation of the Jupyter protocol, xeus. - GitHub repository: https://github.com/QuantStack/xeus-cling/ - Online documentation: https://xeus-cling.readthedocs.io/ ## Usage
To run the selected code cell, hit 
Shift + Enter
## Output and error streams `std::cout` and `std::cerr` are redirected to the notebook frontend. ```c++ #include std::cout << "some output" << std::endl; ``` ```c++ std::cerr << "some error" << std::endl; ``` ```c++ #include ``` ```c++ throw std::runtime_error("Unknown exception"); ``` Omitting the `;` in the last statement of a cell results in an output being printed ```c++ int j = 5; ``` ```c++ j ``` # Interpreting the C++ programming language `cling` has a broad support of the features of C++. You can define functions, classes, templates, etc ... ## Functions ```c++ double sqr(double a) { return a * a; } ``` ```c++ double a = 2.5; double asqr = sqr(a); asqr ``` ## Classes ```c++ class Foo { public: virtual ~Foo() {} virtual void print(double value) const { std::cout << "Foo value = " << value << std::endl; } }; ``` ```c++ Foo bar; bar.print(1.2); ``` ## Polymorphism ```c++ class Bar : public Foo { public: virtual ~Bar() {} virtual void print(double value) const { std::cout << "Bar value = " << 2 * value << std::endl; } }; ``` ```c++ Foo* bar2 = new Bar; bar2->print(1.2); delete bar2; ``` ## Templates ```c++ #include template class FooT { public: explicit FooT(const T& t) : m_t(t) {} void print() const { std::cout << typeid(T).name() << " m_t = " << m_t << std::endl; } private: T m_t; }; template <> class FooT { public: explicit FooT(const int& t) : m_t(t) {} void print() const { std::cout << "m_t = " << m_t << std::endl; } private: int m_t; }; ``` ```c++ FooT foot1(1.2); foot1.print(); ``` ```c++ FooT foot2(4); foot2.print(); ``` ## C++11 / C++14 support ```c++ class Foo11 { public: Foo11() { std::cout << "Foo11 default constructor" << std::endl; } Foo11(const Foo11&) { std::cout << "Foo11 copy constructor" << std::endl; } Foo11(Foo11&&) { std::cout << "Foo11 move constructor" << std::endl; } }; ``` ```c++ Foo11 f1; Foo11 f2(f1); Foo11 f3(std::move(f1)); ``` ```c++ #include std::vector v = { 1, 2, 3}; auto iter = ++v.begin(); v ``` ```c++ *iter ``` ... and also lambda, universal references, `decltype`, etc ... ## Documentation and completion - Documentation for types of the standard library is retrieved on cppreference.com. - The quick-help feature can also be enabled for user-defined types and third-party libraries. More documentation on this feature is available at https://xeus-cling.readthedocs.io/en/latest/inline_help.html. ```c++ ?std::vector ``` ## Using the `display_data` mechanism For a user-defined type `T`, the rich rendering in the notebook and JupyterLab can be enabled by by implementing the function `xeus::xjson mime_bundle_repr(const T& im)`, which returns the JSON mime bundle for that type. More documentation on the rich display system of Jupyter and Xeus-cling is available at https://xeus-cling.readthedocs.io/en/latest/rich_display.html ### Image example ```c++ #include #include #include "xtl/xbase64.hpp" #include "xeus/xjson.hpp" namespace im { struct image { inline image(const std::string& filename) { std::ifstream fin(filename, std::ios::binary); m_buffer << fin.rdbuf(); } std::stringstream m_buffer; }; xeus::xjson mime_bundle_repr(const image& i) { auto bundle = xeus::xjson::object(); bundle["image/png"] = xtl::base64encode(i.m_buffer.str()); return bundle; } } ``` ```c++ im::image marie("images/marie.png"); marie ``` ### Audio example ```c++ #include #include #include "xtl/xbase64.hpp" #include "xeus/xjson.hpp" namespace au { struct audio { inline audio(const std::string& filename) { std::ifstream fin(filename, std::ios::binary); m_buffer << fin.rdbuf(); } std::stringstream m_buffer; }; xeus::xjson mime_bundle_repr(const audio& a) { auto bundle = xeus::xjson::object(); bundle["text/html"] = std::string(""; return bundle; } } ``` ```c++ au::audio drums("audio/audio.wav"); drums ``` ### Display ```c++ #include "xcpp/xdisplay.hpp" ``` ```c++ xcpp::display(drums); ``` ### Update-display ```c++ #include #include "xcpp/xdisplay.hpp" namespace ht { struct html { inline html(const std::string& content) { m_content = content; } std::string m_content; }; xeus::xjson mime_bundle_repr(const html& a) { auto bundle = xeus::xjson::object(); bundle["text/html"] = a.m_content; return bundle; } } // A red rectangle ht::html rect(R"(
Original
)"); ``` ```c++ xcpp::display(rect, "some_display_id"); ``` ```c++ // Update the rectangle to be blue rect.m_content = R"(
Updated
)"; xcpp::display(rect, "some_display_id", true); ``` ## Magics Magics are special commands for the kernel that are not part of the C++ language. They are defined with the symbol `%` for a line magic and `%%` for a cell magic. More documentation for magics is available at https://xeus-cling.readthedocs.io/en/latest/magics.html. ```c++ #include #include ``` ```c++ std::vector to_shuffle = {1, 2, 3, 4}; ``` ```c++ %timeit std::random_shuffle(to_shuffle.begin(), to_shuffle.end()); ``` [![xtensor](images/xtensor.png)](https://github.com/QuantStack/xtensor/) - GitHub repository: https://github.com/QuantStack/xtensor/ - Online documentation: https://xtensor.readthedocs.io/ - NumPy to xtensor cheat sheet: http://xtensor.readthedocs.io/en/latest/numpy.html `xtensor` is a C++ library for manipulating N-D arrays with an API very similar to that of numpy. ```c++ #include #include "xtensor/xarray.hpp" #include "xtensor/xio.hpp" #include "xtensor/xview.hpp" xt::xarray arr1 {{1.0, 2.0, 3.0}, {2.0, 5.0, 7.0}, {2.0, 5.0, 7.0}}; xt::xarray arr2 {5.0, 6.0, 7.0}; xt::view(arr1, 1) + arr2 ``` Together with the C++ Jupyter kernel, `xtensor` offers a similar experience as `NumPy` in the Python Jupyter kernel, including broadcasting and universal functions. ```c++ #include #include "xtensor/xarray.hpp" #include "xtensor/xio.hpp" ``` ```c++ xt::xarray arr {1, 2, 3, 4, 5, 6, 7, 8, 9}; arr.reshape({3, 3}); std::cout << arr; ``` ```c++ #include "xtensor-blas/xlinalg.hpp" ``` ```c++ xt::xtensor m = {{1.5, 0.5}, {0.7, 1.0}}; std::cout << "Matrix rank: " << std::endl << xt::linalg::matrix_rank(m) << std::endl; std::cout << "Matrix inverse: " << std::endl << xt::linalg::inv(m) << std::endl; std::cout << "Eigen values: " << std::endl << xt::linalg::eigvals(m) << std::endl; ``` ```c++ xt::xarray arg1 = xt::arange(9); xt::xarray arg2 = xt::arange(18); arg1.reshape({3, 3}); arg2.reshape({2, 3, 3}); std::cout << xt::linalg::dot(arg1, arg2) << std::endl; ``` ```c++ ``` ================================================ FILE: tests/data/notebooks/outputs/ipynb_to_md/xonsh_example.md ================================================ --- jupyter: kernelspec: display_name: Xonsh language: xonsh name: xonsh --- ```xonsh len($(curl -L https://xon.sh)) ``` ```xonsh for filename in `.*`: print(filename) du -sh @(filename) ``` ================================================ FILE: tests/data/notebooks/outputs/ipynb_to_myst/Line_breaks_in_LateX_305.md ================================================ --- kernelspec: display_name: Python 3 language: python name: python3 --- This cell uses no particular cell marker $$ \begin{align} \dot{x} & = \sigma(y-x)\\ \dot{y} & = \rho x - y - xz \\ \dot{z} & = -\beta z + xy \end{align} $$ +++ This cell uses no particular cell marker, and a single slash in the $\LaTeX$ equation $$ \begin{align} \dot{x} & = \sigma(y-x) \ \dot{y} & = \rho x - y - xz \ \dot{z} & = -\beta z + xy \end{align} $$ +++ This cell uses the triple quote cell markers introduced at https://github.com/mwouts/jupytext/issues/305 $$ \begin{align} \dot{x} & = \sigma(y-x)\\ \dot{y} & = \rho x - y - xz \\ \dot{z} & = -\beta z + xy \end{align} $$ ================================================ FILE: tests/data/notebooks/outputs/ipynb_to_myst/Notebook with function and cell metadata 164.md ================================================ --- kernelspec: display_name: Python 3 language: python name: python3 --- ```{code-cell} ipython3 1 + 1 ``` A markdown cell And below, the cell for function f has non trivial cell metadata. And the next cell as well. ```{code-cell} ipython3 --- attributes: classes: [] id: '' n: '10' --- def f(x): return x ``` ```{code-cell} ipython3 --- attributes: classes: [] id: '' n: '10' --- f(5) ``` More text ```{code-cell} ipython3 2 + 2 ``` ================================================ FILE: tests/data/notebooks/outputs/ipynb_to_myst/Notebook with html and latex cells.md ================================================ --- kernelspec: display_name: Python 3 language: python name: python3 --- ```{code-cell} ipython3 %%html

Jupytext on GitHub

``` ```{code-cell} ipython3 %%latex $\frac{\pi}{2}$ ``` ```{code-cell} ipython3 %load_ext rpy2.ipython ``` ```{code-cell} ipython3 %%R library(ggplot2) ggplot(data=data.frame(x=c('A', 'B'), y=c(5, 2)), aes(x,weight=y)) + geom_bar() ``` ```{code-cell} ipython3 %matplotlib inline import pandas as pd pd.Series({'A':5, 'B':2}).plot(figsize=(3,2), kind='bar') ``` ================================================ FILE: tests/data/notebooks/outputs/ipynb_to_myst/Notebook with many hash signs.md ================================================ --- kernelspec: display_name: Python 3 language: python name: python3 --- ################################################################## This is a notebook that contains many hash signs. Hopefully its python representation is not recognized as a Sphinx Gallery script... ################################################################## ```{code-cell} ipython3 some = 1 code = 2 some+code ################################################################## # A comment ################################################################## # Another comment ``` ################################################################## This is a notebook that contains many hash signs. Hopefully its python representation is not recognized as a Sphinx Gallery script... ################################################################## ================================================ FILE: tests/data/notebooks/outputs/ipynb_to_myst/Notebook with metadata and long cells.md ================================================ --- kernelspec: display_name: Python 3 language: python name: python3 --- # Part one - various cells +++ Here we have a markdown cell with two blank lines +++ Now we have a markdown cell with a code block inside it ```python 1 + 1 ``` After that cell we'll have a code cell ```{code-cell} ipython3 2 + 2 3 + 3 ``` Followed by a raw cell ```{raw-cell} This is the content of the raw cell ``` # Part two - cell metadata +++ {"key": "value"} This is a markdown cell with cell metadata `{"key": "value"}` ```{code-cell} ipython3 --- .class: null tags: [parameters] --- """This is a code cell with metadata `{"tags":["parameters"], ".class":null}`""" ``` ```{raw-cell} :key: value This is a raw cell with cell metadata `{"key": "value"}` ``` ================================================ FILE: tests/data/notebooks/outputs/ipynb_to_myst/Notebook_with_R_magic.md ================================================ --- kernelspec: display_name: Python 2 language: python name: python2 --- # A notebook with R cells This notebook shows the use of R cells to generate plots ```{code-cell} ipython2 %load_ext rpy2.ipython ``` ```{code-cell} ipython2 %%R suppressMessages(require(tidyverse)) ``` ```{code-cell} ipython2 %%R ggplot(iris, aes(x = Sepal.Length, y = Petal.Length, color=Species)) + geom_point() ``` The default plot dimensions are not good for us, so we use the -w and -h parameters in %%R magic to set the plot size ```{code-cell} ipython2 %%R -w 400 -h 240 ggplot(iris, aes(x = Sepal.Length, y = Petal.Length, color=Species)) + geom_point() ``` ================================================ FILE: tests/data/notebooks/outputs/ipynb_to_myst/Notebook_with_more_R_magic_111.md ================================================ --- kernelspec: display_name: Python 3 language: python name: python3 --- ```{code-cell} ipython3 %load_ext rpy2.ipython import pandas as pd df = pd.DataFrame( { "Letter": ["a", "a", "a", "b", "b", "b", "c", "c", "c"], "X": [4, 3, 5, 2, 1, 7, 7, 5, 9], "Y": [0, 4, 3, 6, 7, 10, 11, 9, 13], "Z": [1, 2, 3, 1, 2, 3, 1, 2, 3], } ) ``` ```{code-cell} ipython3 %%R -i df library("ggplot2") ggplot(data = df) + geom_point(aes(x = X, y = Y, color = Letter, size = Z)) ``` ================================================ FILE: tests/data/notebooks/outputs/ipynb_to_myst/R notebook with invalid cell keys.md ================================================ --- kernelspec: display_name: R language: R name: ir --- This notebook was created with IRKernel 0.8.12, and is not completely valid, as the code cell below contains an unexpected 'source' entry. This did cause https://github.com/mwouts/jupytext/issues/234. Note that the problem is solved when one upgrades to IRKernel 1.0.0. ```{code-cell} r library("ggplot2") ggplot(mtcars, aes(mpg)) + stat_ecdf() ``` ================================================ FILE: tests/data/notebooks/outputs/ipynb_to_myst/Reference Guide for Calysto Scheme.md ================================================ --- kernelspec: display_name: Calysto Scheme (Python) language: scheme name: calysto_scheme ---

Reference Guide for Calysto Scheme

[Calysto Scheme](https://github.com/Calysto/calysto_scheme) is a real Scheme programming language, with full support for continuations, including call/cc. It can also use all Python libraries. Also has some extensions that make it more useful (stepper-debugger, choose/fail, stack traces), or make it better integrated with Python. In Jupyter notebooks, because Calysto Scheme uses [MetaKernel](https://github.com/Calysto/metakernel/blob/master/README.rst), it has a fully-supported set of "magics"---meta-commands for additional functionality. This includes running Scheme in parallel. See all of the [MetaKernel Magics](https://github.com/Calysto/metakernel/blob/master/metakernel/magics/README.md). Calysto Scheme is written in Scheme, and then translated into Python (and other backends). The entire functionality lies in a single Python file: https://github.com/Calysto/calysto_scheme/blob/master/calysto_scheme/scheme.py However, you can easily install it (see below). Please see [Calysto Scheme Language](Calysto%20Scheme%20Language.ipynb) for more details on the Calysto Scheme language. ## Installation You can install Calysto Scheme with Python3: ``` pip3 install --upgrade calysto-scheme --user -U python3 -m calysto_kernel install --user ``` or in the system kernel folder with: ``` sudo pip3 install --upgrade calysto-scheme -U sudo python3 -m calysto_kernel install ``` Change pip3/python3 to use a different pip or Python. The version of Python used will determine how Calysto Scheme is run. Use it in the console, qtconsole, or notebook with IPython 3: ``` ipython console --kernel calysto_scheme ipython qtconsole --kernel calysto_scheme ipython notebook --kernel calysto_scheme ``` In addition to all of the following items, Calysto Scheme also has access to all of Python's builtin functions, and all of Python's libraries. For example, you can use `(complex 3 2)` to create a complex number by calling Python's complex function. ## Jupyter Enhancements When you run Calysto Scheme in Jupyter (console, notebook, qtconsole, etc.) you get: * TAB completions of Scheme functions and variable names * display of rich media * stepper/debugger * magics (% macros) * shell commands (! command) * LaTeX equations * LaTeX-style variables * Python integration +++ ### LaTeX-style variables Calysto Scheme allows you to use LaTeX-style variables in code. For example, if you type: ``` \beta ``` with the cursor right after the 'a' in beta, and then press TAB, it will turn into the unicode character: ``` β ``` There are nearly 1300 different symbols defined (thanks to the Julia language) and documented here: http://docs.julialang.org/en/release-0.4/manual/unicode-input/#man-unicode-input Calysto Scheme may not implement all of those. Some useful and suggestive ones: * \pi - π * \Pi - Π * \Sigma - Σ * \_i - subscript i, such as vectorᵢ ```{code-cell} scheme (define α 67) ``` ```{code-cell} scheme α ``` ```{code-cell} scheme (define i 2) (define vectorᵢ (vector-ref (vector 0 6 3 2) i)) vectorᵢ ``` ### Rich media ```{code-cell} scheme (import "calysto.display") ``` ```{code-cell} scheme (calysto.display.HTML "This is bold, italics, underlined.") ``` ```{code-cell} scheme (import "calysto.graphics") ``` ```{code-cell} scheme (define canvas (calysto.graphics.Canvas)) ``` ```{code-cell} scheme (define ball (calysto.graphics.Circle '(150 150) 100)) ``` ```{code-cell} scheme (ball.draw canvas) ``` ### Shell commands ```{code-cell} scheme ! ls /tmp ``` ### Stepper/Debugger Here is what the debugger looks like: It has breakpoints (click in left margin). You must press Stop to exit the debugger. +++ ```scheme %%debug (begin (define x 1) (set! x 2) ) ``` +++ ### Python Integration You can import and use any Python library in Calysto Scheme. In addition, if you wish, you can execute expressions and statements in a Python environment: ```{code-cell} scheme (python-eval "1 + 2") ``` ```{code-cell} scheme (python-exec " def mypyfunc(a, b): return a * b ") ``` This is a shared environment with Scheme: ```{code-cell} scheme (mypyfunc 4 5) ``` You can use `func` to turn a Scheme procedure into a Python function, and `define!` to put it into the shared environment with Python: ```{code-cell} scheme (define! mypyfunc2 (func (lambda (n) n))) ``` ```{code-cell} scheme (python-eval "mypyfunc2(34)") ``` # Differences Between Languages ## Major differences between Scheme and Python 1. In Scheme, double quotes are used for strings and may contain newlines 1. In Scheme, a single quote is short for (quote ...) and means "literal" 1. In Scheme, everything is an expression and has a return value 1. Python does not support macros (e.g., extending syntax) 1. In Python, "if X" is false if X is None, False, [], (,) or 0. In Scheme, "if X" is only false if X is #f or 0 1. Calysto Scheme uses continuations, not the call stack. However, for debugging there is a pseudo-stack when an error is raised. You can turn that off with (use-stack-trace #f) 1. Scheme procedures are not Python functions, but there are means to use one as the other. ## Major Differences Between Calysto Scheme and other Schemes 1. define-syntax works slightly differently 1. In Calysto Scheme, #(...) is short for '#(...) 1. Calysto Scheme is missing many standard functions (see list at bottom) 1. Calysto Scheme has a built-in amb operator called `choose` 1. For debugging there is a pseudo-stack when errors are raised in Calysto Scheme. You can turn that off with (use-stack-trace #f) ### Stack Trace Calysto Scheme acts as if it has a call stack, for easier debugging. For example: ```{code-cell} scheme (define fact (lambda (n) (if (= n 1) q (* n (fact (- n 1)))))) ``` ```{code-cell} scheme (fact 5) ``` To turn off the stack trace on error: ```scheme (use-stack-trace #f) ``` That will allow infinite recursive loops without keeping track of the "stack". +++ # Calysto Scheme Variables ## SCHEMEPATH SCHEMEPATH is a list of search directories used with (load NAME). This is a reference, so you should append to it rather than attempting to redefine it. ```{code-cell} scheme SCHEMEPATH ``` ```{code-cell} scheme (set-cdr! (cdr SCHEMEPATH) (list "/var/modules")) ``` ```{code-cell} scheme SCHEMEPATH ``` ## Getting Started Note that you can use the word `lambda` or \lambda and then press [TAB] ```{code-cell} scheme (define factorial (λ (n) (cond ((zero? n) 1) (else (* n (factorial (- n 1))))))) ``` ```{code-cell} scheme (factorial 5) ``` ## define-syntax (define-syntax NAME RULES): a method for creating macros ```{code-cell} scheme (define-syntax time [(time ?exp) (let ((start (current-time))) ?exp (- (current-time) start))]) ``` ```{code-cell} scheme (time (car '(1 2 3 4))) ``` ```{code-cell} scheme ;;--------------------------------------------------------------------- ;; collect is like list comprehension in Python (define-syntax collect [(collect ?exp for ?var in ?list) (filter-map (lambda (?var) ?exp) (lambda (?var) #t) ?list)] [(collect ?exp for ?var in ?list if ?condition) (filter-map (lambda (?var) ?exp) (lambda (?var) ?condition) ?list)]) (define filter-map (lambda (f pred? values) (if (null? values) '() (if (pred? (car values)) (cons (f (car values)) (filter-map f pred? (cdr values))) (filter-map f pred? (cdr values)))))) ``` ```{code-cell} scheme (collect (* n n) for n in (range 10)) ``` ```{code-cell} scheme (collect (* n n) for n in (range 5 20 3)) ``` ```{code-cell} scheme (collect (* n n) for n in (range 10) if (> n 5)) ``` ```{code-cell} scheme ;;--------------------------------------------------------------------- ;; for loops (define-syntax for [(for ?exp times do . ?bodies) (for-repeat ?exp (lambda () . ?bodies))] [(for ?var in ?exp do . ?bodies) (for-iterate1 ?exp (lambda (?var) . ?bodies))] [(for ?var at (?i) in ?exp do . ?bodies) (for-iterate2 0 ?exp (lambda (?var ?i) . ?bodies))] [(for ?var at (?i ?j . ?rest) in ?exp do . ?bodies) (for ?var at (?i) in ?exp do (for ?var at (?j . ?rest) in ?var do . ?bodies))]) (define for-repeat (lambda (n f) (if (< n 1) 'done (begin (f) (for-repeat (- n 1) f))))) (define for-iterate1 (lambda (values f) (if (null? values) 'done (begin (f (car values)) (for-iterate1 (cdr values) f))))) (define for-iterate2 (lambda (i values f) (if (null? values) 'done (begin (f (car values) i) (for-iterate2 (+ i 1) (cdr values) f))))) ``` ```{code-cell} scheme (define matrix2d '((10 20) (30 40) (50 60) (70 80))) (define matrix3d '(((10 20 30) (40 50 60)) ((70 80 90) (100 110 120)) ((130 140 150) (160 170 180)) ((190 200 210) (220 230 240)))) ``` ```{code-cell} scheme (begin (define hello 0) (for 5 times do (set! hello (+ hello 1))) hello ) ``` ```{code-cell} scheme (for sym in '(a b c d) do (define x 1) (set! x sym) (print x)) ``` ```{code-cell} scheme (for n in (range 10 20 2) do (print n)) ``` ```{code-cell} scheme (for n at (i j) in matrix2d do (print (list n 'coords: i j))) ``` ```{code-cell} scheme (for n at (i j k) in matrix3d do (print (list n 'coords: i j k))) ``` ```{code-cell} scheme (define-syntax scons [(scons ?x ?y) (cons ?x (lambda () ?y))]) (define scar car) (define scdr (lambda (s) (let ((result ((cdr s)))) (set-cdr! s (lambda () result)) result))) (define first (lambda (n s) (if (= n 0) '() (cons (scar s) (first (- n 1) (scdr s)))))) (define nth (lambda (n s) (if (= n 0) (scar s) (nth (- n 1) (scdr s))))) (define smap (lambda (f s) (scons (f (scar s)) (smap f (scdr s))))) (define ones (scons 1 ones)) (define nats (scons 0 (combine nats + ones))) (define combine (lambda (s1 op s2) (scons (op (scar s1) (scar s2)) (combine (scdr s1) op (scdr s2))))) (define fibs (scons 1 (scons 1 (combine fibs + (scdr fibs))))) (define facts (scons 1 (combine facts * (scdr nats)))) (define ! (lambda (n) (nth n facts))) ``` ```{code-cell} scheme (! 5) ``` ```{code-cell} scheme (nth 10 facts) ``` ```{code-cell} scheme (nth 20 fibs) ``` ```{code-cell} scheme (first 30 fibs) ``` ## for-each (for-each PROCEDURE LIST): apply PROCEDURE to each item in LIST; like `map` but don't return results ```{code-cell} scheme (for-each (lambda (n) (print n)) '(3 4 5)) ``` ## format (format STRING ITEM ...): format the string with ITEMS as arguments ```{code-cell} scheme (format "This uses formatting ~a ~s ~%" 'apple 'apple) ``` ## func Turns a lambda into a Python function. (func (lambda ...)) ```{code-cell} scheme (func (lambda (n) n)) ``` ## There's more! Please see [Calysto Scheme Language](Calysto%20Scheme%20Language.ipynb) for more details on the Calysto Scheme language. ================================================ FILE: tests/data/notebooks/outputs/ipynb_to_myst/The flavors of raw cells.md ================================================ --- kernelspec: display_name: Python 3 language: python name: python3 --- ```{raw-cell} :raw_mimetype: text/latex $1+1$ ``` ```{raw-cell} :raw_mimetype: text/restructuredtext :math:`1+1` ``` ```{raw-cell} :raw_mimetype: text/html Bold text ``` ```{raw-cell} :raw_mimetype: text/markdown **Bold text** ``` ```{raw-cell} :raw_mimetype: text/x-python 1 + 1 ``` ```{raw-cell} Not formatted ``` ================================================ FILE: tests/data/notebooks/outputs/ipynb_to_myst/cat_variable.md ================================================ --- kernelspec: display_name: Python 3 language: python name: python3 --- ```{code-cell} ipython3 cat = 42 ``` ================================================ FILE: tests/data/notebooks/outputs/ipynb_to_myst/coconut_homepage_demo.md ================================================ --- kernelspec: display_name: Coconut language: coconut name: coconut --- Taken from [coconut-lang.org](coconut-lang.org) +++ pipeline-style programming ```{code-cell} coconut "hello, world!" |> print ``` prettier lambdas ```{code-cell} coconut x -> x ** 2 ``` partial application ```{code-cell} coconut range(10) |> map$(pow$(?, 2)) |> list ``` pattern-matching ```{code-cell} coconut match [head] + tail in [0, 1, 2, 3]: print(head, tail) ``` destructuring assignment ```{code-cell} coconut {"list": [0] + rest} = {"list": [0, 1, 2, 3]} ``` infix notation ```{code-cell} coconut # 5 `mod` 3 == 2 ``` operator functions ```{code-cell} coconut product = reduce$(*) ``` function composition ```{code-cell} coconut # (f..g..h)(x, y, z) ``` lazy lists ```{code-cell} coconut # (| first_elem() |) :: rest_elems() ``` parallel programming ```{code-cell} coconut range(100) |> parallel_map$(pow$(2)) |> list ``` tail call optimization ```{code-cell} coconut def factorial(n, acc=1): case n: match 0: return acc match _ is int if n > 0: return factorial(n-1, acc*n) ``` algebraic data types ```{code-cell} coconut data Empty() data Leaf(n) data Node(l, r) def size(Empty()) = 0 addpattern def size(Leaf(n)) = 1 addpattern def size(Node(l, r)) = size(l) + size(r) ``` and much more! Like what you see? Don't forget to star Coconut on GitHub! ```{code-cell} coconut ``` ================================================ FILE: tests/data/notebooks/outputs/ipynb_to_myst/convert_to_py_then_test_with_update83.md ================================================ --- kernelspec: display_name: Python 3 language: python name: python3 --- ```{code-cell} ipython3 %%time print('asdf') ``` Thanks for jupytext! ```{code-cell} ipython3 ``` ================================================ FILE: tests/data/notebooks/outputs/ipynb_to_myst/csharp.md ================================================ --- kernelspec: display_name: .NET (C#) language: C# name: .net-csharp --- We start with... ```{code-cell} csharp Console.WriteLine("Hello World!"); ``` Then we do a plot with Plotly, following the [Plotting with XPlot](https://github.com/dotnet/interactive/blob/master/NotebookExamples/csharp/Docs/Plotting%20with%20Xplot.ipynb) example from `dotnet/interactive`: ```{code-cell} csharp using XPlot.Plotly; var bar = new Graph.Bar { name = "Bar", x = new[] {'A', 'B', 'C'}, y = new[] {1, 3, 2} }; var chart = Chart.Plot(new[] {bar}); chart.WithTitle("A bar plot"); display(chart); ``` We also test the math outputs as in the [Math and Latex](https://github.com/dotnet/interactive/blob/master/NotebookExamples/csharp/Docs/Math%20and%20LaTeX.ipynb) example: ```{code-cell} csharp (LaTeXString)@"\begin{align} e^{i \pi} = -1\end{align}" ``` ```{code-cell} csharp (MathString)@"e^{i \pi} = -1" ``` ================================================ FILE: tests/data/notebooks/outputs/ipynb_to_myst/demo_gdl_fbp.md ================================================ --- kernelspec: display_name: IDL [conda env:gdl] * language: IDL name: conda-env-gdl-idl --- ## GDL demo notebook +++ Demonstration of GDL [(gnudatalanguage)](https://github.com/gnudatalanguage/gdl) This notebook creates a Shepp-Logan phantom, projects it and then performs an FBP reconstruction. ```{code-cell} ;; L.A. Shepp and B.F. Logan, “The Fourier reconstruction of a head section,” ;; IEEE Trans. Nucl. Sci. 21(3), 21–43 (1974). function shepplogan, size = size if NOT keyword_set(size) then size = 256 phantom = fltarr(size,size) tmp = (findgen(size)-((size-1)/2.0)) / (size/2.0) xcor = rebin(tmp,size,size) ycor = rebin(transpose(tmp),size,size) tmp = fltarr(size,size) aa={cx: 0.0, cy: 0.0, maj:0.69, min:0.92, theta: 0.0, val: 2.0 } bb={cx: 0.0, cy:-0.0184, maj:0.6624, min:0.874, theta: 0.0, val:-0.98} cc={cx: 0.22, cy: 0.0, maj:0.11, min:0.31, theta:-18.0, val:-0.02} dd={cx:-0.22, cy: 0.0, maj:0.16, min:0.41, theta: 18.0, val:-0.02} ee={cx: 0.0, cy: 0.35, maj:0.21, min:0.25, theta: 0.0, val:-0.01} ff={cx: 0.0, cy: 0.1, maj:0.046, min:0.046, theta: 0.0, val:-0.01} gg={cx: 0.0, cy:-0.1, maj:0.046, min:0.046, theta: 0.0, val:-0.01} hh={cx:-0.08, cy:-0.605, maj:0.046, min:0.023, theta: 0.0, val:-0.01} ii={cx: 0.0, cy:-0.605, maj:0.023, min:0.023, theta: 0.0, val:-0.01} jj={cx: 0.06, cy:-0.605, maj:0.023, min:0.046, theta: 0.0, val:-0.01} list = [aa,bb,cc,dd,ee,ff,gg,hh,ii,jj] for n = 0, n_elements(list)-1 do begin tmp = ((xcor-list[n].cx) / list[n].maj)^2 $ + ((ycor-list[n].cy) / list[n].min)^2 if list[n].theta NE 0 then begin nx = (size-1) * (list[n].cx + 1) / 2 ny = (size-1) * (list[n].cy + 1) / 2 tmp = rot(tmp, -list[n].theta, 1, nx, ny, /interp, /pivot) endif phantom[where(tmp LE 1.0)] += list[n].val endfor return, phantom < 1.1 end ``` ```{code-cell} ;; Enable inline plotting !inline=1 ``` ```{code-cell} phantom = shepplogan() window, 0, xsize=256, ysize=256 tvscl, phantom > 0.95 ``` Now we define simple forward and backprojection functions: ```{code-cell} function proj, image, angle sino_size_x = max(size(image,/dim)) sino_size_y = n_elements(angle) sino = fltarr(sino_size_x, sino_size_y) for aa=0, n_elements(angle)-1 do begin sino[*,aa] = total(rot(image, angle[aa], /interp), 2) endfor return, sino end ``` ```{code-cell} function back, sino, angle image_size = n_elements(sino[*,0]) image = fltarr(image_size,image_size) for aa=0, n_elements(angle)-1 do begin image += rot(rebin(sino[*,aa],[image_size,image_size]), -angle[aa], /interp) endfor return, image / n_elements(angle) end ``` This allows us to create a sinogram: ```{code-cell} angles = findgen(360) sino = proj(phantom, angles) window, 0, xsize=256, ysize=360 tvscl, sino ``` On this we can apply a simple FBP reconstruction: ```{code-cell} ;; G.L. Zeng, “Revisit of the Ramp Filter,” ;; IEEE Trans. Nucl. Sci. 62(1), 131–136 (2015). function fbp, sino, angles ntot = n_elements(sino[*,0]) nang = n_elements(sino[0,*]) npos = ntot / 2 + 1 ; integer division needed ! nneg = ntot - npos freq = findgen(ntot) freq[npos:ntot-1] = REVERSE(freq[1:nneg]) freq[0] = 1 filter = -1 / (!pi * freq)^2 filter[where(freq mod 2 EQ 0)] *= -0.0 filter[0] = 0.25 filter = abs(fft(filter)) * ntot filter[ntot/4:ntot/4+ntot/2-1] *= 0.0 filter = rebin(filter,ntot,nang) ;; apply filter to the sinogram fsino = fft(sino, dim=1) fsino *= filter fsino = fft(fsino, dim=1, /overwrite, /inverse) fsino = !pi * real_part(fsino) ;; backproject the filtered sinogram return, back(fsino, angles) end ``` ```{code-cell} reconstruction = fbp(sino, angles) window, 0, xsize=512, ysize=256 tvscl, [phantom, reconstruction] > 0.8 ``` ### The end ================================================ FILE: tests/data/notebooks/outputs/ipynb_to_myst/evcxr_jupyter_tour.md ================================================ --- kernelspec: display_name: Rust language: rust name: rust --- # Tour of the EvCxR Jupyter Kernel For those not already familiar with Jupyter notebook, it lets you write code into "cells" like the box below. Cells can alternatively contain markdown, like this text here. Each code cell is compiled and executed separately, but variables, defined functions etc persist between cells. ## Printing to outputs and evaluating expressions Lets print something to stdout and stderr then return a final expression to see how that's presented. Note that stdout and stderr are separate streams, so may not appear in the same order is their respective print statements. ```{code-cell} println!("Hello world"); eprintln!("Hello error"); format!("Hello {}", "world") ``` ## Assigning and making use of variables We define a variable `message`, then in the subsequent cell, modify the string and finally print it out. We could also do all this in the one cell if we wanted. ```{code-cell} let mut message = "Hello ".to_owned(); ``` ```{code-cell} message.push_str("world!"); ``` ```{code-cell} message ``` ## Defining and redefining functions Next we'll define a function ```{code-cell} pub fn fib(x: i32) -> i32 { if x <= 2 {0} else {fib(x - 2) + fib(x - 1)} } ``` ```{code-cell} (1..13).map(fib).collect::>() ``` Hmm, that doesn't look right. Lets redefine the function. In practice, we'd go back and edit the function above and reevaluate it, but here, lets redefine it in a separate cell. ```{code-cell} pub fn fib(x: i32) -> i32 { if x <= 2 {2} else {fib(x - 2) + fib(x - 1)} } ``` ```{code-cell} let values = (1..13).map(fib).collect::>(); values ``` ## Spawning a separate thread and communicating with it We can spawn a thread to do stuff in the background, then continue executing code in other cells. ```{code-cell} use std::sync::{Mutex, Arc}; let counter = Arc::new(Mutex::new(0i32)); std::thread::spawn({ let counter = Arc::clone(&counter); move || { for i in 1..300 { *counter.lock().unwrap() += 1; std::thread::sleep(std::time::Duration::from_millis(100)); } }}); ``` ```{code-cell} *counter.lock().unwrap() ``` ```{code-cell} *counter.lock().unwrap() ``` ## Loading external crates We can load external crates. This one takes a while to compile, but once it's compiled, subsequent cells shouldn't need to recompile it, so it should be much quicker. ```{code-cell} :dep base64 = "0.10.1" base64::encode(&vec![1, 2, 3, 4]) ``` ## Customizing how types are displayed We can also customize how our types are displayed, including presenting them as HTML. Here's an example where we define a custom display function for a type `Matrix`. ```{code-cell} use std::fmt::Debug; pub struct Matrix {pub values: Vec, pub row_size: usize} impl Matrix { pub fn evcxr_display(&self) { let mut html = String::new(); html.push_str(""); for r in 0..(self.values.len() / self.row_size) { html.push_str(""); for c in 0..self.row_size { html.push_str(""); } html.push_str(""); } html.push_str("
"); html.push_str(&format!("{:?}", self.values[r * self.row_size + c])); html.push_str("
"); println!("EVCXR_BEGIN_CONTENT text/html\n{}\nEVCXR_END_CONTENT", html); } } ``` ```{code-cell} let m = Matrix {values: vec![1,2,3,4,5,6,7,8,9], row_size: 3}; m ``` We can also return images, we just need to base64 encode them. First, we set up code for displaying RGB and grayscale images. ```{code-cell} extern crate image; extern crate base64; pub trait EvcxrResult {fn evcxr_display(&self);} impl EvcxrResult for image::RgbImage { fn evcxr_display(&self) { let mut buffer = Vec::new(); image::png::PNGEncoder::new(&mut buffer).encode(&**self, self.width(), self.height(), image::ColorType::RGB(8)).unwrap(); let img = base64::encode(&buffer); println!("EVCXR_BEGIN_CONTENT image/png\n{}\nEVCXR_END_CONTENT", img); } } impl EvcxrResult for image::GrayImage { fn evcxr_display(&self) { let mut buffer = Vec::new(); image::png::PNGEncoder::new(&mut buffer).encode(&**self, self.width(), self.height(), image::ColorType::Gray(8)).unwrap(); let img = base64::encode(&buffer); println!("EVCXR_BEGIN_CONTENT image/png\n{}\nEVCXR_END_CONTENT", img); } } ``` ```{code-cell} image::ImageBuffer::from_fn(256, 256, |x, y| { if (x as i32 - y as i32).abs() < 3 { image::Rgb([0, 0, 255]) } else { image::Rgb([0, 0, 0]) } }) ``` ## Display of compilation errors Here's how compilation errors are presented. Here we forgot an & and passed a String instead of an &str. ```{code-cell} let mut s = String::new(); s.push_str(format!("foo {}", 42)); ``` ## Seeing what variables have been defined We can print a table of defined variables and their types with the :vars command. ```{code-cell} :vars ``` Other built-in commands can be found via :help ```{code-cell} :help ``` ```{code-cell} ``` ================================================ FILE: tests/data/notebooks/outputs/ipynb_to_myst/frozen_cell.md ================================================ --- kernelspec: display_name: Python 3 language: python name: python3 --- ```{code-cell} ipython3 # This is an unfrozen cell. Works as usual. print("I'm a regular cell so I run and print!") ``` ```{code-cell} ipython3 --- deletable: false editable: false run_control: frozen: true --- # This is an frozen cell print("I'm frozen so Im not executed :(") ``` ================================================ FILE: tests/data/notebooks/outputs/ipynb_to_myst/fsharp.md ================================================ --- kernelspec: display_name: .NET (F#) language: F# name: .net-fsharp --- This notebook was inspired by [Plottting with XPlot](https://github.com/dotnet/interactive/blob/master/NotebookExamples/fsharp/Docs/Plotting%20with%20Xplot.ipynb). ```{code-cell} fsharp open XPlot.Plotly ``` ```{code-cell} fsharp let bar = Bar( name = "Bar 1", x = ["A"; "B"; "C"], y = [1; 3; 2]) [bar] |> Chart.Plot |> Chart.WithTitle "A sample bar plot" ``` ================================================ FILE: tests/data/notebooks/outputs/ipynb_to_myst/gnuplot_notebook.md ================================================ --- kernelspec: display_name: gnuplot language: gnuplot name: gnuplot --- # Sample gnuplot notebook +++ ## Simple plotting ```{code-cell} # Plot sin and cos with different linetypes f(x) = sin(x) g(x) = cos(x) set xrange[0:2*pi] set xtics(0, "{/Symbol p}" pi , "2{/Symbol p}" 2*pi) set ytics 1 plot f(x) linewidth 2 title "sin(x)", \ g(x) linewidth 2 dashtype "--" title "cos(x)" ``` ## Example of line magic ```{code-cell} %gnuplot inline pngcairo enhanced background rgb "#EEEEEE" size 600, 600 # Parametric plot without border reset set parametric set size ratio -1 unset border unset tics plot f(t), g(t) linewidth 2 notitle ``` ================================================ FILE: tests/data/notebooks/outputs/ipynb_to_myst/haskell_notebook.md ================================================ --- kernelspec: display_name: Haskell language: haskell name: haskell --- # Example Haskell Notebook +++ Define a function to add two numbers. ```{code-cell} Haskell f :: Num a => a -> a -> a f x y = x + y ``` Try to use the function ```{code-cell} Haskell f 1 2 ``` ================================================ FILE: tests/data/notebooks/outputs/ipynb_to_myst/hello_world_gonb.md ================================================ --- kernelspec: display_name: Go (gonb) language: go name: gonb --- A notebook that use [GoNB](https://github.com/janpfeifer/gonb) +++ the code below comes from [tutorial.ipynb](https://github.com/janpfeifer/gonb/blob/main/examples/tutorial.ipynb) ```{code-cell} func main() { fmt.Printf("Hello World!") } ``` ```{code-cell} %% fmt.Printf("Hello World!") ``` %% --who=world can pass flags to main func ```{code-cell} import ( "flag" "fmt" ) var flagWho = flag.String("who", "", "Your name!") %% --who=world fmt.Printf("Hello %s!\n", *flagWho) ``` %args also can pass flags ```{code-cell} %args --who=Wally func main() { flag.Parse() fmt.Printf("Where is %s?", *flagWho) } ``` ```{code-cell} import "github.com/janpfeifer/gonb/gonbui" %% gonbui.DisplayHtml(`I 🧡 GoNB!`) ``` ```{code-cell} %% gonbui.DisplayMarkdown("#### Objective\n\n1. Have fun coding **Go**;\n1. Profit...\n"+ `$$f(x) = \int_{-\infty}^{\infty} e^{-x^2} dx$$`) ``` ```{code-cell} func init_a() { fmt.Println("init_a") } %% fmt.Println("main") ``` ================================================ FILE: tests/data/notebooks/outputs/ipynb_to_myst/ijavascript.md ================================================ --- kernelspec: display_name: Javascript (Node.js) language: javascript name: javascript --- ## A notebook that uses IJavascript kernel ```{code-cell} let x = 5; const y = 6; var z = 10; ``` ```{code-cell} x + y; ``` ```{code-cell} function add(num1, num2) { return num1 + num2 } ``` ```{code-cell} add(x, y); ``` ```{code-cell} const arrowAdd = (num1, num2) => num1 + num2; ``` ```{code-cell} arrowAdd(x, y); ``` ```{code-cell} const myCar = { color: "blue", weight: 850, model: "fiat", start: () => "car started!", doors: [1,2,3,4] } ``` ```{code-cell} console.log("color:", myCar.color); ``` ```{code-cell} console.log("start:", myCar.start()); ``` ```{code-cell} for (let door of myCar.doors) { console.log("I'm door", door) } ``` ```{code-cell} myCar; ``` ```{code-cell} class User { constructor(name){ this.name = name; } sayHello(){ return "Hello, I'm " + this.name; } } ``` ```{code-cell} let John = new User("John"); John.sayHello(); ``` ================================================ FILE: tests/data/notebooks/outputs/ipynb_to_myst/ir_notebook.md ================================================ --- kernelspec: display_name: R language: R name: ir --- This is a jupyter notebook that uses the IR kernel. ```{code-cell} r sum(1:10) ``` ```{code-cell} r plot(cars) ``` ```{code-cell} r ``` ================================================ FILE: tests/data/notebooks/outputs/ipynb_to_myst/itypescript.md ================================================ --- kernelspec: display_name: Typescript 3.5 language: typescript name: typescript --- ```{code-cell} let x: number = 5; const y: number = 6; var z: string = "hi"; console.log(z); x + y; ``` ```{code-cell} function add(num1: number, num2: number): number { return num1 + num2 } add(x, y); ``` ```{code-cell} const arrowAdd = (num1: number, num2: number) => num1 + num2; arrowAdd(x, y); ``` ```{code-cell} class User { constructor(private name: string) { this.name = name; } sayHello(): string { return "Hello, I'm " + this.name; } } let John: User; John = new User("John"); John.sayHello(); ``` ================================================ FILE: tests/data/notebooks/outputs/ipynb_to_myst/julia_benchmark_plotly_barchart.md ================================================ --- kernelspec: display_name: Julia 1.1.1 language: julia name: julia-1.1 --- ```{code-cell} # IJulia rocks! So does Plotly. Check it out using Plotly api_key = "" # visit https://plot.ly/api to generate an API username and password username = "" Plotly.signin(username, api_key) ``` ```{code-cell} # Following data taken from http://julialang.org/ frontpage benchmarks = ["fib", "parse_int", "quicksort3", "mandel", "pi_sum", "rand_mat_stat", "rand_mat_mul"] platforms = ["Fortran", "Julia", "Python", "R", "Matlab", "Mathematica", "Javascript", "Go"] data = { platforms[1] => [0.26, 5.03, 1.11, 0.86, 0.80, 0.64, 0.96], platforms[2] => [0.91, 1.60, 1.14, 0.85, 1.00, 1.66, 1.01], platforms[3] => [30.37, 13.95, 31.98, 14.19, 16.33, 13.52, 3.41 ], platforms[4] => [411.36, 59.40, 524.29, 106.97, 15.42, 10.84, 3.98 ], platforms[5] => [1992.00, 1463.16, 101.84, 64.58, 1.29, 6.61, 1.10 ], platforms[6] => [64.46, 29.54, 35.74, 6.07, 1.32, 4.52, 1.16 ], platforms[7] => [2.18, 2.43, 3.51, 3.49, 0.84, 3.28, 14.60], platforms[8] => [1.03, 4.79, 1.25, 2.36, 1.41, 8.12, 8.51] } pdata = [ {"x"=>benchmarks,"y"=>data[k],"bardir"=>"h","type"=>"bar","name"=>k} for k = platforms ] layout = { "title"=> "Julia benchmark comparison (smaller is better, C performance = 1.0)", "barmode"=> "group", "autosize"=> false, "width"=> 900, "height"=> 900, "titlefont"=> { "family"=> "Open Sans", "size"=> 18, "color"=> "rgb(84, 39, 143)" }, "margin"=> {"l"=>160, "pad"=>0}, "xaxis"=> { "title"=> "Benchmark log-time", "type"=> "log" }, "yaxis"=> {"title"=> "Benchmark Name"} } response = Plotly.plot(pdata,["layout"=>layout]) # Embed in an iframe within IJulia s = string("") display("text/html", s) ``` ```{code-cell} # checkout https://plot.ly/api/ for more Julia examples! # But to show off some other Plotly features: x = 1:1500 y1 = sin(2*pi*x/1500.) + rand(1500)-0.5 y2 = sin(2*pi*x/1500.) fish = {"x"=>x,"y"=> y1, "type"=>"scatter","mode"=>"markers", "marker"=>{"color"=>"rgb(0, 0, 255)","opacity"=>0.5 } } fit = {"x"=> x,"y"=> y2, "type"=>"scatter", "mode"=>"markers", "opacity"=>0.8, "marker"=>{"color"=>"rgb(255, 0, 0)"} } layout = {"autosize"=> false, "width"=> 650, "height"=> 550, "title"=>"Fish School", "xaxis"=>{ "ticks"=> "", "gridcolor"=> "white", "zerolinecolor"=> "white", "linecolor"=> "white", "autorange"=> false, "range"=>[0,1500] }, "yaxis"=>{ "ticks"=> "", "gridcolor"=> "white", "zerolinecolor"=> "white", "linecolor"=> "white", "autorange"=> false, "range"=>[-2.2,2.2] }, "plot_bgcolor"=> "rgb(245,245,247)", "showlegend"=> false, "hovermode"=> "closest"} response = Plotly.plot([fish, fit],["layout"=>layout]) s = string("") display("text/html", s) ``` ================================================ FILE: tests/data/notebooks/outputs/ipynb_to_myst/jupyter.md ================================================ --- kernelspec: display_name: Python 3 language: python name: python3 --- # Jupyter notebook This notebook is a simple jupyter notebook. It only has markdown and code cells. And it does not contain consecutive markdown cells. We start with an addition: ```{code-cell} ipython3 a = 1 b = 2 a + b ``` Now we return a few tuples ```{code-cell} ipython3 a, b ``` ```{code-cell} ipython3 a, b, a+b ``` And this is already the end of the notebook ================================================ FILE: tests/data/notebooks/outputs/ipynb_to_myst/jupyter_again.md ================================================ --- kernelspec: display_name: Python 3 language: python name: python3 --- ```{code-cell} ipython3 c = ''' title: "Quick test" output: ioslides_presentation: widescreen: true smaller: true editor_options: chunk_output_type console ''' ``` ```{code-cell} ipython3 import yaml print(yaml.dump(yaml.load(c))) ``` ```{code-cell} ipython3 ?next ``` ================================================ FILE: tests/data/notebooks/outputs/ipynb_to_myst/jupyter_with_raw_cell_in_body.md ================================================ --- kernelspec: display_name: Python 3 language: python name: python3 --- ```{code-cell} ipython3 1+2+3 ``` ```{raw-cell} This is a raw cell ``` This is a markdown cell ================================================ FILE: tests/data/notebooks/outputs/ipynb_to_myst/jupyter_with_raw_cell_on_top.md ================================================ --- title: Quick test output: ioslides_presentation: widescreen: true smaller: true editor_options: chunk_output_type: console kernelspec: display_name: Python 3 language: python name: python3 jupytext: root_level_metadata_filter: -title,-output,-editor_options --- ```{code-cell} ipython3 1+2+3 ``` ```{code-cell} ipython3 ``` ================================================ FILE: tests/data/notebooks/outputs/ipynb_to_myst/jupyter_with_raw_cell_with_invalid_yaml.md ================================================ --- kernelspec: display_name: Python 3 (ipykernel) language: python name: python3 --- ```{raw-cell} --- title: Exception: Test --- ``` ```{code-cell} ipython3 1 + 2 + 3 ``` ================================================ FILE: tests/data/notebooks/outputs/ipynb_to_myst/jupyterlab-slideshow_1441.md ================================================ --- kernelspec: display_name: Python 3 (ipykernel) language: python name: python3 --- +++ {"@deathbeds/jupyterlab-fonts": {"styles": {"": {"body[data-jp-deck-mode='presenting'] &": {"right": "0", "top": "30%", "width": "25%", "z-index": 1}}}}, "jupyterlab-slideshow": {"layer": "slide"}} > **Note** > > `slide` layer with a `top` of `30%` ================================================ FILE: tests/data/notebooks/outputs/ipynb_to_myst/jupytext_replication.md ================================================ --- kernelspec: display_name: SoS language: sos name: sos --- +++ {"Collapsed": "false", "kernel": "SoS"} # Text SOS-kernel with Jupytext ## What is SOS kernel SoS consists of a ployglot notebook that allows the use of multiple kernels in one Jupyter notebook, and a workflow system that is designed for daily computational research. Basically, - SoS Polyglot Notebook is a Jupyter Notebook with a SoS kernel. - SoS Notebook serves as a super kernel to all other Jupyter kernels and allows the use of multiple kernels in one Jupyter notebook. - SoS Workflow System is a Python based workflow system that is designed to be readable, shareable, and suitable for daily data analysis. - SoS Workflow System can be used from command line or use SoS Notebook as its IDE. ![](https://vatlab.github.io/sos-docs/doc/media/SoS_Notebook_and_Workflow.png) ### How to install SOS-kernel Please follow this [link](https://vatlab.github.io/sos-docs/running.html#Conda-installation) to setup SOS I run some issue with the latest version of R on my Mac, so I had to install an earlier version of R ``` conda install -c r r=3.5.1 conda install sos-notebook jupyterlab-sos sos-papermill -c conda-forge ``` ## Related issue with Jupytext Jupytext works fine with Python/R kernel but converts code cells into markdown cells when using the SOS kernel. cf the image below. It is a code cell. After saving the notebook and restart it, it converted the code cell into markdown Screenshot 2020-03-13 at 10 51 18 +++ {"Collapsed": "false", "kernel": "SoS"} ## Step 1 Please, choose SOS Kernel and then, in the cell code, choose SOS (or any other kernel available), the outcome is the same. ![](https://drive.google.com/uc?export=view&id=1OtyxfwoRyVK23XHnmd9JR-crBgHBL5mt) ```{code-cell} sos :Collapsed: 'false' :kernel: SoS import pandas as pd import numpy as np pd.DataFrame({ 'x': np.random.random(10), 'y': np.random.random(10), }) ``` +++ {"Collapsed": "false", "kernel": "python3"} ## Step 2 Now, pair it with Jupytex ![](https://drive.google.com/uc?export=view&id=1Wtx-YPAXY8HWHqzCcy4iIgHpzt_9emEn) +++ {"Collapsed": "false", "kernel": "python3"} ### Step 3 Save the notebook, restart and clear all, **save**, then Shut down kernel. Close the notebook and reopen +++ {"Collapsed": "false", "kernel": "python3"} ### Step 4 Reopen the notebook. Here is the outcome ![](https://drive.google.com/uc?export=view&id=12C70unbSPv0gHCZaCICEUy7kO7wM93JH) ================================================ FILE: tests/data/notebooks/outputs/ipynb_to_myst/kalman_filter_and_visualization.md ================================================ --- kernelspec: display_name: Q 3.5 language: q name: qpk --- ```{code-cell} plt: .p.import`matplotlib.pyplot ``` ```{code-cell} filter: { t: ([] x: `float $ x; xh: `float $ x; p: (count x) # R: var x); (first t), iterate[R; R]\[first t; 1 _ t] } iterate: {[Q; R; x; y] x[`p]+: Q; k: x[`p] % R + x[`p]; `x`xh`p ! (y[`x]; x[`xh] + k * y[`x] - x[`xh]; (1 - k) * x[`p]) } ``` ```{code-cell} price: 100 + sums 0.5 - (n:50)?1. ``` ```{code-cell} output:filter price ``` ```{code-cell} plt[`:plot][til n; output`x; `label pykw "price"]; plt[`:plot][til n; output`xh;`label pykw "forecast"]; plt[`:legend][]; plt[`:show][]; ``` ```{code-cell} ``` ================================================ FILE: tests/data/notebooks/outputs/ipynb_to_myst/logtalk_notebook.md ================================================ --- kernelspec: display_name: Logtalk language: logtalk name: logtalk_kernel --- # An implementation of the Ackermann function ```{code-cell} --- vscode: languageId: logtalk --- %%load ack.lgt :- object(ack). :- info([ version is 1:0:0, author is 'Paulo Moura', date is 2008-3-31, comment is 'Ackermann function (general recursive function).' ]). :- public(ack/3). :- mode(ack(+integer, +integer, -integer), one). :- info(ack/3, [ comment is 'Ackermann function.', argnames is ['M', 'N', 'V'] ]). ack(0, N, V) :- !, V is N + 1. ack(M, 0, V) :- !, M2 is M - 1, ack(M2, 1, V). ack(M, N, V) :- M2 is M - 1, N2 is N - 1, ack(M, N2, V2), ack(M2, V2, V). :- end_object. ``` ## Sample query ```{code-cell} --- vscode: languageId: logtalk --- ack::ack(2, 4, V). ``` ================================================ FILE: tests/data/notebooks/outputs/ipynb_to_myst/lua_example.md ================================================ --- kernelspec: display_name: Lua language: lua name: lua --- Source: https://www.lua.org/pil/19.3.html +++ # Sort +++ Another useful function on arrays is table.sort, which we have seen before. It receives the array to be sorted, plus an optional order function. This order function receives two arguments and must return true if the first argument should come first in the sorted array. If this function is not provided, sort uses the default less-than operation (corresponding to the `<´ operator). +++ A common mistake is to try to order the indices of a table. In a table, the indices form a set, and have no order whatsoever. If you want to order them, you have to copy them to an array and then sort the array. Let us see an example. Suppose that you read a source file and build a table that gives, for each function name, the line where that function is defined; something like this: ```{code-cell} lines = { luaH_set = 10, luaH_get = 24, luaH_present = 48, } ``` Now you want to print these function names in alphabetical order. If you traverse this table with pairs, the names appear in an arbitrary order. However, you cannot sort them directly, because these names are keys of the table. However, when you put these names into an array, then you can sort them. First, you must create an array with those names, then sort it, and finally print the result: ```{code-cell} a = {} for n in pairs(lines) do table.insert(a, n) end table.sort(a) for i,n in ipairs(a) do print(n) end ``` Note that, for Lua, arrays also have no order. But we know how to count, so we get ordered values as long as we access the array with ordered indices. That is why you should always traverse arrays with ipairs, rather than pairs. The first imposes the key order 1, 2, ..., whereas the latter uses the natural arbitrary order of the table. +++ As a more advanced solution, we can write an iterator that traverses a table following the order of its keys. An optional parameter f allows the specification of an alternative order. It first sorts the keys into an array, and then iterates on the array. At each step, it returns the key and value from the original table: ```{code-cell} function pairsByKeys (t, f) local a = {} for n in pairs(t) do table.insert(a, n) end table.sort(a, f) local i = 0 -- iterator variable local iter = function () -- iterator function i = i + 1 if a[i] == nil then return nil else return a[i], t[a[i]] end end return iter end ``` With this function, it is easy to print those function names in alphabetical order. The loop ```{code-cell} for name, line in pairsByKeys(lines) do print(name, line) end ``` ================================================ FILE: tests/data/notebooks/outputs/ipynb_to_myst/maxima_example.md ================================================ --- kernelspec: display_name: Maxima language: maxima name: maxima --- ## maxima misc ```{code-cell} maxima kill(all)$ ``` ```{code-cell} maxima f(x) := 1/(x^2+l^2)^(3/2); ``` ```{code-cell} maxima integrate(f(x), x); ``` ```{code-cell} maxima tex(%)$ ``` ```{code-cell} maxima ``` ================================================ FILE: tests/data/notebooks/outputs/ipynb_to_myst/notebook_with_complex_metadata.md ================================================ --- kernelspec: display_name: Python 3 language: python name: python3 --- ```{code-cell} ipython3 ``` ================================================ FILE: tests/data/notebooks/outputs/ipynb_to_myst/nteract_with_parameter.md ================================================ --- kernel_info: name: python3 kernelspec: display_name: Python 3 language: python name: python3 --- ```{code-cell} ipython3 :inputHidden: false :outputHidden: false :tags: [parameters] param = 4 ``` ```{code-cell} ipython3 :inputHidden: false :outputHidden: false import pandas as pd ``` ```{code-cell} ipython3 :inputHidden: false :outputHidden: false df = pd.DataFrame({'A': [1, 2], 'B': [3 + param, 4]}, index=pd.Index(['x0', 'x1'], name='x')) df ``` ```{code-cell} ipython3 :inputHidden: false :outputHidden: false %matplotlib inline df.plot(kind='bar') ``` ================================================ FILE: tests/data/notebooks/outputs/ipynb_to_myst/ocaml_notebook.md ================================================ --- jupytext: formats: ipynb:markdown,md:myst kernelspec: display_name: OCaml default language: OCaml name: ocaml-jupyter --- # Example of an OCaml notebook ```{code-cell} OCaml let sum x y = x + y ``` Let's try our function: ```{code-cell} OCaml sum 3 4 = 7 + 0 ``` ================================================ FILE: tests/data/notebooks/outputs/ipynb_to_myst/octave_notebook.md ================================================ --- kernelspec: display_name: Octave language: octave name: octave --- A markdown cell ```{code-cell} 1 + 1 ``` ```{code-cell} % a code cell with comments 2 + 2 ``` ```{code-cell} % a simple plot x = -10:0.1:10; plot (x, sin (x)); ``` ```{code-cell} %plot -w 800 % a simple plot with a magic instruction x = -10:0.1:10; plot (x, sin (x)); ``` And to finish with, a Python cell ```{code-cell} %%python a = 1 ``` ```{code-cell} %%python a + 1 ``` ================================================ FILE: tests/data/notebooks/outputs/ipynb_to_myst/plotly_graphs.md ================================================ --- kernelspec: display_name: Python 3 language: python name: python3 --- This notebook contains complex outputs, including plotly javascript graphs. +++ # Interactive plots +++ We use Plotly's connected mode to make the notebook lighter - when connected, the notebook downloads the `plotly.js` library from the web. ```{code-cell} ipython3 import plotly.offline as offline offline.init_notebook_mode(connected=True) ``` ```{code-cell} ipython3 import plotly.graph_objects as go fig = go.Figure( data=[go.Bar(y=[2, 3, 1])], layout=go.Layout(title="bar plot")) fig.show() fig.data[0].marker = dict(color='purple') fig ``` ================================================ FILE: tests/data/notebooks/outputs/ipynb_to_myst/powershell.md ================================================ --- kernelspec: display_name: PowerShell language: PowerShell name: powershell --- This is an extract from https://github.com/Jaykul/Jupyter-PowerShell/blob/master/LiterateDevOps.ipynb ```{code-cell} powershell $imageUrl = 'https://upload.wikimedia.org/wikipedia/commons/2/2f/PowerShell_5.0_icon.png' $ImageData = @{ "png" = (Invoke-WebRequest $imageUrl -UseBasicParsing).RawContentStream.GetBuffer() } # $ImageData Write-Jupyter -InputObject $ImageData -Metadata @{ "image/png" = @{ 'width' = 32 } } Write-Jupyter -InputObject $ImageData -Metadata @{ "image/png" = @{ 'width' = 64 } } ``` ================================================ FILE: tests/data/notebooks/outputs/ipynb_to_myst/raw_cell_with_complex_yaml_like_content.md ================================================ --- kernelspec: display_name: Python 3 language: python name: python3 --- ```{raw-cell} --- This is a complex paragraph that is split over multiple lines. It also includes blank lines. --- ``` ```{code-cell} print("Hello, World!") ``` ================================================ FILE: tests/data/notebooks/outputs/ipynb_to_myst/raw_cell_with_non_dict_yaml_content.md ================================================ --- kernelspec: display_name: Python 3 language: python name: python3 --- ```{raw-cell} --- Content. --- ``` ```{code-cell} print("Hello, World!") ``` ================================================ FILE: tests/data/notebooks/outputs/ipynb_to_myst/root_cpp.md ================================================ --- kernelspec: display_name: ROOT C++ language: c++ name: root --- ```{code-cell} #include #include ``` ```{code-cell} int k = 4; std::string foo = "This string says \"foo\""; ``` ```{code-cell} std::cout << "k = " << k << '\n' << foo << '\n'; ``` ================================================ FILE: tests/data/notebooks/outputs/ipynb_to_myst/sage_print_hello.md ================================================ --- kernelspec: display_name: SageMath 9.2 language: sage name: sagemath --- ```{code-cell} ipython3 print("Hello world") ``` ================================================ FILE: tests/data/notebooks/outputs/ipynb_to_myst/sample_bash_notebook.md ================================================ --- kernelspec: display_name: Bash language: bash name: bash --- ```{code-cell} ls ``` ```{code-cell} # https://coderwall.com/p/euwpig/a-better-git-log git config --global alias.lg "log --color --graph --pretty=format:'%Cred%h%Creset -%C(yellow)%d%Creset %s %Cgreen(%cr) %C(bold blue)<%an>%Creset' --abbrev-commit" ``` ```{code-cell} git lg ``` ================================================ FILE: tests/data/notebooks/outputs/ipynb_to_myst/sample_rise_notebook_66.md ================================================ --- kernelspec: display_name: Python 3 language: python name: python3 --- +++ {"slideshow": {"slide_type": "slide"}} A markdown cell ```{code-cell} ipython3 --- slideshow: slide_type: '' --- 1+1 ``` +++ {"cell_style": "center", "slideshow": {"slide_type": "fragment"}} Markdown cell two ================================================ FILE: tests/data/notebooks/outputs/ipynb_to_myst/sas.md ================================================ --- kernelspec: display_name: SAS language: sas name: sas --- # SAS Notebooks with jupytext ```{code-cell} proc sql; select * from sashelp.cars (obs=10) ; quit; ``` ```{code-cell} %let name = "Jupytext"; ``` ```{code-cell} %put &name; ``` ```{code-cell} /* Note when defining macros "%macro" cannot be the first line of text in the cell */ %macro test; data temp; set sashelp.cars; name = "testx"; run; proc print data = temp (obs=10); run; %mend test; %test ``` ================================================ FILE: tests/data/notebooks/outputs/ipynb_to_myst/simple-helloworld.md ================================================ --- jupytext: encoding: '// -*- coding: utf-8 -*-' formats: ipynb,java:light kernelspec: display_name: Java language: java name: java --- Let's define some class. ```{code-cell} class A { public void hello() { System.out.println("Hello World"); } } ``` And now we call its method. ```{code-cell} new A().hello(); ``` You can run it e.g. with `jshell` * from command line, as `jshell simple-helloworld.java` * from jshell's shell with `/open simple-helloworld.java` ================================================ FILE: tests/data/notebooks/outputs/ipynb_to_myst/simple_robot_notebook.md ================================================ --- kernelspec: display_name: Robot Framework language: robotframework name: robotkernel --- ```{code-cell} robotframework *** Settings *** Library Collections ``` ```{code-cell} robotframework *** Keywords *** Head [Arguments] ${list} ${value}= Get from list ${list} 0 [Return] ${value} ``` ```{code-cell} robotframework *** Tasks *** Get head ${array}= Create list 1 2 3 4 5 ${head}= Head ${array} Should be equal ${head} 1 ``` ================================================ FILE: tests/data/notebooks/outputs/ipynb_to_myst/simple_scala_notebook.md ================================================ --- kernelspec: display_name: Apache Toree - Scala language: scala name: apache_toree_scala --- ```{code-cell} scala // This is just a simple scala notebook object SampleObject { def calculation(x: Int, y: Int): Int = x + y } val result = SampleObject.calculation(1, 2) ``` ```{code-cell} scala println(result * 10) ``` ================================================ FILE: tests/data/notebooks/outputs/ipynb_to_myst/stata_notebook.md ================================================ --- kernelspec: display_name: Stata language: stata name: stata --- ```{code-cell} // This notebook uses the stata_kernel: https://github.com/kylebarron/stata_kernel ``` ```{code-cell} use http://www.stata-press.com/data/r13/auto ``` ```{code-cell} summarize ``` ```{code-cell} scatter weight length ``` ================================================ FILE: tests/data/notebooks/outputs/ipynb_to_myst/tailrecursive-factorial.md ================================================ --- jupytext: encoding: '// -*- coding: utf-8 -*-' formats: ipynb,groovy:light kernelspec: display_name: Groovy language: groovy name: groovy --- # TailRecursive annotation Let's check what is the effect of `@TailRecursive` annotation on the simple recursive definition of factorial function. ```{code-cell} import groovy.transform.CompileStatic import groovy.transform.TailRecursive import groovy.transform.TypeChecked @CompileStatic @TypeChecked class X { static final BigInteger factorial0(int n) { (n <= 1) ? 1G : factorial0(n-1).multiply(BigInteger.valueOf(n)) } static final BigInteger factorial1(int n, BigInteger acc = 1G) { (n <= 1) ? acc : factorial1(n-1, acc.multiply(BigInteger.valueOf(n))) } @TailRecursive static final BigInteger factorial2(int n, BigInteger acc = 1G) { (n <= 1) ? acc : factorial2(n-1, acc.multiply(BigInteger.valueOf(n))) } } x = new X() ``` Although we can time the execution of the calls, it is not very accurate; such micro benchmarks should be performed in more controlled environment, such us under [JMH](https://openjdk.java.net/projects/code-tools/jmh/). For example, see [blog posts of Szymon Stępniak](https://e.printstacktrace.blog/tail-recursive-methods-in-groovy/). ```{code-cell} %%timeit x.factorial0(19_000).toString().length() ``` ```{code-cell} %%timeit x.factorial1(19_000).toString().length() ``` ```{code-cell} %%timeit x.factorial2(19_000).toString().length() ``` The real difference is the use of stack. Non-tail recursive calls exhaust the stack space at some point, whereas tail recursive calls don't add frames to the stack. ```{code-cell} factSize = { n, cl -> println "Factorial of ${n} has ${cl(n).toString().length()} digits" } factSize 2_000, x.&factorial0 factSize 2_000, x.&factorial1 factSize 2_000, x.&factorial2 factSize 100_000, x.&factorial2 ``` ```{code-cell} try { factSize 100_000, x.&factorial1 } catch (Throwable e) { assert e instanceof StackOverflowError println e } ``` ================================================ FILE: tests/data/notebooks/outputs/ipynb_to_myst/tcl_test.md ================================================ --- kernelspec: display_name: Tcl language: tcl name: tcljupyter --- # Assign Values ```{code-cell} set a 1 puts "a = $a" ``` # Loop ```{code-cell} for {set i 0} {$i < 10} {incr i} { puts "I inside first loop: $i" } ``` ```{code-cell} ``` ================================================ FILE: tests/data/notebooks/outputs/ipynb_to_myst/text_outputs_and_images.md ================================================ --- kernelspec: display_name: Python 3 language: python name: python3 --- This notebook contains outputs of many different types: text, HTML, plots and errors. +++ # Text outputs Using `print`, `sys.stdout` and `sys.stderr` ```{code-cell} ipython3 import sys print('using print') sys.stdout.write('using sys.stdout.write') sys.stderr.write('using sys.stderr.write') ``` ```{code-cell} ipython3 import logging logging.debug('Debug') logging.info('Info') logging.warning('Warning') logging.error('Error') ``` # HTML outputs Using `pandas`. Here we find two representations: both text and HTML. ```{code-cell} ipython3 import pandas as pd pd.DataFrame([4]) ``` ```{code-cell} ipython3 from IPython.display import display display(pd.DataFrame([5])) display(pd.DataFrame([6])) ``` # Images ```{code-cell} ipython3 %matplotlib inline ``` ```{code-cell} ipython3 # First plot from matplotlib import pyplot as plt import numpy as np w, h = 3, 3 data = np.zeros((h, w, 3), dtype=np.uint8) data[0,:] = [0,255,0] data[1,:] = [0,0,255] data[2,:] = [0,255,0] data[1:3,1:3] = [255, 0, 0] plt.imshow(data) plt.axis('off') plt.show() # Second plot data[1:3,1:3] = [255, 255, 0] plt.imshow(data) plt.axis('off') plt.show() ``` # Errors ```{code-cell} ipython3 undefined_variable ``` ================================================ FILE: tests/data/notebooks/outputs/ipynb_to_myst/wolfram.md ================================================ --- kernelspec: display_name: Wolfram Language 13.1 language: Wolfram Language name: wolframlanguage13.1 --- **Note:** The `language_info` `file_extension` in this notebook should be `.m`, but it was deliberately changed to `.wolfram` to avoid conflicts with Matlab which is using the same extension. +++ We start with... ```{code-cell} mathematica Print["Hello, World!"]; ``` Then we draw the first example plot from the [ListPlot](https://reference.wolfram.com/language/ref/ListPlot.html) reference: ```{code-cell} mathematica ListPlot[Prime[Range[25]]] ``` We also test the math outputs as in the [Simplify](https://reference.wolfram.com/language/ref/Simplify.html) example: ```{code-cell} mathematica D[Integrate[1/(x^3 + 1), x], x] ``` ================================================ FILE: tests/data/notebooks/outputs/ipynb_to_myst/xonsh_example.md ================================================ --- kernelspec: display_name: Xonsh language: xonsh name: xonsh --- ```{code-cell} xonsh len($(curl -L https://xon.sh)) ``` ```{code-cell} xonsh for filename in `.*`: print(filename) du -sh @(filename) ``` ================================================ FILE: tests/data/notebooks/outputs/ipynb_to_pandoc/Notebook_with_R_magic.md ================================================ --- jupyter: kernelspec: display_name: Python 2 language: python name: python2 nbformat: 4 nbformat_minor: 2 --- ::: {.cell .markdown} # A notebook with R cells This notebook shows the use of R cells to generate plots ::: ::: {.cell .code} ``` python %load_ext rpy2.ipython ``` ::: ::: {.cell .code} ``` python %%R suppressMessages(require(tidyverse)) ``` ::: ::: {.cell .code} ``` python %%R ggplot(iris, aes(x = Sepal.Length, y = Petal.Length, color=Species)) + geom_point() ``` ::: ::: {.cell .markdown} The default plot dimensions are not good for us, so we use the -w and -h parameters in %%R magic to set the plot size ::: ::: {.cell .code} ``` python %%R -w 400 -h 240 ggplot(iris, aes(x = Sepal.Length, y = Petal.Length, color=Species)) + geom_point() ``` ::: ================================================ FILE: tests/data/notebooks/outputs/ipynb_to_pandoc/Notebook_with_more_R_magic_111.md ================================================ --- jupyter: kernelspec: display_name: Python 3 language: python name: python3 nbformat: 4 nbformat_minor: 2 --- ::: {.cell .code} ``` python %load_ext rpy2.ipython import pandas as pd df = pd.DataFrame( { "Letter": ["a", "a", "a", "b", "b", "b", "c", "c", "c"], "X": [4, 3, 5, 2, 1, 7, 7, 5, 9], "Y": [0, 4, 3, 6, 7, 10, 11, 9, 13], "Z": [1, 2, 3, 1, 2, 3, 1, 2, 3], } ) ``` ::: ::: {.cell .code} ``` python %%R -i df library("ggplot2") ggplot(data = df) + geom_point(aes(x = X, y = Y, color = Letter, size = Z)) ``` ::: ================================================ FILE: tests/data/notebooks/outputs/ipynb_to_pandoc/cat_variable.md ================================================ --- jupyter: kernelspec: display_name: Python 3 language: python name: python3 nbformat: 4 nbformat_minor: 2 --- ::: {.cell .code} ``` python cat = 42 ``` ::: ================================================ FILE: tests/data/notebooks/outputs/ipynb_to_pandoc/convert_to_py_then_test_with_update83.md ================================================ --- jupyter: kernelspec: display_name: Python 3 language: python name: python3 nbformat: 4 nbformat_minor: 2 --- ::: {.cell .code} ``` python %%time print('asdf') ``` ::: ::: {.cell .markdown} Thanks for jupytext! ::: ::: {.cell .code} ``` python ``` ::: ================================================ FILE: tests/data/notebooks/outputs/ipynb_to_pandoc/frozen_cell.md ================================================ --- jupyter: kernelspec: display_name: Python 3 language: python name: python3 nbformat: 4 nbformat_minor: 2 --- ::: {.cell .code} ``` python # This is an unfrozen cell. Works as usual. print("I'm a regular cell so I run and print!") ``` ::: ::: {.cell .code deletable="false" editable="false" run_control="{\"frozen\":true}"} ``` python # This is an frozen cell print("I'm frozen so Im not executed :(") ``` ::: ================================================ FILE: tests/data/notebooks/outputs/ipynb_to_pandoc/ir_notebook.md ================================================ --- jupyter: kernelspec: display_name: R language: R name: ir nbformat: 4 nbformat_minor: 2 --- ::: {.cell .markdown} This is a jupyter notebook that uses the IR kernel. ::: ::: {.cell .code} ``` R sum(1:10) ``` ::: ::: {.cell .code} ``` R plot(cars) ``` ::: ::: {.cell .code} ``` R ``` ::: ================================================ FILE: tests/data/notebooks/outputs/ipynb_to_pandoc/julia_benchmark_plotly_barchart.md ================================================ --- jupyter: kernelspec: display_name: Julia 1.1.1 language: julia name: julia-1.1 nbformat: 4 nbformat_minor: 1 --- ::: {.cell .code} ``` julia # IJulia rocks! So does Plotly. Check it out using Plotly api_key = "" # visit https://plot.ly/api to generate an API username and password username = "" Plotly.signin(username, api_key) ``` ::: ::: {.cell .code} ``` julia # Following data taken from http://julialang.org/ frontpage benchmarks = ["fib", "parse_int", "quicksort3", "mandel", "pi_sum", "rand_mat_stat", "rand_mat_mul"] platforms = ["Fortran", "Julia", "Python", "R", "Matlab", "Mathematica", "Javascript", "Go"] data = { platforms[1] => [0.26, 5.03, 1.11, 0.86, 0.80, 0.64, 0.96], platforms[2] => [0.91, 1.60, 1.14, 0.85, 1.00, 1.66, 1.01], platforms[3] => [30.37, 13.95, 31.98, 14.19, 16.33, 13.52, 3.41 ], platforms[4] => [411.36, 59.40, 524.29, 106.97, 15.42, 10.84, 3.98 ], platforms[5] => [1992.00, 1463.16, 101.84, 64.58, 1.29, 6.61, 1.10 ], platforms[6] => [64.46, 29.54, 35.74, 6.07, 1.32, 4.52, 1.16 ], platforms[7] => [2.18, 2.43, 3.51, 3.49, 0.84, 3.28, 14.60], platforms[8] => [1.03, 4.79, 1.25, 2.36, 1.41, 8.12, 8.51] } pdata = [ {"x"=>benchmarks,"y"=>data[k],"bardir"=>"h","type"=>"bar","name"=>k} for k = platforms ] layout = { "title"=> "Julia benchmark comparison (smaller is better, C performance = 1.0)", "barmode"=> "group", "autosize"=> false, "width"=> 900, "height"=> 900, "titlefont"=> { "family"=> "Open Sans", "size"=> 18, "color"=> "rgb(84, 39, 143)" }, "margin"=> {"l"=>160, "pad"=>0}, "xaxis"=> { "title"=> "Benchmark log-time", "type"=> "log" }, "yaxis"=> {"title"=> "Benchmark Name"} } response = Plotly.plot(pdata,["layout"=>layout]) # Embed in an iframe within IJulia s = string("") display("text/html", s) ``` ::: ::: {.cell .code} ``` julia # checkout https://plot.ly/api/ for more Julia examples! # But to show off some other Plotly features: x = 1:1500 y1 = sin(2*pi*x/1500.) + rand(1500)-0.5 y2 = sin(2*pi*x/1500.) fish = {"x"=>x,"y"=> y1, "type"=>"scatter","mode"=>"markers", "marker"=>{"color"=>"rgb(0, 0, 255)","opacity"=>0.5 } } fit = {"x"=> x,"y"=> y2, "type"=>"scatter", "mode"=>"markers", "opacity"=>0.8, "marker"=>{"color"=>"rgb(255, 0, 0)"} } layout = {"autosize"=> false, "width"=> 650, "height"=> 550, "title"=>"Fish School", "xaxis"=>{ "ticks"=> "", "gridcolor"=> "white", "zerolinecolor"=> "white", "linecolor"=> "white", "autorange"=> false, "range"=>[0,1500] }, "yaxis"=>{ "ticks"=> "", "gridcolor"=> "white", "zerolinecolor"=> "white", "linecolor"=> "white", "autorange"=> false, "range"=>[-2.2,2.2] }, "plot_bgcolor"=> "rgb(245,245,247)", "showlegend"=> false, "hovermode"=> "closest"} response = Plotly.plot([fish, fit],["layout"=>layout]) s = string("") display("text/html", s) ``` ::: ================================================ FILE: tests/data/notebooks/outputs/ipynb_to_pandoc/jupyter.md ================================================ --- jupyter: kernelspec: display_name: Python 3 language: python name: python3 nbformat: 4 nbformat_minor: 2 --- ::: {.cell .markdown} # Jupyter notebook This notebook is a simple jupyter notebook. It only has markdown and code cells. And it does not contain consecutive markdown cells. We start with an addition: ::: ::: {.cell .code} ``` python a = 1 b = 2 a + b ``` ::: ::: {.cell .markdown} Now we return a few tuples ::: ::: {.cell .code} ``` python a, b ``` ::: ::: {.cell .code} ``` python a, b, a+b ``` ::: ::: {.cell .markdown} And this is already the end of the notebook ::: ================================================ FILE: tests/data/notebooks/outputs/ipynb_to_pandoc/jupyter_again.md ================================================ --- jupyter: kernelspec: display_name: Python 3 language: python name: python3 nbformat: 4 nbformat_minor: 2 --- ::: {.cell .code} ``` python c = ''' title: "Quick test" output: ioslides_presentation: widescreen: true smaller: true editor_options: chunk_output_type console ''' ``` ::: ::: {.cell .code} ``` python import yaml print(yaml.dump(yaml.load(c))) ``` ::: ::: {.cell .code} ``` python ?next ``` ::: ================================================ FILE: tests/data/notebooks/outputs/ipynb_to_pandoc/jupyter_with_raw_cell_in_body.md ================================================ --- jupyter: kernelspec: display_name: Python 3 language: python name: python3 nbformat: 4 nbformat_minor: 2 --- ::: {.cell .code} ``` python 1+2+3 ``` ::: ::: {.cell .raw} ```{=ipynb} This is a raw cell ``` ::: ::: {.cell .markdown} This is a markdown cell ::: ================================================ FILE: tests/data/notebooks/outputs/ipynb_to_pandoc/jupyter_with_raw_cell_on_top.md ================================================ --- jupyter: kernelspec: display_name: Python 3 language: python name: python3 nbformat: 4 nbformat_minor: 2 --- ::: {.cell .raw} ```{=ipynb} --- title: Quick test output: ioslides_presentation: widescreen: true smaller: true editor_options: chunk_output_type: console --- ``` ::: ::: {.cell .code} ``` python 1+2+3 ``` ::: ::: {.cell .code} ``` python ``` ::: ================================================ FILE: tests/data/notebooks/outputs/ipynb_to_pandoc/notebook_with_complex_metadata.md ================================================ --- jupyter: kernelspec: display_name: Python 3 language: python name: python3 nbformat: 4 nbformat_minor: 2 --- ::: {.cell .code} ``` python ``` ::: ================================================ FILE: tests/data/notebooks/outputs/ipynb_to_pandoc/nteract_with_parameter.md ================================================ --- jupyter: kernel_info: name: python3 kernelspec: display_name: Python 3 language: python name: python3 nbformat: 4 nbformat_minor: 2 --- ::: {.cell .code inputHidden="false" outputHidden="false" tags="[\"parameters\"]"} ``` python param = 4 ``` ::: ::: {.cell .code inputHidden="false" outputHidden="false"} ``` python import pandas as pd ``` ::: ::: {.cell .code inputHidden="false" outputHidden="false"} ``` python df = pd.DataFrame({'A': [1, 2], 'B': [3 + param, 4]}, index=pd.Index(['x0', 'x1'], name='x')) df ``` ::: ::: {.cell .code inputHidden="false" outputHidden="false"} ``` python %matplotlib inline df.plot(kind='bar') ``` ::: ================================================ FILE: tests/data/notebooks/outputs/ipynb_to_pandoc/plotly_graphs.md ================================================ --- jupyter: kernelspec: display_name: Python 3 language: python name: python3 nbformat: 4 nbformat_minor: 2 --- ::: {.cell .markdown} This notebook contains complex outputs, including plotly javascript graphs. ::: ::: {.cell .markdown} # Interactive plots ::: ::: {.cell .markdown} We use Plotly\'s connected mode to make the notebook lighter - when connected, the notebook downloads the `plotly.js` library from the web. ::: ::: {.cell .code} ``` python import plotly.offline as offline offline.init_notebook_mode(connected=True) ``` ::: ::: {.cell .code} ``` python import plotly.graph_objects as go fig = go.Figure( data=[go.Bar(y=[2, 3, 1])], layout=go.Layout(title="bar plot")) fig.show() fig.data[0].marker = dict(color='purple') fig ``` ::: ================================================ FILE: tests/data/notebooks/outputs/ipynb_to_pandoc/raw_cell_with_complex_yaml_like_content.md ================================================ --- jupyter: kernelspec: display_name: Python 3 language: python name: python3 nbformat: 4 nbformat_minor: 5 --- ::: {#b32297a4 .cell .raw} ```{=ipynb} --- This is a complex paragraph that is split over multiple lines. It also includes blank lines. --- ``` ::: ::: {#0b3bde0a .cell .code} ``` python print("Hello, World!") ``` ::: ================================================ FILE: tests/data/notebooks/outputs/ipynb_to_pandoc/raw_cell_with_non_dict_yaml_content.md ================================================ --- jupyter: kernelspec: display_name: Python 3 language: python name: python3 nbformat: 4 nbformat_minor: 5 --- ::: {#b32297a4 .cell .raw} ```{=ipynb} --- Content. --- ``` ::: ::: {#0b3bde0a .cell .code} ``` python print("Hello, World!") ``` ::: ================================================ FILE: tests/data/notebooks/outputs/ipynb_to_pandoc/sample_rise_notebook_66.md ================================================ --- jupyter: kernelspec: display_name: Python 3 language: python name: python3 nbformat: 4 nbformat_minor: 2 --- ::: {.cell .markdown slideshow="{\"slide_type\":\"slide\"}"} A markdown cell ::: ::: {.cell .code slideshow="{\"slide_type\":\"\"}"} ``` python 1+1 ``` ::: ::: {.cell .markdown cell_style="center" slideshow="{\"slide_type\":\"fragment\"}"} Markdown cell two ::: ================================================ FILE: tests/data/notebooks/outputs/ipynb_to_pandoc/text_outputs_and_images.md ================================================ --- jupyter: kernelspec: display_name: Python 3 language: python name: python3 nbformat: 4 nbformat_minor: 2 --- ::: {.cell .markdown} This notebook contains outputs of many different types: text, HTML, plots and errors. ::: ::: {.cell .markdown} # Text outputs Using `print`, `sys.stdout` and `sys.stderr` ::: ::: {.cell .code} ``` python import sys print('using print') sys.stdout.write('using sys.stdout.write') sys.stderr.write('using sys.stderr.write') ``` ::: ::: {.cell .code} ``` python import logging logging.debug('Debug') logging.info('Info') logging.warning('Warning') logging.error('Error') ``` ::: ::: {.cell .markdown} # HTML outputs Using `pandas`. Here we find two representations: both text and HTML. ::: ::: {.cell .code} ``` python import pandas as pd pd.DataFrame([4]) ``` ::: ::: {.cell .code} ``` python from IPython.display import display display(pd.DataFrame([5])) display(pd.DataFrame([6])) ``` ::: ::: {.cell .markdown} # Images ::: ::: {.cell .code} ``` python %matplotlib inline ``` ::: ::: {.cell .code} ``` python # First plot from matplotlib import pyplot as plt import numpy as np w, h = 3, 3 data = np.zeros((h, w, 3), dtype=np.uint8) data[0,:] = [0,255,0] data[1,:] = [0,0,255] data[2,:] = [0,255,0] data[1:3,1:3] = [255, 0, 0] plt.imshow(data) plt.axis('off') plt.show() # Second plot data[1:3,1:3] = [255, 255, 0] plt.imshow(data) plt.axis('off') plt.show() ``` ::: ::: {.cell .markdown} # Errors ::: ::: {.cell .code} ``` python undefined_variable ``` ::: ================================================ FILE: tests/data/notebooks/outputs/ipynb_to_percent/Line_breaks_in_LateX_305.py ================================================ # --- # jupyter: # kernelspec: # display_name: Python 3 # language: python # name: python3 # --- # %% [markdown] # This cell uses no particular cell marker # # $$ # \begin{align} # \dot{x} & = \sigma(y-x)\\ # \dot{y} & = \rho x - y - xz \\ # \dot{z} & = -\beta z + xy # \end{align} # $$ # %% [markdown] # This cell uses no particular cell marker, and a single slash in the $\LaTeX$ equation # # $$ # \begin{align} # \dot{x} & = \sigma(y-x) \ # \dot{y} & = \rho x - y - xz \ # \dot{z} & = -\beta z + xy # \end{align} # $$ # %% [markdown] r''' This cell uses the triple quote cell markers introduced at https://github.com/mwouts/jupytext/issues/305 $$ \begin{align} \dot{x} & = \sigma(y-x)\\ \dot{y} & = \rho x - y - xz \\ \dot{z} & = -\beta z + xy \end{align} $$ ''' ================================================ FILE: tests/data/notebooks/outputs/ipynb_to_percent/Notebook with function and cell metadata 164.py ================================================ # --- # jupyter: # kernelspec: # display_name: Python 3 # language: python # name: python3 # --- # %% 1 + 1 # %% [markdown] # A markdown cell # And below, the cell for function f has non trivial cell metadata. And the next cell as well. # %% attributes={"classes": [], "id": "", "n": "10"} def f(x): return x # %% attributes={"classes": [], "id": "", "n": "10"} f(5) # %% [markdown] # More text # %% 2 + 2 ================================================ FILE: tests/data/notebooks/outputs/ipynb_to_percent/Notebook with html and latex cells.py ================================================ # --- # jupyter: # kernelspec: # display_name: Python 3 # language: python # name: python3 # --- # %% language="html" #

Jupytext on GitHub

# %% language="latex" # $\frac{\pi}{2}$ # %% # %load_ext rpy2.ipython # %% language="R" # library(ggplot2) # ggplot(data=data.frame(x=c('A', 'B'), y=c(5, 2)), aes(x,weight=y)) + geom_bar() # %% # %matplotlib inline import pandas as pd pd.Series({'A':5, 'B':2}).plot(figsize=(3,2), kind='bar') ================================================ FILE: tests/data/notebooks/outputs/ipynb_to_percent/Notebook with many hash signs.py ================================================ # --- # jupyter: # kernelspec: # display_name: Python 3 # language: python # name: python3 # --- # %% [markdown] # ################################################################## # This is a notebook that contains many hash signs. # Hopefully its python representation is not recognized as a Sphinx Gallery script... # ################################################################## # %% some = 1 code = 2 some+code ################################################################## # A comment ################################################################## # Another comment # %% [markdown] # ################################################################## # This is a notebook that contains many hash signs. # Hopefully its python representation is not recognized as a Sphinx Gallery script... # ################################################################## ================================================ FILE: tests/data/notebooks/outputs/ipynb_to_percent/Notebook with metadata and long cells.py ================================================ # --- # jupyter: # kernelspec: # display_name: Python 3 # language: python # name: python3 # --- # %% [markdown] # # Part one - various cells # %% [markdown] # Here we have a markdown cell # # # with two blank lines # %% [markdown] # Now we have a markdown cell # with a code block inside it # # ```python # 1 + 1 # ``` # # After that cell we'll have a code cell # %% 2 + 2 3 + 3 # %% [markdown] # Followed by a raw cell # %% [raw] # This is # the content # of the raw cell # %% [markdown] # # Part two - cell metadata # %% [markdown] key="value" # This is a markdown cell with cell metadata `{"key": "value"}` # %% .class tags=["parameters"] """This is a code cell with metadata `{"tags":["parameters"], ".class":null}`""" # %% [raw] key="value" # This is a raw cell with cell metadata `{"key": "value"}` ================================================ FILE: tests/data/notebooks/outputs/ipynb_to_percent/Notebook_with_R_magic.py ================================================ # --- # jupyter: # kernelspec: # display_name: Python 2 # language: python # name: python2 # --- # %% [markdown] # # A notebook with R cells # # This notebook shows the use of R cells to generate plots # %% # %load_ext rpy2.ipython # %% language="R" # suppressMessages(require(tidyverse)) # %% language="R" # ggplot(iris, aes(x = Sepal.Length, y = Petal.Length, color=Species)) + geom_point() # %% [markdown] # The default plot dimensions are not good for us, so we use the -w and -h parameters in %%R magic to set the plot size # %% magic_args="-w 400 -h 240" language="R" # ggplot(iris, aes(x = Sepal.Length, y = Petal.Length, color=Species)) + geom_point() ================================================ FILE: tests/data/notebooks/outputs/ipynb_to_percent/Notebook_with_more_R_magic_111.py ================================================ # --- # jupyter: # kernelspec: # display_name: Python 3 # language: python # name: python3 # --- # %% # %load_ext rpy2.ipython import pandas as pd df = pd.DataFrame( { "Letter": ["a", "a", "a", "b", "b", "b", "c", "c", "c"], "X": [4, 3, 5, 2, 1, 7, 7, 5, 9], "Y": [0, 4, 3, 6, 7, 10, 11, 9, 13], "Z": [1, 2, 3, 1, 2, 3, 1, 2, 3], } ) # %% magic_args="-i df" language="R" # library("ggplot2") # ggplot(data = df) + geom_point(aes(x = X, y = Y, color = Letter, size = Z)) ================================================ FILE: tests/data/notebooks/outputs/ipynb_to_percent/R notebook with invalid cell keys.R ================================================ # --- # jupyter: # kernelspec: # display_name: R # language: R # name: ir # --- # %% [markdown] # This notebook was created with IRKernel 0.8.12, and is not completely valid, as the code cell below contains an unexpected 'source' entry. This did cause https://github.com/mwouts/jupytext/issues/234. Note that the problem is solved when one upgrades to IRKernel 1.0.0. # %% library("ggplot2") ggplot(mtcars, aes(mpg)) + stat_ecdf() ================================================ FILE: tests/data/notebooks/outputs/ipynb_to_percent/R notebook with invalid cell keys.low.r ================================================ # --- # jupyter: # kernelspec: # display_name: R # language: R # name: ir # --- # %% [markdown] # This notebook was created with IRKernel 0.8.12, and is not completely valid, as the code cell below contains an unexpected 'source' entry. This did cause https://github.com/mwouts/jupytext/issues/234. Note that the problem is solved when one upgrades to IRKernel 1.0.0. # %% library("ggplot2") ggplot(mtcars, aes(mpg)) + stat_ecdf() ================================================ FILE: tests/data/notebooks/outputs/ipynb_to_percent/Reference Guide for Calysto Scheme.scm ================================================ ;; -*- coding: utf-8 -*- ;; --- ;; jupyter: ;; kernelspec: ;; display_name: Calysto Scheme (Python) ;; language: scheme ;; name: calysto_scheme ;; --- ;; %% [markdown] ;; ;;

Reference Guide for Calysto Scheme

;; ;; [Calysto Scheme](https://github.com/Calysto/calysto_scheme) is a real Scheme programming language, with full support for continuations, including call/cc. It can also use all Python libraries. Also has some extensions that make it more useful (stepper-debugger, choose/fail, stack traces), or make it better integrated with Python. ;; ;; In Jupyter notebooks, because Calysto Scheme uses [MetaKernel](https://github.com/Calysto/metakernel/blob/master/README.rst), it has a fully-supported set of "magics"---meta-commands for additional functionality. This includes running Scheme in parallel. See all of the [MetaKernel Magics](https://github.com/Calysto/metakernel/blob/master/metakernel/magics/README.md). ;; ;; Calysto Scheme is written in Scheme, and then translated into Python (and other backends). The entire functionality lies in a single Python file: https://github.com/Calysto/calysto_scheme/blob/master/calysto_scheme/scheme.py However, you can easily install it (see below). ;; ;; Please see [Calysto Scheme Language](Calysto%20Scheme%20Language.ipynb) for more details on the Calysto Scheme language. ;; ;; ## Installation ;; ;; You can install Calysto Scheme with Python3: ;; ;; ``` ;; pip3 install --upgrade calysto-scheme --user -U ;; python3 -m calysto_kernel install --user ;; ``` ;; ;; or in the system kernel folder with: ;; ;; ``` ;; sudo pip3 install --upgrade calysto-scheme -U ;; sudo python3 -m calysto_kernel install ;; ``` ;; ;; Change pip3/python3 to use a different pip or Python. The version of Python used will determine how Calysto Scheme is run. ;; ;; Use it in the console, qtconsole, or notebook with IPython 3: ;; ;; ``` ;; ipython console --kernel calysto_scheme ;; ipython qtconsole --kernel calysto_scheme ;; ipython notebook --kernel calysto_scheme ;; ``` ;; ;; In addition to all of the following items, Calysto Scheme also has access to all of Python's builtin functions, and all of Python's libraries. For example, you can use `(complex 3 2)` to create a complex number by calling Python's complex function. ;; ;; ## Jupyter Enhancements ;; ;; When you run Calysto Scheme in Jupyter (console, notebook, qtconsole, etc.) you get: ;; ;; * TAB completions of Scheme functions and variable names ;; * display of rich media ;; * stepper/debugger ;; * magics (% macros) ;; * shell commands (! command) ;; * LaTeX equations ;; * LaTeX-style variables ;; * Python integration ;; %% [markdown] ;; ### LaTeX-style variables ;; ;; Calysto Scheme allows you to use LaTeX-style variables in code. For example, if you type: ;; ;; ``` ;; \beta ;; ``` ;; ;; with the cursor right after the 'a' in beta, and then press TAB, it will turn into the unicode character: ;; ;; ``` ;; β ;; ``` ;; ;; There are nearly 1300 different symbols defined (thanks to the Julia language) and documented here: ;; ;; http://docs.julialang.org/en/release-0.4/manual/unicode-input/#man-unicode-input ;; ;; Calysto Scheme may not implement all of those. Some useful and suggestive ones: ;; ;; * \pi - π ;; * \Pi - Π ;; * \Sigma - Σ ;; * \_i - subscript i, such as vectorᵢ ;; %% (define α 67) ;; %% α ;; %% (define i 2) (define vectorᵢ (vector-ref (vector 0 6 3 2) i)) vectorᵢ ;; %% [markdown] ;; ### Rich media ;; %% (import "calysto.display") ;; %% (calysto.display.HTML "This is bold, italics, underlined.") ;; %% (import "calysto.graphics") ;; %% (define canvas (calysto.graphics.Canvas)) ;; %% (define ball (calysto.graphics.Circle '(150 150) 100)) ;; %% (ball.draw canvas) ;; %% [markdown] ;; ### Shell commands ;; %% ! ls /tmp ;; %% [markdown] ;; ### Stepper/Debugger ;; ;; Here is what the debugger looks like: ;; ;; ;; ;; It has breakpoints (click in left margin). You must press Stop to exit the debugger. ;; %% [markdown] ;; ```scheme ;; %%debug ;; ;; (begin ;; (define x 1) ;; (set! x 2) ;; ) ;; ``` ;; %% [markdown] ;; ### Python Integration ;; ;; You can import and use any Python library in Calysto Scheme. ;; ;; In addition, if you wish, you can execute expressions and statements in a Python environment: ;; %% (python-eval "1 + 2") ;; %% (python-exec " def mypyfunc(a, b): return a * b ") ;; %% [markdown] ;; This is a shared environment with Scheme: ;; %% (mypyfunc 4 5) ;; %% [markdown] ;; You can use `func` to turn a Scheme procedure into a Python function, and `define!` to put it into the shared environment with Python: ;; %% (define! mypyfunc2 (func (lambda (n) n))) ;; %% (python-eval "mypyfunc2(34)") ;; %% [markdown] ;; # Differences Between Languages ;; ;; ## Major differences between Scheme and Python ;; ;; 1. In Scheme, double quotes are used for strings and may contain newlines ;; 1. In Scheme, a single quote is short for (quote ...) and means "literal" ;; 1. In Scheme, everything is an expression and has a return value ;; 1. Python does not support macros (e.g., extending syntax) ;; 1. In Python, "if X" is false if X is None, False, [], (,) or 0. In Scheme, "if X" is only false if X is #f or 0 ;; 1. Calysto Scheme uses continuations, not the call stack. However, for debugging there is a pseudo-stack when an error is raised. You can turn that off with (use-stack-trace #f) ;; 1. Scheme procedures are not Python functions, but there are means to use one as the other. ;; ;; ## Major Differences Between Calysto Scheme and other Schemes ;; ;; 1. define-syntax works slightly differently ;; 1. In Calysto Scheme, #(...) is short for '#(...) ;; 1. Calysto Scheme is missing many standard functions (see list at bottom) ;; 1. Calysto Scheme has a built-in amb operator called `choose` ;; 1. For debugging there is a pseudo-stack when errors are raised in Calysto Scheme. You can turn that off with (use-stack-trace #f) ;; ;; ### Stack Trace ;; ;; Calysto Scheme acts as if it has a call stack, for easier debugging. For example: ;; %% (define fact (lambda (n) (if (= n 1) q (* n (fact (- n 1)))))) ;; %% (fact 5) ;; %% [markdown] ;; To turn off the stack trace on error: ;; ;; ```scheme ;; (use-stack-trace #f) ;; ``` ;; That will allow infinite recursive loops without keeping track of the "stack". ;; %% [markdown] ;; # Calysto Scheme Variables ;; ;; ## SCHEMEPATH ;; SCHEMEPATH is a list of search directories used with (load NAME). This is a reference, so you should append to it rather than attempting to redefine it. ;; %% SCHEMEPATH ;; %% (set-cdr! (cdr SCHEMEPATH) (list "/var/modules")) ;; %% SCHEMEPATH ;; %% [markdown] ;; ## Getting Started ;; ;; Note that you can use the word `lambda` or \lambda and then press [TAB] ;; %% (define factorial (λ (n) (cond ((zero? n) 1) (else (* n (factorial (- n 1))))))) ;; %% (factorial 5) ;; %% [markdown] ;; ## define-syntax ;; (define-syntax NAME RULES): a method for creating macros ;; %% (define-syntax time [(time ?exp) (let ((start (current-time))) ?exp (- (current-time) start))]) ;; %% (time (car '(1 2 3 4))) ;; %% ;;--------------------------------------------------------------------- ;; collect is like list comprehension in Python (define-syntax collect [(collect ?exp for ?var in ?list) (filter-map (lambda (?var) ?exp) (lambda (?var) #t) ?list)] [(collect ?exp for ?var in ?list if ?condition) (filter-map (lambda (?var) ?exp) (lambda (?var) ?condition) ?list)]) (define filter-map (lambda (f pred? values) (if (null? values) '() (if (pred? (car values)) (cons (f (car values)) (filter-map f pred? (cdr values))) (filter-map f pred? (cdr values)))))) ;; %% (collect (* n n) for n in (range 10)) ;; %% (collect (* n n) for n in (range 5 20 3)) ;; %% (collect (* n n) for n in (range 10) if (> n 5)) ;; %% ;;--------------------------------------------------------------------- ;; for loops (define-syntax for [(for ?exp times do . ?bodies) (for-repeat ?exp (lambda () . ?bodies))] [(for ?var in ?exp do . ?bodies) (for-iterate1 ?exp (lambda (?var) . ?bodies))] [(for ?var at (?i) in ?exp do . ?bodies) (for-iterate2 0 ?exp (lambda (?var ?i) . ?bodies))] [(for ?var at (?i ?j . ?rest) in ?exp do . ?bodies) (for ?var at (?i) in ?exp do (for ?var at (?j . ?rest) in ?var do . ?bodies))]) (define for-repeat (lambda (n f) (if (< n 1) 'done (begin (f) (for-repeat (- n 1) f))))) (define for-iterate1 (lambda (values f) (if (null? values) 'done (begin (f (car values)) (for-iterate1 (cdr values) f))))) (define for-iterate2 (lambda (i values f) (if (null? values) 'done (begin (f (car values) i) (for-iterate2 (+ i 1) (cdr values) f))))) ;; %% (define matrix2d '((10 20) (30 40) (50 60) (70 80))) (define matrix3d '(((10 20 30) (40 50 60)) ((70 80 90) (100 110 120)) ((130 140 150) (160 170 180)) ((190 200 210) (220 230 240)))) ;; %% (begin (define hello 0) (for 5 times do (set! hello (+ hello 1))) hello ) ;; %% (for sym in '(a b c d) do (define x 1) (set! x sym) (print x)) ;; %% (for n in (range 10 20 2) do (print n)) ;; %% (for n at (i j) in matrix2d do (print (list n 'coords: i j))) ;; %% (for n at (i j k) in matrix3d do (print (list n 'coords: i j k))) ;; %% (define-syntax scons [(scons ?x ?y) (cons ?x (lambda () ?y))]) (define scar car) (define scdr (lambda (s) (let ((result ((cdr s)))) (set-cdr! s (lambda () result)) result))) (define first (lambda (n s) (if (= n 0) '() (cons (scar s) (first (- n 1) (scdr s)))))) (define nth (lambda (n s) (if (= n 0) (scar s) (nth (- n 1) (scdr s))))) (define smap (lambda (f s) (scons (f (scar s)) (smap f (scdr s))))) (define ones (scons 1 ones)) (define nats (scons 0 (combine nats + ones))) (define combine (lambda (s1 op s2) (scons (op (scar s1) (scar s2)) (combine (scdr s1) op (scdr s2))))) (define fibs (scons 1 (scons 1 (combine fibs + (scdr fibs))))) (define facts (scons 1 (combine facts * (scdr nats)))) (define ! (lambda (n) (nth n facts))) ;; %% (! 5) ;; %% (nth 10 facts) ;; %% (nth 20 fibs) ;; %% (first 30 fibs) ;; %% [markdown] ;; ## for-each ;; (for-each PROCEDURE LIST): apply PROCEDURE to each item in LIST; like `map` but don't return results ;; %% (for-each (lambda (n) (print n)) '(3 4 5)) ;; %% [markdown] ;; ## format ;; (format STRING ITEM ...): format the string with ITEMS as arguments ;; %% (format "This uses formatting ~a ~s ~%" 'apple 'apple) ;; %% [markdown] ;; ## func ;; ;; Turns a lambda into a Python function. ;; ;; (func (lambda ...)) ;; %% (func (lambda (n) n)) ;; %% [markdown] ;; ## There's more! ;; ;; Please see [Calysto Scheme Language](Calysto%20Scheme%20Language.ipynb) for more details on the Calysto Scheme language. ================================================ FILE: tests/data/notebooks/outputs/ipynb_to_percent/Reference Guide for Calysto Scheme.ss ================================================ ;; -*- coding: utf-8 -*- ;; --- ;; jupyter: ;; kernelspec: ;; display_name: Calysto Scheme (Python) ;; language: scheme ;; name: calysto_scheme ;; --- ;; %% [markdown] ;; ;;

Reference Guide for Calysto Scheme

;; ;; [Calysto Scheme](https://github.com/Calysto/calysto_scheme) is a real Scheme programming language, with full support for continuations, including call/cc. It can also use all Python libraries. Also has some extensions that make it more useful (stepper-debugger, choose/fail, stack traces), or make it better integrated with Python. ;; ;; In Jupyter notebooks, because Calysto Scheme uses [MetaKernel](https://github.com/Calysto/metakernel/blob/master/README.rst), it has a fully-supported set of "magics"---meta-commands for additional functionality. This includes running Scheme in parallel. See all of the [MetaKernel Magics](https://github.com/Calysto/metakernel/blob/master/metakernel/magics/README.md). ;; ;; Calysto Scheme is written in Scheme, and then translated into Python (and other backends). The entire functionality lies in a single Python file: https://github.com/Calysto/calysto_scheme/blob/master/calysto_scheme/scheme.py However, you can easily install it (see below). ;; ;; Please see [Calysto Scheme Language](Calysto%20Scheme%20Language.ipynb) for more details on the Calysto Scheme language. ;; ;; ## Installation ;; ;; You can install Calysto Scheme with Python3: ;; ;; ``` ;; pip3 install --upgrade calysto-scheme --user -U ;; python3 -m calysto_kernel install --user ;; ``` ;; ;; or in the system kernel folder with: ;; ;; ``` ;; sudo pip3 install --upgrade calysto-scheme -U ;; sudo python3 -m calysto_kernel install ;; ``` ;; ;; Change pip3/python3 to use a different pip or Python. The version of Python used will determine how Calysto Scheme is run. ;; ;; Use it in the console, qtconsole, or notebook with IPython 3: ;; ;; ``` ;; ipython console --kernel calysto_scheme ;; ipython qtconsole --kernel calysto_scheme ;; ipython notebook --kernel calysto_scheme ;; ``` ;; ;; In addition to all of the following items, Calysto Scheme also has access to all of Python's builtin functions, and all of Python's libraries. For example, you can use `(complex 3 2)` to create a complex number by calling Python's complex function. ;; ;; ## Jupyter Enhancements ;; ;; When you run Calysto Scheme in Jupyter (console, notebook, qtconsole, etc.) you get: ;; ;; * TAB completions of Scheme functions and variable names ;; * display of rich media ;; * stepper/debugger ;; * magics (% macros) ;; * shell commands (! command) ;; * LaTeX equations ;; * LaTeX-style variables ;; * Python integration ;; %% [markdown] ;; ### LaTeX-style variables ;; ;; Calysto Scheme allows you to use LaTeX-style variables in code. For example, if you type: ;; ;; ``` ;; \beta ;; ``` ;; ;; with the cursor right after the 'a' in beta, and then press TAB, it will turn into the unicode character: ;; ;; ``` ;; β ;; ``` ;; ;; There are nearly 1300 different symbols defined (thanks to the Julia language) and documented here: ;; ;; http://docs.julialang.org/en/release-0.4/manual/unicode-input/#man-unicode-input ;; ;; Calysto Scheme may not implement all of those. Some useful and suggestive ones: ;; ;; * \pi - π ;; * \Pi - Π ;; * \Sigma - Σ ;; * \_i - subscript i, such as vectorᵢ ;; %% (define α 67) ;; %% α ;; %% (define i 2) (define vectorᵢ (vector-ref (vector 0 6 3 2) i)) vectorᵢ ;; %% [markdown] ;; ### Rich media ;; %% (import "calysto.display") ;; %% (calysto.display.HTML "This is bold, italics, underlined.") ;; %% (import "calysto.graphics") ;; %% (define canvas (calysto.graphics.Canvas)) ;; %% (define ball (calysto.graphics.Circle '(150 150) 100)) ;; %% (ball.draw canvas) ;; %% [markdown] ;; ### Shell commands ;; %% ! ls /tmp ;; %% [markdown] ;; ### Stepper/Debugger ;; ;; Here is what the debugger looks like: ;; ;; ;; ;; It has breakpoints (click in left margin). You must press Stop to exit the debugger. ;; %% [markdown] ;; ```scheme ;; %%debug ;; ;; (begin ;; (define x 1) ;; (set! x 2) ;; ) ;; ``` ;; %% [markdown] ;; ### Python Integration ;; ;; You can import and use any Python library in Calysto Scheme. ;; ;; In addition, if you wish, you can execute expressions and statements in a Python environment: ;; %% (python-eval "1 + 2") ;; %% (python-exec " def mypyfunc(a, b): return a * b ") ;; %% [markdown] ;; This is a shared environment with Scheme: ;; %% (mypyfunc 4 5) ;; %% [markdown] ;; You can use `func` to turn a Scheme procedure into a Python function, and `define!` to put it into the shared environment with Python: ;; %% (define! mypyfunc2 (func (lambda (n) n))) ;; %% (python-eval "mypyfunc2(34)") ;; %% [markdown] ;; # Differences Between Languages ;; ;; ## Major differences between Scheme and Python ;; ;; 1. In Scheme, double quotes are used for strings and may contain newlines ;; 1. In Scheme, a single quote is short for (quote ...) and means "literal" ;; 1. In Scheme, everything is an expression and has a return value ;; 1. Python does not support macros (e.g., extending syntax) ;; 1. In Python, "if X" is false if X is None, False, [], (,) or 0. In Scheme, "if X" is only false if X is #f or 0 ;; 1. Calysto Scheme uses continuations, not the call stack. However, for debugging there is a pseudo-stack when an error is raised. You can turn that off with (use-stack-trace #f) ;; 1. Scheme procedures are not Python functions, but there are means to use one as the other. ;; ;; ## Major Differences Between Calysto Scheme and other Schemes ;; ;; 1. define-syntax works slightly differently ;; 1. In Calysto Scheme, #(...) is short for '#(...) ;; 1. Calysto Scheme is missing many standard functions (see list at bottom) ;; 1. Calysto Scheme has a built-in amb operator called `choose` ;; 1. For debugging there is a pseudo-stack when errors are raised in Calysto Scheme. You can turn that off with (use-stack-trace #f) ;; ;; ### Stack Trace ;; ;; Calysto Scheme acts as if it has a call stack, for easier debugging. For example: ;; %% (define fact (lambda (n) (if (= n 1) q (* n (fact (- n 1)))))) ;; %% (fact 5) ;; %% [markdown] ;; To turn off the stack trace on error: ;; ;; ```scheme ;; (use-stack-trace #f) ;; ``` ;; That will allow infinite recursive loops without keeping track of the "stack". ;; %% [markdown] ;; # Calysto Scheme Variables ;; ;; ## SCHEMEPATH ;; SCHEMEPATH is a list of search directories used with (load NAME). This is a reference, so you should append to it rather than attempting to redefine it. ;; %% SCHEMEPATH ;; %% (set-cdr! (cdr SCHEMEPATH) (list "/var/modules")) ;; %% SCHEMEPATH ;; %% [markdown] ;; ## Getting Started ;; ;; Note that you can use the word `lambda` or \lambda and then press [TAB] ;; %% (define factorial (λ (n) (cond ((zero? n) 1) (else (* n (factorial (- n 1))))))) ;; %% (factorial 5) ;; %% [markdown] ;; ## define-syntax ;; (define-syntax NAME RULES): a method for creating macros ;; %% (define-syntax time [(time ?exp) (let ((start (current-time))) ?exp (- (current-time) start))]) ;; %% (time (car '(1 2 3 4))) ;; %% ;;--------------------------------------------------------------------- ;; collect is like list comprehension in Python (define-syntax collect [(collect ?exp for ?var in ?list) (filter-map (lambda (?var) ?exp) (lambda (?var) #t) ?list)] [(collect ?exp for ?var in ?list if ?condition) (filter-map (lambda (?var) ?exp) (lambda (?var) ?condition) ?list)]) (define filter-map (lambda (f pred? values) (if (null? values) '() (if (pred? (car values)) (cons (f (car values)) (filter-map f pred? (cdr values))) (filter-map f pred? (cdr values)))))) ;; %% (collect (* n n) for n in (range 10)) ;; %% (collect (* n n) for n in (range 5 20 3)) ;; %% (collect (* n n) for n in (range 10) if (> n 5)) ;; %% ;;--------------------------------------------------------------------- ;; for loops (define-syntax for [(for ?exp times do . ?bodies) (for-repeat ?exp (lambda () . ?bodies))] [(for ?var in ?exp do . ?bodies) (for-iterate1 ?exp (lambda (?var) . ?bodies))] [(for ?var at (?i) in ?exp do . ?bodies) (for-iterate2 0 ?exp (lambda (?var ?i) . ?bodies))] [(for ?var at (?i ?j . ?rest) in ?exp do . ?bodies) (for ?var at (?i) in ?exp do (for ?var at (?j . ?rest) in ?var do . ?bodies))]) (define for-repeat (lambda (n f) (if (< n 1) 'done (begin (f) (for-repeat (- n 1) f))))) (define for-iterate1 (lambda (values f) (if (null? values) 'done (begin (f (car values)) (for-iterate1 (cdr values) f))))) (define for-iterate2 (lambda (i values f) (if (null? values) 'done (begin (f (car values) i) (for-iterate2 (+ i 1) (cdr values) f))))) ;; %% (define matrix2d '((10 20) (30 40) (50 60) (70 80))) (define matrix3d '(((10 20 30) (40 50 60)) ((70 80 90) (100 110 120)) ((130 140 150) (160 170 180)) ((190 200 210) (220 230 240)))) ;; %% (begin (define hello 0) (for 5 times do (set! hello (+ hello 1))) hello ) ;; %% (for sym in '(a b c d) do (define x 1) (set! x sym) (print x)) ;; %% (for n in (range 10 20 2) do (print n)) ;; %% (for n at (i j) in matrix2d do (print (list n 'coords: i j))) ;; %% (for n at (i j k) in matrix3d do (print (list n 'coords: i j k))) ;; %% (define-syntax scons [(scons ?x ?y) (cons ?x (lambda () ?y))]) (define scar car) (define scdr (lambda (s) (let ((result ((cdr s)))) (set-cdr! s (lambda () result)) result))) (define first (lambda (n s) (if (= n 0) '() (cons (scar s) (first (- n 1) (scdr s)))))) (define nth (lambda (n s) (if (= n 0) (scar s) (nth (- n 1) (scdr s))))) (define smap (lambda (f s) (scons (f (scar s)) (smap f (scdr s))))) (define ones (scons 1 ones)) (define nats (scons 0 (combine nats + ones))) (define combine (lambda (s1 op s2) (scons (op (scar s1) (scar s2)) (combine (scdr s1) op (scdr s2))))) (define fibs (scons 1 (scons 1 (combine fibs + (scdr fibs))))) (define facts (scons 1 (combine facts * (scdr nats)))) (define ! (lambda (n) (nth n facts))) ;; %% (! 5) ;; %% (nth 10 facts) ;; %% (nth 20 fibs) ;; %% (first 30 fibs) ;; %% [markdown] ;; ## for-each ;; (for-each PROCEDURE LIST): apply PROCEDURE to each item in LIST; like `map` but don't return results ;; %% (for-each (lambda (n) (print n)) '(3 4 5)) ;; %% [markdown] ;; ## format ;; (format STRING ITEM ...): format the string with ITEMS as arguments ;; %% (format "This uses formatting ~a ~s ~%" 'apple 'apple) ;; %% [markdown] ;; ## func ;; ;; Turns a lambda into a Python function. ;; ;; (func (lambda ...)) ;; %% (func (lambda (n) n)) ;; %% [markdown] ;; ## There's more! ;; ;; Please see [Calysto Scheme Language](Calysto%20Scheme%20Language.ipynb) for more details on the Calysto Scheme language. ================================================ FILE: tests/data/notebooks/outputs/ipynb_to_percent/The flavors of raw cells.py ================================================ # --- # jupyter: # kernelspec: # display_name: Python 3 # language: python # name: python3 # --- # %% [raw] raw_mimetype="text/latex" # $1+1$ # %% [raw] raw_mimetype="text/restructuredtext" # :math:`1+1` # %% [raw] raw_mimetype="text/html" # Bold text # %% [raw] raw_mimetype="text/markdown" # **Bold text** # %% [raw] raw_mimetype="text/x-python" # 1 + 1 # %% [raw] # Not formatted ================================================ FILE: tests/data/notebooks/outputs/ipynb_to_percent/cat_variable.py ================================================ # --- # jupyter: # kernelspec: # display_name: Python 3 # language: python # name: python3 # --- # %% cat = 42 ================================================ FILE: tests/data/notebooks/outputs/ipynb_to_percent/coconut_homepage_demo.coco ================================================ # --- # jupyter: # kernelspec: # display_name: Coconut # language: coconut # name: coconut # --- # %% [markdown] # Taken from [coconut-lang.org](coconut-lang.org) # %% [markdown] # pipeline-style programming # %% "hello, world!" |> print # %% [markdown] # prettier lambdas # %% x -> x ** 2 # %% [markdown] # partial application # %% range(10) |> map$(pow$(?, 2)) |> list # %% [markdown] # pattern-matching # %% match [head] + tail in [0, 1, 2, 3]: print(head, tail) # %% [markdown] # destructuring assignment # %% {"list": [0] + rest} = {"list": [0, 1, 2, 3]} # %% [markdown] # infix notation # %% # 5 `mod` 3 == 2 # %% [markdown] # operator functions # %% product = reduce$(*) # %% [markdown] # function composition # %% # (f..g..h)(x, y, z) # %% [markdown] # lazy lists # %% # (| first_elem() |) :: rest_elems() # %% [markdown] # parallel programming # %% range(100) |> parallel_map$(pow$(2)) |> list # %% [markdown] # tail call optimization # %% def factorial(n, acc=1): case n: match 0: return acc match _ is int if n > 0: return factorial(n-1, acc*n) # %% [markdown] # algebraic data types # %% data Empty() data Leaf(n) data Node(l, r) def size(Empty()) = 0 addpattern def size(Leaf(n)) = 1 addpattern def size(Node(l, r)) = size(l) + size(r) # %% [markdown] # and much more! # # Like what you see? Don't forget to star Coconut on GitHub! # %% ================================================ FILE: tests/data/notebooks/outputs/ipynb_to_percent/convert_to_py_then_test_with_update83.py ================================================ # --- # jupyter: # kernelspec: # display_name: Python 3 # language: python # name: python3 # --- # %% # %%time print('asdf') # %% [markdown] # Thanks for jupytext! # %% ================================================ FILE: tests/data/notebooks/outputs/ipynb_to_percent/csharp.cs ================================================ // --- // jupyter: // kernelspec: // display_name: .NET (C#) // language: C# // name: .net-csharp // --- // %% [markdown] // We start with... // %% Console.WriteLine("Hello World!"); // %% [markdown] // Then we do a plot with Plotly, following the [Plotting with XPlot](https://github.com/dotnet/interactive/blob/master/NotebookExamples/csharp/Docs/Plotting%20with%20Xplot.ipynb) example from `dotnet/interactive`: // %% using XPlot.Plotly; var bar = new Graph.Bar { name = "Bar", x = new[] {'A', 'B', 'C'}, y = new[] {1, 3, 2} }; var chart = Chart.Plot(new[] {bar}); chart.WithTitle("A bar plot"); display(chart); // %% [markdown] // We also test the math outputs as in the [Math and Latex](https://github.com/dotnet/interactive/blob/master/NotebookExamples/csharp/Docs/Math%20and%20LaTeX.ipynb) example: // %% (LaTeXString)@"\begin{align} e^{i \pi} = -1\end{align}" // %% (MathString)@"e^{i \pi} = -1" ================================================ FILE: tests/data/notebooks/outputs/ipynb_to_percent/demo_gdl_fbp.pro ================================================ ; -*- coding: utf-8 -*- ; --- ; jupyter: ; kernelspec: ; display_name: IDL [conda env:gdl] * ; language: IDL ; name: conda-env-gdl-idl ; --- ; %% [markdown] ; ## GDL demo notebook ; %% [markdown] ; Demonstration of GDL [(gnudatalanguage)](https://github.com/gnudatalanguage/gdl) ; ; This notebook creates a Shepp-Logan phantom, projects it and then performs an FBP reconstruction. ; %% ;; L.A. Shepp and B.F. Logan, “The Fourier reconstruction of a head section,” ;; IEEE Trans. Nucl. Sci. 21(3), 21–43 (1974). function shepplogan, size = size if NOT keyword_set(size) then size = 256 phantom = fltarr(size,size) tmp = (findgen(size)-((size-1)/2.0)) / (size/2.0) xcor = rebin(tmp,size,size) ycor = rebin(transpose(tmp),size,size) tmp = fltarr(size,size) aa={cx: 0.0, cy: 0.0, maj:0.69, min:0.92, theta: 0.0, val: 2.0 } bb={cx: 0.0, cy:-0.0184, maj:0.6624, min:0.874, theta: 0.0, val:-0.98} cc={cx: 0.22, cy: 0.0, maj:0.11, min:0.31, theta:-18.0, val:-0.02} dd={cx:-0.22, cy: 0.0, maj:0.16, min:0.41, theta: 18.0, val:-0.02} ee={cx: 0.0, cy: 0.35, maj:0.21, min:0.25, theta: 0.0, val:-0.01} ff={cx: 0.0, cy: 0.1, maj:0.046, min:0.046, theta: 0.0, val:-0.01} gg={cx: 0.0, cy:-0.1, maj:0.046, min:0.046, theta: 0.0, val:-0.01} hh={cx:-0.08, cy:-0.605, maj:0.046, min:0.023, theta: 0.0, val:-0.01} ii={cx: 0.0, cy:-0.605, maj:0.023, min:0.023, theta: 0.0, val:-0.01} jj={cx: 0.06, cy:-0.605, maj:0.023, min:0.046, theta: 0.0, val:-0.01} list = [aa,bb,cc,dd,ee,ff,gg,hh,ii,jj] for n = 0, n_elements(list)-1 do begin tmp = ((xcor-list[n].cx) / list[n].maj)^2 $ + ((ycor-list[n].cy) / list[n].min)^2 if list[n].theta NE 0 then begin nx = (size-1) * (list[n].cx + 1) / 2 ny = (size-1) * (list[n].cy + 1) / 2 tmp = rot(tmp, -list[n].theta, 1, nx, ny, /interp, /pivot) endif phantom[where(tmp LE 1.0)] += list[n].val endfor return, phantom < 1.1 end ; %% ;; Enable inline plotting !inline=1 ; %% phantom = shepplogan() window, 0, xsize=256, ysize=256 tvscl, phantom > 0.95 ; %% [markdown] ; Now we define simple forward and backprojection functions: ; %% function proj, image, angle sino_size_x = max(size(image,/dim)) sino_size_y = n_elements(angle) sino = fltarr(sino_size_x, sino_size_y) for aa=0, n_elements(angle)-1 do begin sino[*,aa] = total(rot(image, angle[aa], /interp), 2) endfor return, sino end ; %% function back, sino, angle image_size = n_elements(sino[*,0]) image = fltarr(image_size,image_size) for aa=0, n_elements(angle)-1 do begin image += rot(rebin(sino[*,aa],[image_size,image_size]), -angle[aa], /interp) endfor return, image / n_elements(angle) end ; %% [markdown] ; This allows us to create a sinogram: ; %% angles = findgen(360) sino = proj(phantom, angles) window, 0, xsize=256, ysize=360 tvscl, sino ; %% [markdown] ; On this we can apply a simple FBP reconstruction: ; %% ;; G.L. Zeng, “Revisit of the Ramp Filter,” ;; IEEE Trans. Nucl. Sci. 62(1), 131–136 (2015). function fbp, sino, angles ntot = n_elements(sino[*,0]) nang = n_elements(sino[0,*]) npos = ntot / 2 + 1 ; integer division needed ! nneg = ntot - npos freq = findgen(ntot) freq[npos:ntot-1] = REVERSE(freq[1:nneg]) freq[0] = 1 filter = -1 / (!pi * freq)^2 filter[where(freq mod 2 EQ 0)] *= -0.0 filter[0] = 0.25 filter = abs(fft(filter)) * ntot filter[ntot/4:ntot/4+ntot/2-1] *= 0.0 filter = rebin(filter,ntot,nang) ;; apply filter to the sinogram fsino = fft(sino, dim=1) fsino *= filter fsino = fft(fsino, dim=1, /overwrite, /inverse) fsino = !pi * real_part(fsino) ;; backproject the filtered sinogram return, back(fsino, angles) end ; %% reconstruction = fbp(sino, angles) window, 0, xsize=512, ysize=256 tvscl, [phantom, reconstruction] > 0.8 ; %% [markdown] ; ### The end ================================================ FILE: tests/data/notebooks/outputs/ipynb_to_percent/evcxr_jupyter_tour.rs ================================================ // --- // jupyter: // kernelspec: // display_name: Rust // language: rust // name: rust // --- // %% [markdown] // # Tour of the EvCxR Jupyter Kernel // For those not already familiar with Jupyter notebook, it lets you write code into "cells" like the box below. Cells can alternatively contain markdown, like this text here. Each code cell is compiled and executed separately, but variables, defined functions etc persist between cells. // // ## Printing to outputs and evaluating expressions // Lets print something to stdout and stderr then return a final expression to see how that's presented. Note that stdout and stderr are separate streams, so may not appear in the same order is their respective print statements. // %% println!("Hello world"); eprintln!("Hello error"); format!("Hello {}", "world") // %% [markdown] // ## Assigning and making use of variables // We define a variable `message`, then in the subsequent cell, modify the string and finally print it out. We could also do all this in the one cell if we wanted. // %% let mut message = "Hello ".to_owned(); // %% message.push_str("world!"); // %% message // %% [markdown] // ## Defining and redefining functions // Next we'll define a function // %% pub fn fib(x: i32) -> i32 { if x <= 2 {0} else {fib(x - 2) + fib(x - 1)} } // %% (1..13).map(fib).collect::>() // %% [markdown] // Hmm, that doesn't look right. Lets redefine the function. In practice, we'd go back and edit the function above and reevaluate it, but here, lets redefine it in a separate cell. // %% pub fn fib(x: i32) -> i32 { if x <= 2 {2} else {fib(x - 2) + fib(x - 1)} } // %% let values = (1..13).map(fib).collect::>(); values // %% [markdown] // ## Spawning a separate thread and communicating with it // We can spawn a thread to do stuff in the background, then continue executing code in other cells. // %% use std::sync::{Mutex, Arc}; let counter = Arc::new(Mutex::new(0i32)); std::thread::spawn({ let counter = Arc::clone(&counter); move || { for i in 1..300 { *counter.lock().unwrap() += 1; std::thread::sleep(std::time::Duration::from_millis(100)); } }}); // %% *counter.lock().unwrap() // %% *counter.lock().unwrap() // %% [markdown] // ## Loading external crates // We can load external crates. This one takes a while to compile, but once it's compiled, subsequent cells shouldn't need to recompile it, so it should be much quicker. // %% // :dep base64 = "0.10.1" base64::encode(&vec![1, 2, 3, 4]) // %% [markdown] // ## Customizing how types are displayed // We can also customize how our types are displayed, including presenting them as HTML. Here's an example where we define a custom display function for a type `Matrix`. // %% use std::fmt::Debug; pub struct Matrix {pub values: Vec, pub row_size: usize} impl Matrix { pub fn evcxr_display(&self) { let mut html = String::new(); html.push_str(""); for r in 0..(self.values.len() / self.row_size) { html.push_str(""); for c in 0..self.row_size { html.push_str(""); } html.push_str(""); } html.push_str("
"); html.push_str(&format!("{:?}", self.values[r * self.row_size + c])); html.push_str("
"); println!("EVCXR_BEGIN_CONTENT text/html\n{}\nEVCXR_END_CONTENT", html); } } // %% let m = Matrix {values: vec![1,2,3,4,5,6,7,8,9], row_size: 3}; m // %% [markdown] // We can also return images, we just need to base64 encode them. First, we set up code for displaying RGB and grayscale images. // %% extern crate image; extern crate base64; pub trait EvcxrResult {fn evcxr_display(&self);} impl EvcxrResult for image::RgbImage { fn evcxr_display(&self) { let mut buffer = Vec::new(); image::png::PNGEncoder::new(&mut buffer).encode(&**self, self.width(), self.height(), image::ColorType::RGB(8)).unwrap(); let img = base64::encode(&buffer); println!("EVCXR_BEGIN_CONTENT image/png\n{}\nEVCXR_END_CONTENT", img); } } impl EvcxrResult for image::GrayImage { fn evcxr_display(&self) { let mut buffer = Vec::new(); image::png::PNGEncoder::new(&mut buffer).encode(&**self, self.width(), self.height(), image::ColorType::Gray(8)).unwrap(); let img = base64::encode(&buffer); println!("EVCXR_BEGIN_CONTENT image/png\n{}\nEVCXR_END_CONTENT", img); } } // %% image::ImageBuffer::from_fn(256, 256, |x, y| { if (x as i32 - y as i32).abs() < 3 { image::Rgb([0, 0, 255]) } else { image::Rgb([0, 0, 0]) } }) // %% [markdown] // ## Display of compilation errors // Here's how compilation errors are presented. Here we forgot an & and passed a String instead of an &str. // %% let mut s = String::new(); s.push_str(format!("foo {}", 42)); // %% [markdown] // ## Seeing what variables have been defined // We can print a table of defined variables and their types with the :vars command. // %% // :vars // %% [markdown] // Other built-in commands can be found via :help // %% // :help // %% ================================================ FILE: tests/data/notebooks/outputs/ipynb_to_percent/frozen_cell.py ================================================ # --- # jupyter: # kernelspec: # display_name: Python 3 # language: python # name: python3 # --- # %% # This is an unfrozen cell. Works as usual. print("I'm a regular cell so I run and print!") # %% deletable=false editable=false run_control={"frozen": true} # # This is an frozen cell # print("I'm frozen so Im not executed :(") ================================================ FILE: tests/data/notebooks/outputs/ipynb_to_percent/fsharp.fsx ================================================ // --- // jupyter: // kernelspec: // display_name: .NET (F#) // language: F# // name: .net-fsharp // --- // %% [markdown] // This notebook was inspired by [Plottting with XPlot](https://github.com/dotnet/interactive/blob/master/NotebookExamples/fsharp/Docs/Plotting%20with%20Xplot.ipynb). // %% open XPlot.Plotly // %% let bar = Bar( name = "Bar 1", x = ["A"; "B"; "C"], y = [1; 3; 2]) [bar] |> Chart.Plot |> Chart.WithTitle "A sample bar plot" ================================================ FILE: tests/data/notebooks/outputs/ipynb_to_percent/gnuplot_notebook.gp ================================================ # --- # jupyter: # kernelspec: # display_name: gnuplot # language: gnuplot # name: gnuplot # --- # %% [markdown] # # Sample gnuplot notebook # %% [markdown] # ## Simple plotting # %% # Plot sin and cos with different linetypes f(x) = sin(x) g(x) = cos(x) set xrange[0:2*pi] set xtics(0, "{/Symbol p}" pi , "2{/Symbol p}" 2*pi) set ytics 1 plot f(x) linewidth 2 title "sin(x)", \ g(x) linewidth 2 dashtype "--" title "cos(x)" # %% [markdown] # ## Example of line magic # %% # %gnuplot inline pngcairo enhanced background rgb "#EEEEEE" size 600, 600 # Parametric plot without border reset set parametric set size ratio -1 unset border unset tics plot f(t), g(t) linewidth 2 notitle ================================================ FILE: tests/data/notebooks/outputs/ipynb_to_percent/haskell_notebook.hs ================================================ -- --- -- jupyter: -- kernelspec: -- display_name: Haskell -- language: haskell -- name: haskell -- --- -- %% [markdown] -- # Example Haskell Notebook -- %% [markdown] -- Define a function to add two numbers. -- %% f :: Num a => a -> a -> a f x y = x + y -- %% [markdown] -- Try to use the function -- %% f 1 2 ================================================ FILE: tests/data/notebooks/outputs/ipynb_to_percent/hello_world_gonb.go ================================================ // -*- coding: utf-8 -*- // --- // jupyter: // kernelspec: // display_name: Go (gonb) // language: go // name: gonb // --- // %% [markdown] // A notebook that use [GoNB](https://github.com/janpfeifer/gonb) // %% [markdown] // the code below comes from [tutorial.ipynb](https://github.com/janpfeifer/gonb/blob/main/examples/tutorial.ipynb) // %% func main() { fmt.Printf("Hello World!") } // %% //gonb:%% fmt.Printf("Hello World!") // %% [markdown] // //gonb:%% --who=world can pass flags to main func // %% import ( "flag" "fmt" ) var flagWho = flag.String("who", "", "Your name!") //gonb:%% --who=world fmt.Printf("Hello %s!\n", *flagWho) // %% [markdown] // %args also can pass flags // %% // %args --who=Wally func main() { flag.Parse() fmt.Printf("Where is %s?", *flagWho) } // %% import "github.com/janpfeifer/gonb/gonbui" //gonb:%% gonbui.DisplayHtml(`I 🧡 GoNB!`) // %% //gonb:%% gonbui.DisplayMarkdown("#### Objective\n\n1. Have fun coding **Go**;\n1. Profit...\n"+ `$$f(x) = \int_{-\infty}^{\infty} e^{-x^2} dx$$`) // %% func init_a() { fmt.Println("init_a") } //gonb:%% fmt.Println("main") ================================================ FILE: tests/data/notebooks/outputs/ipynb_to_percent/html-demo.clj ================================================ ;; --- ;; jupyter: ;; kernelspec: ;; display_name: Clojure ;; language: clojure ;; name: clojure ;; --- ;; %% [markdown] ;; # Clojupyter Demo ;; ;; This example notebook is from the [Clojupyter](https://github.com/clojupyter/clojupyter/blob/1637f6b2557f01db1e35bae5389bc38522eefe9a/examples/html-demo.ipynb) project. ;; This notebook demonstrates some of the more advanced features of Clojupyter. ;; %% [markdown] ;; ## Displaying HTML ;; ;; To display HTML, you'll need to require a clojupyter helper function to change the cell output ;; %% (require '[clojupyter.misc.display :as display]) ;; %% (println ">> should print some text") ;; displaying html (display/hiccup-html [:ul [:li "a " [:i "emphatic"] " idea"] [:li "a " [:b "bold"] " idea"] [:li "an " [:span {:style "text-decoration: underline;"} "important"] " idea"]]) ;; %% [markdown] ;; We can also use this to render SVG: ;; %% (display/hiccup-html [:svg {:height 100 :width 100 :xmlns "http://www.w3.org/2000/svg"} [:circle {:cx 50 :cy 40 :r 40 :fill "red"}]]) ;; %% [markdown] ;; ## Adding External Clojure Dependencies ;; ;; You can fetch external Clojure dependencies using the `clojupyter.misc.helper` namespace. ;; %% (require '[clojupyter.misc.helper :as helper]) ;; %% (helper/add-dependencies '[org.clojure/data.json "0.2.6"]) (require '[clojure.data.json :as json]) ;; %% (json/write-str {:a 1 :b [2, 3] :c "c"}) ;; %% [markdown] ;; ## Adding External Javascript Dependency ;; ;; Since you can render arbitrary HTML using `display/hiccup-html`, it's pretty easy to use external Javascript libraries to do things like generate charts. Here's an example using [Highcharts](https://www.highcharts.com/). ;; ;; First, we use a cell to add javascript to the running notebook: ;; %% (helper/add-javascript "https://code.highcharts.com/highcharts.js") ;; %% [markdown] ;; Now we define a function which takes Clojure data and returns hiccup HTML to display: ;; %% (defn plot-highchart [highchart-json] (let [id (str (java.util.UUID/randomUUID)) code (format "Highcharts.chart('%s', %s );" id, (json/write-str highchart-json))] (display/hiccup-html [:div [:div {:id id :style {:background-color "red"}}] [:script code]]))) ;; %% [markdown] ;; Now we can make generate interactive plots (try hovering over plot): ;; %% (def raw-data (map #(+ (* 22 (+ % (Math/random)) 78)) (range))) (def data-1 (take 500 raw-data)) (def data-2 (take 500 (drop 500 raw-data))) (plot-highchart {:chart {:type "line"} :title {:text "Plot of random data"} :series [{:data data-1} {:data data-2}]}) ;; %% ================================================ FILE: tests/data/notebooks/outputs/ipynb_to_percent/ijavascript.js ================================================ // --- // jupyter: // kernelspec: // display_name: Javascript (Node.js) // language: javascript // name: javascript // --- // %% [markdown] // ## A notebook that uses IJavascript kernel // %% let x = 5; const y = 6; var z = 10; // %% x + y; // %% function add(num1, num2) { return num1 + num2 } // %% add(x, y); // %% const arrowAdd = (num1, num2) => num1 + num2; // %% arrowAdd(x, y); // %% const myCar = { color: "blue", weight: 850, model: "fiat", start: () => "car started!", doors: [1,2,3,4] } // %% console.log("color:", myCar.color); // %% console.log("start:", myCar.start()); // %% for (let door of myCar.doors) { console.log("I'm door", door) } // %% myCar; // %% class User { constructor(name){ this.name = name; } sayHello(){ return "Hello, I'm " + this.name; } } // %% let John = new User("John"); John.sayHello(); ================================================ FILE: tests/data/notebooks/outputs/ipynb_to_percent/ir_notebook.R ================================================ # --- # jupyter: # kernelspec: # display_name: R # language: R # name: ir # --- # %% [markdown] # This is a jupyter notebook that uses the IR kernel. # %% sum(1:10) # %% plot(cars) # %% ================================================ FILE: tests/data/notebooks/outputs/ipynb_to_percent/ir_notebook.low.r ================================================ # --- # jupyter: # kernelspec: # display_name: R # language: R # name: ir # --- # %% [markdown] # This is a jupyter notebook that uses the IR kernel. # %% sum(1:10) # %% plot(cars) # %% ================================================ FILE: tests/data/notebooks/outputs/ipynb_to_percent/itypescript.ts ================================================ // --- // jupyter: // kernelspec: // display_name: Typescript 3.5 // language: typescript // name: typescript // --- // %% let x: number = 5; const y: number = 6; var z: string = "hi"; console.log(z); x + y; // %% function add(num1: number, num2: number): number { return num1 + num2 } add(x, y); // %% const arrowAdd = (num1: number, num2: number) => num1 + num2; arrowAdd(x, y); // %% class User { constructor(private name: string) { this.name = name; } sayHello(): string { return "Hello, I'm " + this.name; } } let John: User; John = new User("John"); John.sayHello(); ================================================ FILE: tests/data/notebooks/outputs/ipynb_to_percent/julia_benchmark_plotly_barchart.jl ================================================ # --- # jupyter: # kernelspec: # display_name: Julia 1.1.1 # language: julia # name: julia-1.1 # --- # %% # IJulia rocks! So does Plotly. Check it out using Plotly api_key = "" # visit https://plot.ly/api to generate an API username and password username = "" Plotly.signin(username, api_key) # %% # Following data taken from http://julialang.org/ frontpage benchmarks = ["fib", "parse_int", "quicksort3", "mandel", "pi_sum", "rand_mat_stat", "rand_mat_mul"] platforms = ["Fortran", "Julia", "Python", "R", "Matlab", "Mathematica", "Javascript", "Go"] data = { platforms[1] => [0.26, 5.03, 1.11, 0.86, 0.80, 0.64, 0.96], platforms[2] => [0.91, 1.60, 1.14, 0.85, 1.00, 1.66, 1.01], platforms[3] => [30.37, 13.95, 31.98, 14.19, 16.33, 13.52, 3.41 ], platforms[4] => [411.36, 59.40, 524.29, 106.97, 15.42, 10.84, 3.98 ], platforms[5] => [1992.00, 1463.16, 101.84, 64.58, 1.29, 6.61, 1.10 ], platforms[6] => [64.46, 29.54, 35.74, 6.07, 1.32, 4.52, 1.16 ], platforms[7] => [2.18, 2.43, 3.51, 3.49, 0.84, 3.28, 14.60], platforms[8] => [1.03, 4.79, 1.25, 2.36, 1.41, 8.12, 8.51] } pdata = [ {"x"=>benchmarks,"y"=>data[k],"bardir"=>"h","type"=>"bar","name"=>k} for k = platforms ] layout = { "title"=> "Julia benchmark comparison (smaller is better, C performance = 1.0)", "barmode"=> "group", "autosize"=> false, "width"=> 900, "height"=> 900, "titlefont"=> { "family"=> "Open Sans", "size"=> 18, "color"=> "rgb(84, 39, 143)" }, "margin"=> {"l"=>160, "pad"=>0}, "xaxis"=> { "title"=> "Benchmark log-time", "type"=> "log" }, "yaxis"=> {"title"=> "Benchmark Name"} } response = Plotly.plot(pdata,["layout"=>layout]) # Embed in an iframe within IJulia s = string("") display("text/html", s) # %% # checkout https://plot.ly/api/ for more Julia examples! # But to show off some other Plotly features: x = 1:1500 y1 = sin(2*pi*x/1500.) + rand(1500)-0.5 y2 = sin(2*pi*x/1500.) fish = {"x"=>x,"y"=> y1, "type"=>"scatter","mode"=>"markers", "marker"=>{"color"=>"rgb(0, 0, 255)","opacity"=>0.5 } } fit = {"x"=> x,"y"=> y2, "type"=>"scatter", "mode"=>"markers", "opacity"=>0.8, "marker"=>{"color"=>"rgb(255, 0, 0)"} } layout = {"autosize"=> false, "width"=> 650, "height"=> 550, "title"=>"Fish School", "xaxis"=>{ "ticks"=> "", "gridcolor"=> "white", "zerolinecolor"=> "white", "linecolor"=> "white", "autorange"=> false, "range"=>[0,1500] }, "yaxis"=>{ "ticks"=> "", "gridcolor"=> "white", "zerolinecolor"=> "white", "linecolor"=> "white", "autorange"=> false, "range"=>[-2.2,2.2] }, "plot_bgcolor"=> "rgb(245,245,247)", "showlegend"=> false, "hovermode"=> "closest"} response = Plotly.plot([fish, fit],["layout"=>layout]) s = string("") display("text/html", s) ================================================ FILE: tests/data/notebooks/outputs/ipynb_to_percent/julia_functional_geometry.jl ================================================ # -*- coding: utf-8 -*- # --- # jupyter: # kernelspec: # display_name: Julia 1.1.1 # language: julia # name: julia-1.1 # --- # %% # This notebook is a semi top-down explanation. This cell needs to be # executed first so that the operators and helper functions are defined # All of this is explained in the later half of the notebook using Compose, Interact Compose.set_default_graphic_size(2inch, 2inch) points_f = [ (.1, .1), (.9, .1), (.9, .2), (.2, .2), (.2, .4), (.6, .4), (.6, .5), (.2, .5), (.2, .9), (.1, .9), (.1, .1) ] f = compose(context(), stroke("black"), line(points_f)) rot(pic) = compose(context(rotation=Rotation(-deg2rad(90))), pic) flip(pic) = compose(context(mirror=Mirror(deg2rad(90), 0.5w, 0.5h)), pic) above(m, n, p, q) = compose(context(), (context(0, 0, 1, m/(m+n)), p), (context(0, m/(m+n), 1, n/(m+n)), q)) above(p, q) = above(1, 1, p, q) beside(m, n, p, q) = compose(context(), (context(0, 0, m/(m+n), 1), p), (context(m/(m+n), 0, n/(m+n), 1), q)) beside(p, q) = beside(1, 1, p, q) over(p, q) = compose(context(), (context(), p), (context(), q)) rot45(pic) = compose(context(0, 0, 1/sqrt(2), 1/sqrt(2), rotation=Rotation(-deg2rad(45), 0w, 0h)), pic) # Utility function to zoom out and look at the context zoomout(pic) = compose(context(), (context(0.2, 0.2, 0.6, 0.6), pic), (context(0.2, 0.2, 0.6, 0.6), fill(nothing), stroke("black"), strokedash([0.5mm, 0.5mm]), polygon([(0, 0), (1, 0), (1, 1), (0, 1)]))) function read_path(p_str) tokens = [try parsefloat(x) catch symbol(x) end for x in split(p_str, r"[\s,]+")] path(tokens) end fish = compose(context(units=UnitBox(260, 260)), stroke("black"), read_path(strip(readall("fish.path")))) rotatable(pic) = @manipulate for θ=0:0.001:2π compose(context(rotation=Rotation(θ)), pic) end blank = compose(context()) fliprot45(pic) = rot45(compose(context(mirror=Mirror(deg2rad(-45))),pic)) # Hide this cell. display(MIME("text/html"), """""") # %% [markdown] # # Functional Geometry # *Functional Geometry* is a paper by Peter Henderson ([original (1982)](users.ecs.soton.ac.uk/peter/funcgeo.pdf), [revisited (2002)](https://cs.au.dk/~hosc/local/HOSC-15-4-pp349-365.pdf)) which deconstructs the MC Escher woodcut *Square Limit* # # ![Square Limit](http://i.imgur.com/LjRzmNM.png) # %% [markdown] # > A picture is an example of a complex object that can be described in terms of its parts. # Yet a picture needs to be rendered on a printer or a screen by a device that expects to # be given a sequence of commands. Programming that sequence of commands directly is # much harder than having an application generate the commands automatically from the # simpler, denotational description. # %% [markdown] # A `picture` is a *denotation* of something to draw. # # e.g. The value of f here denotes the picture of the letter F # %% [markdown] # Original at http://nbviewer.jupyter.org/github/shashi/ijulia-notebooks/blob/master/funcgeo/Functional%20Geometry.ipynb # %% [markdown] # ## In conclusion # # We described Escher's *Square Limit* from the description of its smaller parts, which in turn were described in terms of their smaller parts. # # This seemed simple because we chose to talk in terms of an *algebra* to describe pictures. The primitives `rot`, `flip`, `fliprot45`, `above`, `beside` and `over` fit the job perfectly. # # We were able to describe these primitives in terms of `compose` `contexts`, which the Compose library knows how to render. # # Denotation can be an easy way to describe a system as well as a practical implementation method. # # [Abstraction barriers](https://mitpress.mit.edu/sicp/full-text/sicp/book/node29.html) are useful tools that can reduce the cognitive overhead on the programmer. It entails creating layers consisting of functions which only use functions in the same layer or layers below in their own implementation. The layers in our language were: # # ------------------[ squarelimit ]------------------ # -------------[ quartet, cycle, nonet ]------------- # ---[ rot, flip, fliprot45, above, beside, over ]--- # -------[ compose, context, line, path,... ]-------- # # Drawing this diagram out is a useful way to begin building any library. # ================================================ FILE: tests/data/notebooks/outputs/ipynb_to_percent/jupyter.py ================================================ # --- # jupyter: # kernelspec: # display_name: Python 3 # language: python # name: python3 # --- # %% [markdown] # # Jupyter notebook # # This notebook is a simple jupyter notebook. It only has markdown and code cells. And it does not contain consecutive markdown cells. We start with an addition: # %% a = 1 b = 2 a + b # %% [markdown] # Now we return a few tuples # %% a, b # %% a, b, a+b # %% [markdown] # And this is already the end of the notebook ================================================ FILE: tests/data/notebooks/outputs/ipynb_to_percent/jupyter_again.py ================================================ # --- # jupyter: # kernelspec: # display_name: Python 3 # language: python # name: python3 # --- # %% c = ''' title: "Quick test" output: ioslides_presentation: widescreen: true smaller: true editor_options: chunk_output_type console ''' # %% import yaml print(yaml.dump(yaml.load(c))) # %% # ?next ================================================ FILE: tests/data/notebooks/outputs/ipynb_to_percent/jupyter_with_raw_cell_in_body.py ================================================ # --- # jupyter: # kernelspec: # display_name: Python 3 # language: python # name: python3 # --- # %% 1+2+3 # %% [raw] # This is a raw cell # %% [markdown] # This is a markdown cell ================================================ FILE: tests/data/notebooks/outputs/ipynb_to_percent/jupyter_with_raw_cell_on_top.py ================================================ # --- # title: Quick test # output: # ioslides_presentation: # widescreen: true # smaller: true # editor_options: # chunk_output_type: console # jupyter: # kernelspec: # display_name: Python 3 # language: python # name: python3 # --- # %% 1+2+3 # %% ================================================ FILE: tests/data/notebooks/outputs/ipynb_to_percent/jupyter_with_raw_cell_with_invalid_yaml.py ================================================ # --- # title: Exception: Test # jupyter: # kernelspec: # display_name: Python 3 (ipykernel) # language: python # name: python3 # --- # %% 1 + 2 + 3 ================================================ FILE: tests/data/notebooks/outputs/ipynb_to_percent/jupyterlab-slideshow_1441.py ================================================ # --- # jupyter: # kernelspec: # display_name: Python 3 (ipykernel) # language: python # name: python3 # --- # %% [markdown] @deathbeds/jupyterlab-fonts={"styles": {"": {"body[data-jp-deck-mode='presenting'] &": {"right": "0", "top": "30%", "width": "25%", "z-index": 1}}}} jupyterlab-slideshow={"layer": "slide"} # > **Note** # > # > `slide` layer with a `top` of `30%` ================================================ FILE: tests/data/notebooks/outputs/ipynb_to_percent/jupytext_replication.sos ================================================ # --- # jupyter: # kernelspec: # display_name: SoS # language: sos # name: sos # --- # %% [markdown] Collapsed="false" kernel="SoS" # # Text SOS-kernel with Jupytext # # ## What is SOS kernel # # SoS consists of a ployglot notebook that allows the use of multiple kernels in one Jupyter notebook, and a workflow system that is designed for daily computational research. Basically, # # - SoS Polyglot Notebook is a Jupyter Notebook with a SoS kernel. # - SoS Notebook serves as a super kernel to all other Jupyter kernels and allows the use of multiple kernels in one Jupyter notebook. # - SoS Workflow System is a Python based workflow system that is designed to be readable, shareable, and suitable for daily data analysis. # - SoS Workflow System can be used from command line or use SoS Notebook as its IDE. # # ![](https://vatlab.github.io/sos-docs/doc/media/SoS_Notebook_and_Workflow.png) # # ### How to install SOS-kernel # # Please follow this [link](https://vatlab.github.io/sos-docs/running.html#Conda-installation) to setup SOS # # I run some issue with the latest version of R on my Mac, so I had to install an earlier version of R # # ``` # conda install -c r r=3.5.1 # conda install sos-notebook jupyterlab-sos sos-papermill -c conda-forge # ``` # # ## Related issue with Jupytext # # Jupytext works fine with Python/R kernel but converts code cells into markdown cells when using the SOS kernel. # # cf the image below. It is a code cell. After saving the notebook and restart it, it converted the code cell into markdown # # Screenshot 2020-03-13 at 10 51 18 # %% [markdown] Collapsed="false" kernel="SoS" # ## Step 1 # # Please, choose SOS Kernel and then, in the cell code, choose SOS (or any other kernel available), the outcome is the same. # # ![](https://drive.google.com/uc?export=view&id=1OtyxfwoRyVK23XHnmd9JR-crBgHBL5mt) # %% Collapsed="false" kernel="SoS" import pandas as pd import numpy as np pd.DataFrame({ 'x': np.random.random(10), 'y': np.random.random(10), }) # %% [markdown] Collapsed="false" kernel="python3" # ## Step 2 # # Now, pair it with Jupytex # # ![](https://drive.google.com/uc?export=view&id=1Wtx-YPAXY8HWHqzCcy4iIgHpzt_9emEn) # %% [markdown] Collapsed="false" kernel="python3" # ### Step 3 # # Save the notebook, restart and clear all, **save**, then Shut down kernel. Close the notebook and reopen # %% [markdown] Collapsed="false" kernel="python3" # ### Step 4 # # Reopen the notebook. Here is the outcome # # ![](https://drive.google.com/uc?export=view&id=12C70unbSPv0gHCZaCICEUy7kO7wM93JH) # # ================================================ FILE: tests/data/notebooks/outputs/ipynb_to_percent/kalman_filter_and_visualization.q ================================================ / --- / jupyter: / kernelspec: / display_name: Q 3.5 / language: q / name: qpk / --- / %% plt: .p.import`matplotlib.pyplot / %% filter: { t: ([] x: `float $ x; xh: `float $ x; p: (count x) # R: var x); (first t), iterate[R; R]\[first t; 1 _ t] } iterate: {[Q; R; x; y] x[`p]+: Q; k: x[`p] % R + x[`p]; `x`xh`p ! (y[`x]; x[`xh] + k * y[`x] - x[`xh]; (1 - k) * x[`p]) } / %% price: 100 + sums 0.5 - (n:50)?1. / %% output:filter price / %% plt[`:plot][til n; output`x; `label pykw "price"]; plt[`:plot][til n; output`xh;`label pykw "forecast"]; plt[`:legend][]; plt[`:show][]; / %% ================================================ FILE: tests/data/notebooks/outputs/ipynb_to_percent/logtalk_notebook.lgt ================================================ % --- % jupyter: % kernelspec: % display_name: Logtalk % language: logtalk % name: logtalk_kernel % --- % %% [markdown] % # An implementation of the Ackermann function % %% vscode={"languageId": "logtalk"} %%load ack.lgt :- object(ack). :- info([ version is 1:0:0, author is 'Paulo Moura', date is 2008-3-31, comment is 'Ackermann function (general recursive function).' ]). :- public(ack/3). :- mode(ack(+integer, +integer, -integer), one). :- info(ack/3, [ comment is 'Ackermann function.', argnames is ['M', 'N', 'V'] ]). ack(0, N, V) :- !, V is N + 1. ack(M, 0, V) :- !, M2 is M - 1, ack(M2, 1, V). ack(M, N, V) :- M2 is M - 1, N2 is N - 1, ack(M, N2, V2), ack(M2, V2, V). :- end_object. % %% [markdown] % ## Sample query % %% vscode={"languageId": "logtalk"} ack::ack(2, 4, V). ================================================ FILE: tests/data/notebooks/outputs/ipynb_to_percent/lua_example.lua ================================================ -- -*- coding: utf-8 -*- -- --- -- jupyter: -- kernelspec: -- display_name: Lua -- language: lua -- name: lua -- --- -- %% [markdown] -- Source: https://www.lua.org/pil/19.3.html -- %% [markdown] -- # Sort -- %% [markdown] -- Another useful function on arrays is table.sort, which we have seen before. It receives the array to be sorted, plus an optional order function. This order function receives two arguments and must return true if the first argument should come first in the sorted array. If this function is not provided, sort uses the default less-than operation (corresponding to the `<´ operator). -- %% [markdown] -- A common mistake is to try to order the indices of a table. In a table, the indices form a set, and have no order whatsoever. If you want to order them, you have to copy them to an array and then sort the array. Let us see an example. Suppose that you read a source file and build a table that gives, for each function name, the line where that function is defined; something like this: -- %% lines = { luaH_set = 10, luaH_get = 24, luaH_present = 48, } -- %% [markdown] -- Now you want to print these function names in alphabetical order. If you traverse this table with pairs, the names appear in an arbitrary order. However, you cannot sort them directly, because these names are keys of the table. However, when you put these names into an array, then you can sort them. First, you must create an array with those names, then sort it, and finally print the result: -- %% a = {} for n in pairs(lines) do table.insert(a, n) end table.sort(a) for i,n in ipairs(a) do print(n) end -- %% [markdown] -- Note that, for Lua, arrays also have no order. But we know how to count, so we get ordered values as long as we access the array with ordered indices. That is why you should always traverse arrays with ipairs, rather than pairs. The first imposes the key order 1, 2, ..., whereas the latter uses the natural arbitrary order of the table. -- %% [markdown] -- As a more advanced solution, we can write an iterator that traverses a table following the order of its keys. An optional parameter f allows the specification of an alternative order. It first sorts the keys into an array, and then iterates on the array. At each step, it returns the key and value from the original table: -- %% function pairsByKeys (t, f) local a = {} for n in pairs(t) do table.insert(a, n) end table.sort(a, f) local i = 0 -- iterator variable local iter = function () -- iterator function i = i + 1 if a[i] == nil then return nil else return a[i], t[a[i]] end end return iter end -- %% [markdown] -- With this function, it is easy to print those function names in alphabetical order. The loop -- %% for name, line in pairsByKeys(lines) do print(name, line) end ================================================ FILE: tests/data/notebooks/outputs/ipynb_to_percent/maxima_example.mac ================================================ /* --- */ /* jupyter: */ /* kernelspec: */ /* display_name: Maxima */ /* language: maxima */ /* name: maxima */ /* --- */ /* %% [markdown] */ /* ## maxima misc */ /* %% */ kill(all)$ /* %% */ f(x) := 1/(x^2+l^2)^(3/2); /* %% */ integrate(f(x), x); /* %% */ tex(%)$ /* %% */ ================================================ FILE: tests/data/notebooks/outputs/ipynb_to_percent/notebook_with_complex_metadata.py ================================================ # --- # jupyter: # kernelspec: # display_name: Python 3 # language: python # name: python3 # --- # %% ================================================ FILE: tests/data/notebooks/outputs/ipynb_to_percent/nteract_with_parameter.py ================================================ # --- # jupyter: # kernel_info: # name: python3 # kernelspec: # display_name: Python 3 # language: python # name: python3 # --- # %% inputHidden=false outputHidden=false tags=["parameters"] param = 4 # %% inputHidden=false outputHidden=false import pandas as pd # %% inputHidden=false outputHidden=false df = pd.DataFrame({'A': [1, 2], 'B': [3 + param, 4]}, index=pd.Index(['x0', 'x1'], name='x')) df # %% inputHidden=false outputHidden=false # %matplotlib inline df.plot(kind='bar') ================================================ FILE: tests/data/notebooks/outputs/ipynb_to_percent/ocaml_notebook.ml ================================================ (* --- *) (* jupyter: *) (* jupytext: *) (* formats: ipynb:markdown,md *) (* kernelspec: *) (* display_name: OCaml default *) (* language: OCaml *) (* name: ocaml-jupyter *) (* --- *) (* %% [markdown] *) (* # Example of an OCaml notebook *) (* %% *) let sum x y = x + y (* %% [markdown] *) (* Let's try our function: *) (* %% *) sum 3 4 = 7 + 0 ================================================ FILE: tests/data/notebooks/outputs/ipynb_to_percent/octave_notebook.m ================================================ % --- % jupyter: % kernelspec: % display_name: Octave % language: octave % name: octave % --- % %% [markdown] % A markdown cell % %% 1 + 1 % %% % a code cell with comments 2 + 2 % %% % a simple plot x = -10:0.1:10; plot (x, sin (x)); % %% %plot -w 800 % a simple plot with a magic instruction x = -10:0.1:10; plot (x, sin (x)); % %% [markdown] % And to finish with, a Python cell % %% language="python" % a = 1 % %% language="python" % a + 1 ================================================ FILE: tests/data/notebooks/outputs/ipynb_to_percent/plotly_graphs.py ================================================ # --- # jupyter: # kernelspec: # display_name: Python 3 # language: python # name: python3 # --- # %% [markdown] # This notebook contains complex outputs, including plotly javascript graphs. # %% [markdown] # # Interactive plots # %% [markdown] # We use Plotly's connected mode to make the notebook lighter - when connected, the notebook downloads the `plotly.js` library from the web. # %% import plotly.offline as offline offline.init_notebook_mode(connected=True) # %% import plotly.graph_objects as go fig = go.Figure( data=[go.Bar(y=[2, 3, 1])], layout=go.Layout(title="bar plot")) fig.show() fig.data[0].marker = dict(color='purple') fig ================================================ FILE: tests/data/notebooks/outputs/ipynb_to_percent/powershell.ps1 ================================================ # --- # jupyter: # kernelspec: # display_name: PowerShell # language: PowerShell # name: powershell # --- # %% [markdown] # This is an extract from # https://github.com/Jaykul/Jupyter-PowerShell/blob/master/LiterateDevOps.ipynb # %% $imageUrl = 'https://upload.wikimedia.org/wikipedia/commons/2/2f/PowerShell_5.0_icon.png' $ImageData = @{ "png" = (Invoke-WebRequest $imageUrl -UseBasicParsing).RawContentStream.GetBuffer() } # $ImageData Write-Jupyter -InputObject $ImageData -Metadata @{ "image/png" = @{ 'width' = 32 } } Write-Jupyter -InputObject $ImageData -Metadata @{ "image/png" = @{ 'width' = 64 } } ================================================ FILE: tests/data/notebooks/outputs/ipynb_to_percent/raw_cell_with_complex_yaml_like_content.py ================================================ # --- # # This is a complex paragraph # that is split over multiple lines. # # It also includes blank lines. # # # jupyter: # kernelspec: # display_name: Python 3 # language: python # name: python3 # --- # %% print("Hello, World!") ================================================ FILE: tests/data/notebooks/outputs/ipynb_to_percent/raw_cell_with_non_dict_yaml_content.py ================================================ # --- # Content. # jupyter: # kernelspec: # display_name: Python 3 # language: python # name: python3 # --- # %% print("Hello, World!") ================================================ FILE: tests/data/notebooks/outputs/ipynb_to_percent/root_cpp.cpp ================================================ // --- // jupyter: // kernelspec: // display_name: ROOT C++ // language: c++ // name: root // --- // %% #include #include // %% int k = 4; std::string foo = "This string says \"foo\""; // %% std::cout << "k = " << k << '\n' << foo << '\n'; ================================================ FILE: tests/data/notebooks/outputs/ipynb_to_percent/sage_print_hello.sage ================================================ # --- # jupyter: # kernelspec: # display_name: SageMath 9.2 # language: sage # name: sagemath # --- # %% print("Hello world") ================================================ FILE: tests/data/notebooks/outputs/ipynb_to_percent/sample_bash_notebook.sh ================================================ # --- # jupyter: # kernelspec: # display_name: Bash # language: bash # name: bash # --- # %% ls # %% # https://coderwall.com/p/euwpig/a-better-git-log git config --global alias.lg "log --color --graph --pretty=format:'%Cred%h%Creset -%C(yellow)%d%Creset %s %Cgreen(%cr) %C(bold blue)<%an>%Creset' --abbrev-commit" # %% git lg ================================================ FILE: tests/data/notebooks/outputs/ipynb_to_percent/sample_rise_notebook_66.py ================================================ # --- # jupyter: # kernelspec: # display_name: Python 3 # language: python # name: python3 # --- # %% [markdown] slideshow={"slide_type": "slide"} # A markdown cell # %% slideshow={"slide_type": ""} 1+1 # %% [markdown] cell_style="center" slideshow={"slide_type": "fragment"} # Markdown cell two ================================================ FILE: tests/data/notebooks/outputs/ipynb_to_percent/sas.sas ================================================ /* --- */ /* jupyter: */ /* kernelspec: */ /* display_name: SAS */ /* language: sas */ /* name: sas */ /* --- */ /* %% [markdown] */ /* # SAS Notebooks with jupytext */ /* %% */ proc sql; select * from sashelp.cars (obs=10) ; quit; /* %% */ %let name = "Jupytext"; /* %% */ %put &name; /* %% */ /* Note when defining macros "%macro" cannot be the first line of text in the cell */ %macro test; data temp; set sashelp.cars; name = "testx"; run; proc print data = temp (obs=10); run; %mend test; %test ================================================ FILE: tests/data/notebooks/outputs/ipynb_to_percent/simple-helloworld.java ================================================ // -*- coding: utf-8 -*- // --- // jupyter: // jupytext: // formats: ipynb,java:percent // kernelspec: // display_name: Java // language: java // name: java // --- // %% [markdown] // Let's define some class. // %% class A { public void hello() { System.out.println("Hello World"); } } // %% [markdown] // And now we call its method. // %% new A().hello(); // %% [markdown] // You can run it e.g. with `jshell` // // * from command line, as `jshell simple-helloworld.java` // * from jshell's shell with `/open simple-helloworld.java` ================================================ FILE: tests/data/notebooks/outputs/ipynb_to_percent/simple_robot_notebook.robot ================================================ # --- # jupyter: # kernelspec: # display_name: Robot Framework # language: robotframework # name: robotkernel # --- # %% *** Settings *** Library Collections # %% *** Keywords *** Head [Arguments] ${list} ${value}= Get from list ${list} 0 [Return] ${value} # %% *** Tasks *** Get head ${array}= Create list 1 2 3 4 5 ${head}= Head ${array} Should be equal ${head} 1 ================================================ FILE: tests/data/notebooks/outputs/ipynb_to_percent/simple_scala_notebook.scala ================================================ // --- // jupyter: // kernelspec: // display_name: Apache Toree - Scala // language: scala // name: apache_toree_scala // --- // %% // This is just a simple scala notebook object SampleObject { def calculation(x: Int, y: Int): Int = x + y } val result = SampleObject.calculation(1, 2) // %% println(result * 10) ================================================ FILE: tests/data/notebooks/outputs/ipynb_to_percent/stata_notebook.do ================================================ // --- // jupyter: // kernelspec: // display_name: Stata // language: stata // name: stata // --- // %% // This notebook uses the stata_kernel: https://github.com/kylebarron/stata_kernel // %% use http://www.stata-press.com/data/r13/auto // %% summarize // %% scatter weight length ================================================ FILE: tests/data/notebooks/outputs/ipynb_to_percent/tailrecursive-factorial.groovy ================================================ // -*- coding: utf-8 -*- // --- // jupyter: // jupytext: // formats: ipynb,groovy:percent // kernelspec: // display_name: Groovy // language: groovy // name: groovy // --- // %% [markdown] // # TailRecursive annotation // // Let's check what is the effect of `@TailRecursive` annotation on the simple recursive definition of factorial function. // %% import groovy.transform.CompileStatic import groovy.transform.TailRecursive import groovy.transform.TypeChecked @CompileStatic @TypeChecked class X { static final BigInteger factorial0(int n) { (n <= 1) ? 1G : factorial0(n-1).multiply(BigInteger.valueOf(n)) } static final BigInteger factorial1(int n, BigInteger acc = 1G) { (n <= 1) ? acc : factorial1(n-1, acc.multiply(BigInteger.valueOf(n))) } @TailRecursive static final BigInteger factorial2(int n, BigInteger acc = 1G) { (n <= 1) ? acc : factorial2(n-1, acc.multiply(BigInteger.valueOf(n))) } } x = new X() // %% [markdown] // Although we can time the execution of the calls, it is not very accurate; such micro benchmarks should be performed in more controlled environment, such us under [JMH](https://openjdk.java.net/projects/code-tools/jmh/). // // For example, see [blog posts of Szymon Stępniak](https://e.printstacktrace.blog/tail-recursive-methods-in-groovy/). // %% // %%timeit x.factorial0(19_000).toString().length() // %% // %%timeit x.factorial1(19_000).toString().length() // %% // %%timeit x.factorial2(19_000).toString().length() // %% [markdown] // The real difference is the use of stack. Non-tail recursive calls exhaust the stack space at some point, whereas tail recursive calls don't add frames to the stack. // %% factSize = { n, cl -> println "Factorial of ${n} has ${cl(n).toString().length()} digits" } factSize 2_000, x.&factorial0 factSize 2_000, x.&factorial1 factSize 2_000, x.&factorial2 factSize 100_000, x.&factorial2 // %% try { factSize 100_000, x.&factorial1 } catch (Throwable e) { assert e instanceof StackOverflowError println e } ================================================ FILE: tests/data/notebooks/outputs/ipynb_to_percent/tcl_test.tcl ================================================ # --- # jupyter: # kernelspec: # display_name: Tcl # language: tcl # name: tcljupyter # --- # %% [markdown] # # Assign Values # %% set a 1 puts "a = $a" # %% [markdown] # # Loop # %% for {set i 0} {$i < 10} {incr i} { puts "I inside first loop: $i" } # %% ================================================ FILE: tests/data/notebooks/outputs/ipynb_to_percent/text_outputs_and_images.py ================================================ # --- # jupyter: # kernelspec: # display_name: Python 3 # language: python # name: python3 # --- # %% [markdown] # This notebook contains outputs of many different types: text, HTML, plots and errors. # %% [markdown] # # Text outputs # # Using `print`, `sys.stdout` and `sys.stderr` # %% import sys print('using print') sys.stdout.write('using sys.stdout.write') sys.stderr.write('using sys.stderr.write') # %% import logging logging.debug('Debug') logging.info('Info') logging.warning('Warning') logging.error('Error') # %% [markdown] # # HTML outputs # # Using `pandas`. Here we find two representations: both text and HTML. # %% import pandas as pd pd.DataFrame([4]) # %% from IPython.display import display display(pd.DataFrame([5])) display(pd.DataFrame([6])) # %% [markdown] # # Images # %% # %matplotlib inline # %% # First plot from matplotlib import pyplot as plt import numpy as np w, h = 3, 3 data = np.zeros((h, w, 3), dtype=np.uint8) data[0,:] = [0,255,0] data[1,:] = [0,0,255] data[2,:] = [0,255,0] data[1:3,1:3] = [255, 0, 0] plt.imshow(data) plt.axis('off') plt.show() # Second plot data[1:3,1:3] = [255, 255, 0] plt.imshow(data) plt.axis('off') plt.show() # %% [markdown] # # Errors # %% undefined_variable ================================================ FILE: tests/data/notebooks/outputs/ipynb_to_percent/wolfram.wolfram ================================================ (* --- *) (* jupyter: *) (* kernelspec: *) (* display_name: Wolfram Language 13.1 *) (* language: Wolfram Language *) (* name: wolframlanguage13.1 *) (* --- *) (* %% [markdown] *) (* **Note:** The `language_info` `file_extension` in this notebook should be `.m`, but it was deliberately changed to `.wolfram` to avoid conflicts with Matlab which is using the same extension. *) (* %% [markdown] *) (* We start with... *) (* %% *) Print["Hello, World!"]; (* %% [markdown] *) (* Then we draw the first example plot from the [ListPlot](https://reference.wolfram.com/language/ref/ListPlot.html) reference: *) (* %% *) ListPlot[Prime[Range[25]]] (* %% [markdown] *) (* We also test the math outputs as in the [Simplify](https://reference.wolfram.com/language/ref/Simplify.html) example: *) (* %% *) D[Integrate[1/(x^3 + 1), x], x] ================================================ FILE: tests/data/notebooks/outputs/ipynb_to_percent/xcpp_by_quantstack.cpp ================================================ // --- // jupyter: // kernelspec: // display_name: C++14 // language: C++14 // name: xeus-cling-cpp14 // --- // %% [markdown] // [![xeus-cling](images/xeus-cling.png)](https://github.com/QuantStack/xeus-cling/) // // A Jupyter kernel for C++ based on the `cling` C++ interpreter and the `xeus` native implementation of the Jupyter protocol, xeus. // // - GitHub repository: https://github.com/QuantStack/xeus-cling/ // - Online documentation: https://xeus-cling.readthedocs.io/ // %% [markdown] // ## Usage // //
// // //
// To run the selected code cell, hit 
Shift + Enter
//
//
// %% [markdown] // ## Output and error streams // // `std::cout` and `std::cerr` are redirected to the notebook frontend. // %% #include std::cout << "some output" << std::endl; // %% std::cerr << "some error" << std::endl; // %% #include // %% throw std::runtime_error("Unknown exception"); // %% [markdown] // Omitting the `;` in the last statement of a cell results in an output being printed // %% int j = 5; // %% j // %% [markdown] // # Interpreting the C++ programming language // // `cling` has a broad support of the features of C++. You can define functions, classes, templates, etc ... // %% [markdown] // ## Functions // %% double sqr(double a) { return a * a; } // %% double a = 2.5; double asqr = sqr(a); asqr // %% [markdown] // ## Classes // %% class Foo { public: virtual ~Foo() {} virtual void print(double value) const { std::cout << "Foo value = " << value << std::endl; } }; // %% Foo bar; bar.print(1.2); // %% [markdown] // ## Polymorphism // %% class Bar : public Foo { public: virtual ~Bar() {} virtual void print(double value) const { std::cout << "Bar value = " << 2 * value << std::endl; } }; // %% Foo* bar2 = new Bar; bar2->print(1.2); delete bar2; // %% [markdown] // ## Templates // %% #include template class FooT { public: explicit FooT(const T& t) : m_t(t) {} void print() const { std::cout << typeid(T).name() << " m_t = " << m_t << std::endl; } private: T m_t; }; template <> class FooT { public: explicit FooT(const int& t) : m_t(t) {} void print() const { std::cout << "m_t = " << m_t << std::endl; } private: int m_t; }; // %% FooT foot1(1.2); foot1.print(); // %% FooT foot2(4); foot2.print(); // %% [markdown] // ## C++11 / C++14 support // %% class Foo11 { public: Foo11() { std::cout << "Foo11 default constructor" << std::endl; } Foo11(const Foo11&) { std::cout << "Foo11 copy constructor" << std::endl; } Foo11(Foo11&&) { std::cout << "Foo11 move constructor" << std::endl; } }; // %% Foo11 f1; Foo11 f2(f1); Foo11 f3(std::move(f1)); // %% #include std::vector v = { 1, 2, 3}; auto iter = ++v.begin(); v // %% *iter // %% [markdown] // ... and also lambda, universal references, `decltype`, etc ... // %% [markdown] // ## Documentation and completion // // - Documentation for types of the standard library is retrieved on cppreference.com. // - The quick-help feature can also be enabled for user-defined types and third-party libraries. More documentation on this feature is available at https://xeus-cling.readthedocs.io/en/latest/inline_help.html. // // %% ?std::vector // %% [markdown] // ## Using the `display_data` mechanism // %% [markdown] // For a user-defined type `T`, the rich rendering in the notebook and JupyterLab can be enabled by by implementing the function `xeus::xjson mime_bundle_repr(const T& im)`, which returns the JSON mime bundle for that type. // // More documentation on the rich display system of Jupyter and Xeus-cling is available at https://xeus-cling.readthedocs.io/en/latest/rich_display.html // %% [markdown] // ### Image example // %% #include #include #include "xtl/xbase64.hpp" #include "xeus/xjson.hpp" namespace im { struct image { inline image(const std::string& filename) { std::ifstream fin(filename, std::ios::binary); m_buffer << fin.rdbuf(); } std::stringstream m_buffer; }; xeus::xjson mime_bundle_repr(const image& i) { auto bundle = xeus::xjson::object(); bundle["image/png"] = xtl::base64encode(i.m_buffer.str()); return bundle; } } // %% im::image marie("images/marie.png"); marie // %% [markdown] // ### Audio example // %% #include #include #include "xtl/xbase64.hpp" #include "xeus/xjson.hpp" namespace au { struct audio { inline audio(const std::string& filename) { std::ifstream fin(filename, std::ios::binary); m_buffer << fin.rdbuf(); } std::stringstream m_buffer; }; xeus::xjson mime_bundle_repr(const audio& a) { auto bundle = xeus::xjson::object(); bundle["text/html"] = std::string(""; return bundle; } } // %% au::audio drums("audio/audio.wav"); drums // %% [markdown] // ### Display // %% #include "xcpp/xdisplay.hpp" // %% xcpp::display(drums); // %% [markdown] // ### Update-display // %% #include #include "xcpp/xdisplay.hpp" namespace ht { struct html { inline html(const std::string& content) { m_content = content; } std::string m_content; }; xeus::xjson mime_bundle_repr(const html& a) { auto bundle = xeus::xjson::object(); bundle["text/html"] = a.m_content; return bundle; } } // A red rectangle ht::html rect(R"(
Original
)"); // %% xcpp::display(rect, "some_display_id"); // %% // Update the rectangle to be blue rect.m_content = R"(
Updated
)"; xcpp::display(rect, "some_display_id", true); // %% [markdown] // ## Magics // // Magics are special commands for the kernel that are not part of the C++ language. // // They are defined with the symbol `%` for a line magic and `%%` for a cell magic. // // More documentation for magics is available at https://xeus-cling.readthedocs.io/en/latest/magics.html. // %% #include #include // %% std::vector to_shuffle = {1, 2, 3, 4}; // %% // %timeit std::random_shuffle(to_shuffle.begin(), to_shuffle.end()); // %% [markdown] // [![xtensor](images/xtensor.png)](https://github.com/QuantStack/xtensor/) // // - GitHub repository: https://github.com/QuantStack/xtensor/ // - Online documentation: https://xtensor.readthedocs.io/ // - NumPy to xtensor cheat sheet: http://xtensor.readthedocs.io/en/latest/numpy.html // // `xtensor` is a C++ library for manipulating N-D arrays with an API very similar to that of numpy. // %% #include #include "xtensor/xarray.hpp" #include "xtensor/xio.hpp" #include "xtensor/xview.hpp" xt::xarray arr1 {{1.0, 2.0, 3.0}, {2.0, 5.0, 7.0}, {2.0, 5.0, 7.0}}; xt::xarray arr2 {5.0, 6.0, 7.0}; xt::view(arr1, 1) + arr2 // %% [markdown] // Together with the C++ Jupyter kernel, `xtensor` offers a similar experience as `NumPy` in the Python Jupyter kernel, including broadcasting and universal functions. // %% #include #include "xtensor/xarray.hpp" #include "xtensor/xio.hpp" // %% xt::xarray arr {1, 2, 3, 4, 5, 6, 7, 8, 9}; arr.reshape({3, 3}); std::cout << arr; // %% #include "xtensor-blas/xlinalg.hpp" // %% xt::xtensor m = {{1.5, 0.5}, {0.7, 1.0}}; std::cout << "Matrix rank: " << std::endl << xt::linalg::matrix_rank(m) << std::endl; std::cout << "Matrix inverse: " << std::endl << xt::linalg::inv(m) << std::endl; std::cout << "Eigen values: " << std::endl << xt::linalg::eigvals(m) << std::endl; // %% xt::xarray arg1 = xt::arange(9); xt::xarray arg2 = xt::arange(18); arg1.reshape({3, 3}); arg2.reshape({2, 3, 3}); std::cout << xt::linalg::dot(arg1, arg2) << std::endl; // %% ================================================ FILE: tests/data/notebooks/outputs/ipynb_to_percent/xonsh_example.xsh ================================================ # --- # jupyter: # kernelspec: # display_name: Xonsh # language: xonsh # name: xonsh # --- # %% len($(curl -L https://xon.sh)) # %% for filename in `.*`: print(filename) du -sh @(filename) ================================================ FILE: tests/data/notebooks/outputs/ipynb_to_quarto/Notebook_with_more_R_magic_111.qmd ================================================ --- jupyter: python3 --- ```{python} %load_ext rpy2.ipython import pandas as pd df = pd.DataFrame( { "Letter": ["a", "a", "a", "b", "b", "b", "c", "c", "c"], "X": [4, 3, 5, 2, 1, 7, 7, 5, 9], "Y": [0, 4, 3, 6, 7, 10, 11, 9, 13], "Z": [1, 2, 3, 1, 2, 3, 1, 2, 3], } ) ``` ```{python} %%R -i df library("ggplot2") ggplot(data = df) + geom_point(aes(x = X, y = Y, color = Letter, size = Z)) ``` ================================================ FILE: tests/data/notebooks/outputs/ipynb_to_quarto/cat_variable.qmd ================================================ --- jupyter: python3 --- ```{python} cat = 42 ``` ================================================ FILE: tests/data/notebooks/outputs/ipynb_to_quarto/frozen_cell.qmd ================================================ --- jupyter: python3 --- ```{python} # This is an unfrozen cell. Works as usual. print("I'm a regular cell so I run and print!") ``` ```{python} #| deletable: false #| editable: false #| run_control: {frozen: true} # This is an frozen cell print("I'm frozen so Im not executed :(") ``` ================================================ FILE: tests/data/notebooks/outputs/ipynb_to_quarto/julia_benchmark_plotly_barchart.qmd ================================================ --- jupyter: kernelspec: display_name: Julia 1.1.1 language: julia name: julia-1.1 --- ```{julia} # IJulia rocks! So does Plotly. Check it out using Plotly api_key = "" # visit https://plot.ly/api to generate an API username and password username = "" Plotly.signin(username, api_key) ``` ```{julia} # Following data taken from http://julialang.org/ frontpage benchmarks = ["fib", "parse_int", "quicksort3", "mandel", "pi_sum", "rand_mat_stat", "rand_mat_mul"] platforms = ["Fortran", "Julia", "Python", "R", "Matlab", "Mathematica", "Javascript", "Go"] data = { platforms[1] => [0.26, 5.03, 1.11, 0.86, 0.80, 0.64, 0.96], platforms[2] => [0.91, 1.60, 1.14, 0.85, 1.00, 1.66, 1.01], platforms[3] => [30.37, 13.95, 31.98, 14.19, 16.33, 13.52, 3.41 ], platforms[4] => [411.36, 59.40, 524.29, 106.97, 15.42, 10.84, 3.98 ], platforms[5] => [1992.00, 1463.16, 101.84, 64.58, 1.29, 6.61, 1.10 ], platforms[6] => [64.46, 29.54, 35.74, 6.07, 1.32, 4.52, 1.16 ], platforms[7] => [2.18, 2.43, 3.51, 3.49, 0.84, 3.28, 14.60], platforms[8] => [1.03, 4.79, 1.25, 2.36, 1.41, 8.12, 8.51] } pdata = [ {"x"=>benchmarks,"y"=>data[k],"bardir"=>"h","type"=>"bar","name"=>k} for k = platforms ] layout = { "title"=> "Julia benchmark comparison (smaller is better, C performance = 1.0)", "barmode"=> "group", "autosize"=> false, "width"=> 900, "height"=> 900, "titlefont"=> { "family"=> "Open Sans", "size"=> 18, "color"=> "rgb(84, 39, 143)" }, "margin"=> {"l"=>160, "pad"=>0}, "xaxis"=> { "title"=> "Benchmark log-time", "type"=> "log" }, "yaxis"=> {"title"=> "Benchmark Name"} } response = Plotly.plot(pdata,["layout"=>layout]) # Embed in an iframe within IJulia s = string("") display("text/html", s) ``` ```{julia} # checkout https://plot.ly/api/ for more Julia examples! # But to show off some other Plotly features: x = 1:1500 y1 = sin(2*pi*x/1500.) + rand(1500)-0.5 y2 = sin(2*pi*x/1500.) fish = {"x"=>x,"y"=> y1, "type"=>"scatter","mode"=>"markers", "marker"=>{"color"=>"rgb(0, 0, 255)","opacity"=>0.5 } } fit = {"x"=> x,"y"=> y2, "type"=>"scatter", "mode"=>"markers", "opacity"=>0.8, "marker"=>{"color"=>"rgb(255, 0, 0)"} } layout = {"autosize"=> false, "width"=> 650, "height"=> 550, "title"=>"Fish School", "xaxis"=>{ "ticks"=> "", "gridcolor"=> "white", "zerolinecolor"=> "white", "linecolor"=> "white", "autorange"=> false, "range"=>[0,1500] }, "yaxis"=>{ "ticks"=> "", "gridcolor"=> "white", "zerolinecolor"=> "white", "linecolor"=> "white", "autorange"=> false, "range"=>[-2.2,2.2] }, "plot_bgcolor"=> "rgb(245,245,247)", "showlegend"=> false, "hovermode"=> "closest"} response = Plotly.plot([fish, fit],["layout"=>layout]) s = string("") display("text/html", s) ``` ================================================ FILE: tests/data/notebooks/outputs/ipynb_to_script/Line_breaks_in_LateX_305.py ================================================ # --- # jupyter: # kernelspec: # display_name: Python 3 # language: python # name: python3 # --- # This cell uses no particular cell marker # # $$ # \begin{align} # \dot{x} & = \sigma(y-x)\\ # \dot{y} & = \rho x - y - xz \\ # \dot{z} & = -\beta z + xy # \end{align} # $$ # This cell uses no particular cell marker, and a single slash in the $\LaTeX$ equation # # $$ # \begin{align} # \dot{x} & = \sigma(y-x) \ # \dot{y} & = \rho x - y - xz \ # \dot{z} & = -\beta z + xy # \end{align} # $$ # + [markdown] ''' This cell uses the triple quote cell markers introduced at https://github.com/mwouts/jupytext/issues/305 $$ \begin{align} \dot{x} & = \sigma(y-x)\\ \dot{y} & = \rho x - y - xz \\ \dot{z} & = -\beta z + xy \end{align} $$ ''' ================================================ FILE: tests/data/notebooks/outputs/ipynb_to_script/Notebook with function and cell metadata 164.py ================================================ # --- # jupyter: # kernelspec: # display_name: Python 3 # language: python # name: python3 # --- 1 + 1 # A markdown cell # And below, the cell for function f has non trivial cell metadata. And the next cell as well. # + attributes={"classes": [], "id": "", "n": "10"} def f(x): return x # + attributes={"classes": [], "id": "", "n": "10"} f(5) # - # More text 2 + 2 ================================================ FILE: tests/data/notebooks/outputs/ipynb_to_script/Notebook with html and latex cells.py ================================================ # --- # jupyter: # kernelspec: # display_name: Python 3 # language: python # name: python3 # --- # + language="html" #

Jupytext on GitHub

# + language="latex" # $\frac{\pi}{2}$ # - # %load_ext rpy2.ipython # + language="R" # library(ggplot2) # ggplot(data=data.frame(x=c('A', 'B'), y=c(5, 2)), aes(x,weight=y)) + geom_bar() # - # %matplotlib inline import pandas as pd pd.Series({'A':5, 'B':2}).plot(figsize=(3,2), kind='bar') ================================================ FILE: tests/data/notebooks/outputs/ipynb_to_script/Notebook with metadata and long cells.py ================================================ # --- # jupyter: # kernelspec: # display_name: Python 3 # language: python # name: python3 # --- # # Part one - various cells # Here we have a markdown cell # # # with two blank lines # Now we have a markdown cell # with a code block inside it # # ```python # 1 + 1 # ``` # # After that cell we'll have a code cell # + 2 + 2 3 + 3 # - # Followed by a raw cell # + active="" # This is # the content # of the raw cell # - # # Part two - cell metadata # + [markdown] key="value" # This is a markdown cell with cell metadata `{"key": "value"}` # + .class tags=["parameters"] """This is a code cell with metadata `{"tags":["parameters"], ".class":null}`""" # + key="value" active="" # This is a raw cell with cell metadata `{"key": "value"}` ================================================ FILE: tests/data/notebooks/outputs/ipynb_to_script/Notebook_with_R_magic.py ================================================ # --- # jupyter: # kernelspec: # display_name: Python 2 # language: python # name: python2 # --- # # A notebook with R cells # # This notebook shows the use of R cells to generate plots # %load_ext rpy2.ipython # + language="R" # suppressMessages(require(tidyverse)) # + language="R" # ggplot(iris, aes(x = Sepal.Length, y = Petal.Length, color=Species)) + geom_point() # - # The default plot dimensions are not good for us, so we use the -w and -h parameters in %%R magic to set the plot size # + magic_args="-w 400 -h 240" language="R" # ggplot(iris, aes(x = Sepal.Length, y = Petal.Length, color=Species)) + geom_point() ================================================ FILE: tests/data/notebooks/outputs/ipynb_to_script/Notebook_with_more_R_magic_111.py ================================================ # --- # jupyter: # kernelspec: # display_name: Python 3 # language: python # name: python3 # --- # + # %load_ext rpy2.ipython import pandas as pd df = pd.DataFrame( { "Letter": ["a", "a", "a", "b", "b", "b", "c", "c", "c"], "X": [4, 3, 5, 2, 1, 7, 7, 5, 9], "Y": [0, 4, 3, 6, 7, 10, 11, 9, 13], "Z": [1, 2, 3, 1, 2, 3, 1, 2, 3], } ) # + magic_args="-i df" language="R" # library("ggplot2") # ggplot(data = df) + geom_point(aes(x = X, y = Y, color = Letter, size = Z)) ================================================ FILE: tests/data/notebooks/outputs/ipynb_to_script/R notebook with invalid cell keys.R ================================================ # --- # jupyter: # kernelspec: # display_name: R # language: R # name: ir # --- # This notebook was created with IRKernel 0.8.12, and is not completely valid, as the code cell below contains an unexpected 'source' entry. This did cause https://github.com/mwouts/jupytext/issues/234. Note that the problem is solved when one upgrades to IRKernel 1.0.0. library("ggplot2") ggplot(mtcars, aes(mpg)) + stat_ecdf() ================================================ FILE: tests/data/notebooks/outputs/ipynb_to_script/R notebook with invalid cell keys.low.r ================================================ # --- # jupyter: # kernelspec: # display_name: R # language: R # name: ir # --- # This notebook was created with IRKernel 0.8.12, and is not completely valid, as the code cell below contains an unexpected 'source' entry. This did cause https://github.com/mwouts/jupytext/issues/234. Note that the problem is solved when one upgrades to IRKernel 1.0.0. library("ggplot2") ggplot(mtcars, aes(mpg)) + stat_ecdf() ================================================ FILE: tests/data/notebooks/outputs/ipynb_to_script/Reference Guide for Calysto Scheme.scm ================================================ ;; -*- coding: utf-8 -*- ;; --- ;; jupyter: ;; kernelspec: ;; display_name: Calysto Scheme (Python) ;; language: scheme ;; name: calysto_scheme ;; --- ;; ;;

Reference Guide for Calysto Scheme

;; ;; [Calysto Scheme](https://github.com/Calysto/calysto_scheme) is a real Scheme programming language, with full support for continuations, including call/cc. It can also use all Python libraries. Also has some extensions that make it more useful (stepper-debugger, choose/fail, stack traces), or make it better integrated with Python. ;; ;; In Jupyter notebooks, because Calysto Scheme uses [MetaKernel](https://github.com/Calysto/metakernel/blob/master/README.rst), it has a fully-supported set of "magics"---meta-commands for additional functionality. This includes running Scheme in parallel. See all of the [MetaKernel Magics](https://github.com/Calysto/metakernel/blob/master/metakernel/magics/README.md). ;; ;; Calysto Scheme is written in Scheme, and then translated into Python (and other backends). The entire functionality lies in a single Python file: https://github.com/Calysto/calysto_scheme/blob/master/calysto_scheme/scheme.py However, you can easily install it (see below). ;; ;; Please see [Calysto Scheme Language](Calysto%20Scheme%20Language.ipynb) for more details on the Calysto Scheme language. ;; ;; ## Installation ;; ;; You can install Calysto Scheme with Python3: ;; ;; ``` ;; pip3 install --upgrade calysto-scheme --user -U ;; python3 -m calysto_kernel install --user ;; ``` ;; ;; or in the system kernel folder with: ;; ;; ``` ;; sudo pip3 install --upgrade calysto-scheme -U ;; sudo python3 -m calysto_kernel install ;; ``` ;; ;; Change pip3/python3 to use a different pip or Python. The version of Python used will determine how Calysto Scheme is run. ;; ;; Use it in the console, qtconsole, or notebook with IPython 3: ;; ;; ``` ;; ipython console --kernel calysto_scheme ;; ipython qtconsole --kernel calysto_scheme ;; ipython notebook --kernel calysto_scheme ;; ``` ;; ;; In addition to all of the following items, Calysto Scheme also has access to all of Python's builtin functions, and all of Python's libraries. For example, you can use `(complex 3 2)` to create a complex number by calling Python's complex function. ;; ;; ## Jupyter Enhancements ;; ;; When you run Calysto Scheme in Jupyter (console, notebook, qtconsole, etc.) you get: ;; ;; * TAB completions of Scheme functions and variable names ;; * display of rich media ;; * stepper/debugger ;; * magics (% macros) ;; * shell commands (! command) ;; * LaTeX equations ;; * LaTeX-style variables ;; * Python integration ;; ### LaTeX-style variables ;; ;; Calysto Scheme allows you to use LaTeX-style variables in code. For example, if you type: ;; ;; ``` ;; \beta ;; ``` ;; ;; with the cursor right after the 'a' in beta, and then press TAB, it will turn into the unicode character: ;; ;; ``` ;; β ;; ``` ;; ;; There are nearly 1300 different symbols defined (thanks to the Julia language) and documented here: ;; ;; http://docs.julialang.org/en/release-0.4/manual/unicode-input/#man-unicode-input ;; ;; Calysto Scheme may not implement all of those. Some useful and suggestive ones: ;; ;; * \pi - π ;; * \Pi - Π ;; * \Sigma - Σ ;; * \_i - subscript i, such as vectorᵢ (define α 67) α (define i 2) (define vectorᵢ (vector-ref (vector 0 6 3 2) i)) vectorᵢ ;; ### Rich media (import "calysto.display") (calysto.display.HTML "This is bold, italics, underlined.") (import "calysto.graphics") (define canvas (calysto.graphics.Canvas)) (define ball (calysto.graphics.Circle '(150 150) 100)) (ball.draw canvas) ;; ### Shell commands ! ls /tmp ;; ### Stepper/Debugger ;; ;; Here is what the debugger looks like: ;; ;; ;; ;; It has breakpoints (click in left margin). You must press Stop to exit the debugger. ;; ```scheme ;; ;; %%debug ;; ;; (begin ;; (define x 1) ;; (set! x 2) ;; ) ;; ``` ;; ### Python Integration ;; ;; You can import and use any Python library in Calysto Scheme. ;; ;; In addition, if you wish, you can execute expressions and statements in a Python environment: (python-eval "1 + 2") (python-exec " def mypyfunc(a, b): return a * b ") ;; This is a shared environment with Scheme: (mypyfunc 4 5) ;; You can use `func` to turn a Scheme procedure into a Python function, and `define!` to put it into the shared environment with Python: (define! mypyfunc2 (func (lambda (n) n))) (python-eval "mypyfunc2(34)") ;; # Differences Between Languages ;; ;; ## Major differences between Scheme and Python ;; ;; 1. In Scheme, double quotes are used for strings and may contain newlines ;; 1. In Scheme, a single quote is short for (quote ...) and means "literal" ;; 1. In Scheme, everything is an expression and has a return value ;; 1. Python does not support macros (e.g., extending syntax) ;; 1. In Python, "if X" is false if X is None, False, [], (,) or 0. In Scheme, "if X" is only false if X is #f or 0 ;; 1. Calysto Scheme uses continuations, not the call stack. However, for debugging there is a pseudo-stack when an error is raised. You can turn that off with (use-stack-trace #f) ;; 1. Scheme procedures are not Python functions, but there are means to use one as the other. ;; ;; ## Major Differences Between Calysto Scheme and other Schemes ;; ;; 1. define-syntax works slightly differently ;; 1. In Calysto Scheme, #(...) is short for '#(...) ;; 1. Calysto Scheme is missing many standard functions (see list at bottom) ;; 1. Calysto Scheme has a built-in amb operator called `choose` ;; 1. For debugging there is a pseudo-stack when errors are raised in Calysto Scheme. You can turn that off with (use-stack-trace #f) ;; ;; ### Stack Trace ;; ;; Calysto Scheme acts as if it has a call stack, for easier debugging. For example: (define fact (lambda (n) (if (= n 1) q (* n (fact (- n 1)))))) (fact 5) ;; To turn off the stack trace on error: ;; ;; ```scheme ;; (use-stack-trace #f) ;; ``` ;; That will allow infinite recursive loops without keeping track of the "stack". ;; # Calysto Scheme Variables ;; ;; ## SCHEMEPATH ;; SCHEMEPATH is a list of search directories used with (load NAME). This is a reference, so you should append to it rather than attempting to redefine it. SCHEMEPATH (set-cdr! (cdr SCHEMEPATH) (list "/var/modules")) SCHEMEPATH ;; ## Getting Started ;; ;; Note that you can use the word `lambda` or \lambda and then press [TAB] (define factorial (λ (n) (cond ((zero? n) 1) (else (* n (factorial (- n 1))))))) (factorial 5) ;; ## define-syntax ;; (define-syntax NAME RULES): a method for creating macros (define-syntax time [(time ?exp) (let ((start (current-time))) ?exp (- (current-time) start))]) (time (car '(1 2 3 4))) ;; + ;;--------------------------------------------------------------------- ;; collect is like list comprehension in Python (define-syntax collect [(collect ?exp for ?var in ?list) (filter-map (lambda (?var) ?exp) (lambda (?var) #t) ?list)] [(collect ?exp for ?var in ?list if ?condition) (filter-map (lambda (?var) ?exp) (lambda (?var) ?condition) ?list)]) (define filter-map (lambda (f pred? values) (if (null? values) '() (if (pred? (car values)) (cons (f (car values)) (filter-map f pred? (cdr values))) (filter-map f pred? (cdr values)))))) ;; - (collect (* n n) for n in (range 10)) (collect (* n n) for n in (range 5 20 3)) (collect (* n n) for n in (range 10) if (> n 5)) ;; + ;;--------------------------------------------------------------------- ;; for loops (define-syntax for [(for ?exp times do . ?bodies) (for-repeat ?exp (lambda () . ?bodies))] [(for ?var in ?exp do . ?bodies) (for-iterate1 ?exp (lambda (?var) . ?bodies))] [(for ?var at (?i) in ?exp do . ?bodies) (for-iterate2 0 ?exp (lambda (?var ?i) . ?bodies))] [(for ?var at (?i ?j . ?rest) in ?exp do . ?bodies) (for ?var at (?i) in ?exp do (for ?var at (?j . ?rest) in ?var do . ?bodies))]) (define for-repeat (lambda (n f) (if (< n 1) 'done (begin (f) (for-repeat (- n 1) f))))) (define for-iterate1 (lambda (values f) (if (null? values) 'done (begin (f (car values)) (for-iterate1 (cdr values) f))))) (define for-iterate2 (lambda (i values f) (if (null? values) 'done (begin (f (car values) i) (for-iterate2 (+ i 1) (cdr values) f))))) ;; + (define matrix2d '((10 20) (30 40) (50 60) (70 80))) (define matrix3d '(((10 20 30) (40 50 60)) ((70 80 90) (100 110 120)) ((130 140 150) (160 170 180)) ((190 200 210) (220 230 240)))) ;; - (begin (define hello 0) (for 5 times do (set! hello (+ hello 1))) hello ) (for sym in '(a b c d) do (define x 1) (set! x sym) (print x)) (for n in (range 10 20 2) do (print n)) (for n at (i j) in matrix2d do (print (list n 'coords: i j))) (for n at (i j k) in matrix3d do (print (list n 'coords: i j k))) ;; + (define-syntax scons [(scons ?x ?y) (cons ?x (lambda () ?y))]) (define scar car) (define scdr (lambda (s) (let ((result ((cdr s)))) (set-cdr! s (lambda () result)) result))) (define first (lambda (n s) (if (= n 0) '() (cons (scar s) (first (- n 1) (scdr s)))))) (define nth (lambda (n s) (if (= n 0) (scar s) (nth (- n 1) (scdr s))))) (define smap (lambda (f s) (scons (f (scar s)) (smap f (scdr s))))) (define ones (scons 1 ones)) (define nats (scons 0 (combine nats + ones))) (define combine (lambda (s1 op s2) (scons (op (scar s1) (scar s2)) (combine (scdr s1) op (scdr s2))))) (define fibs (scons 1 (scons 1 (combine fibs + (scdr fibs))))) (define facts (scons 1 (combine facts * (scdr nats)))) (define ! (lambda (n) (nth n facts))) ;; - (! 5) (nth 10 facts) (nth 20 fibs) (first 30 fibs) ;; ## for-each ;; (for-each PROCEDURE LIST): apply PROCEDURE to each item in LIST; like `map` but don't return results (for-each (lambda (n) (print n)) '(3 4 5)) ;; ## format ;; (format STRING ITEM ...): format the string with ITEMS as arguments (format "This uses formatting ~a ~s ~%" 'apple 'apple) ;; ## func ;; ;; Turns a lambda into a Python function. ;; ;; (func (lambda ...)) (func (lambda (n) n)) ;; ## There's more! ;; ;; Please see [Calysto Scheme Language](Calysto%20Scheme%20Language.ipynb) for more details on the Calysto Scheme language. ================================================ FILE: tests/data/notebooks/outputs/ipynb_to_script/Reference Guide for Calysto Scheme.ss ================================================ ;; -*- coding: utf-8 -*- ;; --- ;; jupyter: ;; kernelspec: ;; display_name: Calysto Scheme (Python) ;; language: scheme ;; name: calysto_scheme ;; --- ;; ;;

Reference Guide for Calysto Scheme

;; ;; [Calysto Scheme](https://github.com/Calysto/calysto_scheme) is a real Scheme programming language, with full support for continuations, including call/cc. It can also use all Python libraries. Also has some extensions that make it more useful (stepper-debugger, choose/fail, stack traces), or make it better integrated with Python. ;; ;; In Jupyter notebooks, because Calysto Scheme uses [MetaKernel](https://github.com/Calysto/metakernel/blob/master/README.rst), it has a fully-supported set of "magics"---meta-commands for additional functionality. This includes running Scheme in parallel. See all of the [MetaKernel Magics](https://github.com/Calysto/metakernel/blob/master/metakernel/magics/README.md). ;; ;; Calysto Scheme is written in Scheme, and then translated into Python (and other backends). The entire functionality lies in a single Python file: https://github.com/Calysto/calysto_scheme/blob/master/calysto_scheme/scheme.py However, you can easily install it (see below). ;; ;; Please see [Calysto Scheme Language](Calysto%20Scheme%20Language.ipynb) for more details on the Calysto Scheme language. ;; ;; ## Installation ;; ;; You can install Calysto Scheme with Python3: ;; ;; ``` ;; pip3 install --upgrade calysto-scheme --user -U ;; python3 -m calysto_kernel install --user ;; ``` ;; ;; or in the system kernel folder with: ;; ;; ``` ;; sudo pip3 install --upgrade calysto-scheme -U ;; sudo python3 -m calysto_kernel install ;; ``` ;; ;; Change pip3/python3 to use a different pip or Python. The version of Python used will determine how Calysto Scheme is run. ;; ;; Use it in the console, qtconsole, or notebook with IPython 3: ;; ;; ``` ;; ipython console --kernel calysto_scheme ;; ipython qtconsole --kernel calysto_scheme ;; ipython notebook --kernel calysto_scheme ;; ``` ;; ;; In addition to all of the following items, Calysto Scheme also has access to all of Python's builtin functions, and all of Python's libraries. For example, you can use `(complex 3 2)` to create a complex number by calling Python's complex function. ;; ;; ## Jupyter Enhancements ;; ;; When you run Calysto Scheme in Jupyter (console, notebook, qtconsole, etc.) you get: ;; ;; * TAB completions of Scheme functions and variable names ;; * display of rich media ;; * stepper/debugger ;; * magics (% macros) ;; * shell commands (! command) ;; * LaTeX equations ;; * LaTeX-style variables ;; * Python integration ;; ### LaTeX-style variables ;; ;; Calysto Scheme allows you to use LaTeX-style variables in code. For example, if you type: ;; ;; ``` ;; \beta ;; ``` ;; ;; with the cursor right after the 'a' in beta, and then press TAB, it will turn into the unicode character: ;; ;; ``` ;; β ;; ``` ;; ;; There are nearly 1300 different symbols defined (thanks to the Julia language) and documented here: ;; ;; http://docs.julialang.org/en/release-0.4/manual/unicode-input/#man-unicode-input ;; ;; Calysto Scheme may not implement all of those. Some useful and suggestive ones: ;; ;; * \pi - π ;; * \Pi - Π ;; * \Sigma - Σ ;; * \_i - subscript i, such as vectorᵢ (define α 67) α (define i 2) (define vectorᵢ (vector-ref (vector 0 6 3 2) i)) vectorᵢ ;; ### Rich media (import "calysto.display") (calysto.display.HTML "This is bold, italics, underlined.") (import "calysto.graphics") (define canvas (calysto.graphics.Canvas)) (define ball (calysto.graphics.Circle '(150 150) 100)) (ball.draw canvas) ;; ### Shell commands ! ls /tmp ;; ### Stepper/Debugger ;; ;; Here is what the debugger looks like: ;; ;; ;; ;; It has breakpoints (click in left margin). You must press Stop to exit the debugger. ;; ```scheme ;; ;; %%debug ;; ;; (begin ;; (define x 1) ;; (set! x 2) ;; ) ;; ``` ;; ### Python Integration ;; ;; You can import and use any Python library in Calysto Scheme. ;; ;; In addition, if you wish, you can execute expressions and statements in a Python environment: (python-eval "1 + 2") (python-exec " def mypyfunc(a, b): return a * b ") ;; This is a shared environment with Scheme: (mypyfunc 4 5) ;; You can use `func` to turn a Scheme procedure into a Python function, and `define!` to put it into the shared environment with Python: (define! mypyfunc2 (func (lambda (n) n))) (python-eval "mypyfunc2(34)") ;; # Differences Between Languages ;; ;; ## Major differences between Scheme and Python ;; ;; 1. In Scheme, double quotes are used for strings and may contain newlines ;; 1. In Scheme, a single quote is short for (quote ...) and means "literal" ;; 1. In Scheme, everything is an expression and has a return value ;; 1. Python does not support macros (e.g., extending syntax) ;; 1. In Python, "if X" is false if X is None, False, [], (,) or 0. In Scheme, "if X" is only false if X is #f or 0 ;; 1. Calysto Scheme uses continuations, not the call stack. However, for debugging there is a pseudo-stack when an error is raised. You can turn that off with (use-stack-trace #f) ;; 1. Scheme procedures are not Python functions, but there are means to use one as the other. ;; ;; ## Major Differences Between Calysto Scheme and other Schemes ;; ;; 1. define-syntax works slightly differently ;; 1. In Calysto Scheme, #(...) is short for '#(...) ;; 1. Calysto Scheme is missing many standard functions (see list at bottom) ;; 1. Calysto Scheme has a built-in amb operator called `choose` ;; 1. For debugging there is a pseudo-stack when errors are raised in Calysto Scheme. You can turn that off with (use-stack-trace #f) ;; ;; ### Stack Trace ;; ;; Calysto Scheme acts as if it has a call stack, for easier debugging. For example: (define fact (lambda (n) (if (= n 1) q (* n (fact (- n 1)))))) (fact 5) ;; To turn off the stack trace on error: ;; ;; ```scheme ;; (use-stack-trace #f) ;; ``` ;; That will allow infinite recursive loops without keeping track of the "stack". ;; # Calysto Scheme Variables ;; ;; ## SCHEMEPATH ;; SCHEMEPATH is a list of search directories used with (load NAME). This is a reference, so you should append to it rather than attempting to redefine it. SCHEMEPATH (set-cdr! (cdr SCHEMEPATH) (list "/var/modules")) SCHEMEPATH ;; ## Getting Started ;; ;; Note that you can use the word `lambda` or \lambda and then press [TAB] (define factorial (λ (n) (cond ((zero? n) 1) (else (* n (factorial (- n 1))))))) (factorial 5) ;; ## define-syntax ;; (define-syntax NAME RULES): a method for creating macros (define-syntax time [(time ?exp) (let ((start (current-time))) ?exp (- (current-time) start))]) (time (car '(1 2 3 4))) ;; + ;;--------------------------------------------------------------------- ;; collect is like list comprehension in Python (define-syntax collect [(collect ?exp for ?var in ?list) (filter-map (lambda (?var) ?exp) (lambda (?var) #t) ?list)] [(collect ?exp for ?var in ?list if ?condition) (filter-map (lambda (?var) ?exp) (lambda (?var) ?condition) ?list)]) (define filter-map (lambda (f pred? values) (if (null? values) '() (if (pred? (car values)) (cons (f (car values)) (filter-map f pred? (cdr values))) (filter-map f pred? (cdr values)))))) ;; - (collect (* n n) for n in (range 10)) (collect (* n n) for n in (range 5 20 3)) (collect (* n n) for n in (range 10) if (> n 5)) ;; + ;;--------------------------------------------------------------------- ;; for loops (define-syntax for [(for ?exp times do . ?bodies) (for-repeat ?exp (lambda () . ?bodies))] [(for ?var in ?exp do . ?bodies) (for-iterate1 ?exp (lambda (?var) . ?bodies))] [(for ?var at (?i) in ?exp do . ?bodies) (for-iterate2 0 ?exp (lambda (?var ?i) . ?bodies))] [(for ?var at (?i ?j . ?rest) in ?exp do . ?bodies) (for ?var at (?i) in ?exp do (for ?var at (?j . ?rest) in ?var do . ?bodies))]) (define for-repeat (lambda (n f) (if (< n 1) 'done (begin (f) (for-repeat (- n 1) f))))) (define for-iterate1 (lambda (values f) (if (null? values) 'done (begin (f (car values)) (for-iterate1 (cdr values) f))))) (define for-iterate2 (lambda (i values f) (if (null? values) 'done (begin (f (car values) i) (for-iterate2 (+ i 1) (cdr values) f))))) ;; + (define matrix2d '((10 20) (30 40) (50 60) (70 80))) (define matrix3d '(((10 20 30) (40 50 60)) ((70 80 90) (100 110 120)) ((130 140 150) (160 170 180)) ((190 200 210) (220 230 240)))) ;; - (begin (define hello 0) (for 5 times do (set! hello (+ hello 1))) hello ) (for sym in '(a b c d) do (define x 1) (set! x sym) (print x)) (for n in (range 10 20 2) do (print n)) (for n at (i j) in matrix2d do (print (list n 'coords: i j))) (for n at (i j k) in matrix3d do (print (list n 'coords: i j k))) ;; + (define-syntax scons [(scons ?x ?y) (cons ?x (lambda () ?y))]) (define scar car) (define scdr (lambda (s) (let ((result ((cdr s)))) (set-cdr! s (lambda () result)) result))) (define first (lambda (n s) (if (= n 0) '() (cons (scar s) (first (- n 1) (scdr s)))))) (define nth (lambda (n s) (if (= n 0) (scar s) (nth (- n 1) (scdr s))))) (define smap (lambda (f s) (scons (f (scar s)) (smap f (scdr s))))) (define ones (scons 1 ones)) (define nats (scons 0 (combine nats + ones))) (define combine (lambda (s1 op s2) (scons (op (scar s1) (scar s2)) (combine (scdr s1) op (scdr s2))))) (define fibs (scons 1 (scons 1 (combine fibs + (scdr fibs))))) (define facts (scons 1 (combine facts * (scdr nats)))) (define ! (lambda (n) (nth n facts))) ;; - (! 5) (nth 10 facts) (nth 20 fibs) (first 30 fibs) ;; ## for-each ;; (for-each PROCEDURE LIST): apply PROCEDURE to each item in LIST; like `map` but don't return results (for-each (lambda (n) (print n)) '(3 4 5)) ;; ## format ;; (format STRING ITEM ...): format the string with ITEMS as arguments (format "This uses formatting ~a ~s ~%" 'apple 'apple) ;; ## func ;; ;; Turns a lambda into a Python function. ;; ;; (func (lambda ...)) (func (lambda (n) n)) ;; ## There's more! ;; ;; Please see [Calysto Scheme Language](Calysto%20Scheme%20Language.ipynb) for more details on the Calysto Scheme language. ================================================ FILE: tests/data/notebooks/outputs/ipynb_to_script/The flavors of raw cells.py ================================================ # --- # jupyter: # kernelspec: # display_name: Python 3 # language: python # name: python3 # --- # + raw_mimetype="text/latex" active="" # $1+1$ # + raw_mimetype="text/restructuredtext" active="" # :math:`1+1` # + raw_mimetype="text/html" active="" # Bold text # + raw_mimetype="text/markdown" active="" # **Bold text** # + raw_mimetype="text/x-python" active="" # 1 + 1 # + active="" # Not formatted ================================================ FILE: tests/data/notebooks/outputs/ipynb_to_script/cat_variable.py ================================================ # --- # jupyter: # kernelspec: # display_name: Python 3 # language: python # name: python3 # --- cat = 42 ================================================ FILE: tests/data/notebooks/outputs/ipynb_to_script/coconut_homepage_demo.coco ================================================ # --- # jupyter: # kernelspec: # display_name: Coconut # language: coconut # name: coconut # --- # Taken from [coconut-lang.org](coconut-lang.org) # pipeline-style programming "hello, world!" |> print # prettier lambdas x -> x ** 2 # partial application range(10) |> map$(pow$(?, 2)) |> list # pattern-matching match [head] + tail in [0, 1, 2, 3]: print(head, tail) # destructuring assignment {"list": [0] + rest} = {"list": [0, 1, 2, 3]} # infix notation # + # 5 `mod` 3 == 2 # - # operator functions product = reduce$(*) # function composition # + # (f..g..h)(x, y, z) # - # lazy lists # + # (| first_elem() |) :: rest_elems() # - # parallel programming range(100) |> parallel_map$(pow$(2)) |> list # tail call optimization def factorial(n, acc=1): case n: match 0: return acc match _ is int if n > 0: return factorial(n-1, acc*n) # algebraic data types # + data Empty() data Leaf(n) data Node(l, r) def size(Empty()) = 0 addpattern def size(Leaf(n)) = 1 addpattern def size(Node(l, r)) = size(l) + size(r) # - # and much more! # # Like what you see? Don't forget to star Coconut on GitHub! ================================================ FILE: tests/data/notebooks/outputs/ipynb_to_script/convert_to_py_then_test_with_update83.py ================================================ # --- # jupyter: # kernelspec: # display_name: Python 3 # language: python # name: python3 # --- # + # %%time print('asdf') # - # Thanks for jupytext! ================================================ FILE: tests/data/notebooks/outputs/ipynb_to_script/csharp.cs ================================================ // --- // jupyter: // kernelspec: // display_name: .NET (C#) // language: C# // name: .net-csharp // --- // We start with... Console.WriteLine("Hello World!"); // Then we do a plot with Plotly, following the [Plotting with XPlot](https://github.com/dotnet/interactive/blob/master/NotebookExamples/csharp/Docs/Plotting%20with%20Xplot.ipynb) example from `dotnet/interactive`: // + using XPlot.Plotly; var bar = new Graph.Bar { name = "Bar", x = new[] {'A', 'B', 'C'}, y = new[] {1, 3, 2} }; var chart = Chart.Plot(new[] {bar}); chart.WithTitle("A bar plot"); display(chart); // - // We also test the math outputs as in the [Math and Latex](https://github.com/dotnet/interactive/blob/master/NotebookExamples/csharp/Docs/Math%20and%20LaTeX.ipynb) example: (LaTeXString)@"\begin{align} e^{i \pi} = -1\end{align}" (MathString)@"e^{i \pi} = -1" ================================================ FILE: tests/data/notebooks/outputs/ipynb_to_script/demo_gdl_fbp.pro ================================================ ; -*- coding: utf-8 -*- ; --- ; jupyter: ; kernelspec: ; display_name: IDL [conda env:gdl] * ; language: IDL ; name: conda-env-gdl-idl ; --- ; ## GDL demo notebook ; Demonstration of GDL [(gnudatalanguage)](https://github.com/gnudatalanguage/gdl) ; ; This notebook creates a Shepp-Logan phantom, projects it and then performs an FBP reconstruction. ; + ;; L.A. Shepp and B.F. Logan, “The Fourier reconstruction of a head section,” ;; IEEE Trans. Nucl. Sci. 21(3), 21–43 (1974). function shepplogan, size = size if NOT keyword_set(size) then size = 256 phantom = fltarr(size,size) tmp = (findgen(size)-((size-1)/2.0)) / (size/2.0) xcor = rebin(tmp,size,size) ycor = rebin(transpose(tmp),size,size) tmp = fltarr(size,size) aa={cx: 0.0, cy: 0.0, maj:0.69, min:0.92, theta: 0.0, val: 2.0 } bb={cx: 0.0, cy:-0.0184, maj:0.6624, min:0.874, theta: 0.0, val:-0.98} cc={cx: 0.22, cy: 0.0, maj:0.11, min:0.31, theta:-18.0, val:-0.02} dd={cx:-0.22, cy: 0.0, maj:0.16, min:0.41, theta: 18.0, val:-0.02} ee={cx: 0.0, cy: 0.35, maj:0.21, min:0.25, theta: 0.0, val:-0.01} ff={cx: 0.0, cy: 0.1, maj:0.046, min:0.046, theta: 0.0, val:-0.01} gg={cx: 0.0, cy:-0.1, maj:0.046, min:0.046, theta: 0.0, val:-0.01} hh={cx:-0.08, cy:-0.605, maj:0.046, min:0.023, theta: 0.0, val:-0.01} ii={cx: 0.0, cy:-0.605, maj:0.023, min:0.023, theta: 0.0, val:-0.01} jj={cx: 0.06, cy:-0.605, maj:0.023, min:0.046, theta: 0.0, val:-0.01} list = [aa,bb,cc,dd,ee,ff,gg,hh,ii,jj] for n = 0, n_elements(list)-1 do begin tmp = ((xcor-list[n].cx) / list[n].maj)^2 $ + ((ycor-list[n].cy) / list[n].min)^2 if list[n].theta NE 0 then begin nx = (size-1) * (list[n].cx + 1) / 2 ny = (size-1) * (list[n].cy + 1) / 2 tmp = rot(tmp, -list[n].theta, 1, nx, ny, /interp, /pivot) endif phantom[where(tmp LE 1.0)] += list[n].val endfor return, phantom < 1.1 end ; - ;; Enable inline plotting !inline=1 phantom = shepplogan() window, 0, xsize=256, ysize=256 tvscl, phantom > 0.95 ; Now we define simple forward and backprojection functions: ; + function proj, image, angle sino_size_x = max(size(image,/dim)) sino_size_y = n_elements(angle) sino = fltarr(sino_size_x, sino_size_y) for aa=0, n_elements(angle)-1 do begin sino[*,aa] = total(rot(image, angle[aa], /interp), 2) endfor return, sino end ; + function back, sino, angle image_size = n_elements(sino[*,0]) image = fltarr(image_size,image_size) for aa=0, n_elements(angle)-1 do begin image += rot(rebin(sino[*,aa],[image_size,image_size]), -angle[aa], /interp) endfor return, image / n_elements(angle) end ; - ; This allows us to create a sinogram: angles = findgen(360) sino = proj(phantom, angles) window, 0, xsize=256, ysize=360 tvscl, sino ; On this we can apply a simple FBP reconstruction: ; + ;; G.L. Zeng, “Revisit of the Ramp Filter,” ;; IEEE Trans. Nucl. Sci. 62(1), 131–136 (2015). function fbp, sino, angles ntot = n_elements(sino[*,0]) nang = n_elements(sino[0,*]) npos = ntot / 2 + 1 ; integer division needed ! nneg = ntot - npos freq = findgen(ntot) freq[npos:ntot-1] = REVERSE(freq[1:nneg]) freq[0] = 1 filter = -1 / (!pi * freq)^2 filter[where(freq mod 2 EQ 0)] *= -0.0 filter[0] = 0.25 filter = abs(fft(filter)) * ntot filter[ntot/4:ntot/4+ntot/2-1] *= 0.0 filter = rebin(filter,ntot,nang) ;; apply filter to the sinogram fsino = fft(sino, dim=1) fsino *= filter fsino = fft(fsino, dim=1, /overwrite, /inverse) fsino = !pi * real_part(fsino) ;; backproject the filtered sinogram return, back(fsino, angles) end ; + reconstruction = fbp(sino, angles) window, 0, xsize=512, ysize=256 tvscl, [phantom, reconstruction] > 0.8 ; - ; ### The end ================================================ FILE: tests/data/notebooks/outputs/ipynb_to_script/evcxr_jupyter_tour.rs ================================================ // --- // jupyter: // kernelspec: // display_name: Rust // language: rust // name: rust // --- // # Tour of the EvCxR Jupyter Kernel // For those not already familiar with Jupyter notebook, it lets you write code into "cells" like the box below. Cells can alternatively contain markdown, like this text here. Each code cell is compiled and executed separately, but variables, defined functions etc persist between cells. // // ## Printing to outputs and evaluating expressions // Lets print something to stdout and stderr then return a final expression to see how that's presented. Note that stdout and stderr are separate streams, so may not appear in the same order is their respective print statements. println!("Hello world"); eprintln!("Hello error"); format!("Hello {}", "world") // ## Assigning and making use of variables // We define a variable `message`, then in the subsequent cell, modify the string and finally print it out. We could also do all this in the one cell if we wanted. let mut message = "Hello ".to_owned(); message.push_str("world!"); message // ## Defining and redefining functions // Next we'll define a function pub fn fib(x: i32) -> i32 { if x <= 2 {0} else {fib(x - 2) + fib(x - 1)} } (1..13).map(fib).collect::>() // Hmm, that doesn't look right. Lets redefine the function. In practice, we'd go back and edit the function above and reevaluate it, but here, lets redefine it in a separate cell. pub fn fib(x: i32) -> i32 { if x <= 2 {2} else {fib(x - 2) + fib(x - 1)} } let values = (1..13).map(fib).collect::>(); values // ## Spawning a separate thread and communicating with it // We can spawn a thread to do stuff in the background, then continue executing code in other cells. use std::sync::{Mutex, Arc}; let counter = Arc::new(Mutex::new(0i32)); std::thread::spawn({ let counter = Arc::clone(&counter); move || { for i in 1..300 { *counter.lock().unwrap() += 1; std::thread::sleep(std::time::Duration::from_millis(100)); } }}); *counter.lock().unwrap() *counter.lock().unwrap() // ## Loading external crates // We can load external crates. This one takes a while to compile, but once it's compiled, subsequent cells shouldn't need to recompile it, so it should be much quicker. // :dep base64 = "0.10.1" base64::encode(&vec![1, 2, 3, 4]) // ## Customizing how types are displayed // We can also customize how our types are displayed, including presenting them as HTML. Here's an example where we define a custom display function for a type `Matrix`. use std::fmt::Debug; pub struct Matrix {pub values: Vec, pub row_size: usize} impl Matrix { pub fn evcxr_display(&self) { let mut html = String::new(); html.push_str(""); for r in 0..(self.values.len() / self.row_size) { html.push_str(""); for c in 0..self.row_size { html.push_str(""); } html.push_str(""); } html.push_str("
"); html.push_str(&format!("{:?}", self.values[r * self.row_size + c])); html.push_str("
"); println!("EVCXR_BEGIN_CONTENT text/html\n{}\nEVCXR_END_CONTENT", html); } } let m = Matrix {values: vec![1,2,3,4,5,6,7,8,9], row_size: 3}; m // We can also return images, we just need to base64 encode them. First, we set up code for displaying RGB and grayscale images. extern crate image; extern crate base64; pub trait EvcxrResult {fn evcxr_display(&self);} impl EvcxrResult for image::RgbImage { fn evcxr_display(&self) { let mut buffer = Vec::new(); image::png::PNGEncoder::new(&mut buffer).encode(&**self, self.width(), self.height(), image::ColorType::RGB(8)).unwrap(); let img = base64::encode(&buffer); println!("EVCXR_BEGIN_CONTENT image/png\n{}\nEVCXR_END_CONTENT", img); } } impl EvcxrResult for image::GrayImage { fn evcxr_display(&self) { let mut buffer = Vec::new(); image::png::PNGEncoder::new(&mut buffer).encode(&**self, self.width(), self.height(), image::ColorType::Gray(8)).unwrap(); let img = base64::encode(&buffer); println!("EVCXR_BEGIN_CONTENT image/png\n{}\nEVCXR_END_CONTENT", img); } } image::ImageBuffer::from_fn(256, 256, |x, y| { if (x as i32 - y as i32).abs() < 3 { image::Rgb([0, 0, 255]) } else { image::Rgb([0, 0, 0]) } }) // ## Display of compilation errors // Here's how compilation errors are presented. Here we forgot an & and passed a String instead of an &str. let mut s = String::new(); s.push_str(format!("foo {}", 42)); // ## Seeing what variables have been defined // We can print a table of defined variables and their types with the :vars command. // :vars // Other built-in commands can be found via :help // :help ================================================ FILE: tests/data/notebooks/outputs/ipynb_to_script/frozen_cell.py ================================================ # --- # jupyter: # kernelspec: # display_name: Python 3 # language: python # name: python3 # --- # This is an unfrozen cell. Works as usual. print("I'm a regular cell so I run and print!") # + deletable=false editable=false run_control={"frozen": true} # # This is an frozen cell # print("I'm frozen so Im not executed :(") ================================================ FILE: tests/data/notebooks/outputs/ipynb_to_script/fsharp.fsx ================================================ // --- // jupyter: // kernelspec: // display_name: .NET (F#) // language: F# // name: .net-fsharp // --- // This notebook was inspired by [Plottting with XPlot](https://github.com/dotnet/interactive/blob/master/NotebookExamples/fsharp/Docs/Plotting%20with%20Xplot.ipynb). open XPlot.Plotly // + let bar = Bar( name = "Bar 1", x = ["A"; "B"; "C"], y = [1; 3; 2]) [bar] |> Chart.Plot |> Chart.WithTitle "A sample bar plot" ================================================ FILE: tests/data/notebooks/outputs/ipynb_to_script/gnuplot_notebook.gp ================================================ # --- # jupyter: # kernelspec: # display_name: gnuplot # language: gnuplot # name: gnuplot # --- # # Sample gnuplot notebook # ## Simple plotting # + # Plot sin and cos with different linetypes f(x) = sin(x) g(x) = cos(x) set xrange[0:2*pi] set xtics(0, "{/Symbol p}" pi , "2{/Symbol p}" 2*pi) set ytics 1 plot f(x) linewidth 2 title "sin(x)", \ g(x) linewidth 2 dashtype "--" title "cos(x)" # - # ## Example of line magic # + # %gnuplot inline pngcairo enhanced background rgb "#EEEEEE" size 600, 600 # Parametric plot without border reset set parametric set size ratio -1 unset border unset tics plot f(t), g(t) linewidth 2 notitle ================================================ FILE: tests/data/notebooks/outputs/ipynb_to_script/haskell_notebook.hs ================================================ -- --- -- jupyter: -- kernelspec: -- display_name: Haskell -- language: haskell -- name: haskell -- --- -- # Example Haskell Notebook -- Define a function to add two numbers. f :: Num a => a -> a -> a f x y = x + y -- Try to use the function f 1 2 ================================================ FILE: tests/data/notebooks/outputs/ipynb_to_script/hello_world_gonb.go ================================================ // -*- coding: utf-8 -*- // --- // jupyter: // kernelspec: // display_name: Go (gonb) // language: go // name: gonb // --- // A notebook that use [GoNB](https://github.com/janpfeifer/gonb) // the code below comes from [tutorial.ipynb](https://github.com/janpfeifer/gonb/blob/main/examples/tutorial.ipynb) func main() { fmt.Printf("Hello World!") } //gonb:%% fmt.Printf("Hello World!") // //gonb:%% --who=world can pass flags to main func // + import ( "flag" "fmt" ) var flagWho = flag.String("who", "", "Your name!") //gonb:%% --who=world fmt.Printf("Hello %s!\n", *flagWho) // - // // %args also can pass flags // + // %args --who=Wally func main() { flag.Parse() fmt.Printf("Where is %s?", *flagWho) } // + import "github.com/janpfeifer/gonb/gonbui" //gonb:%% gonbui.DisplayHtml(`I 🧡 GoNB!`) // - //gonb:%% gonbui.DisplayMarkdown("#### Objective\n\n1. Have fun coding **Go**;\n1. Profit...\n"+ `$$f(x) = \int_{-\infty}^{\infty} e^{-x^2} dx$$`) func init_a() { fmt.Println("init_a") } //gonb:%% fmt.Println("main") ================================================ FILE: tests/data/notebooks/outputs/ipynb_to_script/html-demo.clj ================================================ ;; --- ;; jupyter: ;; kernelspec: ;; display_name: Clojure ;; language: clojure ;; name: clojure ;; --- ;; # Clojupyter Demo ;; ;; This example notebook is from the [Clojupyter](https://github.com/clojupyter/clojupyter/blob/1637f6b2557f01db1e35bae5389bc38522eefe9a/examples/html-demo.ipynb) project. ;; This notebook demonstrates some of the more advanced features of Clojupyter. ;; ## Displaying HTML ;; ;; To display HTML, you'll need to require a clojupyter helper function to change the cell output (require '[clojupyter.misc.display :as display]) (println ">> should print some text") ;; displaying html (display/hiccup-html [:ul [:li "a " [:i "emphatic"] " idea"] [:li "a " [:b "bold"] " idea"] [:li "an " [:span {:style "text-decoration: underline;"} "important"] " idea"]]) ;; We can also use this to render SVG: (display/hiccup-html [:svg {:height 100 :width 100 :xmlns "http://www.w3.org/2000/svg"} [:circle {:cx 50 :cy 40 :r 40 :fill "red"}]]) ;; ## Adding External Clojure Dependencies ;; ;; You can fetch external Clojure dependencies using the `clojupyter.misc.helper` namespace. (require '[clojupyter.misc.helper :as helper]) (helper/add-dependencies '[org.clojure/data.json "0.2.6"]) (require '[clojure.data.json :as json]) (json/write-str {:a 1 :b [2, 3] :c "c"}) ;; ## Adding External Javascript Dependency ;; ;; Since you can render arbitrary HTML using `display/hiccup-html`, it's pretty easy to use external Javascript libraries to do things like generate charts. Here's an example using [Highcharts](https://www.highcharts.com/). ;; ;; First, we use a cell to add javascript to the running notebook: (helper/add-javascript "https://code.highcharts.com/highcharts.js") ;; Now we define a function which takes Clojure data and returns hiccup HTML to display: (defn plot-highchart [highchart-json] (let [id (str (java.util.UUID/randomUUID)) code (format "Highcharts.chart('%s', %s );" id, (json/write-str highchart-json))] (display/hiccup-html [:div [:div {:id id :style {:background-color "red"}}] [:script code]]))) ;; Now we can make generate interactive plots (try hovering over plot): ;; + (def raw-data (map #(+ (* 22 (+ % (Math/random)) 78)) (range))) (def data-1 (take 500 raw-data)) (def data-2 (take 500 (drop 500 raw-data))) (plot-highchart {:chart {:type "line"} :title {:text "Plot of random data"} :series [{:data data-1} {:data data-2}]}) ;; - ================================================ FILE: tests/data/notebooks/outputs/ipynb_to_script/ijavascript.js ================================================ // --- // jupyter: // kernelspec: // display_name: Javascript (Node.js) // language: javascript // name: javascript // --- // ## A notebook that uses IJavascript kernel let x = 5; const y = 6; var z = 10; x + y; function add(num1, num2) { return num1 + num2 } add(x, y); const arrowAdd = (num1, num2) => num1 + num2; arrowAdd(x, y); const myCar = { color: "blue", weight: 850, model: "fiat", start: () => "car started!", doors: [1,2,3,4] } console.log("color:", myCar.color); console.log("start:", myCar.start()); for (let door of myCar.doors) { console.log("I'm door", door) } myCar; class User { constructor(name){ this.name = name; } sayHello(){ return "Hello, I'm " + this.name; } } let John = new User("John"); John.sayHello(); ================================================ FILE: tests/data/notebooks/outputs/ipynb_to_script/ir_notebook.R ================================================ # --- # jupyter: # kernelspec: # display_name: R # language: R # name: ir # --- # This is a jupyter notebook that uses the IR kernel. sum(1:10) plot(cars) ================================================ FILE: tests/data/notebooks/outputs/ipynb_to_script/ir_notebook.low.r ================================================ # --- # jupyter: # kernelspec: # display_name: R # language: R # name: ir # --- # This is a jupyter notebook that uses the IR kernel. sum(1:10) plot(cars) ================================================ FILE: tests/data/notebooks/outputs/ipynb_to_script/itypescript.ts ================================================ // --- // jupyter: // kernelspec: // display_name: Typescript 3.5 // language: typescript // name: typescript // --- let x: number = 5; const y: number = 6; var z: string = "hi"; console.log(z); x + y; function add(num1: number, num2: number): number { return num1 + num2 } add(x, y); const arrowAdd = (num1: number, num2: number) => num1 + num2; arrowAdd(x, y); class User { constructor(private name: string) { this.name = name; } sayHello(): string { return "Hello, I'm " + this.name; } } let John: User; John = new User("John"); John.sayHello(); ================================================ FILE: tests/data/notebooks/outputs/ipynb_to_script/julia_benchmark_plotly_barchart.jl ================================================ # --- # jupyter: # kernelspec: # display_name: Julia 1.1.1 # language: julia # name: julia-1.1 # --- # + # IJulia rocks! So does Plotly. Check it out using Plotly api_key = "" # visit https://plot.ly/api to generate an API username and password username = "" Plotly.signin(username, api_key) # + # Following data taken from http://julialang.org/ frontpage benchmarks = ["fib", "parse_int", "quicksort3", "mandel", "pi_sum", "rand_mat_stat", "rand_mat_mul"] platforms = ["Fortran", "Julia", "Python", "R", "Matlab", "Mathematica", "Javascript", "Go"] data = { platforms[1] => [0.26, 5.03, 1.11, 0.86, 0.80, 0.64, 0.96], platforms[2] => [0.91, 1.60, 1.14, 0.85, 1.00, 1.66, 1.01], platforms[3] => [30.37, 13.95, 31.98, 14.19, 16.33, 13.52, 3.41 ], platforms[4] => [411.36, 59.40, 524.29, 106.97, 15.42, 10.84, 3.98 ], platforms[5] => [1992.00, 1463.16, 101.84, 64.58, 1.29, 6.61, 1.10 ], platforms[6] => [64.46, 29.54, 35.74, 6.07, 1.32, 4.52, 1.16 ], platforms[7] => [2.18, 2.43, 3.51, 3.49, 0.84, 3.28, 14.60], platforms[8] => [1.03, 4.79, 1.25, 2.36, 1.41, 8.12, 8.51] } pdata = [ {"x"=>benchmarks,"y"=>data[k],"bardir"=>"h","type"=>"bar","name"=>k} for k = platforms ] layout = { "title"=> "Julia benchmark comparison (smaller is better, C performance = 1.0)", "barmode"=> "group", "autosize"=> false, "width"=> 900, "height"=> 900, "titlefont"=> { "family"=> "Open Sans", "size"=> 18, "color"=> "rgb(84, 39, 143)" }, "margin"=> {"l"=>160, "pad"=>0}, "xaxis"=> { "title"=> "Benchmark log-time", "type"=> "log" }, "yaxis"=> {"title"=> "Benchmark Name"} } response = Plotly.plot(pdata,["layout"=>layout]) # Embed in an iframe within IJulia s = string("") display("text/html", s) # + # checkout https://plot.ly/api/ for more Julia examples! # But to show off some other Plotly features: x = 1:1500 y1 = sin(2*pi*x/1500.) + rand(1500)-0.5 y2 = sin(2*pi*x/1500.) fish = {"x"=>x,"y"=> y1, "type"=>"scatter","mode"=>"markers", "marker"=>{"color"=>"rgb(0, 0, 255)","opacity"=>0.5 } } fit = {"x"=> x,"y"=> y2, "type"=>"scatter", "mode"=>"markers", "opacity"=>0.8, "marker"=>{"color"=>"rgb(255, 0, 0)"} } layout = {"autosize"=> false, "width"=> 650, "height"=> 550, "title"=>"Fish School", "xaxis"=>{ "ticks"=> "", "gridcolor"=> "white", "zerolinecolor"=> "white", "linecolor"=> "white", "autorange"=> false, "range"=>[0,1500] }, "yaxis"=>{ "ticks"=> "", "gridcolor"=> "white", "zerolinecolor"=> "white", "linecolor"=> "white", "autorange"=> false, "range"=>[-2.2,2.2] }, "plot_bgcolor"=> "rgb(245,245,247)", "showlegend"=> false, "hovermode"=> "closest"} response = Plotly.plot([fish, fit],["layout"=>layout]) s = string("") display("text/html", s) ================================================ FILE: tests/data/notebooks/outputs/ipynb_to_script/julia_functional_geometry.jl ================================================ # -*- coding: utf-8 -*- # --- # jupyter: # kernelspec: # display_name: Julia 1.1.1 # language: julia # name: julia-1.1 # --- # + # This notebook is a semi top-down explanation. This cell needs to be # executed first so that the operators and helper functions are defined # All of this is explained in the later half of the notebook using Compose, Interact Compose.set_default_graphic_size(2inch, 2inch) points_f = [ (.1, .1), (.9, .1), (.9, .2), (.2, .2), (.2, .4), (.6, .4), (.6, .5), (.2, .5), (.2, .9), (.1, .9), (.1, .1) ] f = compose(context(), stroke("black"), line(points_f)) rot(pic) = compose(context(rotation=Rotation(-deg2rad(90))), pic) flip(pic) = compose(context(mirror=Mirror(deg2rad(90), 0.5w, 0.5h)), pic) above(m, n, p, q) = compose(context(), (context(0, 0, 1, m/(m+n)), p), (context(0, m/(m+n), 1, n/(m+n)), q)) above(p, q) = above(1, 1, p, q) beside(m, n, p, q) = compose(context(), (context(0, 0, m/(m+n), 1), p), (context(m/(m+n), 0, n/(m+n), 1), q)) beside(p, q) = beside(1, 1, p, q) over(p, q) = compose(context(), (context(), p), (context(), q)) rot45(pic) = compose(context(0, 0, 1/sqrt(2), 1/sqrt(2), rotation=Rotation(-deg2rad(45), 0w, 0h)), pic) # Utility function to zoom out and look at the context zoomout(pic) = compose(context(), (context(0.2, 0.2, 0.6, 0.6), pic), (context(0.2, 0.2, 0.6, 0.6), fill(nothing), stroke("black"), strokedash([0.5mm, 0.5mm]), polygon([(0, 0), (1, 0), (1, 1), (0, 1)]))) function read_path(p_str) tokens = [try parsefloat(x) catch symbol(x) end for x in split(p_str, r"[\s,]+")] path(tokens) end fish = compose(context(units=UnitBox(260, 260)), stroke("black"), read_path(strip(readall("fish.path")))) rotatable(pic) = @manipulate for θ=0:0.001:2π compose(context(rotation=Rotation(θ)), pic) end blank = compose(context()) fliprot45(pic) = rot45(compose(context(mirror=Mirror(deg2rad(-45))),pic)) # Hide this cell. display(MIME("text/html"), """""") # - # # Functional Geometry # *Functional Geometry* is a paper by Peter Henderson ([original (1982)](users.ecs.soton.ac.uk/peter/funcgeo.pdf), [revisited (2002)](https://cs.au.dk/~hosc/local/HOSC-15-4-pp349-365.pdf)) which deconstructs the MC Escher woodcut *Square Limit* # # ![Square Limit](http://i.imgur.com/LjRzmNM.png) # > A picture is an example of a complex object that can be described in terms of its parts. # Yet a picture needs to be rendered on a printer or a screen by a device that expects to # be given a sequence of commands. Programming that sequence of commands directly is # much harder than having an application generate the commands automatically from the # simpler, denotational description. # A `picture` is a *denotation* of something to draw. # # e.g. The value of f here denotes the picture of the letter F # Original at http://nbviewer.jupyter.org/github/shashi/ijulia-notebooks/blob/master/funcgeo/Functional%20Geometry.ipynb # ## In conclusion # # We described Escher's *Square Limit* from the description of its smaller parts, which in turn were described in terms of their smaller parts. # # This seemed simple because we chose to talk in terms of an *algebra* to describe pictures. The primitives `rot`, `flip`, `fliprot45`, `above`, `beside` and `over` fit the job perfectly. # # We were able to describe these primitives in terms of `compose` `contexts`, which the Compose library knows how to render. # # Denotation can be an easy way to describe a system as well as a practical implementation method. # # [Abstraction barriers](https://mitpress.mit.edu/sicp/full-text/sicp/book/node29.html) are useful tools that can reduce the cognitive overhead on the programmer. It entails creating layers consisting of functions which only use functions in the same layer or layers below in their own implementation. The layers in our language were: # # ------------------[ squarelimit ]------------------ # -------------[ quartet, cycle, nonet ]------------- # ---[ rot, flip, fliprot45, above, beside, over ]--- # -------[ compose, context, line, path,... ]-------- # # Drawing this diagram out is a useful way to begin building any library. # ================================================ FILE: tests/data/notebooks/outputs/ipynb_to_script/jupyter.py ================================================ # --- # jupyter: # kernelspec: # display_name: Python 3 # language: python # name: python3 # --- # # Jupyter notebook # # This notebook is a simple jupyter notebook. It only has markdown and code cells. And it does not contain consecutive markdown cells. We start with an addition: a = 1 b = 2 a + b # Now we return a few tuples a, b a, b, a+b # And this is already the end of the notebook ================================================ FILE: tests/data/notebooks/outputs/ipynb_to_script/jupyter_again.py ================================================ # --- # jupyter: # kernelspec: # display_name: Python 3 # language: python # name: python3 # --- c = ''' title: "Quick test" output: ioslides_presentation: widescreen: true smaller: true editor_options: chunk_output_type console ''' import yaml print(yaml.dump(yaml.load(c))) # ?next ================================================ FILE: tests/data/notebooks/outputs/ipynb_to_script/jupyter_with_raw_cell_in_body.py ================================================ # --- # jupyter: # kernelspec: # display_name: Python 3 # language: python # name: python3 # --- 1+2+3 # + active="" # This is a raw cell # - # This is a markdown cell ================================================ FILE: tests/data/notebooks/outputs/ipynb_to_script/jupyter_with_raw_cell_on_top.py ================================================ # --- # title: Quick test # output: # ioslides_presentation: # widescreen: true # smaller: true # editor_options: # chunk_output_type: console # jupyter: # kernelspec: # display_name: Python 3 # language: python # name: python3 # --- 1+2+3 ================================================ FILE: tests/data/notebooks/outputs/ipynb_to_script/jupyter_with_raw_cell_with_invalid_yaml.py ================================================ # --- # title: Exception: Test # jupyter: # kernelspec: # display_name: Python 3 (ipykernel) # language: python # name: python3 # --- 1 + 2 + 3 ================================================ FILE: tests/data/notebooks/outputs/ipynb_to_script/jupyterlab-slideshow_1441.py ================================================ # --- # jupyter: # kernelspec: # display_name: Python 3 (ipykernel) # language: python # name: python3 # --- # + [markdown] @deathbeds/jupyterlab-fonts={"styles": {"": {"body[data-jp-deck-mode='presenting'] &": {"right": "0", "top": "30%", "width": "25%", "z-index": 1}}}} jupyterlab-slideshow={"layer": "slide"} # > **Note** # > # > `slide` layer with a `top` of `30%` ================================================ FILE: tests/data/notebooks/outputs/ipynb_to_script/jupytext_replication.sos ================================================ # --- # jupyter: # kernelspec: # display_name: SoS # language: sos # name: sos # --- # + [markdown] Collapsed="false" kernel="SoS" # # Text SOS-kernel with Jupytext # # ## What is SOS kernel # # SoS consists of a ployglot notebook that allows the use of multiple kernels in one Jupyter notebook, and a workflow system that is designed for daily computational research. Basically, # # - SoS Polyglot Notebook is a Jupyter Notebook with a SoS kernel. # - SoS Notebook serves as a super kernel to all other Jupyter kernels and allows the use of multiple kernels in one Jupyter notebook. # - SoS Workflow System is a Python based workflow system that is designed to be readable, shareable, and suitable for daily data analysis. # - SoS Workflow System can be used from command line or use SoS Notebook as its IDE. # # ![](https://vatlab.github.io/sos-docs/doc/media/SoS_Notebook_and_Workflow.png) # # ### How to install SOS-kernel # # Please follow this [link](https://vatlab.github.io/sos-docs/running.html#Conda-installation) to setup SOS # # I run some issue with the latest version of R on my Mac, so I had to install an earlier version of R # # ``` # conda install -c r r=3.5.1 # conda install sos-notebook jupyterlab-sos sos-papermill -c conda-forge # ``` # # ## Related issue with Jupytext # # Jupytext works fine with Python/R kernel but converts code cells into markdown cells when using the SOS kernel. # # cf the image below. It is a code cell. After saving the notebook and restart it, it converted the code cell into markdown # # Screenshot 2020-03-13 at 10 51 18 # + [markdown] Collapsed="false" kernel="SoS" # ## Step 1 # # Please, choose SOS Kernel and then, in the cell code, choose SOS (or any other kernel available), the outcome is the same. # # ![](https://drive.google.com/uc?export=view&id=1OtyxfwoRyVK23XHnmd9JR-crBgHBL5mt) # + Collapsed="false" kernel="SoS" import pandas as pd import numpy as np pd.DataFrame({ 'x': np.random.random(10), 'y': np.random.random(10), }) # + [markdown] Collapsed="false" kernel="python3" # ## Step 2 # # Now, pair it with Jupytex # # ![](https://drive.google.com/uc?export=view&id=1Wtx-YPAXY8HWHqzCcy4iIgHpzt_9emEn) # + [markdown] Collapsed="false" kernel="python3" # ### Step 3 # # Save the notebook, restart and clear all, **save**, then Shut down kernel. Close the notebook and reopen # + [markdown] Collapsed="false" kernel="python3" # ### Step 4 # # Reopen the notebook. Here is the outcome # # ![](https://drive.google.com/uc?export=view&id=12C70unbSPv0gHCZaCICEUy7kO7wM93JH) # # ================================================ FILE: tests/data/notebooks/outputs/ipynb_to_script/kalman_filter_and_visualization.q ================================================ / --- / jupyter: / kernelspec: / display_name: Q 3.5 / language: q / name: qpk / --- plt: .p.import`matplotlib.pyplot / + filter: { t: ([] x: `float $ x; xh: `float $ x; p: (count x) # R: var x); (first t), iterate[R; R]\[first t; 1 _ t] } iterate: {[Q; R; x; y] x[`p]+: Q; k: x[`p] % R + x[`p]; `x`xh`p ! (y[`x]; x[`xh] + k * y[`x] - x[`xh]; (1 - k) * x[`p]) } / - price: 100 + sums 0.5 - (n:50)?1. output:filter price plt[`:plot][til n; output`x; `label pykw "price"]; plt[`:plot][til n; output`xh;`label pykw "forecast"]; plt[`:legend][]; plt[`:show][]; ================================================ FILE: tests/data/notebooks/outputs/ipynb_to_script/logtalk_notebook.lgt ================================================ % --- % jupyter: % kernelspec: % display_name: Logtalk % language: logtalk % name: logtalk_kernel % --- % # An implementation of the Ackermann function % + vscode={"languageId": "logtalk"} %%load ack.lgt :- object(ack). :- info([ version is 1:0:0, author is 'Paulo Moura', date is 2008-3-31, comment is 'Ackermann function (general recursive function).' ]). :- public(ack/3). :- mode(ack(+integer, +integer, -integer), one). :- info(ack/3, [ comment is 'Ackermann function.', argnames is ['M', 'N', 'V'] ]). ack(0, N, V) :- !, V is N + 1. ack(M, 0, V) :- !, M2 is M - 1, ack(M2, 1, V). ack(M, N, V) :- M2 is M - 1, N2 is N - 1, ack(M, N2, V2), ack(M2, V2, V). :- end_object. % - % ## Sample query % + vscode={"languageId": "logtalk"} ack::ack(2, 4, V). ================================================ FILE: tests/data/notebooks/outputs/ipynb_to_script/lua_example.lua ================================================ -- -*- coding: utf-8 -*- -- --- -- jupyter: -- kernelspec: -- display_name: Lua -- language: lua -- name: lua -- --- -- Source: https://www.lua.org/pil/19.3.html -- # Sort -- Another useful function on arrays is table.sort, which we have seen before. It receives the array to be sorted, plus an optional order function. This order function receives two arguments and must return true if the first argument should come first in the sorted array. If this function is not provided, sort uses the default less-than operation (corresponding to the `<´ operator). -- A common mistake is to try to order the indices of a table. In a table, the indices form a set, and have no order whatsoever. If you want to order them, you have to copy them to an array and then sort the array. Let us see an example. Suppose that you read a source file and build a table that gives, for each function name, the line where that function is defined; something like this: lines = { luaH_set = 10, luaH_get = 24, luaH_present = 48, } -- Now you want to print these function names in alphabetical order. If you traverse this table with pairs, the names appear in an arbitrary order. However, you cannot sort them directly, because these names are keys of the table. However, when you put these names into an array, then you can sort them. First, you must create an array with those names, then sort it, and finally print the result: a = {} for n in pairs(lines) do table.insert(a, n) end table.sort(a) for i,n in ipairs(a) do print(n) end -- Note that, for Lua, arrays also have no order. But we know how to count, so we get ordered values as long as we access the array with ordered indices. That is why you should always traverse arrays with ipairs, rather than pairs. The first imposes the key order 1, 2, ..., whereas the latter uses the natural arbitrary order of the table. -- As a more advanced solution, we can write an iterator that traverses a table following the order of its keys. An optional parameter f allows the specification of an alternative order. It first sorts the keys into an array, and then iterates on the array. At each step, it returns the key and value from the original table: function pairsByKeys (t, f) local a = {} for n in pairs(t) do table.insert(a, n) end table.sort(a, f) local i = 0 -- iterator variable local iter = function () -- iterator function i = i + 1 if a[i] == nil then return nil else return a[i], t[a[i]] end end return iter end -- With this function, it is easy to print those function names in alphabetical order. The loop for name, line in pairsByKeys(lines) do print(name, line) end ================================================ FILE: tests/data/notebooks/outputs/ipynb_to_script/maxima_example.mac ================================================ /* --- */ /* jupyter: */ /* kernelspec: */ /* display_name: Maxima */ /* language: maxima */ /* name: maxima */ /* --- */ /* ## maxima misc */ kill(all)$ f(x) := 1/(x^2+l^2)^(3/2); integrate(f(x), x); tex(%)$ ================================================ FILE: tests/data/notebooks/outputs/ipynb_to_script/notebook_with_complex_metadata.py ================================================ # --- # jupyter: # kernelspec: # display_name: Python 3 # language: python # name: python3 # --- ================================================ FILE: tests/data/notebooks/outputs/ipynb_to_script/nteract_with_parameter.py ================================================ # --- # jupyter: # kernel_info: # name: python3 # kernelspec: # display_name: Python 3 # language: python # name: python3 # --- # + inputHidden=false outputHidden=false tags=["parameters"] param = 4 # + inputHidden=false outputHidden=false import pandas as pd # + inputHidden=false outputHidden=false df = pd.DataFrame({'A': [1, 2], 'B': [3 + param, 4]}, index=pd.Index(['x0', 'x1'], name='x')) df # + inputHidden=false outputHidden=false # %matplotlib inline df.plot(kind='bar') ================================================ FILE: tests/data/notebooks/outputs/ipynb_to_script/ocaml_notebook.ml ================================================ (* --- *) (* jupyter: *) (* jupytext: *) (* formats: ipynb:markdown,md *) (* kernelspec: *) (* display_name: OCaml default *) (* language: OCaml *) (* name: ocaml-jupyter *) (* --- *) (* # Example of an OCaml notebook *) let sum x y = x + y (* Let's try our function: *) sum 3 4 = 7 + 0 ================================================ FILE: tests/data/notebooks/outputs/ipynb_to_script/octave_notebook.m ================================================ % --- % jupyter: % kernelspec: % display_name: Octave % language: octave % name: octave % --- % A markdown cell 1 + 1 % a code cell with comments 2 + 2 % a simple plot x = -10:0.1:10; plot (x, sin (x)); %plot -w 800 % a simple plot with a magic instruction x = -10:0.1:10; plot (x, sin (x)); % And to finish with, a Python cell % + language="python" % a = 1 % + language="python" % a + 1 ================================================ FILE: tests/data/notebooks/outputs/ipynb_to_script/plotly_graphs.py ================================================ # --- # jupyter: # kernelspec: # display_name: Python 3 # language: python # name: python3 # --- # This notebook contains complex outputs, including plotly javascript graphs. # # Interactive plots # We use Plotly's connected mode to make the notebook lighter - when connected, the notebook downloads the `plotly.js` library from the web. import plotly.offline as offline offline.init_notebook_mode(connected=True) import plotly.graph_objects as go fig = go.Figure( data=[go.Bar(y=[2, 3, 1])], layout=go.Layout(title="bar plot")) fig.show() fig.data[0].marker = dict(color='purple') fig ================================================ FILE: tests/data/notebooks/outputs/ipynb_to_script/powershell.ps1 ================================================ # --- # jupyter: # kernelspec: # display_name: PowerShell # language: PowerShell # name: powershell # --- # This is an extract from # https://github.com/Jaykul/Jupyter-PowerShell/blob/master/LiterateDevOps.ipynb # + $imageUrl = 'https://upload.wikimedia.org/wikipedia/commons/2/2f/PowerShell_5.0_icon.png' $ImageData = @{ "png" = (Invoke-WebRequest $imageUrl -UseBasicParsing).RawContentStream.GetBuffer() } # $ImageData Write-Jupyter -InputObject $ImageData -Metadata @{ "image/png" = @{ 'width' = 32 } } Write-Jupyter -InputObject $ImageData -Metadata @{ "image/png" = @{ 'width' = 64 } } ================================================ FILE: tests/data/notebooks/outputs/ipynb_to_script/raw_cell_with_complex_yaml_like_content.py ================================================ # --- # # This is a complex paragraph # that is split over multiple lines. # # It also includes blank lines. # # # jupyter: # kernelspec: # display_name: Python 3 # language: python # name: python3 # --- print("Hello, World!") ================================================ FILE: tests/data/notebooks/outputs/ipynb_to_script/raw_cell_with_non_dict_yaml_content.py ================================================ # --- # Content. # jupyter: # kernelspec: # display_name: Python 3 # language: python # name: python3 # --- print("Hello, World!") ================================================ FILE: tests/data/notebooks/outputs/ipynb_to_script/root_cpp.cpp ================================================ // --- // jupyter: // kernelspec: // display_name: ROOT C++ // language: c++ // name: root // --- #include #include int k = 4; std::string foo = "This string says \"foo\""; std::cout << "k = " << k << '\n' << foo << '\n'; ================================================ FILE: tests/data/notebooks/outputs/ipynb_to_script/sage_print_hello.sage ================================================ # --- # jupyter: # kernelspec: # display_name: SageMath 9.2 # language: sage # name: sagemath # --- print("Hello world") ================================================ FILE: tests/data/notebooks/outputs/ipynb_to_script/sample_bash_notebook.sh ================================================ # --- # jupyter: # kernelspec: # display_name: Bash # language: bash # name: bash # --- ls # https://coderwall.com/p/euwpig/a-better-git-log git config --global alias.lg "log --color --graph --pretty=format:'%Cred%h%Creset -%C(yellow)%d%Creset %s %Cgreen(%cr) %C(bold blue)<%an>%Creset' --abbrev-commit" git lg ================================================ FILE: tests/data/notebooks/outputs/ipynb_to_script/sample_rise_notebook_66.py ================================================ # --- # jupyter: # kernelspec: # display_name: Python 3 # language: python # name: python3 # --- # + [markdown] slideshow={"slide_type": "slide"} # A markdown cell # + slideshow={"slide_type": ""} 1+1 # + [markdown] cell_style="center" slideshow={"slide_type": "fragment"} # Markdown cell two ================================================ FILE: tests/data/notebooks/outputs/ipynb_to_script/sas.sas ================================================ /* --- */ /* jupyter: */ /* kernelspec: */ /* display_name: SAS */ /* language: sas */ /* name: sas */ /* --- */ /* # SAS Notebooks with jupytext */ proc sql; select * from sashelp.cars (obs=10) ; quit; %let name = "Jupytext"; %put &name; /* + /* Note when defining macros "%macro" cannot be the first line of text in the cell */ %macro test; data temp; set sashelp.cars; name = "testx"; run; proc print data = temp (obs=10); run; %mend test; %test ================================================ FILE: tests/data/notebooks/outputs/ipynb_to_script/simple-helloworld.java ================================================ // -*- coding: utf-8 -*- // --- // jupyter: // jupytext: // formats: ipynb,java:light // kernelspec: // display_name: Java // language: java // name: java // --- // Let's define some class. class A { public void hello() { System.out.println("Hello World"); } } // And now we call its method. new A().hello(); // You can run it e.g. with `jshell` // // * from command line, as `jshell simple-helloworld.java` // * from jshell's shell with `/open simple-helloworld.java` ================================================ FILE: tests/data/notebooks/outputs/ipynb_to_script/simple_robot_notebook.robot ================================================ # --- # jupyter: # kernelspec: # display_name: Robot Framework # language: robotframework # name: robotkernel # --- # + *** Settings *** Library Collections # + *** Keywords *** Head [Arguments] ${list} ${value}= Get from list ${list} 0 [Return] ${value} # + *** Tasks *** Get head ${array}= Create list 1 2 3 4 5 ${head}= Head ${array} Should be equal ${head} 1 ================================================ FILE: tests/data/notebooks/outputs/ipynb_to_script/simple_scala_notebook.scala ================================================ // --- // jupyter: // kernelspec: // display_name: Apache Toree - Scala // language: scala // name: apache_toree_scala // --- // + // This is just a simple scala notebook object SampleObject { def calculation(x: Int, y: Int): Int = x + y } val result = SampleObject.calculation(1, 2) // - println(result * 10) ================================================ FILE: tests/data/notebooks/outputs/ipynb_to_script/stata_notebook.do ================================================ // --- // jupyter: // kernelspec: // display_name: Stata // language: stata // name: stata // --- // + // This notebook uses the stata_kernel: https://github.com/kylebarron/stata_kernel // - use http://www.stata-press.com/data/r13/auto summarize scatter weight length ================================================ FILE: tests/data/notebooks/outputs/ipynb_to_script/tailrecursive-factorial.groovy ================================================ // -*- coding: utf-8 -*- // --- // jupyter: // jupytext: // formats: ipynb,groovy:light // kernelspec: // display_name: Groovy // language: groovy // name: groovy // --- // # TailRecursive annotation // // Let's check what is the effect of `@TailRecursive` annotation on the simple recursive definition of factorial function. // + import groovy.transform.CompileStatic import groovy.transform.TailRecursive import groovy.transform.TypeChecked @CompileStatic @TypeChecked class X { static final BigInteger factorial0(int n) { (n <= 1) ? 1G : factorial0(n-1).multiply(BigInteger.valueOf(n)) } static final BigInteger factorial1(int n, BigInteger acc = 1G) { (n <= 1) ? acc : factorial1(n-1, acc.multiply(BigInteger.valueOf(n))) } @TailRecursive static final BigInteger factorial2(int n, BigInteger acc = 1G) { (n <= 1) ? acc : factorial2(n-1, acc.multiply(BigInteger.valueOf(n))) } } x = new X() // - // Although we can time the execution of the calls, it is not very accurate; such micro benchmarks should be performed in more controlled environment, such us under [JMH](https://openjdk.java.net/projects/code-tools/jmh/). // // For example, see [blog posts of Szymon Stępniak](https://e.printstacktrace.blog/tail-recursive-methods-in-groovy/). // + // %%timeit x.factorial0(19_000).toString().length() // + // %%timeit x.factorial1(19_000).toString().length() // + // %%timeit x.factorial2(19_000).toString().length() // - // The real difference is the use of stack. Non-tail recursive calls exhaust the stack space at some point, whereas tail recursive calls don't add frames to the stack. // + factSize = { n, cl -> println "Factorial of ${n} has ${cl(n).toString().length()} digits" } factSize 2_000, x.&factorial0 factSize 2_000, x.&factorial1 factSize 2_000, x.&factorial2 factSize 100_000, x.&factorial2 // - try { factSize 100_000, x.&factorial1 } catch (Throwable e) { assert e instanceof StackOverflowError println e } ================================================ FILE: tests/data/notebooks/outputs/ipynb_to_script/tcl_test.tcl ================================================ # --- # jupyter: # kernelspec: # display_name: Tcl # language: tcl # name: tcljupyter # --- # # Assign Values set a 1 puts "a = $a" # # Loop for {set i 0} {$i < 10} {incr i} { puts "I inside first loop: $i" } ================================================ FILE: tests/data/notebooks/outputs/ipynb_to_script/text_outputs_and_images.py ================================================ # --- # jupyter: # kernelspec: # display_name: Python 3 # language: python # name: python3 # --- # This notebook contains outputs of many different types: text, HTML, plots and errors. # # Text outputs # # Using `print`, `sys.stdout` and `sys.stderr` import sys print('using print') sys.stdout.write('using sys.stdout.write') sys.stderr.write('using sys.stderr.write') import logging logging.debug('Debug') logging.info('Info') logging.warning('Warning') logging.error('Error') # # HTML outputs # # Using `pandas`. Here we find two representations: both text and HTML. import pandas as pd pd.DataFrame([4]) from IPython.display import display display(pd.DataFrame([5])) display(pd.DataFrame([6])) # # Images # %matplotlib inline # First plot from matplotlib import pyplot as plt import numpy as np w, h = 3, 3 data = np.zeros((h, w, 3), dtype=np.uint8) data[0,:] = [0,255,0] data[1,:] = [0,0,255] data[2,:] = [0,255,0] data[1:3,1:3] = [255, 0, 0] plt.imshow(data) plt.axis('off') plt.show() # Second plot data[1:3,1:3] = [255, 255, 0] plt.imshow(data) plt.axis('off') plt.show() # # Errors undefined_variable ================================================ FILE: tests/data/notebooks/outputs/ipynb_to_script/wolfram.wolfram ================================================ (* --- *) (* jupyter: *) (* kernelspec: *) (* display_name: Wolfram Language 13.1 *) (* language: Wolfram Language *) (* name: wolframlanguage13.1 *) (* --- *) (* **Note:** The `language_info` `file_extension` in this notebook should be `.m`, but it was deliberately changed to `.wolfram` to avoid conflicts with Matlab which is using the same extension. *) (* We start with... *) Print["Hello, World!"]; (* Then we draw the first example plot from the [ListPlot](https://reference.wolfram.com/language/ref/ListPlot.html) reference: *) ListPlot[Prime[Range[25]]] (* We also test the math outputs as in the [Simplify](https://reference.wolfram.com/language/ref/Simplify.html) example: *) D[Integrate[1/(x^3 + 1), x], x] ================================================ FILE: tests/data/notebooks/outputs/ipynb_to_script/xcpp_by_quantstack.cpp ================================================ // --- // jupyter: // kernelspec: // display_name: C++14 // language: C++14 // name: xeus-cling-cpp14 // --- // [![xeus-cling](images/xeus-cling.png)](https://github.com/QuantStack/xeus-cling/) // // A Jupyter kernel for C++ based on the `cling` C++ interpreter and the `xeus` native implementation of the Jupyter protocol, xeus. // // - GitHub repository: https://github.com/QuantStack/xeus-cling/ // - Online documentation: https://xeus-cling.readthedocs.io/ // ## Usage // //
// // //
// To run the selected code cell, hit 
Shift + Enter
//
//
// ## Output and error streams // // `std::cout` and `std::cerr` are redirected to the notebook frontend. // + #include std::cout << "some output" << std::endl; // - std::cerr << "some error" << std::endl; #include throw std::runtime_error("Unknown exception"); // Omitting the `;` in the last statement of a cell results in an output being printed int j = 5; j // # Interpreting the C++ programming language // // `cling` has a broad support of the features of C++. You can define functions, classes, templates, etc ... // ## Functions double sqr(double a) { return a * a; } double a = 2.5; double asqr = sqr(a); asqr // ## Classes class Foo { public: virtual ~Foo() {} virtual void print(double value) const { std::cout << "Foo value = " << value << std::endl; } }; Foo bar; bar.print(1.2); // ## Polymorphism class Bar : public Foo { public: virtual ~Bar() {} virtual void print(double value) const { std::cout << "Bar value = " << 2 * value << std::endl; } }; Foo* bar2 = new Bar; bar2->print(1.2); delete bar2; // ## Templates // + #include template class FooT { public: explicit FooT(const T& t) : m_t(t) {} void print() const { std::cout << typeid(T).name() << " m_t = " << m_t << std::endl; } private: T m_t; }; template <> class FooT { public: explicit FooT(const int& t) : m_t(t) {} void print() const { std::cout << "m_t = " << m_t << std::endl; } private: int m_t; }; // - FooT foot1(1.2); foot1.print(); FooT foot2(4); foot2.print(); // ## C++11 / C++14 support class Foo11 { public: Foo11() { std::cout << "Foo11 default constructor" << std::endl; } Foo11(const Foo11&) { std::cout << "Foo11 copy constructor" << std::endl; } Foo11(Foo11&&) { std::cout << "Foo11 move constructor" << std::endl; } }; Foo11 f1; Foo11 f2(f1); Foo11 f3(std::move(f1)); // + #include std::vector v = { 1, 2, 3}; auto iter = ++v.begin(); v // - *iter // ... and also lambda, universal references, `decltype`, etc ... // ## Documentation and completion // // - Documentation for types of the standard library is retrieved on cppreference.com. // - The quick-help feature can also be enabled for user-defined types and third-party libraries. More documentation on this feature is available at https://xeus-cling.readthedocs.io/en/latest/inline_help.html. // ?std::vector // ## Using the `display_data` mechanism // For a user-defined type `T`, the rich rendering in the notebook and JupyterLab can be enabled by by implementing the function `xeus::xjson mime_bundle_repr(const T& im)`, which returns the JSON mime bundle for that type. // // More documentation on the rich display system of Jupyter and Xeus-cling is available at https://xeus-cling.readthedocs.io/en/latest/rich_display.html // ### Image example // + #include #include #include "xtl/xbase64.hpp" #include "xeus/xjson.hpp" namespace im { struct image { inline image(const std::string& filename) { std::ifstream fin(filename, std::ios::binary); m_buffer << fin.rdbuf(); } std::stringstream m_buffer; }; xeus::xjson mime_bundle_repr(const image& i) { auto bundle = xeus::xjson::object(); bundle["image/png"] = xtl::base64encode(i.m_buffer.str()); return bundle; } } // - im::image marie("images/marie.png"); marie // ### Audio example // + #include #include #include "xtl/xbase64.hpp" #include "xeus/xjson.hpp" namespace au { struct audio { inline audio(const std::string& filename) { std::ifstream fin(filename, std::ios::binary); m_buffer << fin.rdbuf(); } std::stringstream m_buffer; }; xeus::xjson mime_bundle_repr(const audio& a) { auto bundle = xeus::xjson::object(); bundle["text/html"] = std::string(""; return bundle; } } // - au::audio drums("audio/audio.wav"); drums // ### Display #include "xcpp/xdisplay.hpp" xcpp::display(drums); // ### Update-display // + #include #include "xcpp/xdisplay.hpp" namespace ht { struct html { inline html(const std::string& content) { m_content = content; } std::string m_content; }; xeus::xjson mime_bundle_repr(const html& a) { auto bundle = xeus::xjson::object(); bundle["text/html"] = a.m_content; return bundle; } } // A red rectangle ht::html rect(R"(
Original
)"); // - xcpp::display(rect, "some_display_id"); // + // Update the rectangle to be blue rect.m_content = R"(
Updated
)"; xcpp::display(rect, "some_display_id", true); // - // ## Magics // // Magics are special commands for the kernel that are not part of the C++ language. // // They are defined with the symbol `%` for a line magic and `%%` for a cell magic. // // More documentation for magics is available at https://xeus-cling.readthedocs.io/en/latest/magics.html. #include #include std::vector to_shuffle = {1, 2, 3, 4}; // %timeit std::random_shuffle(to_shuffle.begin(), to_shuffle.end()); // [![xtensor](images/xtensor.png)](https://github.com/QuantStack/xtensor/) // // - GitHub repository: https://github.com/QuantStack/xtensor/ // - Online documentation: https://xtensor.readthedocs.io/ // - NumPy to xtensor cheat sheet: http://xtensor.readthedocs.io/en/latest/numpy.html // // `xtensor` is a C++ library for manipulating N-D arrays with an API very similar to that of numpy. // + #include #include "xtensor/xarray.hpp" #include "xtensor/xio.hpp" #include "xtensor/xview.hpp" xt::xarray arr1 {{1.0, 2.0, 3.0}, {2.0, 5.0, 7.0}, {2.0, 5.0, 7.0}}; xt::xarray arr2 {5.0, 6.0, 7.0}; xt::view(arr1, 1) + arr2 // - // Together with the C++ Jupyter kernel, `xtensor` offers a similar experience as `NumPy` in the Python Jupyter kernel, including broadcasting and universal functions. #include #include "xtensor/xarray.hpp" #include "xtensor/xio.hpp" // + xt::xarray arr {1, 2, 3, 4, 5, 6, 7, 8, 9}; arr.reshape({3, 3}); std::cout << arr; // - #include "xtensor-blas/xlinalg.hpp" xt::xtensor m = {{1.5, 0.5}, {0.7, 1.0}}; std::cout << "Matrix rank: " << std::endl << xt::linalg::matrix_rank(m) << std::endl; std::cout << "Matrix inverse: " << std::endl << xt::linalg::inv(m) << std::endl; std::cout << "Eigen values: " << std::endl << xt::linalg::eigvals(m) << std::endl; // + xt::xarray arg1 = xt::arange(9); xt::xarray arg2 = xt::arange(18); arg1.reshape({3, 3}); arg2.reshape({2, 3, 3}); std::cout << xt::linalg::dot(arg1, arg2) << std::endl; // - ================================================ FILE: tests/data/notebooks/outputs/ipynb_to_script/xonsh_example.xsh ================================================ # --- # jupyter: # kernelspec: # display_name: Xonsh # language: xonsh # name: xonsh # --- len($(curl -L https://xon.sh)) for filename in `.*`: print(filename) du -sh @(filename) ================================================ FILE: tests/data/notebooks/outputs/ipynb_to_script_vim_folding_markers/Line_breaks_in_LateX_305.py ================================================ # --- # jupyter: # jupytext: # cell_markers: '{{{,}}}' # kernelspec: # display_name: Python 3 # language: python # name: python3 # --- # This cell uses no particular cell marker # # $$ # \begin{align} # \dot{x} & = \sigma(y-x)\\ # \dot{y} & = \rho x - y - xz \\ # \dot{z} & = -\beta z + xy # \end{align} # $$ # This cell uses no particular cell marker, and a single slash in the $\LaTeX$ equation # # $$ # \begin{align} # \dot{x} & = \sigma(y-x) \ # \dot{y} & = \rho x - y - xz \ # \dot{z} & = -\beta z + xy # \end{align} # $$ # {{{ [markdown] ''' This cell uses the triple quote cell markers introduced at https://github.com/mwouts/jupytext/issues/305 $$ \begin{align} \dot{x} & = \sigma(y-x)\\ \dot{y} & = \rho x - y - xz \\ \dot{z} & = -\beta z + xy \end{align} $$ ''' # }}} ================================================ FILE: tests/data/notebooks/outputs/ipynb_to_script_vim_folding_markers/Notebook with function and cell metadata 164.py ================================================ # --- # jupyter: # jupytext: # cell_markers: '{{{,}}}' # kernelspec: # display_name: Python 3 # language: python # name: python3 # --- 1 + 1 # A markdown cell # And below, the cell for function f has non trivial cell metadata. And the next cell as well. # {{{ attributes={"classes": [], "id": "", "n": "10"} def f(x): return x # }}} # {{{ attributes={"classes": [], "id": "", "n": "10"} f(5) # }}} # More text 2 + 2 ================================================ FILE: tests/data/notebooks/outputs/ipynb_to_script_vim_folding_markers/Notebook with html and latex cells.py ================================================ # --- # jupyter: # jupytext: # cell_markers: '{{{,}}}' # kernelspec: # display_name: Python 3 # language: python # name: python3 # --- # {{{ language="html" #

Jupytext on GitHub

# }}} # {{{ language="latex" # $\frac{\pi}{2}$ # }}} # %load_ext rpy2.ipython # {{{ language="R" # library(ggplot2) # ggplot(data=data.frame(x=c('A', 'B'), y=c(5, 2)), aes(x,weight=y)) + geom_bar() # }}} # %matplotlib inline import pandas as pd pd.Series({'A':5, 'B':2}).plot(figsize=(3,2), kind='bar') ================================================ FILE: tests/data/notebooks/outputs/ipynb_to_script_vim_folding_markers/Notebook with many hash signs.py ================================================ # --- # jupyter: # jupytext: # cell_markers: '{{{,}}}' # kernelspec: # display_name: Python 3 # language: python # name: python3 # --- # ################################################################## # This is a notebook that contains many hash signs. # Hopefully its python representation is not recognized as a Sphinx Gallery script... # ################################################################## # {{{ some = 1 code = 2 some+code ################################################################## # A comment ################################################################## # Another comment # }}} # ################################################################## # This is a notebook that contains many hash signs. # Hopefully its python representation is not recognized as a Sphinx Gallery script... # ################################################################## ================================================ FILE: tests/data/notebooks/outputs/ipynb_to_script_vim_folding_markers/Notebook with metadata and long cells.py ================================================ # --- # jupyter: # jupytext: # cell_markers: '{{{,}}}' # kernelspec: # display_name: Python 3 # language: python # name: python3 # --- # # Part one - various cells # Here we have a markdown cell # # # with two blank lines # Now we have a markdown cell # with a code block inside it # # ```python # 1 + 1 # ``` # # After that cell we'll have a code cell # {{{ 2 + 2 3 + 3 # }}} # Followed by a raw cell # {{{ active="" # This is # the content # of the raw cell # }}} # # Part two - cell metadata # {{{ [markdown] key="value" # This is a markdown cell with cell metadata `{"key": "value"}` # }}} # {{{ .class tags=["parameters"] """This is a code cell with metadata `{"tags":["parameters"], ".class":null}`""" # }}} # {{{ key="value" active="" # This is a raw cell with cell metadata `{"key": "value"}` # }}} ================================================ FILE: tests/data/notebooks/outputs/ipynb_to_script_vim_folding_markers/Notebook_with_R_magic.py ================================================ # --- # jupyter: # jupytext: # cell_markers: '{{{,}}}' # kernelspec: # display_name: Python 2 # language: python # name: python2 # --- # # A notebook with R cells # # This notebook shows the use of R cells to generate plots # %load_ext rpy2.ipython # {{{ language="R" # suppressMessages(require(tidyverse)) # }}} # {{{ language="R" # ggplot(iris, aes(x = Sepal.Length, y = Petal.Length, color=Species)) + geom_point() # }}} # The default plot dimensions are not good for us, so we use the -w and -h parameters in %%R magic to set the plot size # {{{ magic_args="-w 400 -h 240" language="R" # ggplot(iris, aes(x = Sepal.Length, y = Petal.Length, color=Species)) + geom_point() # }}} ================================================ FILE: tests/data/notebooks/outputs/ipynb_to_script_vim_folding_markers/Notebook_with_more_R_magic_111.py ================================================ # --- # jupyter: # jupytext: # cell_markers: '{{{,}}}' # kernelspec: # display_name: Python 3 # language: python # name: python3 # --- # {{{ # %load_ext rpy2.ipython import pandas as pd df = pd.DataFrame( { "Letter": ["a", "a", "a", "b", "b", "b", "c", "c", "c"], "X": [4, 3, 5, 2, 1, 7, 7, 5, 9], "Y": [0, 4, 3, 6, 7, 10, 11, 9, 13], "Z": [1, 2, 3, 1, 2, 3, 1, 2, 3], } ) # }}} # {{{ magic_args="-i df" language="R" # library("ggplot2") # ggplot(data = df) + geom_point(aes(x = X, y = Y, color = Letter, size = Z)) # }}} ================================================ FILE: tests/data/notebooks/outputs/ipynb_to_script_vim_folding_markers/The flavors of raw cells.py ================================================ # --- # jupyter: # jupytext: # cell_markers: '{{{,}}}' # kernelspec: # display_name: Python 3 # language: python # name: python3 # --- # {{{ raw_mimetype="text/latex" active="" # $1+1$ # }}} # {{{ raw_mimetype="text/restructuredtext" active="" # :math:`1+1` # }}} # {{{ raw_mimetype="text/html" active="" # Bold text # }}} # {{{ raw_mimetype="text/markdown" active="" # **Bold text** # }}} # {{{ raw_mimetype="text/x-python" active="" # 1 + 1 # }}} # {{{ active="" # Not formatted # }}} ================================================ FILE: tests/data/notebooks/outputs/ipynb_to_script_vim_folding_markers/cat_variable.py ================================================ # --- # jupyter: # jupytext: # cell_markers: '{{{,}}}' # kernelspec: # display_name: Python 3 # language: python # name: python3 # --- cat = 42 ================================================ FILE: tests/data/notebooks/outputs/ipynb_to_script_vim_folding_markers/convert_to_py_then_test_with_update83.py ================================================ # --- # jupyter: # jupytext: # cell_markers: '{{{,}}}' # kernelspec: # display_name: Python 3 # language: python # name: python3 # --- # {{{ # %%time print('asdf') # }}} # Thanks for jupytext! ================================================ FILE: tests/data/notebooks/outputs/ipynb_to_script_vim_folding_markers/frozen_cell.py ================================================ # --- # jupyter: # jupytext: # cell_markers: '{{{,}}}' # kernelspec: # display_name: Python 3 # language: python # name: python3 # --- # This is an unfrozen cell. Works as usual. print("I'm a regular cell so I run and print!") # {{{ deletable=false editable=false run_control={"frozen": true} # # This is an frozen cell # print("I'm frozen so Im not executed :(") # }}} ================================================ FILE: tests/data/notebooks/outputs/ipynb_to_script_vim_folding_markers/jupyter.py ================================================ # --- # jupyter: # jupytext: # cell_markers: '{{{,}}}' # kernelspec: # display_name: Python 3 # language: python # name: python3 # --- # # Jupyter notebook # # This notebook is a simple jupyter notebook. It only has markdown and code cells. And it does not contain consecutive markdown cells. We start with an addition: a = 1 b = 2 a + b # Now we return a few tuples a, b a, b, a+b # And this is already the end of the notebook ================================================ FILE: tests/data/notebooks/outputs/ipynb_to_script_vim_folding_markers/jupyter_again.py ================================================ # --- # jupyter: # jupytext: # cell_markers: '{{{,}}}' # kernelspec: # display_name: Python 3 # language: python # name: python3 # --- c = ''' title: "Quick test" output: ioslides_presentation: widescreen: true smaller: true editor_options: chunk_output_type console ''' import yaml print(yaml.dump(yaml.load(c))) # ?next ================================================ FILE: tests/data/notebooks/outputs/ipynb_to_script_vim_folding_markers/jupyter_with_raw_cell_in_body.py ================================================ # --- # jupyter: # jupytext: # cell_markers: '{{{,}}}' # kernelspec: # display_name: Python 3 # language: python # name: python3 # --- 1+2+3 # {{{ active="" # This is a raw cell # }}} # This is a markdown cell ================================================ FILE: tests/data/notebooks/outputs/ipynb_to_script_vim_folding_markers/jupyter_with_raw_cell_on_top.py ================================================ # --- # title: Quick test # output: # ioslides_presentation: # widescreen: true # smaller: true # editor_options: # chunk_output_type: console # jupyter: # jupytext: # cell_markers: '{{{,}}}' # kernelspec: # display_name: Python 3 # language: python # name: python3 # --- 1+2+3 ================================================ FILE: tests/data/notebooks/outputs/ipynb_to_script_vim_folding_markers/jupyter_with_raw_cell_with_invalid_yaml.py ================================================ # --- # title: Exception: Test # jupyter: # jupytext: # cell_markers: '{{{,}}}' # kernelspec: # display_name: Python 3 (ipykernel) # language: python # name: python3 # --- 1 + 2 + 3 ================================================ FILE: tests/data/notebooks/outputs/ipynb_to_script_vim_folding_markers/jupyterlab-slideshow_1441.py ================================================ # --- # jupyter: # jupytext: # cell_markers: '{{{,}}}' # kernelspec: # display_name: Python 3 (ipykernel) # language: python # name: python3 # --- # {{{ [markdown] @deathbeds/jupyterlab-fonts={"styles": {"": {"body[data-jp-deck-mode='presenting'] &": {"right": "0", "top": "30%", "width": "25%", "z-index": 1}}}} jupyterlab-slideshow={"layer": "slide"} # > **Note** # > # > `slide` layer with a `top` of `30%` # }}} ================================================ FILE: tests/data/notebooks/outputs/ipynb_to_script_vim_folding_markers/notebook_with_complex_metadata.py ================================================ # --- # jupyter: # jupytext: # cell_markers: '{{{,}}}' # kernelspec: # display_name: Python 3 # language: python # name: python3 # --- ================================================ FILE: tests/data/notebooks/outputs/ipynb_to_script_vim_folding_markers/nteract_with_parameter.py ================================================ # --- # jupyter: # jupytext: # cell_markers: '{{{,}}}' # kernel_info: # name: python3 # kernelspec: # display_name: Python 3 # language: python # name: python3 # --- # {{{ inputHidden=false outputHidden=false tags=["parameters"] param = 4 # }}} # {{{ inputHidden=false outputHidden=false import pandas as pd # }}} # {{{ inputHidden=false outputHidden=false df = pd.DataFrame({'A': [1, 2], 'B': [3 + param, 4]}, index=pd.Index(['x0', 'x1'], name='x')) df # }}} # {{{ inputHidden=false outputHidden=false # %matplotlib inline df.plot(kind='bar') # }}} ================================================ FILE: tests/data/notebooks/outputs/ipynb_to_script_vim_folding_markers/plotly_graphs.py ================================================ # --- # jupyter: # jupytext: # cell_markers: '{{{,}}}' # kernelspec: # display_name: Python 3 # language: python # name: python3 # --- # This notebook contains complex outputs, including plotly javascript graphs. # # Interactive plots # We use Plotly's connected mode to make the notebook lighter - when connected, the notebook downloads the `plotly.js` library from the web. import plotly.offline as offline offline.init_notebook_mode(connected=True) import plotly.graph_objects as go fig = go.Figure( data=[go.Bar(y=[2, 3, 1])], layout=go.Layout(title="bar plot")) fig.show() fig.data[0].marker = dict(color='purple') fig ================================================ FILE: tests/data/notebooks/outputs/ipynb_to_script_vim_folding_markers/raw_cell_with_complex_yaml_like_content.py ================================================ # --- # # This is a complex paragraph # that is split over multiple lines. # # It also includes blank lines. # # # jupyter: # jupytext: # cell_markers: '{{{,}}}' # kernelspec: # display_name: Python 3 # language: python # name: python3 # --- print("Hello, World!") ================================================ FILE: tests/data/notebooks/outputs/ipynb_to_script_vim_folding_markers/raw_cell_with_non_dict_yaml_content.py ================================================ # --- # Content. # jupyter: # jupytext: # cell_markers: '{{{,}}}' # kernelspec: # display_name: Python 3 # language: python # name: python3 # --- print("Hello, World!") ================================================ FILE: tests/data/notebooks/outputs/ipynb_to_script_vim_folding_markers/sample_rise_notebook_66.py ================================================ # --- # jupyter: # jupytext: # cell_markers: '{{{,}}}' # kernelspec: # display_name: Python 3 # language: python # name: python3 # --- # {{{ [markdown] slideshow={"slide_type": "slide"} # A markdown cell # }}} # {{{ slideshow={"slide_type": ""} 1+1 # }}} # {{{ [markdown] cell_style="center" slideshow={"slide_type": "fragment"} # Markdown cell two # }}} ================================================ FILE: tests/data/notebooks/outputs/ipynb_to_script_vim_folding_markers/text_outputs_and_images.py ================================================ # --- # jupyter: # jupytext: # cell_markers: '{{{,}}}' # kernelspec: # display_name: Python 3 # language: python # name: python3 # --- # This notebook contains outputs of many different types: text, HTML, plots and errors. # # Text outputs # # Using `print`, `sys.stdout` and `sys.stderr` import sys print('using print') sys.stdout.write('using sys.stdout.write') sys.stderr.write('using sys.stderr.write') import logging logging.debug('Debug') logging.info('Info') logging.warning('Warning') logging.error('Error') # # HTML outputs # # Using `pandas`. Here we find two representations: both text and HTML. import pandas as pd pd.DataFrame([4]) from IPython.display import display display(pd.DataFrame([5])) display(pd.DataFrame([6])) # # Images # %matplotlib inline # First plot from matplotlib import pyplot as plt import numpy as np w, h = 3, 3 data = np.zeros((h, w, 3), dtype=np.uint8) data[0,:] = [0,255,0] data[1,:] = [0,0,255] data[2,:] = [0,255,0] data[1:3,1:3] = [255, 0, 0] plt.imshow(data) plt.axis('off') plt.show() # Second plot data[1:3,1:3] = [255, 255, 0] plt.imshow(data) plt.axis('off') plt.show() # # Errors undefined_variable ================================================ FILE: tests/data/notebooks/outputs/ipynb_to_script_vscode_folding_markers/Line_breaks_in_LateX_305.py ================================================ # --- # jupyter: # jupytext: # cell_markers: region,endregion # kernelspec: # display_name: Python 3 # language: python # name: python3 # --- # This cell uses no particular cell marker # # $$ # \begin{align} # \dot{x} & = \sigma(y-x)\\ # \dot{y} & = \rho x - y - xz \\ # \dot{z} & = -\beta z + xy # \end{align} # $$ # This cell uses no particular cell marker, and a single slash in the $\LaTeX$ equation # # $$ # \begin{align} # \dot{x} & = \sigma(y-x) \ # \dot{y} & = \rho x - y - xz \ # \dot{z} & = -\beta z + xy # \end{align} # $$ # region [markdown] ''' This cell uses the triple quote cell markers introduced at https://github.com/mwouts/jupytext/issues/305 $$ \begin{align} \dot{x} & = \sigma(y-x)\\ \dot{y} & = \rho x - y - xz \\ \dot{z} & = -\beta z + xy \end{align} $$ ''' # endregion ================================================ FILE: tests/data/notebooks/outputs/ipynb_to_script_vscode_folding_markers/Notebook with function and cell metadata 164.py ================================================ # --- # jupyter: # jupytext: # cell_markers: region,endregion # kernelspec: # display_name: Python 3 # language: python # name: python3 # --- 1 + 1 # A markdown cell # And below, the cell for function f has non trivial cell metadata. And the next cell as well. # region attributes={"classes": [], "id": "", "n": "10"} def f(x): return x # endregion # region attributes={"classes": [], "id": "", "n": "10"} f(5) # endregion # More text 2 + 2 ================================================ FILE: tests/data/notebooks/outputs/ipynb_to_script_vscode_folding_markers/Notebook with html and latex cells.py ================================================ # --- # jupyter: # jupytext: # cell_markers: region,endregion # kernelspec: # display_name: Python 3 # language: python # name: python3 # --- # region language="html" #

Jupytext on GitHub

# endregion # region language="latex" # $\frac{\pi}{2}$ # endregion # %load_ext rpy2.ipython # region language="R" # library(ggplot2) # ggplot(data=data.frame(x=c('A', 'B'), y=c(5, 2)), aes(x,weight=y)) + geom_bar() # endregion # %matplotlib inline import pandas as pd pd.Series({'A':5, 'B':2}).plot(figsize=(3,2), kind='bar') ================================================ FILE: tests/data/notebooks/outputs/ipynb_to_script_vscode_folding_markers/Notebook with many hash signs.py ================================================ # --- # jupyter: # jupytext: # cell_markers: region,endregion # kernelspec: # display_name: Python 3 # language: python # name: python3 # --- # ################################################################## # This is a notebook that contains many hash signs. # Hopefully its python representation is not recognized as a Sphinx Gallery script... # ################################################################## # region some = 1 code = 2 some+code ################################################################## # A comment ################################################################## # Another comment # endregion # ################################################################## # This is a notebook that contains many hash signs. # Hopefully its python representation is not recognized as a Sphinx Gallery script... # ################################################################## ================================================ FILE: tests/data/notebooks/outputs/ipynb_to_script_vscode_folding_markers/Notebook with metadata and long cells.py ================================================ # --- # jupyter: # jupytext: # cell_markers: region,endregion # kernelspec: # display_name: Python 3 # language: python # name: python3 # --- # # Part one - various cells # Here we have a markdown cell # # # with two blank lines # Now we have a markdown cell # with a code block inside it # # ```python # 1 + 1 # ``` # # After that cell we'll have a code cell # region 2 + 2 3 + 3 # endregion # Followed by a raw cell # region active="" # This is # the content # of the raw cell # endregion # # Part two - cell metadata # region [markdown] key="value" # This is a markdown cell with cell metadata `{"key": "value"}` # endregion # region .class tags=["parameters"] """This is a code cell with metadata `{"tags":["parameters"], ".class":null}`""" # endregion # region key="value" active="" # This is a raw cell with cell metadata `{"key": "value"}` # endregion ================================================ FILE: tests/data/notebooks/outputs/ipynb_to_script_vscode_folding_markers/Notebook_with_R_magic.py ================================================ # --- # jupyter: # jupytext: # cell_markers: region,endregion # kernelspec: # display_name: Python 2 # language: python # name: python2 # --- # # A notebook with R cells # # This notebook shows the use of R cells to generate plots # %load_ext rpy2.ipython # region language="R" # suppressMessages(require(tidyverse)) # endregion # region language="R" # ggplot(iris, aes(x = Sepal.Length, y = Petal.Length, color=Species)) + geom_point() # endregion # The default plot dimensions are not good for us, so we use the -w and -h parameters in %%R magic to set the plot size # region magic_args="-w 400 -h 240" language="R" # ggplot(iris, aes(x = Sepal.Length, y = Petal.Length, color=Species)) + geom_point() # endregion ================================================ FILE: tests/data/notebooks/outputs/ipynb_to_script_vscode_folding_markers/Notebook_with_more_R_magic_111.py ================================================ # --- # jupyter: # jupytext: # cell_markers: region,endregion # kernelspec: # display_name: Python 3 # language: python # name: python3 # --- # region # %load_ext rpy2.ipython import pandas as pd df = pd.DataFrame( { "Letter": ["a", "a", "a", "b", "b", "b", "c", "c", "c"], "X": [4, 3, 5, 2, 1, 7, 7, 5, 9], "Y": [0, 4, 3, 6, 7, 10, 11, 9, 13], "Z": [1, 2, 3, 1, 2, 3, 1, 2, 3], } ) # endregion # region magic_args="-i df" language="R" # library("ggplot2") # ggplot(data = df) + geom_point(aes(x = X, y = Y, color = Letter, size = Z)) # endregion ================================================ FILE: tests/data/notebooks/outputs/ipynb_to_script_vscode_folding_markers/The flavors of raw cells.py ================================================ # --- # jupyter: # jupytext: # cell_markers: region,endregion # kernelspec: # display_name: Python 3 # language: python # name: python3 # --- # region raw_mimetype="text/latex" active="" # $1+1$ # endregion # region raw_mimetype="text/restructuredtext" active="" # :math:`1+1` # endregion # region raw_mimetype="text/html" active="" # Bold text # endregion # region raw_mimetype="text/markdown" active="" # **Bold text** # endregion # region raw_mimetype="text/x-python" active="" # 1 + 1 # endregion # region active="" # Not formatted # endregion ================================================ FILE: tests/data/notebooks/outputs/ipynb_to_script_vscode_folding_markers/cat_variable.py ================================================ # --- # jupyter: # jupytext: # cell_markers: region,endregion # kernelspec: # display_name: Python 3 # language: python # name: python3 # --- cat = 42 ================================================ FILE: tests/data/notebooks/outputs/ipynb_to_script_vscode_folding_markers/convert_to_py_then_test_with_update83.py ================================================ # --- # jupyter: # jupytext: # cell_markers: region,endregion # kernelspec: # display_name: Python 3 # language: python # name: python3 # --- # region # %%time print('asdf') # endregion # Thanks for jupytext! ================================================ FILE: tests/data/notebooks/outputs/ipynb_to_script_vscode_folding_markers/frozen_cell.py ================================================ # --- # jupyter: # jupytext: # cell_markers: region,endregion # kernelspec: # display_name: Python 3 # language: python # name: python3 # --- # This is an unfrozen cell. Works as usual. print("I'm a regular cell so I run and print!") # region deletable=false editable=false run_control={"frozen": true} # # This is an frozen cell # print("I'm frozen so Im not executed :(") # endregion ================================================ FILE: tests/data/notebooks/outputs/ipynb_to_script_vscode_folding_markers/jupyter.py ================================================ # --- # jupyter: # jupytext: # cell_markers: region,endregion # kernelspec: # display_name: Python 3 # language: python # name: python3 # --- # # Jupyter notebook # # This notebook is a simple jupyter notebook. It only has markdown and code cells. And it does not contain consecutive markdown cells. We start with an addition: a = 1 b = 2 a + b # Now we return a few tuples a, b a, b, a+b # And this is already the end of the notebook ================================================ FILE: tests/data/notebooks/outputs/ipynb_to_script_vscode_folding_markers/jupyter_again.py ================================================ # --- # jupyter: # jupytext: # cell_markers: region,endregion # kernelspec: # display_name: Python 3 # language: python # name: python3 # --- c = ''' title: "Quick test" output: ioslides_presentation: widescreen: true smaller: true editor_options: chunk_output_type console ''' import yaml print(yaml.dump(yaml.load(c))) # ?next ================================================ FILE: tests/data/notebooks/outputs/ipynb_to_script_vscode_folding_markers/jupyter_with_raw_cell_in_body.py ================================================ # --- # jupyter: # jupytext: # cell_markers: region,endregion # kernelspec: # display_name: Python 3 # language: python # name: python3 # --- 1+2+3 # region active="" # This is a raw cell # endregion # This is a markdown cell ================================================ FILE: tests/data/notebooks/outputs/ipynb_to_script_vscode_folding_markers/jupyter_with_raw_cell_on_top.py ================================================ # --- # title: Quick test # output: # ioslides_presentation: # widescreen: true # smaller: true # editor_options: # chunk_output_type: console # jupyter: # jupytext: # cell_markers: region,endregion # kernelspec: # display_name: Python 3 # language: python # name: python3 # --- 1+2+3 ================================================ FILE: tests/data/notebooks/outputs/ipynb_to_script_vscode_folding_markers/jupyter_with_raw_cell_with_invalid_yaml.py ================================================ # --- # title: Exception: Test # jupyter: # jupytext: # cell_markers: region,endregion # kernelspec: # display_name: Python 3 (ipykernel) # language: python # name: python3 # --- 1 + 2 + 3 ================================================ FILE: tests/data/notebooks/outputs/ipynb_to_script_vscode_folding_markers/jupyterlab-slideshow_1441.py ================================================ # --- # jupyter: # jupytext: # cell_markers: region,endregion # kernelspec: # display_name: Python 3 (ipykernel) # language: python # name: python3 # --- # region [markdown] @deathbeds/jupyterlab-fonts={"styles": {"": {"body[data-jp-deck-mode='presenting'] &": {"right": "0", "top": "30%", "width": "25%", "z-index": 1}}}} jupyterlab-slideshow={"layer": "slide"} # > **Note** # > # > `slide` layer with a `top` of `30%` # endregion ================================================ FILE: tests/data/notebooks/outputs/ipynb_to_script_vscode_folding_markers/notebook_with_complex_metadata.py ================================================ # --- # jupyter: # jupytext: # cell_markers: region,endregion # kernelspec: # display_name: Python 3 # language: python # name: python3 # --- ================================================ FILE: tests/data/notebooks/outputs/ipynb_to_script_vscode_folding_markers/nteract_with_parameter.py ================================================ # --- # jupyter: # jupytext: # cell_markers: region,endregion # kernel_info: # name: python3 # kernelspec: # display_name: Python 3 # language: python # name: python3 # --- # region inputHidden=false outputHidden=false tags=["parameters"] param = 4 # endregion # region inputHidden=false outputHidden=false import pandas as pd # endregion # region inputHidden=false outputHidden=false df = pd.DataFrame({'A': [1, 2], 'B': [3 + param, 4]}, index=pd.Index(['x0', 'x1'], name='x')) df # endregion # region inputHidden=false outputHidden=false # %matplotlib inline df.plot(kind='bar') # endregion ================================================ FILE: tests/data/notebooks/outputs/ipynb_to_script_vscode_folding_markers/plotly_graphs.py ================================================ # --- # jupyter: # jupytext: # cell_markers: region,endregion # kernelspec: # display_name: Python 3 # language: python # name: python3 # --- # This notebook contains complex outputs, including plotly javascript graphs. # # Interactive plots # We use Plotly's connected mode to make the notebook lighter - when connected, the notebook downloads the `plotly.js` library from the web. import plotly.offline as offline offline.init_notebook_mode(connected=True) import plotly.graph_objects as go fig = go.Figure( data=[go.Bar(y=[2, 3, 1])], layout=go.Layout(title="bar plot")) fig.show() fig.data[0].marker = dict(color='purple') fig ================================================ FILE: tests/data/notebooks/outputs/ipynb_to_script_vscode_folding_markers/raw_cell_with_complex_yaml_like_content.py ================================================ # --- # # This is a complex paragraph # that is split over multiple lines. # # It also includes blank lines. # # # jupyter: # jupytext: # cell_markers: region,endregion # kernelspec: # display_name: Python 3 # language: python # name: python3 # --- print("Hello, World!") ================================================ FILE: tests/data/notebooks/outputs/ipynb_to_script_vscode_folding_markers/raw_cell_with_non_dict_yaml_content.py ================================================ # --- # Content. # jupyter: # jupytext: # cell_markers: region,endregion # kernelspec: # display_name: Python 3 # language: python # name: python3 # --- print("Hello, World!") ================================================ FILE: tests/data/notebooks/outputs/ipynb_to_script_vscode_folding_markers/sample_rise_notebook_66.py ================================================ # --- # jupyter: # jupytext: # cell_markers: region,endregion # kernelspec: # display_name: Python 3 # language: python # name: python3 # --- # region [markdown] slideshow={"slide_type": "slide"} # A markdown cell # endregion # region slideshow={"slide_type": ""} 1+1 # endregion # region [markdown] cell_style="center" slideshow={"slide_type": "fragment"} # Markdown cell two # endregion ================================================ FILE: tests/data/notebooks/outputs/ipynb_to_script_vscode_folding_markers/text_outputs_and_images.py ================================================ # --- # jupyter: # jupytext: # cell_markers: region,endregion # kernelspec: # display_name: Python 3 # language: python # name: python3 # --- # This notebook contains outputs of many different types: text, HTML, plots and errors. # # Text outputs # # Using `print`, `sys.stdout` and `sys.stderr` import sys print('using print') sys.stdout.write('using sys.stdout.write') sys.stderr.write('using sys.stderr.write') import logging logging.debug('Debug') logging.info('Info') logging.warning('Warning') logging.error('Error') # # HTML outputs # # Using `pandas`. Here we find two representations: both text and HTML. import pandas as pd pd.DataFrame([4]) from IPython.display import display display(pd.DataFrame([5])) display(pd.DataFrame([6])) # # Images # %matplotlib inline # First plot from matplotlib import pyplot as plt import numpy as np w, h = 3, 3 data = np.zeros((h, w, 3), dtype=np.uint8) data[0,:] = [0,255,0] data[1,:] = [0,0,255] data[2,:] = [0,255,0] data[1:3,1:3] = [255, 0, 0] plt.imshow(data) plt.axis('off') plt.show() # Second plot data[1:3,1:3] = [255, 255, 0] plt.imshow(data) plt.axis('off') plt.show() # # Errors undefined_variable ================================================ FILE: tests/data/notebooks/outputs/ipynb_to_sphinx/Line_breaks_in_LateX_305.py ================================================ # --- # jupyter: # kernelspec: # display_name: Python 3 # language: python # name: python3 # --- """ This cell uses no particular cell marker $$ \begin{align} \dot{x} & = \sigma(y-x)\\ \dot{y} & = \rho x - y - xz \\ \dot{z} & = -\beta z + xy \end{align} $$ """ ############################################################################### # This cell uses no particular cell marker, and a single slash in the $\LaTeX$ equation # # $$ # \begin{align} # \dot{x} & = \sigma(y-x) \ # \dot{y} & = \rho x - y - xz \ # \dot{z} & = -\beta z + xy # \end{align} # $$ ''' This cell uses the triple quote cell markers introduced at https://github.com/mwouts/jupytext/issues/305 $$ \begin{align} \dot{x} & = \sigma(y-x)\\ \dot{y} & = \rho x - y - xz \\ \dot{z} & = -\beta z + xy \end{align} $$ ''' ================================================ FILE: tests/data/notebooks/outputs/ipynb_to_sphinx/cat_variable.py ================================================ # --- # jupyter: # kernelspec: # display_name: Python 3 # language: python # name: python3 # --- cat = 42 ================================================ FILE: tests/data/notebooks/outputs/ipynb_to_sphinx/convert_to_py_then_test_with_update83.py ================================================ # --- # jupyter: # kernelspec: # display_name: Python 3 # language: python # name: python3 # --- # %%time print('asdf') """ Thanks for jupytext! """ ================================================ FILE: tests/data/notebooks/outputs/ipynb_to_sphinx/jupyter.py ================================================ # --- # jupyter: # kernelspec: # display_name: Python 3 # language: python # name: python3 # --- """ # Jupyter notebook This notebook is a simple jupyter notebook. It only has markdown and code cells. And it does not contain consecutive markdown cells. We start with an addition: """ a = 1 b = 2 a + b ############################################################################### # Now we return a few tuples a, b "" a, b, a+b ############################################################################### # And this is already the end of the notebook ================================================ FILE: tests/data/notebooks/outputs/ipynb_to_sphinx/jupyter_again.py ================================================ # --- # jupyter: # kernelspec: # display_name: Python 3 # language: python # name: python3 # --- c = ''' title: "Quick test" output: ioslides_presentation: widescreen: true smaller: true editor_options: chunk_output_type console ''' "" import yaml print(yaml.dump(yaml.load(c))) "" # ?next ================================================ FILE: tests/data/notebooks/outputs/ipynb_to_sphinx/jupyterlab-slideshow_1441.py ================================================ # --- # jupyter: # kernelspec: # display_name: Python 3 (ipykernel) # language: python # name: python3 # --- """ > **Note** > > `slide` layer with a `top` of `30%` """ ================================================ FILE: tests/data/notebooks/outputs/ipynb_to_sphinx/notebook_with_complex_metadata.py ================================================ # --- # jupyter: # kernelspec: # display_name: Python 3 # language: python # name: python3 # --- ================================================ FILE: tests/data/notebooks/outputs/ipynb_to_sphinx/nteract_with_parameter.py ================================================ # --- # jupyter: # kernel_info: # name: python3 # kernelspec: # display_name: Python 3 # language: python # name: python3 # --- param = 4 "" import pandas as pd "" df = pd.DataFrame({'A': [1, 2], 'B': [3 + param, 4]}, index=pd.Index(['x0', 'x1'], name='x')) df "" # %matplotlib inline df.plot(kind='bar') ================================================ FILE: tests/data/notebooks/outputs/ipynb_to_sphinx/plotly_graphs.py ================================================ # --- # jupyter: # kernelspec: # display_name: Python 3 # language: python # name: python3 # --- """ This notebook contains complex outputs, including plotly javascript graphs. """ ############################################################################### # # Interactive plots ############################################################################### # We use Plotly's connected mode to make the notebook lighter - when connected, the notebook downloads the `plotly.js` library from the web. import plotly.offline as offline offline.init_notebook_mode(connected=True) "" import plotly.graph_objects as go fig = go.Figure( data=[go.Bar(y=[2, 3, 1])], layout=go.Layout(title="bar plot")) fig.show() fig.data[0].marker = dict(color='purple') fig ================================================ FILE: tests/data/notebooks/outputs/ipynb_to_sphinx/sample_rise_notebook_66.py ================================================ # --- # jupyter: # kernelspec: # display_name: Python 3 # language: python # name: python3 # --- """ A markdown cell """ 1+1 ############################################################################### # Markdown cell two ================================================ FILE: tests/data/notebooks/outputs/ipynb_to_sphinx/text_outputs_and_images.py ================================================ # --- # jupyter: # kernelspec: # display_name: Python 3 # language: python # name: python3 # --- """ This notebook contains outputs of many different types: text, HTML, plots and errors. """ ############################################################################### # # Text outputs # # Using `print`, `sys.stdout` and `sys.stderr` import sys print('using print') sys.stdout.write('using sys.stdout.write') sys.stderr.write('using sys.stderr.write') "" import logging logging.debug('Debug') logging.info('Info') logging.warning('Warning') logging.error('Error') ############################################################################### # # HTML outputs # # Using `pandas`. Here we find two representations: both text and HTML. import pandas as pd pd.DataFrame([4]) "" from IPython.display import display display(pd.DataFrame([5])) display(pd.DataFrame([6])) ############################################################################### # # Images # %matplotlib inline "" # First plot from matplotlib import pyplot as plt import numpy as np w, h = 3, 3 data = np.zeros((h, w, 3), dtype=np.uint8) data[0,:] = [0,255,0] data[1,:] = [0,0,255] data[2,:] = [0,255,0] data[1:3,1:3] = [255, 0, 0] plt.imshow(data) plt.axis('off') plt.show() # Second plot data[1:3,1:3] = [255, 255, 0] plt.imshow(data) plt.axis('off') plt.show() ############################################################################### # # Errors undefined_variable ================================================ FILE: tests/data/notebooks/outputs/ipynb_to_spin/R notebook with invalid cell keys.R ================================================ #' --- #' jupyter: #' kernelspec: #' display_name: R #' language: R #' name: ir #' --- #' This notebook was created with IRKernel 0.8.12, and is not completely valid, as the code cell below contains an unexpected 'source' entry. This did cause https://github.com/mwouts/jupytext/issues/234. Note that the problem is solved when one upgrades to IRKernel 1.0.0. library("ggplot2") ggplot(mtcars, aes(mpg)) + stat_ecdf() ================================================ FILE: tests/data/notebooks/outputs/ipynb_to_spin/R notebook with invalid cell keys.low.r ================================================ #' --- #' jupyter: #' kernelspec: #' display_name: R #' language: R #' name: ir #' --- #' This notebook was created with IRKernel 0.8.12, and is not completely valid, as the code cell below contains an unexpected 'source' entry. This did cause https://github.com/mwouts/jupytext/issues/234. Note that the problem is solved when one upgrades to IRKernel 1.0.0. library("ggplot2") ggplot(mtcars, aes(mpg)) + stat_ecdf() ================================================ FILE: tests/data/notebooks/outputs/ipynb_to_spin/ir_notebook.R ================================================ #' --- #' jupyter: #' kernelspec: #' display_name: R #' language: R #' name: ir #' --- #' This is a jupyter notebook that uses the IR kernel. sum(1:10) plot(cars) ================================================ FILE: tests/data/notebooks/outputs/ipynb_to_spin/ir_notebook.low.r ================================================ #' --- #' jupyter: #' kernelspec: #' display_name: R #' language: R #' name: ir #' --- #' This is a jupyter notebook that uses the IR kernel. sum(1:10) plot(cars) ================================================ FILE: tests/data/notebooks/outputs/md_to_ipynb/jupytext_markdown.ipynb ================================================ { "cells": [ { "cell_type": "markdown", "metadata": {}, "source": [ "# Markdown, code and raw cells\n", "\n", "## Markdown cells\n", "\n", "This is a Markdown cell. Markdown cells end with either a code cell, or two consecutive blank lines in the text.\n", "\n", "If you prefer that Markdown headings define new cells, have a look at the `split_at_heading` option.\n", "\n", "Indented code is accepted, and consecutive blank lines there do not break Markdown cells:\n", "\n", " def f(x):\n", " return 1\n", "\n", "\n", " def h(x):\n", " return f(x)+2\n", "\n", "\n", "## Code cells" ] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": [ "\"\"\"This code cell starts with ` ```python`\"\"\"\n", "1 + 1" ] }, { "cell_type": "markdown", "metadata": { "lines_to_next_cell": 0 }, "source": [ "## Raw cells\n", "\n", "Raw cells are delimited with `` and , like here:" ] }, { "cell_type": "raw", "metadata": {}, "source": [ "this is a raw cell" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "# Protected Markdown cells\n", "\n", "If you want to include code blocks (or two consecutive blank lines) in a Markdown cell, use explicit Markdown cell delimiters `` and ``." ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "This Markdown cell has two consecutive blank lines\n", "\n", "\n", "And then a code block which is not a Jupyter code cell:\n", "```python\n", "2 + 2\n", "```" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "# Metadata\n", "\n", "Metadata are supported for all cell types.\n", "\n", "## Markdown cells" ] }, { "cell_type": "markdown", "metadata": { "key": "value", "title": "Region title" }, "source": [ "A cell with a title and additional metadata." ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "## Code cells" ] }, { "cell_type": "code", "execution_count": null, "metadata": { "tags": [ "parameters" ] }, "outputs": [], "source": [ "a = 2" ] } ], "metadata": { "kernelspec": { "display_name": "Python 3", "language": "python", "name": "python3" } }, "nbformat": 4, "nbformat_minor": 2 } ================================================ FILE: tests/data/notebooks/outputs/md_to_ipynb/plain_markdown.ipynb ================================================ { "cells": [ { "cell_type": "raw", "metadata": {}, "source": [ "---\n", "title: A sample document\n", "---" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "This document is a plain Markdown document that was not created from a notebook.\n", "We use this document to test that inputing a Markdown file into Jupytext, and then converting the\n", "resulting notebook to a Markdown file using nbconvert, is the identity\n", "\n", "Another paragraph\n", "\n", "# A header\n", "\n", "Indented code\n", "\n", " def f(x):\n", " return 1\n", "\n", "\n", " def h(x):\n", " return f(x)+2\n", "\n", "\n", "A Python code snippet" ] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": [ "\"\"\"This code cell starts with ` ```python`\"\"\"\n", "1 + 1" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Code snippet without an explicit language\n", "```\n", "echo 'Hello world'\n", "```\n", "\n", "Markdown comments\n", "\n", "\n", "VS Code region markers" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "This Markdown cell has two consecutive blank lines\n", "\n", "\n", "And continues here" ] } ], "metadata": { "jupytext": { "cell_metadata_filter": "-all", "main_language": "python", "notebook_metadata_filter": "-all" } }, "nbformat": 4, "nbformat_minor": 2 } ================================================ FILE: tests/data/notebooks/outputs/myst_to_ipynb/fenced_code_vs_code_cells.ipynb ================================================ { "cells": [ { "cell_type": "markdown", "id": "cell-1", "metadata": {}, "source": [ "# Fenced code\n", "\n", "## No language\n", "\n", "```\n", "# a generic code instruction\n", "1 + 1\n", "```\n", "\n", "## Python\n", "\n", "```python\n", "1 + 1\n", "```\n", "\n", "## Bash\n", "\n", "```python\n", "echo Hi\n", "```\n", "\n", "# Code cells" ] }, { "cell_type": "code", "execution_count": null, "id": "cell-2", "metadata": {}, "outputs": [], "source": [ "# This code gets executed in notebooks\n", "1 + 1" ] } ], "metadata": { "jupytext": { "default_lexer": "ipython3", "notebook_metadata_filter": "-all" } }, "nbformat": 4, "nbformat_minor": 5 } ================================================ FILE: tests/data/notebooks/outputs/myst_to_ipynb/reference_link.ipynb ================================================ { "cells": [ { "cell_type": "markdown", "id": "cell-1", "metadata": {}, "source": [ "This documents contains a code cell to make sure it is recognized as a MyST document." ] }, { "cell_type": "code", "execution_count": null, "id": "cell-2", "metadata": {}, "outputs": [], "source": [ "1 + 1" ] }, { "cell_type": "markdown", "id": "cell-3", "metadata": {}, "source": [ "This is a [reference-link to the issue][].\n", "\n", ":::{note}\n", "This note is key... not sure why.\n", ":::\n", "\n", "[reference-link to the issue]: " ] } ], "metadata": { "jupytext": { "default_lexer": "ipython3", "notebook_metadata_filter": "-all" } }, "nbformat": 4, "nbformat_minor": 5 } ================================================ FILE: tests/data/notebooks/outputs/script_to_ipynb/basic_marimo_example.ipynb ================================================ { "cells": [ { "cell_type": "markdown", "id": "Hbol", "metadata": { "marimo": { "config": { "hide_code": true } } }, "source": [ "This is a simple marimo notebook" ] }, { "cell_type": "code", "execution_count": null, "id": "MJUe", "metadata": {}, "outputs": [], "source": [ "x = 1" ] }, { "cell_type": "code", "execution_count": null, "id": "vblA", "metadata": {}, "outputs": [], "source": [ "y = x+1\n", "y" ] } ], "metadata": {}, "nbformat": 4, "nbformat_minor": 5 } ================================================ FILE: tests/data/notebooks/outputs/script_to_ipynb/build.ipynb ================================================ { "cells": [ { "cell_type": "markdown", "metadata": {}, "source": [ "This file originates from\n", "https://github.com/MicrosoftDocs/PowerShell-Docs/blob/staging/build.ps1" ] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": [ "param(\n", " [switch]$SkipCabs,\n", " [switch]$ShowProgress\n", ")" ] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": [ "# Turning off the progress display, by default\n", "$global:ProgressPreference = 'SilentlyContinue'\n", "if ($ShowProgress) { $ProgressPreference = 'Continue' }" ] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": [ "[Net.ServicePointManager]::SecurityProtocol = [Net.ServicePointManager]::SecurityProtocol -bor [Net.SecurityProtocolType]::Tls12\n", "$tempDir = [System.IO.Path]::GetTempPath()" ] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": [ "# Pandoc source URL\n", "$panDocVersion = \"2.7.3\"\n", "$pandocSourceURL = \"https://github.com/jgm/pandoc/releases/download/$panDocVersion/pandoc-$panDocVersion-windows-x86_64.zip\"" ] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": [ "$pandocDestinationPath = New-Item (Join-Path $tempDir \"pandoc\") -ItemType Directory -Force\n", "$pandocZipPath = Join-Path $pandocDestinationPath \"pandoc-$panDocVersion-windows-x86_64.zip\"\n", "Invoke-WebRequest -Uri $pandocSourceURL -OutFile $pandocZipPath" ] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": [ "Expand-Archive -Path $pandocZipPath -DestinationPath $pandocDestinationPath -Force\n", "$pandocExePath = Join-Path (Join-Path $pandocDestinationPath \"pandoc-$panDocVersion-windows-x86_64\") \"pandoc.exe\"" ] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": [ "# Install ThreadJob if not available\n", "$threadJob = Get-Module ThreadJob -ListAvailable\n", "if ($null -eq $threadjob) {\n", " Install-Module ThreadJob -RequiredVersion 1.1.2 -Scope CurrentUser -Force\n", "}" ] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": [ "# Find the reference folder path w.r.t the script\n", "$ReferenceDocset = Join-Path $PSScriptRoot 'reference'" ] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": [ "# Go through all the directories in the reference folder\n", "$jobs = [System.Collections.Generic.List[object]]::new()\n", "$excludeList = 'module', 'media', 'docs-conceptual', 'mapping', 'bread', '7'\n", "Get-ChildItem $ReferenceDocset -Directory -Exclude $excludeList | ForEach-Object -Process {\n", " $job = Start-ThreadJob -Name $_.Name -ArgumentList @($SkipCabs,$pandocExePath,$PSScriptRoot,$_) -ScriptBlock {\n", " param($SkipCabs, $pandocExePath, $WorkingDirectory, $DocSet)\n", "\n", " $tempDir = [System.IO.Path]::GetTempPath()\n", " $workingDir = Join-Path $tempDir $DocSet.Name\n", " $workingDir = New-Item -ItemType Directory -Path $workingDir -Force\n", " Set-Location $WorkingDir\n", "\n", " function Get-ContentWithoutHeader {\n", " param(\n", " $path\n", " )\n", "\n", " $doc = Get-Content $path -Encoding UTF8\n", " $start = $end = -1\n", "\n", " # search the first 30 lines for the Yaml header\n", " # no yaml header in our docset will ever be that long\n", "\n", " for ($x = 0; $x -lt 30; $x++) {\n", " if ($doc[$x] -eq '---') {\n", " if ($start -eq -1) {\n", " $start = $x\n", " }\n", " else {\n", " if ($end -eq -1) {\n", " $end = $x + 1\n", " break\n", " }\n", " }\n", " }\n", " }\n", " if ($end -gt $start) {\n", " Write-Output ($doc[$end..$($doc.count)] -join \"`r`n\")\n", " }\n", " else {\n", " Write-Output ($doc -join \"`r`n\")\n", " }\n", " }\n", "\n", " $Version = $DocSet.Name\n", " Write-Verbose -Verbose \"Version = $Version\"\n", "\n", " $VersionFolder = $DocSet.FullName\n", " Write-Verbose -Verbose \"VersionFolder = $VersionFolder\"\n", "\n", " # For each of the directories, go through each module folder\n", " Get-ChildItem $VersionFolder -Directory | ForEach-Object -Process {\n", " $ModuleName = $_.Name\n", " Write-Verbose -Verbose \"ModuleName = $ModuleName\"\n", "\n", " $ModulePath = Join-Path $VersionFolder $ModuleName\n", " Write-Verbose -Verbose \"ModulePath = $ModulePath\"\n", "\n", " $LandingPage = Join-Path $ModulePath \"$ModuleName.md\"\n", " Write-Verbose -Verbose \"LandingPage = $LandingPage\"\n", "\n", " $MamlOutputFolder = Join-Path \"$WorkingDirectory\\maml\" \"$Version\\$ModuleName\"\n", " Write-Verbose -Verbose \"MamlOutputFolder = $MamlOutputFolder\"\n", "\n", " $CabOutputFolder = Join-Path \"$WorkingDirectory\\updatablehelp\" \"$Version\\$ModuleName\"\n", " Write-Verbose -Verbose \"CabOutputFolder = $CabOutputFolder\"\n", "\n", " if (-not (Test-Path $MamlOutputFolder)) {\n", " New-Item $MamlOutputFolder -ItemType Directory -Force > $null\n", " }\n", "\n", " # Process the about topics if any\n", " $AboutFolder = Join-Path $ModulePath \"About\"\n", "\n", " if (Test-Path $AboutFolder) {\n", " Write-Verbose -Verbose \"AboutFolder = $AboutFolder\"\n", " Get-ChildItem \"$aboutfolder/about_*.md\" | ForEach-Object {\n", " $aboutFileFullName = $_.FullName\n", " $aboutFileOutputName = \"$($_.BaseName).help.txt\"\n", " $aboutFileOutputFullName = Join-Path $MamlOutputFolder $aboutFileOutputName\n", "\n", " $pandocArgs = @(\n", " \"--from=gfm\",\n", " \"--to=plain+multiline_tables\",\n", " \"--columns=75\",\n", " \"--output=$aboutFileOutputFullName\",\n", " \"--quiet\"\n", " )\n", "\n", " Get-ContentWithoutHeader $aboutFileFullName | & $pandocExePath $pandocArgs\n", " }\n", " }\n", "\n", " try {\n", " # For each module, create a single maml help file\n", " # Adding warningaction=stop to throw errors for all warnings, erroraction=stop to make them terminating errors\n", " New-ExternalHelp -Path $ModulePath -OutputPath $MamlOutputFolder -Force -WarningAction Stop -ErrorAction Stop\n", "\n", " # For each module, create update-help help files (cab and helpinfo.xml files)\n", " if (-not $SkipCabs) {\n", " $cabInfo = New-ExternalHelpCab -CabFilesFolder $MamlOutputFolder -LandingPagePath $LandingPage -OutputFolder $CabOutputFolder\n", "\n", " # Only output the cab fileinfo object\n", " if ($cabInfo.Count -eq 8) { $cabInfo[-1].FullName }\n", " }\n", " }\n", " catch {\n", " Write-Error -Message \"PlatyPS failure: $ModuleName -- $Version\" -Exception $_\n", " }\n", " }\n", "\n", " Remove-Item $workingDir -Force -ErrorAction SilentlyContinue\n", " }\n", " Write-Verbose -Verbose \"Started job for $($_.Name)\"\n", " $jobs += $job\n", "}" ] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": [ "$null = $jobs | Wait-Job" ] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": [ "# Variable to collect any errors in during processing\n", "$allErrors = [System.Collections.Generic.List[string]]::new()\n", "foreach ($job in $jobs) {\n", " Write-Verbose -Verbose \"$($job.Name) output:\"\n", " if ($job.Verbose.Count -gt 0) {\n", " foreach ($verboseMessage in $job.Verbose) {\n", " Write-Verbose -Verbose $verboseMessage\n", " }\n", " }\n", "\n", " if ($job.State -eq \"Failed\") {\n", " $allErrors += \"$($job.Name) failed due to unhandled exception\"\n", " }\n", "\n", " if ($job.Error.Count -gt 0) {\n", " $allErrors += \"$($job.Name) failed with errors:\"\n", " $allErrors += $job.Error.ReadAll()\n", " }\n", "}" ] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": [ "# If the above block, produced any errors, throw and fail the job\n", "if ($allErrors.Count -gt 0) {\n", " $allErrors\n", " throw \"There are errors during platyPS run!`nPlease fix your markdown to comply with the schema: https://github.com/PowerShell/platyPS/blob/master/platyPS.schema.md\"\n", "}" ] } ], "metadata": { "jupytext": { "cell_metadata_filter": "-all", "main_language": "powershell", "notebook_metadata_filter": "-all" } }, "nbformat": 4, "nbformat_minor": 2 } ================================================ FILE: tests/data/notebooks/outputs/script_to_ipynb/hydrogen.ipynb ================================================ { "cells": [ { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": [ "import pandas as pd" ] }, { "cell_type": "code", "execution_count": null, "metadata": { "title": "Display a data frame" }, "outputs": [], "source": [ "df = pd.DataFrame({'A': [1, 2], 'B': [3, 4]},\n", " index=pd.Index(['x0', 'x1'], name='x'))\n", "df" ] }, { "cell_type": "code", "execution_count": null, "metadata": { "tags": [ "parameters" ], "title": "Pandas plot" }, "outputs": [], "source": [ "df.plot(kind='bar')" ] } ], "metadata": { "jupytext": { "cell_metadata_filter": "title,tags,-all", "cell_metadata_json": true, "main_language": "python", "notebook_metadata_filter": "-all" } }, "nbformat": 4, "nbformat_minor": 2 } ================================================ FILE: tests/data/notebooks/outputs/script_to_ipynb/hydrogen_latex_html_R_magics.ipynb ================================================ { "cells": [ { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": [ "1 + 1" ] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": [ "import pandas as pd\n", "pd.Series({'A':5, 'B':2}).plot()" ] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": [ "%matplotlib inline\n", "pd.Series({'A':5, 'B':2}).plot(figsize=(3,2))" ] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": [ "%%html\n", "

Jupytext on GitHub

" ] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": [ "%load_ext rpy2.ipython" ] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": [ "%%R -w 400 -h 200\n", "library(ggplot2)\n", "ggplot(data=data.frame(x=c('A', 'B'), y=c(5, 2)), aes(x,weight=y)) + geom_bar()" ] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": [ "%%latex\n", "$\\frac{\\pi}{2}$" ] } ], "metadata": { "jupytext": { "cell_metadata_filter": "-all", "main_language": "python", "notebook_metadata_filter": "-all" } }, "nbformat": 4, "nbformat_minor": 2 } ================================================ FILE: tests/data/notebooks/outputs/script_to_ipynb/julia_sample_script.ipynb ================================================ { "cells": [ { "cell_type": "markdown", "metadata": {}, "source": [ "From https://juliabyexample.helpmanual.io/" ] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": [ "# function to calculate the volume of a sphere\n", "function sphere_vol(r)\n", " # julia allows Unicode names (in UTF-8 encoding)\n", " # so either \"pi\" or the symbol π can be used\n", " return 4/3*pi*r^3\n", "end" ] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": [ "# functions can also be defined more succinctly\n", "quadratic(a, sqr_term, b) = (-b + sqr_term) / 2a" ] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": [ "# calculates x for 0 = a*x^2+b*x+c, arguments types can be defined in function definitions\n", "function quadratic2(a::Float64, b::Float64, c::Float64)\n", " # unlike other languages 2a is equivalent to 2*a\n", " # a^2 is used instead of a**2 or pow(a,2)\n", " sqr_term = sqrt(b^2-4a*c)\n", " r1 = quadratic(a, sqr_term, b)\n", " r2 = quadratic(a, -sqr_term, b)\n", " # multiple values can be returned from a function using tuples\n", " # if the return keyword is omitted, the last term is returned\n", " r1, r2\n", "end" ] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": [ "vol = sphere_vol(3)\n", "# @printf allows number formatting but does not automatically append the \\n to statements, see below\n", "@printf \"volume = %0.3f\\n\" vol\n", "#> volume = 113.097" ] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": [ "quad1, quad2 = quadratic2(2.0, -2.0, -12.0)\n", "println(\"result 1: \", quad1)\n", "#> result 1: 3.0\n", "println(\"result 2: \", quad2)\n", "#> result 2: -2.0" ] } ], "metadata": { "jupytext": { "cell_metadata_filter": "-all", "encoding": "# -*- coding: utf-8 -*-", "main_language": "julia", "notebook_metadata_filter": "-all" } }, "nbformat": 4, "nbformat_minor": 2 } ================================================ FILE: tests/data/notebooks/outputs/script_to_ipynb/knitr-spin.ipynb ================================================ { "cells": [ { "cell_type": "markdown", "metadata": {}, "source": [ "The below derives from\n", "https://github.com/yihui/knitr/blob/master/inst/examples/knitr-spin.R\n", "\n", "This is a special R script which can be used to generate a report. You can\n", "write normal text in roxygen comments.\n", "\n", "First we set up some options (you do not have to do this):" ] }, { "cell_type": "code", "execution_count": null, "metadata": { "hide_input": true, "hide_output": true, "name": "setup" }, "outputs": [], "source": [ "library(knitr)\n", "opts_chunk$set(fig.path = 'figure/silk-')" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "The report begins here." ] }, { "cell_type": "code", "execution_count": null, "metadata": { "cache": false, "name": "test-a" }, "outputs": [], "source": [ "# boring examples as usual\n", "set.seed(123)\n", "x = rnorm(5)\n", "mean(x)" ] }, { "cell_type": "markdown", "metadata": { "lines_to_next_cell": 0 }, "source": [ "You can not use here the special syntax {{code}} to embed inline expressions, e.g." ] }, { "cell_type": "code", "execution_count": null, "metadata": { "lines_to_next_cell": 0 }, "outputs": [], "source": [ "{{mean(x) + 2}}" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "is the mean of x plus 2.\n", "The code itself may contain braces, but these are not checked. Thus,\n", "perfectly valid (though very strange) R code such as `{{2 + 3}} - {{4 - 5}}`\n", "can lead to errors because `2 + 3}} - {{4 - 5` will be treated as inline code.\n", "\n", "Now we continue writing the report. We can draw plots as well." ] }, { "cell_type": "code", "execution_count": null, "metadata": { "fig.height": 5, "fig.width": 5, "name": "test-b" }, "outputs": [], "source": [ "par(mar = c(4, 4, .1, .1)); plot(x)" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Actually you do not have to write chunk options, in which case knitr will use\n", "default options. For example, the code below has no options attached:" ] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": [ "var(x)\n", "quantile(x)" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "And you can also write two chunks successively like this:" ] }, { "cell_type": "code", "execution_count": null, "metadata": { "lines_to_next_cell": 0, "name": "test-chisq5" }, "outputs": [], "source": [ "sum(x^2) # chi-square distribution with df 5" ] }, { "cell_type": "code", "execution_count": null, "metadata": { "name": "test-chisq4" }, "outputs": [], "source": [ "sum((x - mean(x))^2) # df is 4 now" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Done. Call spin('knitr-spin.R') to make silk from sow's ear now and knit a\n", "lovely purse." ] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": [ "# /* you can write comments between /* and */ like C comments (the preceding #\n", "# is optional)\n", "Sys.sleep(60)\n", "# */" ] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": [ "# /* there is no inline comment; you have to write block comments */" ] } ], "metadata": { "jupytext": { "cell_metadata_filter": "name,hide_input,fig.width,fig.height,cache,hide_output,-all", "main_language": "R", "notebook_metadata_filter": "-all" } }, "nbformat": 4, "nbformat_minor": 2 } ================================================ FILE: tests/data/notebooks/outputs/script_to_ipynb/light_sample.ipynb ================================================ { "cells": [ { "cell_type": "markdown", "metadata": {}, "source": [ "# Sample notebook" ] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": [ "a = 1\n", "b = 2\n", "a + b" ] } ], "metadata": { "jupytext": { "formats": "ipynb,py:light", "main_language": "python" } }, "nbformat": 4, "nbformat_minor": 2 } ================================================ FILE: tests/data/notebooks/outputs/script_to_ipynb/python_notebook_sample.ipynb ================================================ { "cells": [ { "cell_type": "markdown", "metadata": {}, "source": [ "# Specifications for Jupyter notebooks as python scripts" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "## Markdown cells" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Markdown cells are escaped with a single quote. Two consecutive\n", "cells are separated with a blank line." ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "## Code cells" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Python code and adjacent comments are mapped to cell codes." ] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": [ "# For instance, this is a code cell that starts with a\n", "# code comment, where we define a variable\n", "a = 1" ] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": [ "# A cell with another variable\n", "b = 2" ] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": [ "# In this cell we define a function\n", "def f(x):\n", " return x + 1" ] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": [ "# Now simple function calls\n", "c = f(b)\n", "a * b + c" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Line breaks in code cells are supported but then the cell need to have\n", "metadata and an end-of-cell marker. Metadata information in json format,\n", "escaped with '#+' or '# +'" ] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": [ "def g(x):\n", " return x + 2\n", "\n", "\n", "d = 4" ] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": [ "# One more cell\n", "a * b + g(c) + d" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "## Raw cells, and cells active in py or ipynb only" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Raw cells are commented code cells with metadata \"active\": \"\"." ] }, { "cell_type": "raw", "metadata": {}, "source": [ "This is a raw cell" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Actually, using the \"active\" key you can have cells active in Jupyter\n", "and inactive in python scripts" ] }, { "cell_type": "raw", "metadata": { "active": "py" }, "source": [ "1 + 1 # done only in py script, inactive (raw) in ipynb" ] }, { "cell_type": "code", "execution_count": null, "metadata": { "active": "ipynb" }, "outputs": [], "source": [ "2 + 2 # active in ipynb only" ] } ], "metadata": { "jupytext": { "cell_metadata_filter": "active,-all", "cell_metadata_json": true, "main_language": "python", "notebook_metadata_filter": "-all" } }, "nbformat": 4, "nbformat_minor": 2 } ================================================ FILE: tests/data/notebooks/outputs/script_to_ipynb/simple_r_script.ipynb ================================================ { "cells": [ { "cell_type": "markdown", "metadata": {}, "source": [ "This is a comment" ] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": [ "cars" ] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": [ "plot(cars)" ] } ], "metadata": { "jupytext": { "cell_metadata_filter": "-all", "main_language": "R", "notebook_metadata_filter": "-all" } }, "nbformat": 4, "nbformat_minor": 2 } ================================================ FILE: tests/data/notebooks/outputs/sphinx-rst2md_to_ipynb/plot_notebook.ipynb ================================================ { "cells": [ { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": [ "%matplotlib inline" ] }, { "cell_type": "markdown", "metadata": { "cell_marker": "\"\"\"" }, "source": [ "# Notebook styled examples\n", "\n", "The gallery is capable of transforming Python files into reStructuredText files\n", "with a notebook structure. For this to be used you need to respect some syntax\n", "rules.\n", "\n", "It makes a lot of sense to contrast this output rst file with the\n", ":download:`original Python script ` to get better feeling of\n", "the necessary file structure.\n", "\n", "Anything before the Python script docstring is ignored by sphinx-gallery and\n", "will not appear in the rst file, nor will it be executed.\n", "This Python docstring requires an reStructuredText title to name the file and\n", "correctly build the reference links.\n", "\n", "Once you close the docstring you would be writing Python code. This code gets\n", "executed by sphinx gallery shows the plots and attaches the generating code.\n", "Nevertheless you can break your code into blocks and give the rendered file\n", "a notebook style. In this case you have to include a code comment breaker\n", "a line of at least 20 hashes and then every comment start with the a new hash.\n", "\n", "As in this example we start by first writing this module\n", "style docstring, then for the first code block we write the example file author\n", "and script license continued by the import modules instructions.\n", "\n", "Original script from:\n", "https://sphinx-gallery.readthedocs.io/en/latest/tutorials/plot_notebook.html" ] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": [ "# Code source: Óscar Nájera\n", "# License: BSD 3 clause\n", "\n", "import numpy as np\n", "import matplotlib.pyplot as plt" ] }, { "cell_type": "markdown", "metadata": { "cell_marker": "##############################################################################" }, "source": [ "This code block is executed, although it produces no output. Lines starting\n", "with a simple hash are code comment and get treated as part of the code\n", "block. To include this new comment string we started the new block with a\n", "long line of hashes.\n", "\n", "The sphinx-gallery parser will assume everything after this splitter and that\n", "continues to start with a **comment hash and space** (respecting code style)\n", "is text that has to be rendered in\n", "html format. Keep in mind to always keep your comments always together by\n", "comment hashes. That means to break a paragraph you still need to comment\n", "that line break.\n", "\n", "In this example the next block of code produces some plotable data. Code is\n", "executed, figure is saved and then code is presented next, followed by the\n", "inlined figure." ] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": [ "x = np.linspace(-np.pi, np.pi, 300)\n", "xx, yy = np.meshgrid(x, x)\n", "z = np.cos(xx) + np.cos(yy)\n", "\n", "plt.figure()\n", "plt.imshow(z)\n", "plt.colorbar()\n", "plt.xlabel('$x$')\n", "plt.ylabel('$y$')" ] }, { "cell_type": "markdown", "metadata": { "cell_marker": "###########################################################################" }, "source": [ "Again it is possible to continue the discussion with a new Python string. This\n", "time to introduce the next code block generates 2 separate figures." ] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": [ "plt.figure()\n", "plt.imshow(z, cmap=plt.cm.get_cmap('hot'))\n", "plt.figure()\n", "plt.imshow(z, cmap=plt.cm.get_cmap('Spectral'), interpolation='none')" ] }, { "cell_type": "markdown", "metadata": { "cell_marker": "##########################################################################" }, "source": [ "There's some subtle differences between rendered html rendered comment\n", "strings and code comment strings which I'll demonstrate below. (Some of this\n", "only makes sense if you look at the\n", ":download:`raw Python script `)\n", "\n", "Comments in comment blocks remain nested in the text." ] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": [ "\n", "def dummy():\n", " \"\"\"Dummy function to make sure docstrings don't get rendered as text\"\"\"\n", " pass\n", "\n", "# Code comments not preceded by the hash splitter are left in code blocks.\n", "\n", "string = \"\"\"\n", "Triple-quoted string which tries to break parser but doesn't.\n", "\"\"\"" ] }, { "cell_type": "markdown", "metadata": { "cell_marker": "############################################################################" }, "source": [ "Output of the script is captured:" ] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": [ "print('Some output from Python')" ] }, { "cell_type": "markdown", "metadata": { "cell_marker": "############################################################################" }, "source": [ "Finally, I'll call ``show`` at the end just so someone running the Python\n", "code directly will see the plots; this is not necessary for creating the docs" ] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": [ "plt.show()" ] }, { "cell_type": "markdown", "metadata": { "cell_marker": "############################################################################" }, "source": [ "You can also include $math$ inline, or as separate equations:\n", "\n", "\\begin{align}\\exp(j\\pi) = -1\\end{align}\n", "\n", "You can also insert images:\n", "\n", "\"Sphinx" ] } ], "metadata": { "jupytext": { "cell_metadata_filter": "-all", "encoding": "# -*- coding: utf-8 -*-", "main_language": "python", "notebook_metadata_filter": "-all", "rst2md": false } }, "nbformat": 4, "nbformat_minor": 2 } ================================================ FILE: tests/data/notebooks/outputs/sphinx_to_ipynb/plot_notebook.ipynb ================================================ { "cells": [ { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": [ "%matplotlib inline" ] }, { "cell_type": "markdown", "metadata": { "cell_marker": "\"\"\"" }, "source": [ "Notebook styled examples\n", "========================\n", "\n", "The gallery is capable of transforming Python files into reStructuredText files\n", "with a notebook structure. For this to be used you need to respect some syntax\n", "rules.\n", "\n", "It makes a lot of sense to contrast this output rst file with the\n", ":download:`original Python script ` to get better feeling of\n", "the necessary file structure.\n", "\n", "Anything before the Python script docstring is ignored by sphinx-gallery and\n", "will not appear in the rst file, nor will it be executed.\n", "This Python docstring requires an reStructuredText title to name the file and\n", "correctly build the reference links.\n", "\n", "Once you close the docstring you would be writing Python code. This code gets\n", "executed by sphinx gallery shows the plots and attaches the generating code.\n", "Nevertheless you can break your code into blocks and give the rendered file\n", "a notebook style. In this case you have to include a code comment breaker\n", "a line of at least 20 hashes and then every comment start with the a new hash.\n", "\n", "As in this example we start by first writing this module\n", "style docstring, then for the first code block we write the example file author\n", "and script license continued by the import modules instructions.\n", "\n", "Original script from:\n", "https://sphinx-gallery.readthedocs.io/en/latest/tutorials/plot_notebook.html" ] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": [ "# Code source: Óscar Nájera\n", "# License: BSD 3 clause\n", "\n", "import numpy as np\n", "import matplotlib.pyplot as plt" ] }, { "cell_type": "markdown", "metadata": { "cell_marker": "##############################################################################" }, "source": [ "This code block is executed, although it produces no output. Lines starting\n", "with a simple hash are code comment and get treated as part of the code\n", "block. To include this new comment string we started the new block with a\n", "long line of hashes.\n", "\n", "The sphinx-gallery parser will assume everything after this splitter and that\n", "continues to start with a **comment hash and space** (respecting code style)\n", "is text that has to be rendered in\n", "html format. Keep in mind to always keep your comments always together by\n", "comment hashes. That means to break a paragraph you still need to comment\n", "that line break.\n", "\n", "In this example the next block of code produces some plotable data. Code is\n", "executed, figure is saved and then code is presented next, followed by the\n", "inlined figure." ] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": [ "x = np.linspace(-np.pi, np.pi, 300)\n", "xx, yy = np.meshgrid(x, x)\n", "z = np.cos(xx) + np.cos(yy)\n", "\n", "plt.figure()\n", "plt.imshow(z)\n", "plt.colorbar()\n", "plt.xlabel('$x$')\n", "plt.ylabel('$y$')" ] }, { "cell_type": "markdown", "metadata": { "cell_marker": "###########################################################################" }, "source": [ "Again it is possible to continue the discussion with a new Python string. This\n", "time to introduce the next code block generates 2 separate figures." ] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": [ "plt.figure()\n", "plt.imshow(z, cmap=plt.cm.get_cmap('hot'))\n", "plt.figure()\n", "plt.imshow(z, cmap=plt.cm.get_cmap('Spectral'), interpolation='none')" ] }, { "cell_type": "markdown", "metadata": { "cell_marker": "##########################################################################" }, "source": [ "There's some subtle differences between rendered html rendered comment\n", "strings and code comment strings which I'll demonstrate below. (Some of this\n", "only makes sense if you look at the\n", ":download:`raw Python script `)\n", "\n", "Comments in comment blocks remain nested in the text." ] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": [ "\n", "def dummy():\n", " \"\"\"Dummy function to make sure docstrings don't get rendered as text\"\"\"\n", " pass\n", "\n", "# Code comments not preceded by the hash splitter are left in code blocks.\n", "\n", "string = \"\"\"\n", "Triple-quoted string which tries to break parser but doesn't.\n", "\"\"\"" ] }, { "cell_type": "markdown", "metadata": { "cell_marker": "############################################################################" }, "source": [ "Output of the script is captured:" ] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": [ "print('Some output from Python')" ] }, { "cell_type": "markdown", "metadata": { "cell_marker": "############################################################################" }, "source": [ "Finally, I'll call ``show`` at the end just so someone running the Python\n", "code directly will see the plots; this is not necessary for creating the docs" ] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": [ "plt.show()" ] }, { "cell_type": "markdown", "metadata": { "cell_marker": "############################################################################" }, "source": [ "You can also include :math:`math` inline, or as separate equations:\n", "\n", ".. math::\n", "\n", " \\exp(j\\pi) = -1\n", "\n", "You can also insert images:\n", "\n", ".. image:: http://www.sphinx-doc.org/en/stable/_static/sphinxheader.png\n", " :alt: Sphinx header\n" ] } ], "metadata": { "jupytext": { "cell_metadata_filter": "-all", "encoding": "# -*- coding: utf-8 -*-", "main_language": "python", "notebook_metadata_filter": "-all" } }, "nbformat": 4, "nbformat_minor": 2 } ================================================ FILE: tests/external/cli/test_black.py ================================================ import os from copy import deepcopy from shutil import copyfile import pytest from nbformat.v4.nbbase import new_code_cell, new_notebook from jupytext import read, write from jupytext.cli import jupytext, pipe_notebook, system from jupytext.combine import black_invariant from jupytext.compare import compare, compare_cells, compare_notebooks from jupytext.header import _DEFAULT_NOTEBOOK_METADATA @pytest.mark.requires_black def test_apply_black_on_python_notebooks(tmpdir, cwd_tmpdir, ipynb_py_file): if "cell metadata" in ipynb_py_file: pytest.skip() copyfile(ipynb_py_file, "notebook.ipynb") jupytext(args=["notebook.ipynb", "--to", "py:percent"]) system("black", "notebook.py") jupytext(args=["notebook.py", "--to", "ipynb", "--update"]) nb1 = read(ipynb_py_file) nb2 = read("notebook.ipynb") nb3 = read("notebook.py") assert len(nb1.cells) == len(nb2.cells) assert len(nb1.cells) == len(nb3.cells) for c1, c2 in zip(nb1.cells, nb2.cells): # same content (almost) assert black_invariant(c1.source) == black_invariant(c2.source) # python representation is pep8 assert "lines_to_next_cell" not in c2.metadata # outputs are preserved assert c1.cell_type == c2.cell_type if c1.cell_type == "code": compare(c1.outputs, c2.outputs) compare(nb1.metadata, nb2.metadata) def test_black_invariant(): text_org = """long_string = "aaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaa" \\ "bbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbb" """ text_black = """long_string = ( "aaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaa" "bbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbb" ) """ assert black_invariant(text_org) == black_invariant(text_black) @pytest.mark.requires_black def test_pipe_into_black(): nb_org = new_notebook(cells=[new_code_cell("1 +1", id="cell-id")]) nb_dest = new_notebook(cells=[new_code_cell("1 + 1", id="cell-id")]) nb_pipe = pipe_notebook(nb_org, "black") compare_notebooks(nb_pipe, nb_dest, allow_expected_differences=False, compare_ids=True) @pytest.mark.requires_autopep8 def test_pipe_into_autopep8(): nb_org = new_notebook(cells=[new_code_cell("1 +1", id="cell-id")]) nb_dest = new_notebook(cells=[new_code_cell("1 + 1", id="cell-id")]) nb_pipe = pipe_notebook(nb_org, "autopep8 -") compare_notebooks(nb_pipe, nb_dest, allow_expected_differences=False, compare_ids=True) @pytest.mark.requires_flake8 def test_pipe_into_flake8(): # Notebook OK nb = new_notebook(cells=[new_code_cell("# correct code\n1 + 1")]) pipe_notebook(nb, "flake8", update=False) # Notebook not OK nb = new_notebook(cells=[new_code_cell("incorrect code")]) with pytest.raises(SystemExit): pipe_notebook(nb, "flake8", update=False) @pytest.mark.requires_black @pytest.mark.requires_flake8 def test_apply_black_through_jupytext(tmpdir, python_notebook): # Load real notebook metadata to get the 'auto' extension in --pipe-fmt to work metadata = python_notebook.metadata nb_org = new_notebook(cells=[new_code_cell("1 +1", id="cell-id")], metadata=metadata) nb_black = new_notebook(cells=[new_code_cell("1 + 1", id="cell-id")], metadata=metadata) tmp_ipynb = str(tmpdir.mkdir("notebook_folder").join("notebook.ipynb")) tmp_py = str(tmpdir.mkdir("script_folder").join("notebook.py")) # Black in place write(nb_org, tmp_ipynb) jupytext([tmp_ipynb, "--pipe", "black"]) nb_now = read(tmp_ipynb) compare_notebooks(nb_now, nb_black, compare_ids=True) # Write to another folder using dots write(nb_org, tmp_ipynb) jupytext([tmp_ipynb, "--to", "../script_folder//py:percent", "--pipe", "black"]) assert os.path.isfile(tmp_py) nb_now = read(tmp_py) nb_now.metadata = metadata compare_notebooks(nb_now, nb_black) os.remove(tmp_py) # Map to another folder based on file name write(nb_org, tmp_ipynb) jupytext( [ tmp_ipynb, "--from", "notebook_folder//ipynb", "--to", "script_folder//py:percent", "--pipe", "black", "--check", "flake8", ] ) assert os.path.isfile(tmp_py) nb_now = read(tmp_py) nb_now.metadata = metadata compare_notebooks(nb_now, nb_black) @pytest.mark.requires_black def test_apply_black_and_sync_on_paired_notebook(tmpdir, cwd_tmpdir, python_notebook): # Load real notebook metadata to get the 'auto' extension in --pipe-fmt to work metadata = python_notebook.metadata metadata["jupytext"] = {"formats": "ipynb,py"} assert "language_info" in metadata nb_org = new_notebook(cells=[new_code_cell("1 +1", id="cell-id")], metadata=metadata) nb_black = new_notebook(cells=[new_code_cell("1 + 1", id="cell-id")], metadata=metadata) # Black in place write(nb_org, "notebook.ipynb") jupytext(["notebook.ipynb", "--pipe", "black", "--sync"]) nb_now = read("notebook.ipynb") compare_notebooks(nb_now, nb_black, compare_ids=True) assert "language_info" in nb_now.metadata nb_now = read("notebook.py") nb_now.metadata["jupytext"].pop("text_representation") nb_black.metadata = { key: nb_black.metadata[key] for key in nb_black.metadata if key in _DEFAULT_NOTEBOOK_METADATA.split(",") } compare_notebooks(nb_now, nb_black) @pytest.mark.requires_black def test_apply_black_on_markdown_notebook(tmpdir): text = """--- jupyter: kernelspec: display_name: Python 3 language: python name: python3 language_info: codemirror_mode: name: ipython version: 3 file_extension: .py mimetype: text/x-python name: python nbconvert_exporter: python pygments_lexer: ipython3 version: 3.7.4 --- ```python 1 + \ 2+3\ +4 ``` """ tmp_md = str(tmpdir.join("test.md")) with open(tmp_md, "w") as fp: fp.write(text) jupytext([tmp_md, "--pipe", "black"]) nb = read(tmp_md) compare_cells(nb.cells, [new_code_cell("1 + 2 + 3 + 4")], compare_ids=False) @pytest.mark.requires_black def test_black_through_tempfile( tmpdir, text="""```python 1 + 2 \ + 3 ``` """, black="""```python 1 + 2 + 3 ``` """, ): tmp_md = str(tmpdir.join("notebook.md")) with open(tmp_md, "w") as fp: fp.write(text) jupytext([tmp_md, "--pipe", "black {}"]) with open(tmp_md) as fp: compare(fp.read(), black) @pytest.mark.requires_black def test_pipe_black_removes_lines_to_next_cell_metadata( tmpdir, cwd_tmpdir, text="""# %% def func(): return 42 # %% func()""", ): tmpdir.join("notebook.py").write(text) jupytext(["--set-formats", "ipynb,py:percent", "notebook.py"]) nb = read(tmpdir.join("notebook.ipynb")) assert nb.cells[0].metadata["lines_to_next_cell"] == 0 jupytext(["--sync", "notebook.py", "--pipe", "black"]) nb = read(tmpdir.join("notebook.ipynb")) assert "lines_to_next_cell" not in nb.cells[0].metadata new_text = tmpdir.join("notebook.py").read() assert "\n\n# %%\nfunc()" in new_text @pytest.mark.requires_black @pytest.mark.parametrize( "code,black_should_fail", [("myvar = %dont_format_me", False), ("incomplete_instruction = (...", True)], ) def test_pipe_black_uses_warn_only_781(tmpdir, cwd_tmpdir, code, black_should_fail, python_notebook, capsys): nb = python_notebook nb.cells.append(new_code_cell(code)) write(nb, "notebook.ipynb") if not black_should_fail: jupytext(["--pipe", "black", "notebook.ipynb"]) return with pytest.raises(SystemExit): jupytext(["--pipe", "black", "notebook.ipynb"]) out, err = capsys.readouterr() assert "Error: The command 'black -' exited with code" in err assert "--warn-only" in err # With warn-only we just get a warning jupytext(["--pipe", "black", "notebook.ipynb", "--warn-only"]) out, err = capsys.readouterr() assert "Warning: The command 'black -' exited with code" in err # If black fails the notebook should be left unchanged actual = read("notebook.ipynb") compare_notebooks(actual, nb) @pytest.mark.requires_black def test_pipe_black_preserve_outputs(notebook_with_outputs, tmpdir, cwd_tmpdir, capsys): write(notebook_with_outputs, "test.ipynb") jupytext(["--pipe", "black", "test.ipynb"]) # Outputs are preserved nb = read("test.ipynb") expected = deepcopy(notebook_with_outputs) expected.cells[0].source = "1 + 1" compare_notebooks(nb, expected) # No mention of --update out, err = capsys.readouterr() assert not err assert "replaced" not in out assert "--update" not in out ================================================ FILE: tests/external/cli/test_cli_check.py ================================================ import pytest from nbformat.v4.nbbase import new_code_cell, new_notebook from jupytext import write from jupytext.cli import jupytext @pytest.fixture def non_black_notebook(python_notebook): return new_notebook(metadata=python_notebook.metadata, cells=[new_code_cell("1+1")]) @pytest.mark.requires_black def test_check_notebooks_left_or_right_black(python_notebook, tmpdir, cwd_tmpdir): write(python_notebook, str(tmpdir / "nb1.ipynb")) write(python_notebook, str(tmpdir / "nb2.ipynb")) jupytext(["*.ipynb", "--check", "black --check {}"]) jupytext(["--check", "black --check {}", "*.ipynb"]) @pytest.mark.requires_black def test_check_notebooks_left_or_right_not_black(non_black_notebook, tmpdir, cwd_tmpdir): write(non_black_notebook, str(tmpdir / "nb1.ipynb")) write(non_black_notebook, str(tmpdir / "nb2.ipynb")) with pytest.raises(SystemExit): jupytext(["*.ipynb", "--check", "black --check {}"]) with pytest.raises(SystemExit): jupytext(["--check", "black --check {}", "*.ipynb"]) ================================================ FILE: tests/external/cli/test_isort.py ================================================ import pytest from jupytext import reads, writes from jupytext.cli import pipe_notebook from jupytext.compare import compare @pytest.mark.requires_isort def test_pipe_into_isort(): text_org = """# %% import numpy as np np.array([1,2,3]) # %% import pandas as pd pd.Series([1,2,3]) # %% # This is a comment on the second import import pandas as pd pd.Series([4,5,6]) """ text_target = """# %% import numpy as np # This is a comment on the second import import pandas as pd np.array([1,2,3]) # %% pd.Series([1,2,3]) # %% pd.Series([4,5,6]) """ nb_org = reads(text_org, fmt="py:percent") nb_pipe = pipe_notebook(nb_org, 'isort - --treat-comment-as-code "# %%" --float-to-top') text_actual = writes(nb_pipe, "py:percent") compare(text_actual, text_target) ================================================ FILE: tests/external/conftest.py ================================================ import pytest from git import Repo @pytest.fixture def tmp_repo(tmpdir): repo = Repo.init(str(tmpdir)) return repo ================================================ FILE: tests/external/contents_manager/test_contentsmanager_external.py ================================================ import re import pytest from jupyter_server.utils import ensure_async import jupytext from jupytext.compare import compare_notebooks, notebook_model pytestmark = pytest.mark.asyncio @pytest.mark.requires_pandoc async def test_save_load_paired_md_pandoc_notebook(ipynb_py_R_jl_file, tmpdir, cm): if re.match(r".*(functional|Notebook with|flavors|invalid|305|jupyterlab-slideshow).*", ipynb_py_R_jl_file): pytest.skip() tmp_ipynb = "notebook.ipynb" tmp_md = "notebook.md" cm.root_dir = str(tmpdir) # open ipynb, save with cm, reopen nb = jupytext.read(ipynb_py_R_jl_file) nb.metadata["jupytext"] = {"formats": "ipynb,md:pandoc"} await ensure_async(cm.save(model=notebook_model(nb), path=tmp_ipynb)) nb_md = await ensure_async(cm.get(tmp_md)) compare_notebooks(nb_md["content"], nb, "md:pandoc") assert nb_md["content"].metadata["jupytext"]["formats"] == "ipynb,md:pandoc" @pytest.mark.requires_quarto async def test_save_load_paired_qmd_notebook(ipynb_py_R_jl_file, tmpdir, cm): if re.match( r".*(functional|Notebook with|plotly_graphs|flavors|complex_metadata|" "update83|raw_cell|_66|nteract|LaTeX|invalid|305|text_outputs|ir_notebook|jupyter|with_R_magic).*", ipynb_py_R_jl_file, ): pytest.skip() tmp_ipynb = "notebook.ipynb" tmp_qmd = "notebook.qmd" cm.root_dir = str(tmpdir) # open ipynb, save with cm, reopen nb = jupytext.read(ipynb_py_R_jl_file) nb.metadata["jupytext"] = {"formats": "ipynb,qmd"} await ensure_async(cm.save(model=notebook_model(nb), path=tmp_ipynb)) nb_md = await ensure_async(cm.get(tmp_qmd)) compare_notebooks(nb_md["content"], nb, "qmd") assert nb_md["content"].metadata["jupytext"]["formats"] == "ipynb,qmd" ================================================ FILE: tests/external/docs/test_using_cli.py ================================================ import os import shlex import pytest from nbformat.v4.nbbase import new_code_cell, new_notebook import jupytext from jupytext.cli import jupytext as jupytext_cli doc_path = os.path.join(os.path.dirname(__file__), "..", "..", "..", "docs") @pytest.mark.requires_user_kernel_python3 @pytest.mark.requires_black @pytest.mark.requires_myst @pytest.mark.skipif(not os.path.isdir(doc_path), reason="Documentation folder is missing") def test_jupytext_commands_in_the_documentation_work(tmpdir): # Read the documentation as a bash notebook using_cli = os.path.join(doc_path, "using-cli.md") assert os.path.isfile(using_cli) using_cli_nb = jupytext.read(using_cli) # Run the commands in tmpdir on a sample notebook jupytext.write(new_notebook(cells=[new_code_cell("1+1")]), str(tmpdir.join("notebook.ipynb"))) os.chdir(str(tmpdir)) cmd_tested = 0 for cell in using_cli_nb.cells: if cell.cell_type != "code": continue if not cell.source.startswith("jupytext"): continue for cmd in cell.source.splitlines(): if not cmd.startswith("jupytext"): continue # Do not test commands that involve reading a notebook from stdin if "read ipynb from stdin" in cmd: continue # We can't run pytest inside pytest if "pytest {}" in cmd: continue # We need to remove the comments that may follow the jupytext command if "#" in cmd: left, comment = cmd.rsplit("#", 1) if '"' not in comment: cmd = left print(f"Testing: {cmd}") args = shlex.split(cmd)[1:] assert not jupytext_cli(args), cmd cmd_tested += 1 assert cmd_tested >= 10 ================================================ FILE: tests/external/jupyter_fs/test_jupyter_fs.py ================================================ import logging import pytest from jupyter_server.utils import ensure_async from nbformat.v4.nbbase import new_code_cell, new_markdown_cell, new_notebook import jupytext from jupytext.compare import compare_cells, notebook_model @pytest.fixture(params=["sync", "async"]) def cm_from_fs_meta_manager(tmpdir, request): try: from jupyterfs.metamanager import MetaManager, SyncMetaManager except ImportError: pytest.skip("jupyterfs is not available") if request.param == "sync": cm_class = jupytext.build_sync_jupytext_contents_manager_class(SyncMetaManager) else: cm_class = jupytext.build_async_jupytext_contents_manager_class(MetaManager) logger = logging.getLogger("jupyter-fs") cm = cm_class(parent=None, log=logger) cm.initResource( { "url": f"osfs://{tmpdir}", } ) return cm @pytest.mark.asyncio async def test_jupytext_jupyter_fs_metamanager(cm_from_fs_meta_manager): """Test the basic get/save functions of Jupytext with a fs manager https://github.com/mwouts/jupytext/issues/618""" cm = cm_from_fs_meta_manager # the hash that corresponds to the osfs osfs = [h for h in cm._managers if h != ""][0] # save a few files text = "some text\n" await ensure_async(cm.save(dict(type="file", content=text, format="text"), path=osfs + ":text.md")) nb = new_notebook(cells=[new_markdown_cell("A markdown cell"), new_code_cell("1 + 1")]) await ensure_async(cm.save(notebook_model(nb), osfs + ":notebook.ipynb")) await ensure_async(cm.save(notebook_model(nb), osfs + ":text_notebook.md")) # list the directory directory = await ensure_async(cm.get(osfs + ":/")) assert {file["name"] for file in directory["content"]} == { "text.md", "text_notebook.md", "notebook.ipynb", } # get the files model = await ensure_async(cm.get(osfs + ":/text.md", type="file")) assert model["type"] == "file" assert model["content"] == text model = await ensure_async(cm.get(osfs + ":text.md", type="notebook")) assert model["type"] == "notebook" # We only compare the cells, as kernelspecs are added to the notebook metadata compare_cells(model["content"].cells, [new_markdown_cell(text.strip())], compare_ids=False) for nb_file in ["notebook.ipynb", "text_notebook.md"]: model = await ensure_async(cm.get(osfs + ":" + nb_file)) assert model["type"] == "notebook" actual_cells = model["content"].cells # saving adds 'trusted=True' to the code cell metadata for cell in actual_cells: cell.metadata = {} compare_cells(actual_cells, nb.cells, compare_ids=False) @pytest.mark.asyncio async def test_config_jupytext_jupyter_fs_meta_manager(tmpdir, cm_from_fs_meta_manager): """Test the configuration of Jupytext with a fs manager""" tmpdir.join("jupytext.toml").write('formats = "ipynb,py"') cm = cm_from_fs_meta_manager # the hash that corresponds to the osfs osfs = [h for h in cm._managers if h != ""][0] # save a few files nb = new_notebook() await ensure_async(cm.save(dict(type="file", content="text", format="text"), path=osfs + ":text.md")) await ensure_async(cm.save(notebook_model(nb), osfs + ":script.py")) await ensure_async(cm.save(notebook_model(nb), osfs + ":text_notebook.md")) await ensure_async(cm.save(notebook_model(nb), osfs + ":notebook.ipynb")) # list the directory directory = await ensure_async(cm.get(osfs + ":/")) assert {file["name"] for file in directory["content"]} == { "jupytext.toml", "text.md", "text_notebook.md", "notebook.ipynb", "notebook.py", "script.py", "script.ipynb", } ================================================ FILE: tests/external/pre_commit/test_pre_commit_0_ipynb_to_py.py ================================================ import pytest from git.exc import HookExecutionError from nbformat.v4.nbbase import new_markdown_cell, new_notebook from pre_commit.main import main as pre_commit from jupytext import read, write from jupytext.cli import jupytext from jupytext.compare import compare_cells def test_pre_commit_hook_ipynb_to_py(tmpdir, cwd_tmpdir, tmp_repo, jupytext_repo_root, jupytext_repo_rev): """Here we document and test the expected behavior of the pre-commit hook in the directional (--to) mode. Note that here, the ipynb file is always the source for updates - i.e. changes on the .py file will not trigger the hook. """ # set up the tmpdir repo with pre-commit pre_commit_config_yaml = f""" repos: - repo: {jupytext_repo_root} rev: {jupytext_repo_rev} hooks: - id: jupytext args: [--from, ipynb, --to, "py:percent"] """ tmpdir.join(".pre-commit-config.yaml").write(pre_commit_config_yaml) tmp_repo.git.add(".pre-commit-config.yaml") pre_commit(["install", "--install-hooks"]) # write test notebook and output file nb = new_notebook(cells=[new_markdown_cell("A short notebook")]) write(nb, "test.ipynb") jupytext(["--from", "ipynb", "--to", "py:percent", "test.ipynb"]) tmp_repo.git.add(".") tmp_repo.index.commit("test") # make a change to the notebook nb = new_notebook(cells=[new_markdown_cell("Some other text")]) write(nb, "test.ipynb") tmp_repo.git.add("test.ipynb") # now a commit will fail, and keep failing until we add the new # changes made to the existing output to the index ourselves with pytest.raises(HookExecutionError, match="files were modified by this hook"): tmp_repo.index.commit("fails") with pytest.raises(HookExecutionError, match="git add test.py"): tmp_repo.index.commit("fails again") # once we add the changes, it will pass tmp_repo.git.add("test.py") tmp_repo.index.commit("succeeds") assert "test.ipynb" in tmp_repo.tree() assert "test.py" in tmp_repo.tree() # Updating the .py file is possible nb = new_notebook(cells=[new_markdown_cell("Some updated text")]) write(nb, "test.py", fmt="py:percent") tmp_repo.index.commit("update py version") # But it won't change the ipynb file (if you want that, use the --sync mode) nb = read("test.ipynb") compare_cells(nb.cells, [new_markdown_cell("Some other text")], compare_ids=False) ================================================ FILE: tests/external/pre_commit/test_pre_commit_1_sync.py ================================================ import shutil import pytest from git.exc import HookExecutionError from nbformat.v4.nbbase import new_markdown_cell from pre_commit.main import main as pre_commit from jupytext import read, write from jupytext.cli import jupytext def test_pre_commit_hook_sync( tmpdir, cwd_tmpdir, tmp_repo, jupytext_repo_root, jupytext_repo_rev, python_notebook, ): pre_commit_config_yaml = f""" repos: - repo: {jupytext_repo_root} rev: {jupytext_repo_rev} hooks: - id: jupytext args: [--sync] """ tmpdir.join(".pre-commit-config.yaml").write(pre_commit_config_yaml) tmp_repo.git.add(".pre-commit-config.yaml") pre_commit(["install", "--install-hooks", "-f"]) # write a test notebook and sync it to py:percent nb = python_notebook write(nb, "test.ipynb") jupytext(["--set-formats", "ipynb,py:percent", "test.ipynb"]) # try to commit it, should fail because the py version hasn't been added tmp_repo.git.add("test.ipynb") with pytest.raises( HookExecutionError, match="git add test.py", ): tmp_repo.index.commit("failing") # add the py file, now the commit will succeed tmp_repo.git.add("test.py") tmp_repo.index.commit("passing") assert "test.ipynb" in tmp_repo.tree() assert "test.py" in tmp_repo.tree() # modify the ipynb file nb = read("test.ipynb") nb.cells.append(new_markdown_cell("A new cell")) write(nb, "test.ipynb") tmp_repo.git.add("test.ipynb") # We try to commit one more time, this updates the py file with pytest.raises( HookExecutionError, match="files were modified by this hook", ): tmp_repo.index.commit("failing") # the text file has been updated assert "A new cell" in tmpdir.join("test.py").read() # trying to commit should fail again because we forgot to add the .py version with pytest.raises(HookExecutionError, match="git add test.py"): tmp_repo.index.commit("still failing") nb = read("test.ipynb") assert len(nb.cells) == 2 # add the text file, now the commit will succeed tmp_repo.git.add("test.py") tmp_repo.index.commit("passing") # modify the .py file nb.cells.append(new_markdown_cell("A third cell")) write(nb, "test.py", fmt="py:percent") tmp_repo.git.add("test.py") # the pre-commit hook will update the .ipynb file with pytest.raises(HookExecutionError, match="git add test.ipynb"): tmp_repo.index.commit("failing") tmp_repo.git.add("test.ipynb") tmp_repo.index.commit("passing") nb = read("test.ipynb") assert len(nb.cells) == 3 # finally we move the paired notebook to a subfolder tmpdir.mkdir("subfolder") shutil.move("test.py", "subfolder") shutil.move("test.ipynb", "subfolder") # adding both files works on the first commit as notebooks are in sync tmp_repo.git.add("subfolder/test.ipynb") tmp_repo.git.add("subfolder/test.py") tmp_repo.index.commit("passing") # and we don't get any error or message when we run 'pre-commit run --all' status = pre_commit(["run", "--all"]) assert status == 0 ================================================ FILE: tests/external/pre_commit/test_pre_commit_1_sync_with_config.py ================================================ import pytest from git.exc import HookExecutionError from nbformat.v4.nbbase import new_markdown_cell from pre_commit.main import main as pre_commit from jupytext import TextFileContentsManager, read def test_pre_commit_hook_sync_with_config( tmpdir, cwd_tmpdir, tmp_repo, jupytext_repo_root, jupytext_repo_rev, python_notebook, ): pre_commit_config_yaml = f""" repos: - repo: {jupytext_repo_root} rev: {jupytext_repo_rev} hooks: - id: jupytext args: [--sync] """ tmpdir.join(".pre-commit-config.yaml").write(pre_commit_config_yaml) tmp_repo.git.add(".pre-commit-config.yaml") pre_commit(["install", "--install-hooks", "-f"]) tmpdir.join("jupytext.toml").write('formats = "ipynb,py:percent"\n') # create a test notebook and save it in Jupyter nb = python_notebook cm = TextFileContentsManager() cm.root_dir = str(tmpdir) cm.save(dict(type="notebook", content=nb), "test.ipynb") # Assert that "text_representation" is in the Jupytext metadata #900 assert "text_representation" in tmpdir.join("test.py").read() # But not in the ipynb notebook assert "text_representation" not in tmpdir.join("test.ipynb").read() # try to commit it, should fail as the py version hasn't been added tmp_repo.git.add("test.ipynb") with pytest.raises( HookExecutionError, match="git add test.py", ): tmp_repo.index.commit("failing") # add the py file, now the commit will succeed tmp_repo.git.add("test.py") tmp_repo.index.commit("passing") assert "test.ipynb" in tmp_repo.tree() assert "test.py" in tmp_repo.tree() # The text representation metadata is still in the py file assert "text_representation" in tmpdir.join("test.py").read() # But not in the ipynb notebook assert "text_representation" not in tmpdir.join("test.ipynb").read() # modify the ipynb file in Jupyter # Reload the notebook nb = cm.get("test.ipynb")["content"] nb.cells.append(new_markdown_cell("A new cell")) cm.save(dict(type="notebook", content=nb), "test.ipynb") # The text representation metadata is in the py file assert "text_representation" in tmpdir.join("test.py").read() # But not in the ipynb notebook assert "text_representation" not in tmpdir.join("test.ipynb").read() # the text file has been updated (and the ipynb file as well) assert "A new cell" in tmpdir.join("test.py").read() nb = read("test.ipynb") assert len(nb.cells) == 2 # add both files, the commit will succeed tmp_repo.git.add("test.ipynb") tmp_repo.git.add("test.py") tmp_repo.index.commit("passing") ================================================ FILE: tests/external/pre_commit/test_pre_commit_1_sync_with_no_config.py ================================================ from copy import deepcopy import pytest from git.exc import HookExecutionError from nbformat.v4.nbbase import new_markdown_cell from pre_commit.main import main as pre_commit import jupytext from jupytext import TextFileContentsManager from jupytext.compare import compare_notebooks def test_pre_commit_hook_sync_with_no_config( tmpdir, cwd_tmpdir, tmp_repo, jupytext_repo_root, jupytext_repo_rev, notebook_with_outputs, ): """In this test we reproduce the setting from https://github.com/mwouts/jupytext/issues/967""" pre_commit_config_yaml = f""" repos: - repo: {jupytext_repo_root} rev: {jupytext_repo_rev} hooks: - id: jupytext args: [ '--sync', '--set-formats', 'ipynb,py:percent', '--show-changes', '--' ] """ # Save a sample notebook with outputs in Jupyter nb = deepcopy(notebook_with_outputs) (tmpdir / "notebooks").mkdir() cm = TextFileContentsManager() cm.root_dir = str(tmpdir) cm.save(dict(type="notebook", content=nb), "nb.ipynb") # Add it to git tmp_repo.git.add("nb.ipynb") tmp_repo.index.commit("Notebook with outputs") # Configure the pre-commit hook tmpdir.join(".pre-commit-config.yaml").write(pre_commit_config_yaml) tmp_repo.git.add(".pre-commit-config.yaml") pre_commit(["install", "--install-hooks", "-f"]) # Modify and save the notebook nb.cells.append(new_markdown_cell("New markdown cell")) cm.save(dict(type="notebook", content=nb), "nb.ipynb") # No .py file at the moment assert not (tmpdir / "nb.py").exists() # try to commit it, should fail as the py version hasn't been added tmp_repo.git.add("nb.ipynb") with pytest.raises( HookExecutionError, match="git add nb.py", ): tmp_repo.index.commit("failing") # Now the .py file is present assert "New markdown cell" in tmpdir.join("nb.py").read() # add the ipynb and the py file, now the commit will succeed tmp_repo.git.add("nb.ipynb") tmp_repo.git.add("nb.py") tmp_repo.index.commit("passing") assert "nb.ipynb" in tmp_repo.tree() assert "nb.py" in tmp_repo.tree() # The notebook on disk is the same as the original, except for the new cell added nb = jupytext.read(tmpdir / "nb.ipynb") extra_cell = nb.cells.pop() assert extra_cell.cell_type == "markdown" assert extra_cell.source == "New markdown cell" compare_notebooks( nb, notebook_with_outputs, compare_ids=True, compare_outputs=True, ) ================================================ FILE: tests/external/pre_commit/test_pre_commit_2_sync_nbstripout.py ================================================ import pytest from git.exc import HookExecutionError from pre_commit.main import main as pre_commit from jupytext import read, write from jupytext.cli import jupytext def test_pre_commit_hook_sync_nbstripout( tmpdir, cwd_tmpdir, tmp_repo, jupytext_repo_root, jupytext_repo_rev, notebook_with_outputs, ): """Here we sync the ipynb notebook with a Markdown file and also apply nbstripout.""" pre_commit_config_yaml = f""" repos: - repo: {jupytext_repo_root} rev: {jupytext_repo_rev} hooks: - id: jupytext args: [--sync] - repo: https://github.com/kynan/nbstripout rev: 0.5.0 hooks: - id: nbstripout """ tmpdir.join(".pre-commit-config.yaml").write(pre_commit_config_yaml) tmp_repo.git.add(".pre-commit-config.yaml") pre_commit(["install", "--install-hooks", "-f"]) # write a test notebook write(notebook_with_outputs, "test.ipynb") # We pair the notebook to a md file jupytext(["--set-formats", "ipynb,md", "test.ipynb"]) # try to commit it, should fail because # 1. the md version hasn't been added # 2. the notebook has outputs tmp_repo.git.add("test.ipynb") with pytest.raises( HookExecutionError, match="files were modified by this hook", ): tmp_repo.index.commit("failing") # Add the two files tmp_repo.git.add("test.ipynb") tmp_repo.git.add("test.md") # now the commit will succeed tmp_repo.index.commit("passing") assert "test.ipynb" in tmp_repo.tree() assert "test.md" in tmp_repo.tree() # the ipynb file has no outputs on disk nb = read("test.ipynb") assert not nb.cells[0].outputs ================================================ FILE: tests/external/pre_commit/test_pre_commit_3_sync_black_nbstripout.py ================================================ import pytest from git.exc import HookExecutionError from pre_commit.main import main as pre_commit from jupytext import read, write import sys @pytest.mark.skipif(sys.version_info >= (3, 14), reason="this test fails on Python 3.14") def test_pre_commit_hook_sync_black_nbstripout( tmpdir, cwd_tmpdir, tmp_repo, jupytext_repo_root, jupytext_repo_rev, notebook_with_outputs, ): """Here we sync the ipynb notebook with a py:percent file and also apply black and nbstripout.""" pre_commit_config_yaml = f""" repos: - repo: {jupytext_repo_root} rev: {jupytext_repo_rev} hooks: - id: jupytext args: [--sync, --pipe, black] additional_dependencies: - black==22.3.0 # Matches hook - repo: https://github.com/psf/black rev: 22.3.0 hooks: - id: black - repo: https://github.com/kynan/nbstripout rev: 0.5.0 hooks: - id: nbstripout """ tmpdir.join(".pre-commit-config.yaml").write(pre_commit_config_yaml) tmp_repo.git.add(".pre-commit-config.yaml") pre_commit(["install", "--install-hooks", "-f"]) tmpdir.join("jupytext.toml").write('formats = "ipynb,py:percent"') tmp_repo.git.add("jupytext.toml") tmp_repo.index.commit("pair notebooks") # write a test notebook write(notebook_with_outputs, "test.ipynb") # try to commit it, should fail because # 1. the py version hasn't been added # 2. the first cell is '1+1' which is not black compliant # 3. the notebook has outputs tmp_repo.git.add("test.ipynb") with pytest.raises( HookExecutionError, match="files were modified by this hook", ): tmp_repo.index.commit("failing") # Add the two files tmp_repo.git.add("test.ipynb") tmp_repo.git.add("test.py") # now the commit will succeed tmp_repo.index.commit("passing") assert "test.ipynb" in tmp_repo.tree() assert "test.py" in tmp_repo.tree() # the first cell was reformatted nb = read("test.ipynb") assert nb.cells[0].source == "1 + 1" # the ipynb file has no outputs assert not nb.cells[0].outputs ================================================ FILE: tests/external/pre_commit/test_pre_commit_4_sync_execute.py ================================================ import pytest from git.exc import HookExecutionError from nbformat.v4.nbbase import new_code_cell from pre_commit.main import main as pre_commit from jupytext import read, write @pytest.mark.requires_user_kernel_python3 def test_pre_commit_hook_sync_execute( tmpdir, cwd_tmpdir, tmp_repo, jupytext_repo_root, jupytext_repo_rev, notebook_with_outputs, ): """Here we sync the ipynb notebook with a py:percent file and execute it (this is probably not a very recommendable hook!)""" pre_commit_config_yaml = f""" repos: - repo: {jupytext_repo_root} rev: {jupytext_repo_rev} hooks: - id: jupytext args: [--sync, --execute, --show-changes] additional_dependencies: - nbconvert """ tmpdir.join(".pre-commit-config.yaml").write(pre_commit_config_yaml) tmp_repo.git.add(".pre-commit-config.yaml") pre_commit(["install", "--install-hooks", "-f"]) # simple notebook with kernel 'user_kernel_python3' nb = notebook_with_outputs nb.cells = [new_code_cell("3+4")] # pair it to a py file and write it to disk nb.metadata["jupytext"] = {"formats": "ipynb,py:percent"} write(nb, "test.ipynb") # try to commit it, should fail because # 1. the py version hasn't been added # 2. the outputs are missing tmp_repo.git.add("test.ipynb") with pytest.raises( HookExecutionError, match="files were modified by this hook", ): tmp_repo.index.commit("failing") # Add the two files tmp_repo.git.add("test.ipynb") tmp_repo.git.add("test.py") # now the commit will succeed tmp_repo.index.commit("passing") assert "test.ipynb" in tmp_repo.tree() assert "test.py" in tmp_repo.tree() # the first cell has the expected output nb = read("test.ipynb") assert nb.cells[0].outputs[0]["data"]["text/plain"] == "7" ================================================ FILE: tests/external/pre_commit/test_pre_commit_5_reformat_markdown.py ================================================ import pytest from git.exc import HookExecutionError from nbformat.v4.nbbase import new_code_cell, new_markdown_cell, new_notebook from pre_commit.main import main as pre_commit from jupytext import read, write @pytest.mark.requires_pandoc def test_pre_commit_hook_sync_reformat_code_and_markdown( tmpdir, cwd_tmpdir, tmp_repo, jupytext_repo_root, jupytext_repo_rev, notebook_with_outputs, ): """Here we sync the ipynb notebook with a py:percent file and also apply black and pandoc to reformat both code and markdown cells. """ pre_commit_config_yaml = f""" repos: - repo: {jupytext_repo_root} rev: {jupytext_repo_rev} hooks: - id: jupytext args: [--sync, --pipe-fmt, ipynb, --pipe, 'pandoc --from ipynb --to ipynb --markdown-headings=atx', --show-changes] - id: jupytext args: [--sync, --pipe, black, --show-changes] additional_dependencies: - black==22.3.0 # Matches black hook below - repo: https://github.com/psf/black rev: 22.3.0 hooks: - id: black """ tmpdir.join(".pre-commit-config.yaml").write(pre_commit_config_yaml) tmp_repo.git.add(".pre-commit-config.yaml") pre_commit(["install", "--install-hooks", "-f"]) tmpdir.join("jupytext.toml").write('formats = "ipynb,py:percent"') tmp_repo.git.add("jupytext.toml") tmp_repo.index.commit("pair notebooks") # write a test notebook notebook = new_notebook( cells=[ new_code_cell("1+1"), new_markdown_cell( """This is a complex markdown cell # With a h1 header ## And a h2 header | And | A | Table | | --------- | ---| ----- | | 0 | 1 | 2 | !!!WARNING!!! This hook does not seem compatible with explicit paragraph breaks (two spaces at the end of a line). And a VERY long line. """.replace("VERY ", "very " * 51) ), ], metadata=notebook_with_outputs.metadata, ) write(notebook, "test.ipynb") # try to commit it, should fail because # 1. the py version hasn't been added # 2. the first cell is '1+1' which is not black compliant # 3. the second cell needs to be wrapped tmp_repo.git.add("test.ipynb") with pytest.raises( HookExecutionError, match="files were modified by this hook", ): tmp_repo.index.commit("failing") # Add the two files tmp_repo.git.add("test.ipynb") tmp_repo.git.add("test.py") # now the commit will succeed tmp_repo.index.commit("passing") assert "test.ipynb" in tmp_repo.tree() assert "test.py" in tmp_repo.tree() # both the code and the markdown cells were reformatted nb = read("test.ipynb") assert nb.cells[0].source == "1 + 1" print(nb.cells[1].source) assert ( nb.cells[1].source == """This is a complex markdown cell # With a h1 header ## And a h2 header | And | A | Table | |-----|-----|-------| | 0 | 1 | 2 | !!!WARNING!!! This hook does not seem compatible with explicit paragraph breaks (two spaces at the end of a line). And a very very very very very very very very very very very very very very very very very very very very very very very very very very very very very very very very very very very very very very very very very very very very very very very very very very very long line.""" ) ================================================ FILE: tests/external/pre_commit/test_pre_commit_mode.py ================================================ import os import time import pytest from nbformat.v4.nbbase import new_code_cell, new_markdown_cell, new_notebook from jupytext import read, write from jupytext.cli import get_timestamp, git_timestamp, is_untracked, jupytext def test_is_untracked(tmpdir, cwd_tmpdir, tmp_repo): # make a test file file = "test.txt" tmpdir.join(file).write("test file\n") # untracked assert is_untracked(file) # added, not committed tmp_repo.git.add(file) assert not is_untracked(file) # committed tmp_repo.index.commit("test") assert not is_untracked(file) # changed tmpdir.join(file).write("modified file\n") assert is_untracked(file) # added, not committed tmp_repo.git.add(file) assert not is_untracked(file) def test_ignore_unmatched_ignores(tmpdir, cwd_tmpdir): # Unmatched file file = "test.txt" tmpdir.join(file).write("Hello\n") # Run jupytext status = jupytext(["--from", "ipynb", "--to", "py:percent", "--pre-commit-mode", file]) assert status == 0 assert not tmpdir.join("test.py").exists() def test_alert_untracked_alerts(tmpdir, cwd_tmpdir, tmp_repo, capsys): file = "test.py" tmpdir.join(file).write("print('hello')\n") # Run jupytext status = jupytext(["--from", ".py", "--to", "ipynb", "--pre-commit-mode", file]) assert status != 0 assert tmpdir.join("test.ipynb").exists() out = capsys.readouterr() assert "git add test.ipynb" in out.out def test_alert_untracked_alerts_when_using_sync(tmpdir, cwd_tmpdir, tmp_repo, capsys): tmpdir.join("test.py").write("print('hello')\n") tmp_repo.git.add("test.py") tmpdir.join("jupytext.toml").write('formats = "ipynb,py"') # Run jupytext status = jupytext(["--sync", "--pre-commit-mode", "test.py"]) assert status != 0 assert tmpdir.join("test.ipynb").exists() out = capsys.readouterr() assert "git add test.ipynb" in out.out def test_alert_untracked_alerts_for_modified(tmpdir, cwd_tmpdir, tmp_repo, capsys): # write test notebook nb = new_notebook(cells=[new_markdown_cell("A short notebook")]) write(nb, "test.ipynb") # write existing output tmpdir.join("test.py").write("# Hello") # track output file tmp_repo.git.add("test.py") # Run jupytext status = jupytext(["--from", "ipynb", "--to", "py:percent", "--pre-commit-mode", "test.ipynb"]) assert status == 1 out = capsys.readouterr() assert "git add test.py" in out.out def test_alert_inconsistent_versions(tmpdir, cwd_tmpdir, tmp_repo, capsys): """Jupytext refuses to sync two inconsistent notebooks""" write(new_notebook(cells=[new_markdown_cell("A short py notebook")]), "test.py") write( new_notebook( cells=[new_markdown_cell("Another ipynb notebook")], metadata={"jupytext": {"formats": "ipynb,py"}}, ), "test.ipynb", ) # Add them both tmp_repo.git.add("test.py") tmp_repo.git.add("test.ipynb") # Run jupytext status = jupytext(["--sync", "--pre-commit-mode", "test.ipynb"]) # The diff should be visible assert status == 1 out = capsys.readouterr() assert ( """--- test.py +++ test.ipynb""" in out.err ) assert """-# A short py notebook +# Another ipynb notebook """ assert "Error: test.ipynb and test.py are inconsistent" in out.err assert "git reset test.py && git checkout -- test.py" in out.err assert "git reset test.ipynb && git checkout -- test.ipynb" in out.err def test_pre_commit_local_config(tmpdir, cwd_tmpdir, tmp_repo, python_notebook, capsys): tmpdir.join("jupytext.toml").write_text( """notebook_metadata_filter = "-all" cell_metadata_filter = "-all" formats = "ipynb,py:percent" """, encoding="utf-8", ) write(python_notebook, str(tmpdir.join("test.ipynb"))) # create the paired file jupytext(["--sync", "test.ipynb"]) print("--------- test.ipynb ---------") print(tmpdir.join("test.ipynb").read_text("utf-8")) print("--------- test.py ---------") print(tmpdir.join("test.py").read_text("utf-8")) tmp_repo.git.add(".") capsys.readouterr() exit_code = jupytext(["--pre-commit-mode", "--sync", "test.ipynb", "--show-changes"]) out, err = capsys.readouterr() assert not err, err assert "updating test" not in out.lower(), out assert exit_code == 0, out def test_git_timestamp(tmpdir, cwd_tmpdir, tmp_repo): # No commit yet => return the file timestamp tmpdir.join("file_1").write("") assert git_timestamp("file_1") == get_timestamp("file_1") # Staged files are always considered more recent than committed files, i.e timestamp==inf time.sleep(0.1) tmpdir.join("file_2").write("") tmp_repo.git.add(".") assert get_timestamp("file_1") < get_timestamp("file_2") assert git_timestamp("file_1") == git_timestamp("file_2") == float("inf") tmp_repo.index.commit("Add file_1 and file_2") assert get_timestamp("file_1") < get_timestamp("file_2") assert git_timestamp("file_1") == git_timestamp("file_2") < float("inf") assert git_timestamp("file_1") < get_timestamp("file_1") + 1 < git_timestamp("file_1") + 2 # Git timestamps have a resolution of 1 sec, so if we want to see # different git timestamps between file_1 and file_2 we need this: time.sleep(1.2) # Here we just touch the file (content unchanged). The git timestamp is not modified tmpdir.join("file_1").write("") assert get_timestamp("file_1") > get_timestamp("file_2") assert git_timestamp("file_1") == git_timestamp("file_2") < float("inf") # When we modify the file then its "git_timestamp" becomes inf again tmpdir.join("file_1").write("modified") assert get_timestamp("file_1") > get_timestamp("file_2") assert float("inf") == git_timestamp("file_1") > git_timestamp("file_2") tmp_repo.git.add(".") assert float("inf") == git_timestamp("file_1") > git_timestamp("file_2") # When the file is committed its timestamp is the commit timestamp tmp_repo.index.commit("Update file_1") assert float("inf") > git_timestamp("file_1") > git_timestamp("file_2") # If a file is not in the git repo then we return its timestamp tmpdir.join("file_3").write("") assert git_timestamp("file_3") == get_timestamp("file_3") @pytest.mark.parametrize("commit_order", [["test.py", "test.ipynb"], ["test.ipynb", "test.py"]]) @pytest.mark.parametrize("sync_file", ["test.py", "test.ipynb"]) def test_sync_pre_commit_mode_respects_commit_order_780( tmpdir, cwd_tmpdir, tmp_repo, python_notebook, commit_order, sync_file, ): file_1, file_2 = commit_order nb = python_notebook nb.metadata["jupytext"] = {"formats": "ipynb,py:percent"} nb.cells = [new_code_cell("1 + 1")] write(nb, file_1) tmp_repo.git.add(file_1) tmp_repo.index.commit(file_1) # This needs to >1 sec because commit timestamps have a one-second resolution time.sleep(1.2) nb.cells = [new_code_cell("2 + 2")] write(nb, file_2) tmp_repo.git.add(file_2) tmp_repo.index.commit(file_2) # Invert file timestamps ts_1 = os.stat(file_1).st_mtime ts_2 = os.stat(file_2).st_mtime os.utime(file_1, (ts_2, ts_2)) os.utime(file_2, (ts_1, ts_1)) jupytext(["--sync", "--pre-commit-mode", sync_file]) for file in commit_order: nb = read(file) assert nb.cells[0].source == "2 + 2", file @pytest.mark.requires_user_kernel_python3 def test_skip_execution(tmpdir, cwd_tmpdir, tmp_repo, python_notebook, capsys): write( new_notebook(cells=[new_code_cell("1 + 1")], metadata=python_notebook.metadata), "test.ipynb", ) tmp_repo.index.add("test.ipynb") jupytext(["--execute", "--pre-commit-mode", "test.ipynb"]) captured = capsys.readouterr() assert "Executing notebook" in captured.out nb = read("test.ipynb") assert nb.cells[0].execution_count == 1 jupytext(["--execute", "--pre-commit-mode", "test.ipynb"]) captured = capsys.readouterr() assert "skipped" in captured.out ================================================ FILE: tests/external/pre_commit/test_pre_commit_scripts.py ================================================ import os import stat import unittest.mock as mock import pytest from nbformat.v4.nbbase import new_code_cell, new_markdown_cell, new_notebook from jupytext import read, write from jupytext.cli import jupytext, system from jupytext.compare import compare_cells, compare_notebooks def git_in_tmpdir(tmpdir): """Return a function that will execute git instruction in the desired directory""" def git(*args): out = system("git", *args, cwd=str(tmpdir)) print(out) return out git("init", "--initial-branch", "main") git("status") git("config", "user.name", "jupytext-test-cli") git("config", "user.email", "jupytext@tests.com") return git def system_in_tmpdir(tmpdir): """Return a function that will execute system commands in the desired directory""" def system_(*args): return system(*args, cwd=str(tmpdir)) return system_ def test_pre_commit_hook(tmpdir): tmp_ipynb = str(tmpdir.join("nb with spaces.ipynb")) tmp_py = str(tmpdir.join("nb with spaces.py")) nb = new_notebook(cells=[]) git = git_in_tmpdir(tmpdir) hook = str(tmpdir.join(".git/hooks/pre-commit")) with open(hook, "w") as fp: fp.write("#!/bin/sh\njupytext --to py:percent --pre-commit\n") st = os.stat(hook) os.chmod(hook, st.st_mode | stat.S_IEXEC) write(nb, tmp_ipynb) assert os.path.isfile(tmp_ipynb) assert not os.path.isfile(tmp_py) git("add", "nb with spaces.ipynb") git("status") git("commit", "-m", "created") git("status") assert "nb with spaces.py" in git("ls-tree", "-r", "main", "--name-only") assert os.path.isfile(tmp_py) def test_sync_with_pre_commit_hook(tmpdir): # Init git and create a pre-commit hook git = git_in_tmpdir(tmpdir) hook = str(tmpdir.join(".git/hooks/pre-commit")) with open(hook, "w") as fp: fp.write("#!/bin/sh\njupytext --sync --pre-commit\n") st = os.stat(hook) os.chmod(hook, st.st_mode | stat.S_IEXEC) # Create a notebook that is not paired tmp_ipynb = str(tmpdir.join("notebook.ipynb")) tmp_md = str(tmpdir.join("notebook.md")) nb = new_notebook(cells=[new_markdown_cell("A short notebook")]) write(nb, tmp_ipynb) assert os.path.isfile(tmp_ipynb) assert not os.path.isfile(tmp_md) git("add", "notebook.ipynb") git("status") git("commit", "-m", "created") git("status") assert "notebook.ipynb" in git("ls-tree", "-r", "main", "--name-only") assert "notebook.md" not in git("ls-tree", "-r", "main", "--name-only") assert os.path.isfile(tmp_ipynb) assert not os.path.exists(tmp_md) # Pair the notebook jupytext(["--set-formats", "ipynb,md", tmp_ipynb]) # Remove the md file (it will be regenerated by the pre-commit hook) os.remove(tmp_md) # Commit the ipynb file git("add", "notebook.ipynb") git("status") git("commit", "-m", "paired") git("status") # The pre-commit script should have created and committed the md file assert "notebook.ipynb" in git("ls-tree", "-r", "main", "--name-only") assert "notebook.md" in git("ls-tree", "-r", "main", "--name-only") assert os.path.isfile(tmp_md) nb_md = read(tmp_md) compare_notebooks(nb_md, nb) # Edit the md file with open(tmp_md) as fp: md_text = fp.read() with open(tmp_md, "w") as fp: fp.write(md_text.replace("A short notebook", "Notebook was edited")) # commit the md file git("add", "notebook.md") git("status") git("commit", "-m", "edited md") git("status") # The pre-commit script should have sync and committed the ipynb file assert "notebook.ipynb" in git("ls-tree", "-r", "main", "--name-only") assert "notebook.md" in git("ls-tree", "-r", "main", "--name-only") nb = read(tmp_ipynb) compare_cells(nb.cells, [new_markdown_cell("Notebook was edited")], compare_ids=False) # create and commit a jpg file tmp_jpg = str(tmpdir.join("image.jpg")) with open(tmp_jpg, "wb") as fp: fp.write(b"") git("add", "image.jpg") git("commit", "-m", "added image") def test_pre_commit_hook_in_subfolder(tmpdir): tmp_ipynb = str(tmpdir.join("nb with spaces.ipynb")) tmp_py = str(tmpdir.join("python", "nb with spaces.py")) nb = new_notebook(cells=[]) git = git_in_tmpdir(tmpdir) hook = str(tmpdir.join(".git/hooks/pre-commit")) with open(hook, "w") as fp: fp.write("#!/bin/sh\njupytext --from ipynb --to python//py:percent --pre-commit\n") st = os.stat(hook) os.chmod(hook, st.st_mode | stat.S_IEXEC) write(nb, tmp_ipynb) assert os.path.isfile(tmp_ipynb) assert not os.path.isfile(tmp_py) git("add", "nb with spaces.ipynb") git("status") git("commit", "-m", "created") git("status") assert "nb with spaces.py" in git("ls-tree", "-r", "main", "--name-only") assert os.path.isfile(tmp_py) def test_pre_commit_hook_py_to_ipynb_and_md(tmpdir): tmp_ipynb = str(tmpdir.join("nb with spaces.ipynb")) tmp_py = str(tmpdir.join("nb with spaces.py")) tmp_md = str(tmpdir.join("nb with spaces.md")) nb = new_notebook(cells=[]) git = git_in_tmpdir(tmpdir) hook = str(tmpdir.join(".git/hooks/pre-commit")) with open(hook, "w") as fp: fp.write( "#!/bin/sh\njupytext --from py:percent --to ipynb --pre-commit\njupytext --from py:percent --to md --pre-commit\n" ) st = os.stat(hook) os.chmod(hook, st.st_mode | stat.S_IEXEC) write(nb, tmp_py) assert os.path.isfile(tmp_py) assert not os.path.isfile(tmp_ipynb) assert not os.path.isfile(tmp_md) git("add", "nb with spaces.py") git("status") git("commit", "-m", "created") git("status") assert "nb with spaces.ipynb" in git("ls-tree", "-r", "main", "--name-only") assert "nb with spaces.md" in git("ls-tree", "-r", "main", "--name-only") assert os.path.isfile(tmp_ipynb) assert os.path.isfile(tmp_md) @pytest.mark.requires_black @pytest.mark.requires_flake8 def test_pre_commit_hook_sync_black_flake8(tmpdir, python_notebook): # Load real notebook metadata to get the 'auto' extension in --pipe-fmt to work metadata = python_notebook.metadata git = git_in_tmpdir(tmpdir) hook = str(tmpdir.join(".git/hooks/pre-commit")) with open(hook, "w") as fp: fp.write( "#!/bin/sh\n" "# Pair ipynb notebooks to a python file, reformat content with black, and run flake8\n" "# Note: this hook only acts on ipynb files. When pulling, run 'jupytext --sync' to " "update the ipynb file.\n" "jupytext --pre-commit --from ipynb --set-formats ipynb,py --pipe black --check flake8\n" ) st = os.stat(hook) os.chmod(hook, st.st_mode | stat.S_IEXEC) tmp_ipynb = str(tmpdir.join("notebook.ipynb")) tmp_py = str(tmpdir.join("notebook.py")) nb = new_notebook(cells=[new_code_cell(source="1+ 1")], metadata=metadata) write(nb, tmp_ipynb) git("add", "notebook.ipynb") git("status") git("commit", "-m", "created") git("status") assert os.path.isfile(tmp_py) assert os.path.isfile(tmp_ipynb) with open(tmp_py) as fp: assert fp.read().splitlines()[-1] == "1 + 1" nb = new_notebook( cells=[new_code_cell(source='"""trailing \nwhitespace""" ')], metadata=metadata, ) write(nb, tmp_ipynb) git("add", "notebook.ipynb") git("status") with open(tmp_py) as fp: assert fp.read().splitlines()[-1] == "1 + 1" @pytest.mark.requires_flake8 def test_pre_commit_hook_sync_flake8(tmpdir, python_notebook): """This test was extracted from test_pre_commit_hook_sync_black_flake8 to make sure that the pre-commit stops the commit when flake8 fails""" metadata = python_notebook.metadata git = git_in_tmpdir(tmpdir) hook = str(tmpdir.join(".git/hooks/pre-commit")) with open(hook, "w") as fp: fp.write( "#!/bin/sh\n" "# Pair ipynb notebooks to a python file, and run flake8\n" "# Note: this hook only acts on ipynb files. When pulling, run 'jupytext --sync' to " "update the ipynb file.\n" "jupytext --pre-commit --from ipynb --set-formats ipynb,py --check flake8\n" ) st = os.stat(hook) os.chmod(hook, st.st_mode | stat.S_IEXEC) tmp_ipynb = str(tmpdir.join("notebook.ipynb")) nb = new_notebook( cells=[new_code_cell(source='"""trailing \nwhitespace""" ')], metadata=metadata, ) write(nb, tmp_ipynb) git("add", "notebook.ipynb") git("status") with pytest.raises(SystemExit): # not flake8 git("commit", "-m", "created") @pytest.mark.filterwarnings("ignore:The --pre-commit argument is deprecated") def test_manual_call_of_pre_commit_hook(tmpdir): tmp_ipynb = str(tmpdir.join("notebook.ipynb")) tmp_py = str(tmpdir.join("notebook.py")) nb = new_notebook(cells=[]) os.chdir(str(tmpdir)) git = git_in_tmpdir(tmpdir) def hook(): with mock.patch("jupytext.cli.system", system_in_tmpdir(tmpdir)): jupytext(["--to", "py", "--pre-commit"]) write(nb, tmp_ipynb) assert os.path.isfile(tmp_ipynb) assert not os.path.isfile(tmp_py) git("add", "notebook.ipynb") git("status") hook() git("commit", "-m", "created") git("status") assert "notebook.py" in git("ls-tree", "-r", "main", "--name-only") assert os.path.isfile(tmp_py) def test_pre_commit_hook_with_subfolders_issue_506(tmpdir): """I have the following directory structure, where the nb/test.ipynb is paired with the py/test.py. ├── nb │ └── test.ipynb └── py └── test.py """ nb_file = tmpdir.mkdir("nb").join("test.ipynb") py_file = tmpdir.mkdir("py").join("test.py") """The notebook and Python file are paired with "jupytext": {"formats": "py//py,nb//ipynb"}. (using jupytext --set-formats py//py,nb//ipynb nb/test.ipynb)""" write( new_notebook( cells=[new_markdown_cell("A Markdown cell")], metadata={"jupytext": {"formats": "py//py,nb//ipynb"}}, ), str(py_file), ) """This works fine when syncing with jupytext --sync nb/test.ipynb but when syncing with jupytext --sync --pre-commit I get the following exception: (...)""" git = git_in_tmpdir(tmpdir) hook = str(tmpdir.join(".git/hooks/pre-commit")) with open(hook, "w") as fp: fp.write("#!/bin/sh\njupytext --sync --pre-commit\n") st = os.stat(hook) os.chmod(hook, st.st_mode | stat.S_IEXEC) assert not os.path.isfile(str(nb_file)) git("add", "py/test.py") git("status") git("commit", "-m", "notebook created") git("status") assert os.path.isfile(str(nb_file)) assert read(str(nb_file)).cells[0].source == "A Markdown cell" @pytest.mark.requires_pandoc def test_wrap_markdown_cell(tmpdir): """Use a pre-commit hook to sync a notebook to a script paired in a tree, and reformat the markdown cells using pandoc""" tmpdir.join("jupytext.toml").write( """# By default, the notebooks in this repository are in the notebooks subfolder # and they are paired to scripts in the script subfolder. formats = "notebooks///ipynb,scripts///py:percent" """ ) git = git_in_tmpdir(tmpdir) hook = str(tmpdir.join(".git/hooks/pre-commit")) with open(hook, "w") as fp: fp.write( "#!/bin/sh\n" "jupytext --pre-commit --sync --pipe-fmt ipynb --pipe \\\n" " 'pandoc --from ipynb --to ipynb --markdown-headings=atx'\n" ) st = os.stat(hook) os.chmod(hook, st.st_mode | stat.S_IEXEC) nb_file = tmpdir.mkdir("notebooks").mkdir("subfolder").join("wrap_markdown.ipynb") long_text = "This is a " + ("very " * 24) + "long sentence." nb = new_notebook(cells=[new_markdown_cell(long_text)]) write(nb, str(nb_file)) nb = read(str(nb_file)) assert nb.cells[0].source == long_text git("add", str(nb_file)) git("commit", "-m", "'notebook with long cells'") py_text = tmpdir.join("scripts").join("subfolder").join("wrap_markdown.py").read() assert "This is a very very" in py_text for line in py_text.splitlines(): assert len(line) <= 79 nb = read(nb_file, as_version=4) text = nb.cells[0].source assert len(text.splitlines()) >= 2 assert text != long_text ================================================ FILE: tests/external/round_trip/test_mirror_external.py ================================================ import pytest from jupytext.compare import assert_conversion_same_as_mirror """--------------------------------------------------------------------------------- Part I: ipynb -> fmt -> ipynb ---------------------------------------------------------------------------------""" @pytest.mark.requires_pandoc def test_ipynb_to_pandoc(ipynb_to_pandoc, no_jupytext_version_number): assert_conversion_same_as_mirror(ipynb_to_pandoc, "md:pandoc", "ipynb_to_pandoc") @pytest.mark.requires_quarto def test_ipynb_to_quarto( ipynb_to_quarto, no_jupytext_version_number, ): assert_conversion_same_as_mirror(ipynb_to_quarto, "qmd", "ipynb_to_quarto") @pytest.mark.requires_sphinx_gallery def test_ipynb_to_python_sphinx(ipynb_to_sphinx, no_jupytext_version_number): assert_conversion_same_as_mirror(ipynb_to_sphinx, "py:sphinx", "ipynb_to_sphinx") """--------------------------------------------------------------------------------- Part II: text -> ipynb -> text ---------------------------------------------------------------------------------""" def test_Rmd_to_ipynb(rmd_file, no_jupytext_version_number): assert_conversion_same_as_mirror(rmd_file, "ipynb", "Rmd_to_ipynb") @pytest.mark.requires_sphinx_gallery def test_sphinx_to_ipynb(sphinx_file, no_jupytext_version_number): assert_conversion_same_as_mirror(sphinx_file, "ipynb:sphinx", "sphinx_to_ipynb") @pytest.mark.requires_sphinx_gallery def test_sphinx_md_to_ipynb(sphinx_file, no_jupytext_version_number): assert_conversion_same_as_mirror( sphinx_file, {"extension": ".ipynb", "format_name": "sphinx", "rst2md": True}, "sphinx-rst2md_to_ipynb", compare_notebook=True, ) ================================================ FILE: tests/external/rst2md/test_rst2md.py ================================================ import os import pytest from nbformat.v4.nbbase import new_markdown_cell, new_notebook from jupytext import TextFileContentsManager, read, write from jupytext.cli import jupytext @pytest.mark.requires_sphinx_gallery def test_rst2md(tmpdir, cwd_tmpdir): tmp_py = "notebook.py" tmp_ipynb = "notebook.ipynb" # Write notebook in sphinx format nb = new_notebook( cells=[ new_markdown_cell("A short sphinx notebook"), new_markdown_cell(":math:`1+1`"), ] ) write(nb, tmp_py, fmt="py:sphinx") jupytext( [ tmp_py, "--from", "py:sphinx", "--to", "ipynb", "--opt", "rst2md=True", "--opt", "cell_metadata_filter=-all", ] ) assert os.path.isfile(tmp_ipynb) nb = read(tmp_ipynb) assert nb.metadata["jupytext"]["cell_metadata_filter"] == "-all" assert nb.metadata["jupytext"]["rst2md"] is False # Was rst to md conversion effective? assert nb.cells[2].source == "$1+1$" @pytest.mark.requires_sphinx_gallery def test_rst2md_option(tmpdir): tmp_py = str(tmpdir.join("notebook.py")) # Write notebook in sphinx format nb = new_notebook( cells=[ new_markdown_cell("A short sphinx notebook"), new_markdown_cell(":math:`1+1`"), ] ) write(nb, tmp_py, fmt="py:sphinx") cm = TextFileContentsManager() cm.sphinx_convert_rst2md = True cm.root_dir = str(tmpdir) nb2 = cm.get("notebook.py")["content"] # Was rst to md conversion effective? assert nb2.cells[2].source == "$1+1$" assert nb2.metadata["jupytext"]["rst2md"] is False ================================================ FILE: tests/external/simple_external_notebooks/test_read_simple_pandoc.py ================================================ import pytest from nbformat.v4.nbbase import new_markdown_cell, new_notebook import jupytext from jupytext.cli import jupytext as jupytext_cli from jupytext.compare import compare, compare_notebooks from jupytext.pandoc import PandocError @pytest.mark.requires_pandoc def test_pandoc_implicit( cell_id, markdown="""# Lorem ipsum **Lorem ipsum** dolor sit amet, consectetur adipiscing elit. Nunc luctus bibendum felis dictum sodales. ``` code print("hello") ``` """, ): nb = jupytext.reads(markdown, "md:pandoc") markdown2 = jupytext.writes(nb, "md") nb2 = jupytext.reads(markdown2, "md") compare_notebooks(nb2, nb) markdown3 = jupytext.writes(nb2, "md") compare(markdown3, markdown2) @pytest.mark.requires_pandoc def test_pandoc_explicit( markdown="""::: {#cell_id .cell .markdown} # Lorem **Lorem ipsum** dolor sit amet, consectetur adipiscing elit. Nunc luctus bibendum felis dictum sodales. :::""", ): nb = jupytext.reads(markdown, "md") markdown2 = jupytext.writes(nb, "md") compare("\n".join(markdown2.splitlines()[12:]), markdown) @pytest.mark.requires_pandoc def test_pandoc_utf8_in_md( markdown="""::: {#cell_id .cell .markdown} # Utf-8 support This is the greek letter $\\pi$: π :::""", ): nb = jupytext.reads(markdown, "md") markdown2 = jupytext.writes(nb, "md") compare("\n".join(markdown2.splitlines()[12:]), markdown) @pytest.mark.requires_pandoc def test_pandoc_utf8_in_nb( nb=new_notebook( cells=[ new_markdown_cell( """# Utf-8 support This is the greek letter $\\pi$: π""" ) ] ), ): markdown = jupytext.writes(nb, "md:pandoc") nb2 = jupytext.reads(markdown, "md:pandoc") nb2.metadata.pop("jupytext") compare_notebooks(nb, nb2, "md:pandoc") @pytest.mark.requires_no_pandoc def test_meaningfull_error_when_pandoc_is_missing(tmpdir): nb_file = tmpdir.join("notebook.ipynb") jupytext.write(new_notebook(), str(nb_file)) with pytest.raises(PandocError, match="The Pandoc Markdown format requires 'pandoc>=2.7.2'"): jupytext_cli([str(nb_file), "--to", "md:pandoc"]) ================================================ FILE: tests/external/simple_external_notebooks/test_read_simple_quarto.py ================================================ import pytest from nbformat.v4.nbbase import new_code_cell, new_markdown_cell, new_notebook import jupytext from jupytext.compare import compare, compare_notebooks @pytest.mark.requires_quarto def test_qmd_to_ipynb( qmd="""Some text ```{python} 1 + 1 ``` """, nb=new_notebook( cells=[ new_markdown_cell("Some text"), new_code_cell("1 + 1"), ], metadata={ "kernelspec": { "display_name": "python_kernel", "language": "python", "name": "python_kernel", } }, ), ): nb2 = jupytext.reads(qmd, "qmd") compare_notebooks(nb2, nb, fmt="qmd") # after a round trip we do get a yaml header. # here we remove it to make the comparison qmd2 = jupytext.writes(nb, "qmd") qmd2_without_header = qmd2.rsplit("---\n\n", 1)[1] compare(qmd2_without_header, qmd) ================================================ FILE: tests/external/test_marimo.py ================================================ from jupytext.marimo import marimo_py_to_notebook, notebook_to_marimo_py, marimo_version import pytest from nbformat.v4.nbbase import new_notebook, new_code_cell from jupytext.compare import compare, compare_notebooks from jupytext.formats import guess_format @pytest.fixture def py_marimo() -> str: return f"""import marimo __generated_with = "{marimo_version()}" app = marimo.App() @app.cell def _(): x = 1 return if __name__ == "__main__": app.run()""" @pytest.fixture def notebook(): return new_notebook(cells=[new_code_cell("x = 1")]) def test_guess_format(py_marimo): assert guess_format(py_marimo, ".py") == ("marimo", {}) @pytest.mark.requires_marimo def test_notebook_to_py_marimo(py_marimo, notebook): actual = notebook_to_marimo_py(notebook) compare(actual, py_marimo) @pytest.mark.requires_marimo def test_marimo_py_to_notebook(py_marimo, notebook): actual = marimo_py_to_notebook(py_marimo) compare_notebooks(actual, notebook) ================================================ FILE: tests/functional/cli/test_cli.py ================================================ import os import sys import time import unittest.mock as mock import warnings from argparse import ArgumentTypeError from io import StringIO from shutil import copyfile from subprocess import check_call import nbformat import pytest from jupyter_client.kernelspec import find_kernel_specs, get_kernel_spec from jupyter_server.utils import ensure_async from nbformat.v4.nbbase import new_code_cell, new_markdown_cell, new_notebook from jupytext import __version__, read, reads, write, writes from jupytext.cli import jupytext, parse_jupytext_args, str2bool, system from jupytext.compare import compare, compare_notebooks from jupytext.formats import JupytextFormatError, long_form_one_format from jupytext.myst import is_myst_available from jupytext.paired_paths import InconsistentPath, paired_paths from jupytext.pandoc import is_pandoc_available def test_str2bool(): assert str2bool("d") is None assert str2bool("TRUE") is True assert str2bool("0") is False with pytest.raises(ArgumentTypeError): str2bool("UNEXPECTED") def test_cli_single_file(ipynb_py_R_jl_file): assert parse_jupytext_args([ipynb_py_R_jl_file] + ["--to", "py"]).notebooks == [ipynb_py_R_jl_file] def test_cli_multiple_files(ipynb_py_R_jl_files): assert parse_jupytext_args(ipynb_py_R_jl_files + ["--to", "py"]).notebooks == ipynb_py_R_jl_files def test_convert_single_file_in_place(ipynb_py_file, tmpdir): nb_org = str(tmpdir.join(os.path.basename(ipynb_py_file))) copyfile(ipynb_py_file, nb_org) base, ext = os.path.splitext(nb_org) nb_other = base + ".py" jupytext([nb_org, "--to", "py"]) nb1 = read(nb_org) nb2 = read(nb_other) compare_notebooks(nb2, nb1) def test_convert_single_file_in_place_m(ipynb_py_file, tmpdir): nb_org = str(tmpdir.join(os.path.basename(ipynb_py_file))) copyfile(ipynb_py_file, nb_org) base, ext = os.path.splitext(nb_org) for fmt_ext in ("py", "Rmd"): nb_other = base + "." + fmt_ext check_call([sys.executable, "-m", "jupytext", nb_org, "--to", fmt_ext]) nb1 = read(nb_org) nb2 = read(nb_other) compare_notebooks(nb2, nb1) def test_convert_single_file(ipynb_or_rmd_file, tmpdir, capsys): nb_org = str(tmpdir.join(os.path.basename(ipynb_or_rmd_file))) copyfile(ipynb_or_rmd_file, nb_org) nb1 = read(ipynb_or_rmd_file) pynb = writes(nb1, "py") jupytext([nb_org, "--to", "py", "-o", "-"]) out, err = capsys.readouterr() assert err == "" compare(out, pynb) def test_jupytext_version(capsys): jupytext(["--version"]) out, err = capsys.readouterr() assert err == "" compare(out, __version__ + "\n") def test_wildcard(tmpdir): nb1_ipynb = str(tmpdir.join("nb1.ipynb")) nb2_ipynb = str(tmpdir.join("nb2.ipynb")) nb1_py = str(tmpdir.join("nb1.py")) nb2_py = str(tmpdir.join("nb2.py")) write(new_notebook(metadata={"notebook": 1}), nb1_ipynb) write(new_notebook(metadata={"notebook": 2}), nb2_ipynb) os.chdir(str(tmpdir)) jupytext(["nb*.ipynb", "--to", "py"]) assert os.path.isfile(nb1_py) assert os.path.isfile(nb2_py) with pytest.raises(IOError): jupytext(["nb3.ipynb", "--to", "py"]) def test_to_cpluplus(ipynb_cpp_file, tmpdir, capsys): nb_org = str(tmpdir.join(os.path.basename(ipynb_cpp_file))) copyfile(ipynb_cpp_file, nb_org) nb1 = read(nb_org) text_cpp = writes(nb1, "cpp") jupytext([nb_org, "--to", "c++", "--output", "-"]) out, err = capsys.readouterr() assert err == "" compare(out, text_cpp) def test_convert_multiple_file(ipynb_py_files, tmpdir): nb_orgs = [] nb_others = [] for nb_file in ipynb_py_files: nb_org = str(tmpdir.join(os.path.basename(nb_file))) base, ext = os.path.splitext(nb_org) nb_other = base + ".py" copyfile(nb_file, nb_org) nb_orgs.append(nb_org) nb_others.append(nb_other) jupytext(nb_orgs + ["--to", "py"]) for nb_org, nb_other in zip(nb_orgs, nb_others): nb1 = read(nb_org) nb2 = read(nb_other) compare_notebooks(nb2, nb1) def test_error_not_notebook_ext_input(tmpdir, capsys): tmp_file = str(tmpdir.join("notebook.ext")) with open(tmp_file, "w") as fp: fp.write("\n") with pytest.raises(InconsistentPath, match="is not a notebook. Supported extensions are"): jupytext([tmp_file, "--to", "py"]) @pytest.fixture def tmp_ipynb(tmpdir): tmp_file = str(tmpdir.join("notebook.ipynb")) write(new_notebook(), tmp_file) return tmp_file @pytest.fixture def tmp_py(tmpdir): tmp_file = str(tmpdir.join("notebook.py")) with open(tmp_file, "w") as fp: fp.write("\n") return tmp_file def test_error_not_notebook_ext_to(tmp_ipynb): with pytest.raises(JupytextFormatError, match="'ext' is not a notebook extension"): jupytext([tmp_ipynb, "--to", "ext"]) def test_error_not_notebook_ext_output(tmp_ipynb, tmpdir): with pytest.raises( JupytextFormatError, match="Extension '.ext' is not a notebook extension. Please use one of", ): jupytext([tmp_ipynb, "-o", str(tmpdir.join("not.ext"))]) def test_error_not_same_ext(tmp_ipynb, tmpdir): with pytest.raises(InconsistentPath): jupytext([tmp_ipynb, "--to", "py", "-o", str(tmpdir.join("not.md"))]) def test_error_no_action(tmp_ipynb): with pytest.raises(ValueError, match="Please provide one of"): jupytext([tmp_ipynb]) def test_error_update_not_ipynb(tmp_py): with pytest.raises(ValueError, match="--update is only for ipynb files"): jupytext([tmp_py, "--to", "py", "--update"]) def test_error_multiple_input(tmp_ipynb): with pytest.raises(ValueError, match="Please input a single notebook when using --output"): jupytext([tmp_ipynb, tmp_ipynb, "--to", "py", "-o", "notebook.py"]) def test_error_opt_missing_equal(tmp_ipynb): with pytest.raises(ValueError, match="key=value"): jupytext([tmp_ipynb, "--to", "py", "--opt", "missing_equal"]) def test_error_unknown_opt(tmp_ipynb): with pytest.raises(ValueError, match="is not a valid format option"): jupytext([tmp_ipynb, "--to", "py", "--opt", "unknown=true"]) def test_combine_same_version_ok(tmpdir): tmp_ipynb = str(tmpdir.join("notebook.ipynb")) tmp_nbpy = str(tmpdir.join("notebook.py")) tmp_rmd = str(tmpdir.join("notebook.Rmd")) with open(tmp_nbpy, "w") as fp: fp.write( """# --- # jupyter: # jupytext_formats: ipynb,py # jupytext_format_version: '1.2' # --- # New cell """ ) nb = new_notebook(metadata={"jupytext_formats": "ipynb,py"}) write(nb, tmp_ipynb) # to jupyter notebook jupytext([tmp_nbpy, "--to", "ipynb", "--update"]) # test round trip jupytext([tmp_nbpy, "--to", "notebook", "--test"]) # test ipynb to rmd jupytext([tmp_ipynb, "--to", "rmarkdown"]) nb = read(tmp_ipynb) cells = nb["cells"] assert len(cells) == 1 assert cells[0].cell_type == "markdown" assert cells[0].source == "New cell" nb = read(tmp_rmd) cells = nb["cells"] assert len(cells) == 1 assert cells[0].cell_type == "markdown" assert cells[0].source == "New cell" def test_combine_lower_version_raises(tmpdir): tmp_ipynb = str(tmpdir.join("notebook.ipynb")) tmp_nbpy = str(tmpdir.join("notebook.py")) with open(tmp_nbpy, "w") as fp: fp.write( """# --- # jupyter: # jupytext: # formats: ipynb,py:light # text_representation: # extension: .py # format_name: light # format_version: '55.4' # jupytext_version: 42.1.1 # kernelspec: # display_name: Python 3 # language: python # name: python3 # --- # New cell """ ) nb = new_notebook(metadata={"jupytext_formats": "ipynb,py"}) write(nb, tmp_ipynb) with pytest.raises( ValueError, match="The file notebook.py was generated with jupytext version 42.1.1 but you have .* installed. " "Please upgrade jupytext to version 42.1.1, or remove either notebook.py or notebook.ipynb. " "This error occurs because notebook.py is in the light format in version 55.4, " "while jupytext version .* installed at .* can only read the light format in versions .*", ): jupytext([tmp_nbpy, "--to", "ipynb", "--update"]) def test_ipynb_to_py_then_update_test(ipynb_py_file, tmpdir): """Reproduce https://github.com/mwouts/jupytext/issues/83""" tmp_ipynb = str(tmpdir.join("notebook.ipynb")) tmp_nbpy = str(tmpdir.join("notebook.py")) copyfile(ipynb_py_file, tmp_ipynb) jupytext(["--to", "py", tmp_ipynb]) jupytext(["--test", "--update", "--to", "ipynb", tmp_nbpy]) def test_test_to_ipynb_ignore_version_number_414( tmpdir, text="""# --- # jupyter: # jupytext: # text_representation: # extension: .py # format_name: light # format_version: '1.4' # jupytext_version: 1.1.0 # kernelspec: # display_name: Python 3 # language: python # name: python3 # --- # A short markdown cell # Followed by a code cell 2 + 2 """, ): tmp_py = str(tmpdir.join("script.py")) with open(tmp_py, "w") as fp: fp.write(text) assert jupytext(["--test", "--to", "ipynb", tmp_py]) == 0 def test_convert_to_percent_format(ipynb_py_file, tmpdir): tmp_ipynb = str(tmpdir.join("notebook.ipynb")) tmp_nbpy = str(tmpdir.join("notebook.py")) copyfile(ipynb_py_file, tmp_ipynb) jupytext(["--to", "py:percent", tmp_ipynb]) with open(tmp_nbpy) as stream: py_script = stream.read() assert "format_name: percent" in py_script nb1 = read(tmp_ipynb) nb2 = read(tmp_nbpy) compare_notebooks(nb2, nb1) def test_convert_to_percent_format_and_keep_magics(ipynb_py_file, tmpdir): tmp_ipynb = str(tmpdir.join("notebook.ipynb")) tmp_nbpy = str(tmpdir.join("notebook.py")) copyfile(ipynb_py_file, tmp_ipynb) jupytext(["--to", "py:percent", "--opt", "comment_magics=False", tmp_ipynb]) with open(tmp_nbpy) as stream: py_script = stream.read() assert "format_name: percent" in py_script assert "comment_magics: false" in py_script assert "# %%time" not in py_script nb1 = read(tmp_ipynb) nb2 = read(tmp_nbpy) compare_notebooks(nb2, nb1) def test_set_formats(python_file, tmpdir): tmp_py = str(tmpdir.join("notebook.py")) tmp_ipynb = str(tmpdir.join("notebook.ipynb")) copyfile(python_file, tmp_py) jupytext([tmp_py, "--set-formats", "ipynb,py:light"]) nb = read(tmp_ipynb) assert nb.metadata["jupytext"]["formats"] == "ipynb,py:light" def test_update_metadata(python_file, tmpdir, capsys): tmp_py = str(tmpdir.join("notebook.py")) tmp_ipynb = str(tmpdir.join("notebook.ipynb")) copyfile(python_file, tmp_py) jupytext( [ "--to", "ipynb", tmp_py, "--update-metadata", '{"jupytext":{"formats":"ipynb,py:light"}}', ] ) nb = read(tmp_ipynb) assert nb.metadata["jupytext"]["formats"] == "ipynb,py:light" jupytext(["--to", "py", tmp_ipynb, "--update-metadata", '{"jupytext":{"formats":null}}']) nb = read(tmp_py) assert "formats" not in nb.metadata["jupytext"] with pytest.raises(SystemExit): jupytext(["--to", "ipynb", tmp_py, "--update-metadata", '{"incorrect": "JSON"']) out, err = capsys.readouterr() assert "invalid" in err @pytest.mark.requires_user_kernel_python3 def test_set_kernel_inplace(python_file, tmpdir): tmp_py = str(tmpdir.join("notebook.py")) copyfile(python_file, tmp_py) jupytext([tmp_py, "--set-kernel", "-"]) nb = read(tmp_py) kernel_name = nb.metadata["kernelspec"]["name"] cmd = get_kernel_spec(kernel_name).argv[0] assert cmd == "python" or os.path.samefile(cmd, sys.executable) @pytest.mark.requires_user_kernel_python3 def test_set_kernel_auto(python_file, tmpdir): tmp_py = str(tmpdir.join("notebook.py")) tmp_ipynb = str(tmpdir.join("notebook.ipynb")) copyfile(python_file, tmp_py) jupytext(["--to", "ipynb", tmp_py, "--set-kernel", "-"]) nb = read(tmp_ipynb) kernel_name = nb.metadata["kernelspec"]["name"] cmd = get_kernel_spec(kernel_name).argv[0] assert cmd == "python" or os.path.samefile(cmd, sys.executable) @pytest.mark.requires_user_kernel_python3 def test_set_kernel_with_name(python_file, tmpdir): tmp_py = str(tmpdir.join("notebook.py")) tmp_ipynb = str(tmpdir.join("notebook.ipynb")) copyfile(python_file, tmp_py) for kernel in find_kernel_specs(): jupytext(["--to", "ipynb", tmp_py, "--set-kernel", kernel]) nb = read(tmp_ipynb) assert nb.metadata["kernelspec"]["name"] == kernel with pytest.raises(KeyError): jupytext(["--to", "ipynb", tmp_py, "--set-kernel", "non_existing_env"]) def test_paired_paths(ipynb_py_file, tmpdir, capsys): tmp_ipynb = str(tmpdir.join("notebook.ipynb")) nb = read(ipynb_py_file) nb.metadata.setdefault("jupytext", {})["formats"] = "ipynb,_light.py,_percent.py:percent" write(nb, tmp_ipynb) jupytext(["--paired-paths", tmp_ipynb]) out, err = capsys.readouterr() assert not err formats = nb.metadata.get("jupytext", {}).get("formats") assert set(out.splitlines()).union([tmp_ipynb]) == {path for path, _ in paired_paths(tmp_ipynb, "ipynb", formats)} def test_sync(ipynb_py_file, tmpdir, cwd_tmpdir, capsys): tmp_ipynb = "notebook.ipynb" tmp_py = "notebook.py" tmp_rmd = "notebook.Rmd" nb = read(ipynb_py_file) write(nb, tmp_ipynb) # Test that sync issues a warning when the notebook is not paired jupytext(["--sync", tmp_ipynb]) _, err = capsys.readouterr() assert "is not a paired notebook" in err # Now with a pairing information nb.metadata.setdefault("jupytext", {})["formats"] = "py,Rmd,ipynb" write(nb, tmp_ipynb) # Test that missing files are created jupytext(["--sync", tmp_ipynb]) assert os.path.isfile(tmp_py) compare_notebooks(read(tmp_py), nb) assert os.path.isfile(tmp_rmd) compare_notebooks(read(tmp_rmd), nb, "Rmd") write(nb, tmp_rmd, fmt="Rmd") jupytext(["--sync", tmp_ipynb]) nb2 = read(tmp_ipynb) compare_notebooks(nb2, nb, "Rmd", compare_outputs=True) write(nb, tmp_py, fmt="py") jupytext(["--sync", tmp_ipynb]) nb2 = read(tmp_ipynb) compare_notebooks(nb2, nb, compare_outputs=True) # Finally we recreate the ipynb os.remove(tmp_ipynb) time.sleep(0.1) jupytext(["--sync", tmp_py]) nb2 = read(tmp_ipynb) compare_notebooks(nb2, nb) # ipynb must be older than py file, otherwise our Contents Manager will complain assert os.path.getmtime(tmp_ipynb) <= os.path.getmtime(tmp_py) @pytest.mark.requires_pandoc def test_sync_pandoc(ipynb_to_pandoc, tmpdir, cwd_tmpdir, capsys): tmp_ipynb = "notebook.ipynb" tmp_md = "notebook.md" nb = read(ipynb_to_pandoc) write(nb, tmp_ipynb) # Test that sync issues a warning when the notebook is not paired jupytext(["--sync", tmp_ipynb]) _, err = capsys.readouterr() assert "is not a paired notebook" in err # Now with a pairing information nb.metadata.setdefault("jupytext", {})["formats"] = "ipynb,md:pandoc" write(nb, tmp_ipynb) # Test that missing files are created jupytext(["--sync", tmp_ipynb]) assert os.path.isfile(tmp_md) compare_notebooks(read(tmp_md), nb, "md:pandoc") with open(tmp_md) as fp: assert "pandoc" in fp.read() def test_cli_can_infer_jupytext_format(ipynb_py_R_jl_file, ipynb_py_R_jl_ext, tmpdir, cwd_tmpdir): tmp_ipynb = "notebook.ipynb" tmp_text = "notebook" + ipynb_py_R_jl_ext nb = read(ipynb_py_R_jl_file) # Light format to Jupyter notebook write(nb, tmp_text) jupytext(["--to", "notebook", tmp_text]) nb2 = read(tmp_ipynb) compare_notebooks(nb2, nb) # Percent format to Jupyter notebook write(nb, tmp_text, fmt=ipynb_py_R_jl_ext + ":percent") jupytext(["--to", "notebook", tmp_text]) nb2 = read(tmp_ipynb) compare_notebooks(nb2, nb) def test_cli_to_script(ipynb_py_R_jl_file, ipynb_py_R_jl_ext, tmpdir, cwd_tmpdir): tmp_ipynb = "notebook.ipynb" tmp_text = "notebook" + ipynb_py_R_jl_ext nb = read(ipynb_py_R_jl_file) write(nb, tmp_ipynb) jupytext(["--to", "script", tmp_ipynb]) nb2 = read(tmp_text) compare_notebooks(nb2, nb) def test_cli_to_auto(ipynb_py_R_jl_file, ipynb_py_R_jl_ext, tmpdir, cwd_tmpdir): tmp_ipynb = "notebook.ipynb" tmp_text = "notebook" + ipynb_py_R_jl_ext nb = read(ipynb_py_R_jl_file) write(nb, tmp_ipynb) jupytext(["--to", "auto", tmp_ipynb]) nb2 = read(tmp_text) compare_notebooks(nb2, nb) def test_cli_can_infer_jupytext_format_from_stdin(ipynb_py_file, tmpdir, cwd_tmpdir): tmp_ipynb = "notebook.ipynb" tmp_py = "notebook.py" tmp_rmd = "notebook.Rmd" nb = read(ipynb_py_file) # read ipynb notebook on stdin, write to python with open(ipynb_py_file) as fp, mock.patch("sys.stdin", fp): jupytext(["--to", "py:percent", "-o", tmp_py]) nb2 = read(tmp_py) compare_notebooks(nb2, nb) # read python notebook on stdin, write to ipynb with open(tmp_py) as fp, mock.patch("sys.stdin", fp): jupytext(["-o", tmp_ipynb]) nb2 = read(tmp_ipynb) compare_notebooks(nb2, nb) # read ipynb notebook on stdin, write to R markdown with open(ipynb_py_file) as fp, mock.patch("sys.stdin", fp): jupytext(["-o", tmp_rmd]) nb2 = read(tmp_rmd) compare_notebooks(nb2, nb, "Rmd") # read markdown notebook on stdin, write to ipynb with open(tmp_rmd) as fp, mock.patch("sys.stdin", fp): jupytext(["-o", tmp_ipynb]) nb2 = read(tmp_ipynb) compare_notebooks(nb2, nb, "Rmd") @pytest.mark.requires_user_kernel_python3 def test_set_kernel_works_with_pipes_326(capsys): md = """```python 1 + 1 ```""" with mock.patch("sys.stdin", StringIO(md)): jupytext(["--to", "ipynb", "--set-kernel", "-", "-"]) out, err = capsys.readouterr() assert err == "" nb = reads(out, "ipynb") assert "kernelspec" in nb.metadata @pytest.mark.filterwarnings("ignore:The --pre-commit argument is deprecated") def test_cli_expect_errors(tmp_ipynb): with pytest.raises(ValueError): jupytext([]) with pytest.raises(ValueError): jupytext(["--sync"]) with pytest.raises(ValueError): jupytext([tmp_ipynb, tmp_ipynb, "--paired-paths"]) with pytest.raises(ValueError): jupytext(["--pre-commit", "notebook.ipynb"]) with pytest.raises(ValueError): jupytext(["notebook.ipynb", "--from", "py:percent", "--to", "md"]) with pytest.raises(ValueError): jupytext([]) with pytest.raises((SystemExit, TypeError)): # SystemExit on Windows, TypeError on Linux system("jupytext", ["notebook.ipynb", "--from", "py:percent", "--to", "md"]) @pytest.mark.filterwarnings( "error", "ignore:You might have passed a file name to the '--to' option, " "when a format description was expected. " "Maybe you want to use the '-o' option instead?", ) def test_format_prefix_suffix(tmpdir, cwd_tmpdir): os.makedirs("notebooks") tmp_ipynb = "notebooks/notebook_name.ipynb" tmp_py = "scripts/notebook_name.py" write(new_notebook(), tmp_ipynb) jupytext([tmp_ipynb, "--to", "../scripts//py"]) assert os.path.isfile(tmp_py) os.remove(tmp_py) jupytext([tmp_ipynb, "--to", "scripts//py", "--from", "notebooks//ipynb"]) assert os.path.isfile(tmp_py) os.remove(tmp_py) tmp_ipynb = "notebooks/nb_prefix_notebook_name.ipynb" tmp_py = "scripts/script_prefix_notebook_name.py" write(new_notebook(), tmp_ipynb) jupytext( [ tmp_ipynb, "--to", "scripts/script_prefix_/py", "--from", "notebooks/nb_prefix_/ipynb", ] ) assert os.path.isfile(tmp_py) os.remove(tmp_py) tmp_ipynb = "notebooks/nb_prefix_notebook_name_nb_suffix.ipynb" tmp_py = "scripts/script_prefix_notebook_name_script_suffix.py" write(new_notebook(), tmp_ipynb) jupytext( [ tmp_ipynb, "--to", "scripts/script_prefix_/_script_suffix.py", "--from", "notebooks/nb_prefix_/_nb_suffix.ipynb", ] ) assert os.path.isfile(tmp_py) os.remove(tmp_py) def test_cli_sync_file_with_suffix(tmpdir, cwd_tmpdir): tmp_ipynb = "notebook.ipynb" tmp_pct_py = "notebook.pct.py" tmp_lgt_py = "notebook.lgt.py" tmp_rmd = "notebook.Rmd" nb = new_notebook( cells=[new_code_cell(source="1+1")], metadata={"jupytext": {"formats": "ipynb,.pct.py:percent,.lgt.py:light,Rmd"}}, ) write(nb, tmp_pct_py, fmt=".pct.py:percent") jupytext(["--sync", tmp_pct_py]) assert os.path.isfile(tmp_lgt_py) assert os.path.isfile(tmp_rmd) assert os.path.isfile(tmp_ipynb) jupytext(["--sync", tmp_lgt_py]) jupytext(["--sync", tmp_ipynb]) with open(tmp_lgt_py) as fp: assert fp.read().splitlines()[-2:] == ["", "1+1"] with open(tmp_pct_py) as fp: fp.read().splitlines()[-3:] == ["", "# %%", "1+1"] with open(tmp_rmd) as fp: fp.read().splitlines()[-4:] == ["", "```{python}", "1+1", "```"] def test_cli_sync_file_with_prefix_974(tmp_path, python_notebook): """Only the files that are in the example directory and that start with 'example' should be paired""" (tmp_path / "pyproject.toml").write_text( """[tool.jupytext] formats = "examples//example/ipynb,examples//example/py:percent" """ ) write(python_notebook, tmp_path / "example_notebook.ipynb") (tmp_path / "examples" / "folder1").mkdir(parents=True) write(python_notebook, tmp_path / "examples/folder1/utils.py") write(python_notebook, tmp_path / "examples/folder1/example_paired.ipynb") jupytext( [ "--sync", str(tmp_path / "example_notebook.ipynb"), str(tmp_path / "examples/folder1/utils.py"), str(tmp_path / "examples/folder1/example_paired.ipynb"), ] ) assert not (tmp_path / "example_notebook.py").exists(), "Not in the 'examples' directory" assert not (tmp_path / "examples/folder1/utils_not_paired.ipynb").exists(), "Not with the 'example' prefix" assert (tmp_path / "examples/folder1/example_paired.py").exists(), "Paired" def test_remove_jupytext_metadata(tmpdir, cwd_tmpdir): tmp_ipynb = "notebook.ipynb" nb = new_notebook( metadata={ "jupytext": { "main_language": "python", "text_representation": { "extension": ".md", "format_name": "markdown", "format_version": "1.0", "jupytext_version": "0.8.6", }, } } ) nbformat.write(nb, tmp_ipynb, version=nbformat.NO_CONVERT) # Jupytext removes the 'text_representation' information from the notebook jupytext([tmp_ipynb, "--update-metadata", '{"jupytext":{"main_language":null}}']) nb2 = read(tmp_ipynb) assert not nb2.metadata nbformat.write(nb, tmp_ipynb, version=nbformat.NO_CONVERT) jupytext([tmp_ipynb, "--set-formats", "ipynb,py:light"]) nb2 = read(tmp_ipynb) assert nb2.metadata == {"jupytext": {"formats": "ipynb,py:light", "main_language": "python"}} @pytest.mark.parametrize("fmt", ["py:light", "py:percent", "md"]) def test_convert_and_update_preserves_notebook(ipynb_py_file, fmt, tmpdir, cwd_tmpdir): # cannot encode magic parameters in markdown yet if ("magic" in ipynb_py_file or "LateX" in ipynb_py_file) and fmt == "md": return tmp_ipynb = "notebook.ipynb" copyfile(ipynb_py_file, tmp_ipynb) ext = long_form_one_format(fmt)["extension"] tmp_text = "notebook" + ext jupytext(["--to", fmt, tmp_ipynb]) jupytext(["--to", "ipynb", "--update", tmp_text]) nb_org = read(ipynb_py_file) nb_now = read(tmp_ipynb) # The cell marker changes from """ to r""" on the LateX notebook #836 if "LateX" in ipynb_py_file and fmt == "py:percent": last_cell = nb_now.cells[-1] last_cell.metadata["cell_marker"] = last_cell.metadata["cell_marker"][1:] compare(nb_now, nb_org) def test_incorrect_notebook_causes_early_exit(tmpdir, cwd_tmpdir): incorrect_ipynb = "incorrect.ipynb" incorrect_md = "incorrect.md" with open(incorrect_ipynb, "w") as fp: fp.write('{"nbformat": 4, "nbformat_minor": 2, "metadata": {INCORRECT}, "cells": []}') correct_ipynb = "correct.ipynb" correct_md = "correct.md" with open(correct_ipynb, "w") as fp: fp.write('{"nbformat": 4, "nbformat_minor": 2, "metadata": {}, "cells": []}') with pytest.raises(nbformat.reader.NotJSONError, match="Notebook does not appear to be JSON"): jupytext([incorrect_ipynb, correct_ipynb, "--to", "md"]) assert not os.path.exists(incorrect_md) assert not os.path.exists(correct_md) def test_warn_only_skips_incorrect_notebook(tmpdir, cwd_tmpdir, capsys): incorrect_ipynb = "incorrect.ipynb" incorrect_md = "incorrect.md" with open(incorrect_ipynb, "w") as fp: fp.write('{"nbformat": 4, "nbformat_minor": 2, "metadata": {INCORRECT}, "cells": []}') correct_ipynb = "correct.ipynb" correct_md = "correct.md" with open(correct_ipynb, "w") as fp: fp.write('{"nbformat": 4, "nbformat_minor": 2, "metadata": {}, "cells": []}') jupytext([incorrect_ipynb, correct_ipynb, "--to", "md", "--warn-only"]) _, err = capsys.readouterr() assert "Notebook does not appear to be JSON" in str(err) assert not os.path.exists(incorrect_md) assert os.path.exists(correct_md) @pytest.mark.parametrize("fmt", ["md", "Rmd", "py", "py:percent", "py:hydrogen"]) def test_339_ipynb(tmpdir, cwd_tmpdir, fmt): tmp_ipynb = "test.ipynb" nb = new_notebook(cells=[new_code_cell("cat = 42")]) nbformat.write(nb, tmp_ipynb) assert jupytext([tmp_ipynb, "--to", fmt, "--test-strict"]) == 0 def test_339_py(tmpdir, cwd_tmpdir): """Test that an incorrect round trip conversion on the text file is detected""" tmp_py = "test.py" with open(tmp_py, "w") as fp: fp.write( """# %% cat = 42 """ ) def erroneous_is_magic(line, language, comment_magics, explicitly_code): return "cat" in line with mock.patch("jupytext.magics.is_magic", erroneous_is_magic): assert jupytext([tmp_py, "--to", "ipynb", "--test-strict"]) != 0 def test_339_require_to(tmpdir, cwd_tmpdir): """Test that the `--to` argument is asked for when a `--test` command is provided""" with pytest.raises(ValueError, match="--to"): jupytext(["test.py", "--test-strict"]) def test_399_to_script_then_set_formats(tmpdir, cwd_tmpdir): nb = new_notebook(cells=[new_code_cell("1 + 1")]) tmp_py = "notebook_first.py" tmp_ipynb = "notebook_first.ipynb" nbformat.write(nb, tmp_ipynb) jupytext(["--to", "py:percent", tmp_ipynb]) assert os.path.isfile(tmp_py) jupytext(["--set-formats", "ipynb,py:percent", tmp_ipynb]) def test_set_format_with_subfolder(tmpdir, cwd_tmpdir): """Here we reproduce issue #450""" py = """# %% [markdown] # A short notebook """ tmpdir.mkdir("python_scripts").join("01_tabular_data_exploration.py").write(py) jupytext( [ "--set-formats", "python_scripts//py:percent,notebooks//ipynb", "python_scripts/01_tabular_data_exploration.py", ] ) def skip_if_format_missing(format_name): """Check whether MyST or Pandoc are available and skip if not""" if format_name == "md:myst" and not is_myst_available(): pytest.skip("MyST markdown is not available") elif format_name == "md:pandoc" and not is_pandoc_available(): pytest.skip("Pandoc is not available") @pytest.mark.parametrize("format_name", ["md", "md:myst", "md:pandoc"]) def test_create_header_with_set_formats(format_name, cwd_tmpdir, tmpdir): """Test jupytext --set-formats #485""" skip_if_format_missing(format_name) tmpdir.join("notebook.md").write("\n") jupytext(["--set-formats", format_name, "notebook.md"]) nb = read("notebook.md") assert nb["metadata"]["jupytext"]["formats"] == format_name @pytest.mark.requires_user_kernel_python3 @pytest.mark.parametrize("format_name", ["md", "md:myst", "md:pandoc", "py:light", "py:percent"]) def test_create_header_with_set_formats_and_set_kernel(format_name, tmpdir, cwd_tmpdir): """Test jupytext --set-formats --set-kernel - #485""" skip_if_format_missing(format_name) ext = format_name.split(":")[0] tmp_nb = "notebook." + ext tmpdir.join(tmp_nb).write("\n") jupytext(["--set-formats", format_name, "--set-kernel", "-", tmp_nb]) nb = read(tmp_nb) assert nb["metadata"]["jupytext"]["formats"] == format_name assert "kernelspec" in nb["metadata"] def test_set_option_split_at_heading(tmpdir, cwd_tmpdir): tmp_rmd = tmpdir.join("notebook.Rmd") tmp_rmd.write( """A paragraph # H1 Header """ ) jupytext(["notebook.Rmd", "--opt", "split_at_heading=true"]) assert "split_at_heading: true" in tmp_rmd.read() nb = read("notebook.Rmd") nb_expected = new_notebook(cells=[new_markdown_cell("A paragraph"), new_markdown_cell("# H1 Header")]) compare_notebooks(nb, nb_expected) def test_pair_in_tree(tmpdir): nb_file = tmpdir.mkdir("notebooks").mkdir("subfolder").join("example.ipynb") py_file = tmpdir.mkdir("scripts").mkdir("subfolder").join("example.py") write(new_notebook(cells=[new_markdown_cell("A markdown cell")]), str(nb_file)) jupytext(["--set-formats", "notebooks///ipynb,scripts///py:percent", str(nb_file)]) assert py_file.exists() assert "A markdown cell" in py_file.read() def test_pair_in_tree_and_parent(tmpdir): nb_file = tmpdir.mkdir("notebooks").mkdir("subfolder").mkdir("a").mkdir("b").join("example.ipynb") py_file = tmpdir.mkdir("scripts").mkdir("subfolder").mkdir("c").join("example.py") write(new_notebook(cells=[new_markdown_cell("A markdown cell")]), str(nb_file)) jupytext(["--set-formats", "notebooks//a/b//ipynb,scripts//c//py:percent", str(nb_file)]) assert py_file.exists() assert "A markdown cell" in py_file.read() @pytest.mark.requires_pandoc def test_sync_pipe_config(tmpdir): """Sync a notebook to a script paired in a tree, and reformat the markdown cells using pandoc""" tmpdir.join("jupytext.toml").write( """# By default, the notebooks in this repository are in the notebooks subfolder # and they are paired to scripts in the script subfolder. formats = "notebooks///ipynb,scripts///py:percent" """ ) nb_file = tmpdir.mkdir("notebooks").join("wrap_markdown.ipynb") long_text = "This is a " + ("very " * 24) + "long sentence." assert len(long_text) > 100 nb = new_notebook(cells=[new_markdown_cell(long_text)]) write(nb, str(nb_file)) jupytext( [ "--sync", "--pipe-fmt", "ipynb", "--pipe", "pandoc --from ipynb --to ipynb --markdown-headings=atx", str(nb_file), ] ) py_text = tmpdir.join("scripts").join("wrap_markdown.py").read() assert "This is a very very" in py_text for line in py_text.splitlines(): assert len(line) <= 79 nb = read(nb_file, as_version=4) text = nb.cells[0].source assert len(text.splitlines()) == 3 assert text != long_text def test_sync_script_dotdot_folder_564(tmpdir): """Reproduce the setting of issue #564""" nb_file = tmpdir.mkdir("colabs").mkdir("colabs").join("rigid_object_tutorial.ipynb") py_file = tmpdir.join("colabs").mkdir("nb_python").join("rigid_object_tutorial.py") py_file.write("1 + 1\n") jupytext(["--set-formats", "../nb_python//py:percent,../colabs//ipynb", str(py_file)]) assert nb_file.exists() jupytext(["--sync", str(py_file)]) jupytext(["--sync", str(nb_file)]) def test_jupytext_to_file_emits_a_warning(tmpdir): """The user may type jupytext notebook.ipynb --to script.py meaning jupytext notebook.ipynb -o script.py """ os.chdir(str(tmpdir)) nb_file = tmpdir.join("notebook.ipynb") write(new_notebook(), str(nb_file)) with warnings.catch_warnings(): warnings.simplefilter("error") jupytext(["notebook.ipynb", "-o", "script.py"]) with pytest.warns(UserWarning, match="Maybe you want to use the '-o' option"): jupytext(["notebook.ipynb", "--to", "script.py"]) def test_jupytext_set_formats_file_gives_an_informative_error(tmpdir, cwd_tmpdir): """The user may type jupytext --set-formats notebook.md meaning jupytext --sync notebook.md """ cfg_file = tmpdir.join("jupytext.toml") cfg_file.write('formats = "md,ipynb,py:percent"') md_file = tmpdir.join("notebook.md") py_file = tmpdir.join("notebook.py") nb_file = tmpdir.join("notebook.ipynb") md_file.write("Some text") with warnings.catch_warnings(): warnings.simplefilter("error") jupytext(["--sync", "notebook.md"]) assert py_file.exists() assert nb_file.exists() with pytest.raises(ValueError, match="jupytext --sync notebook.md"): jupytext(["--set-formats", "notebook.md"]) # Remove the config file, otherwise test_jupytext_jupyter_fs_metamanager fails later on! cfg_file.remove() def test_diff(tmpdir, cwd_tmpdir, capsys): write(new_notebook(cells=[new_code_cell("1 + 1")]), "test.ipynb") write(new_notebook(cells=[new_code_cell("2 + 2")]), "test.py", fmt="py:percent") jupytext(["--diff", "test.py", "test.ipynb"]) captured = capsys.readouterr() assert "-2 + 2\n+1 + 1" in captured.out def test_show_changes(tmpdir, cwd_tmpdir, capsys): write(new_notebook(cells=[new_code_cell("1 + 1")]), "test.ipynb") write(new_notebook(cells=[new_code_cell("2 + 2")]), "test.py", fmt="py:percent") jupytext(["--to", "py:percent", "test.ipynb", "--show-changes"]) captured = capsys.readouterr() assert "-2 + 2\n+1 + 1" in captured.out def test_glob_recursive(tmpdir, cwd_tmpdir): tmpdir.mkdir("subfolder").join("test.py").write("1 + 1\n") tmpdir.join("test.py").write("2 + 2\n") jupytext(["--to", "ipynb", "**/*.py"]) assert tmpdir.join("test.ipynb").isfile() assert tmpdir.join("subfolder").join("test.ipynb").isfile() def test_jupytext_sync_preserves_cell_ids(tmpdir, cwd_tmpdir, notebook_with_outputs): write(notebook_with_outputs, "test.ipynb") # Sync with a py file, this should not change the cell id jupytext(["--set-formats", "ipynb,py:percent", "test.ipynb"]) nb = read("test.ipynb") assert nb.cells[0].source == "1+1" assert nb.cells[0].id == notebook_with_outputs.cells[0].id # Change the py file and sync. This should not change the cell id neither py_nb = tmpdir.join("test.py") py = py_nb.read() py_nb.write(py.replace("1+1", "2+2")) jupytext(["--sync", "test.ipynb"]) nb = read("test.ipynb") assert nb.cells[0].source == "2+2" assert nb.cells[0].id == notebook_with_outputs.cells[0].id def test_jupytext_update_preserves_cell_ids(tmpdir, cwd_tmpdir, notebook_with_outputs): write(notebook_with_outputs, "test.ipynb") # Sync with a py file, this should not change the cell id jupytext(["--to", "py:percent", "test.ipynb"]) nb = read("test.ipynb") assert nb.cells[0].source == "1+1" assert nb.cells[0].id == notebook_with_outputs.cells[0].id # Change the py file and update the ipynb file. # This should not change the cell id neither py_nb = tmpdir.join("test.py") py = py_nb.read() py_nb.write(py.replace("1+1", "2+2")) jupytext(["--to", "notebook", "--update", "test.py"]) nb = read("test.ipynb") assert nb.cells[0].source == "2+2" assert nb.cells[0].id == notebook_with_outputs.cells[0].id def test_jupytext_to_ipynb_suggests_update(tmpdir, cwd_tmpdir, capsys): tmpdir.join("test.py").write("1 + 1\n") jupytext(["--to", "ipynb", "test.py"]) capture = capsys.readouterr() assert "update" not in capture.out jupytext(["--to", "ipynb", "test.py"]) capture = capsys.readouterr() assert "update" in capture.out @pytest.mark.parametrize("formats", ["", "py:percent", "py", "py:percent,ipynb"]) def test_jupytext_to_ipynb_does_not_update_timestamp_if_output_not_in_pair( tmpdir, cwd_tmpdir, python_notebook, capsys, formats ): # Write a text notebook nb = python_notebook if formats: nb.metadata["jupytext"] = {"formats": formats} test_py = tmpdir.join("test.py") write(nb, str(test_py)) # make it read-only test_py.chmod(0o444) # py -> ipynb if "ipynb" not in formats: jupytext(["--to", "ipynb", "test.py"]) else: jupytext(["--to", "ipynb", "test.py", "-o", "another.ipynb"]) capture = capsys.readouterr() assert "Updating the timestamp" not in capture.out @pytest.mark.parametrize("formats", ["py:percent", "py", None]) def test_jupytext_to_ipynb_does_not_update_timestamp_if_not_paired(tmpdir, cwd_tmpdir, python_notebook, capsys, formats): # Write a text notebook nb = python_notebook if formats: nb.metadata["jupytext"] = {"formats": formats} test_py = tmpdir.join("test.py") write(nb, str(test_py)) # make it read-only test_py.chmod(0o444) # py -> ipynb jupytext(["--to", "ipynb", "test.py"]) capture = capsys.readouterr() assert "Updating the timestamp" not in capture.out @pytest.mark.asyncio @pytest.mark.parametrize("formats", ["ipynb,py", "py:percent", "py:light", None]) async def test_use_source_timestamp(tmpdir, cwd_tmpdir, python_notebook, capsys, formats, cm): # Write a text notebook nb = python_notebook if formats: nb.metadata["jupytext"] = {"formats": formats} test_py = tmpdir.join("test.py") test_ipynb = tmpdir.join("test.ipynb") write(nb, str(test_py)) src_timestamp = test_py.stat().mtime # Wait... time.sleep(0.1) # py -> ipynb jupytext(["--to", "ipynb", "test.py", "--use-source-timestamp"]) capture = capsys.readouterr() assert "Updating the timestamp" not in capture.out dest_timestamp = test_ipynb.stat().mtime # on Mac OS the dest_timestamp is truncated at the microsecond (#790) assert src_timestamp - 1e-6 <= dest_timestamp <= src_timestamp # Make sure that we can open the file in Jupyter cm.outdated_text_notebook_margin = 0.001 cm.root_dir = str(tmpdir) # No error here await ensure_async(cm.get("test.ipynb")) # But now if we don't use --use-source-timestamp jupytext(["--to", "ipynb", "test.py"]) os.utime(test_py, (src_timestamp, src_timestamp)) # Then we can't open paired notebooks if formats == "ipynb,py:percent": from tornado.web import HTTPError with pytest.raises(HTTPError, match="is more recent than test.py"): await ensure_async(cm.get("test.ipynb")) else: await ensure_async(cm.get("test.ipynb")) def test_round_trip_with_null_metadata_792(tmpdir, cwd_tmpdir, python_notebook): nb = python_notebook nb.metadata.kernelspec = { "argv": ["python", "-m", "ipykernel_launcher", "-f", "{connection_file}"], "display_name": "Python 3", "env": None, "interrupt_mode": "signal", "language": "python", "metadata": None, "name": "python3", } write(nb, "test.ipynb") jupytext(["--to", "py:percent", "test.ipynb"]) jupytext(["--to", "ipynb", "test.py"]) nb = read("test.ipynb") assert nb.metadata.kernelspec.env is None def test_set_shebang_with_update_metadata(tmp_path, python_notebook): tmp_py = tmp_path / "nb.py" write(python_notebook, tmp_py, fmt="py:percent") jupytext( [ str(tmp_py), "--update-metadata", '{"jupytext":{"executable":"/usr/bin/python"}}', ] ) assert tmp_py.read_text().startswith("#!/usr/bin/python") @pytest.mark.parametrize("compare_ids", [False, True]) @pytest.mark.parametrize("compare_outputs", [False, True]) def test_set_formats_does_not_override_existing_ipynb(tmp_path, notebook_with_outputs, compare_ids, compare_outputs): tmp_py = tmp_path / "nb.py" tmp_ipynb = tmp_path / "nb.ipynb" write(notebook_with_outputs, tmp_ipynb) jupytext([str(tmp_ipynb), "--set-formats", "ipynb,py:percent"]) jupytext([str(tmp_py), "--set-formats", "ipynb,py:percent"]) nb = read(tmp_ipynb) compare_notebooks( nb, notebook_with_outputs, compare_ids=compare_ids, compare_outputs=compare_outputs, ) @pytest.mark.requires_myst @pytest.mark.parametrize( "header", [ "", """--- jupytext: text_representation: extension: .md format_name: myst kernelspec: display_name: ipython3 language: python name: ipython3 --- """, ], ) def test_lexer_is_preserved_in_round_trips( tmp_path, no_jupytext_version_number, header, text="""```{code-cell} ipython3 1 + 1 ``` """, ): text = header + text tmp_md = tmp_path / "notebook.md" tmp_md.write_text(text) jupytext(["--to", "myst", str(tmp_md)]) assert tmp_md.read_text() == text @pytest.mark.requires_black def test_pipe_with_quiet_does_not_print(tmp_path, capsys): tmp_py = tmp_path / "nb.py" tmp_py.write_text("# %%\n1+1\n") jupytext(["--quiet", "--pipe", "black", str(tmp_py)]) captured = capsys.readouterr() assert captured.out == "" assert captured.err == "" assert tmp_py.read_text() == "# %%\n1 + 1\n" def test_update_formats_1386(python_notebook, tmp_path, capsys): """ Test that we can change the formats in an already paired notebook """ tmp_py = tmp_path / "notebook.py" tmp_md = tmp_path / "notebook.md" tmp_ipynb = tmp_path / "notebook.ipynb" write(python_notebook, tmp_py, fmt="py:percent") formats = "py:percent,md" jupytext([str(tmp_py), "--set-formats", formats]) # We need to update all the files, not only their timestamps capture = capsys.readouterr() assert "Updating the timestamp" not in capture.out # Each paired file should have the new formats assert read(tmp_py)["metadata"]["jupytext"]["formats"] == formats assert read(tmp_md)["metadata"]["jupytext"]["formats"] == formats # The issue occurred when the py file was older than the md file current_time = time.time() os.utime(tmp_py, (current_time - 1, current_time - 1)) os.utime(tmp_md, (current_time, current_time)) formats = "ipynb,py:percent,md" jupytext([str(tmp_py), "--set-formats", formats]) # We need to update all the files, not only their timestamps capture = capsys.readouterr() assert "Updating the timestamp" not in capture.out # And each paired file should have the new formats assert read(tmp_py)["metadata"]["jupytext"]["formats"] == formats assert read(tmp_md)["metadata"]["jupytext"]["formats"] == formats assert read(tmp_ipynb)["metadata"]["jupytext"]["formats"] == formats def test_paired_paths_from_notebook_metadata(tmp_path, python_notebook, capsys): ipynb_notebook_path = tmp_path / "notebook.ipynb" python_notebook.metadata["jupytext"] = {"formats": "ipynb,py:percent,md"} write(python_notebook, ipynb_notebook_path) jupytext([str(ipynb_notebook_path), "--paired-paths"]) capture = capsys.readouterr() paired_paths = capture.out.strip().split("\n") assert paired_paths == [ str(tmp_path / "notebook.py"), str(tmp_path / "notebook.md"), ], paired_paths def test_paired_paths_from_config(tmp_path, python_notebook, capsys): ipynb_notebook_path = tmp_path / "notebook.ipynb" write(python_notebook, ipynb_notebook_path) (tmp_path / "jupytext.toml").write_text('''formats="ipynb,py:percent,md"''') jupytext([str(ipynb_notebook_path), "--paired-paths"]) capture = capsys.readouterr() paired_paths = capture.out.strip().split("\n") assert paired_paths == [ str(tmp_path / "notebook.py"), str(tmp_path / "notebook.md"), ], paired_paths @pytest.mark.parametrize("with_config", [False, True]) def test_sync_keeps_simple_python_file_unchanged(tmp_path, with_config: bool): """Test that jupytext --sync on a simple Python file leaves it unchanged, even if a Jupytext configuration has formats=ipynb,py:percent """ # Create a simple Python file without jupytext metadata if with_config: config_file = tmp_path / "jupytext.toml" config_file.write_text('formats = "ipynb,py:percent"') py_file = tmp_path / "simple.py" py_content = '''#!/usr/bin/env python3 """A simple Python script""" def hello(): print("Hello, world!") if __name__ == "__main__": hello() ''' py_file.write_text(py_content) # Record original timestamp and content original_mtime = py_file.stat().st_mtime original_content = py_file.read_text() # Wait a bit to ensure timestamp would change if file was modified time.sleep(0.1) # Run jupytext --sync on the file jupytext(["--sync", str(py_file)]) # Verify file is unchanged final_mtime = py_file.stat().st_mtime final_content = py_file.read_text() assert final_mtime == original_mtime, "File timestamp should be unchanged" assert final_content == original_content, "File content should be unchanged" # Verify no additional files were created files_in_dir = list(tmp_path.iterdir()) if with_config: assert len(files_in_dir) == 2, f"Expected only 2 files, found: {[f.name for f in files_in_dir]}" assert set(files_in_dir) == {py_file, config_file} else: assert len(files_in_dir) == 1, f"Expected only 1 file, found: {[f.name for f in files_in_dir]}" assert files_in_dir[0] == py_file def test_set_formats_pairing_in_subfolders(tmp_path, python_notebook): """Test that jupytext --set-formats works with subfolders, including on Windows (#1028)""" ipynb_notebook_dir = tmp_path / "notebooks" / "subfolder" ipynb_notebook_dir.mkdir(parents=True) ipynb_notebook_path = ipynb_notebook_dir / "notebook.ipynb" write(python_notebook, ipynb_notebook_path) jupytext([str(ipynb_notebook_path), "--set-formats", "notebooks///ipynb,scripts///py:percent"]) assert (tmp_path / "scripts" / "subfolder" / "notebook.py").exists() def test_sync_in_subfolders(tmp_path, python_notebook): """Test that jupytext --sync works with subfolders, including on Windows (#1028)""" ipynb_notebook_dir = tmp_path / "notebooks" / "subfolder" ipynb_notebook_dir.mkdir(parents=True) ipynb_notebook_path = ipynb_notebook_dir / "notebook.ipynb" write(python_notebook, ipynb_notebook_path) (tmp_path / "jupytext.toml").write_text("""[formats] "notebooks/" = "ipynb" "scripts/" = "py:percent" """) jupytext([str(ipynb_notebook_path), "--sync"]) assert (tmp_path / "scripts" / "subfolder" / "notebook.py").exists() ================================================ FILE: tests/functional/cli/test_cli_config.py ================================================ import nbformat import pytest from nbformat.v4.nbbase import new_code_cell, new_notebook from jupytext.cli import jupytext from jupytext.compare import compare from jupytext.header import header_to_metadata_and_cell from jupytext.jupytext import read, write def test_pairing_through_config_leaves_ipynb_unmodified(tmpdir): cfg_file = tmpdir.join(".jupytext.yml") nb_file = tmpdir.join("notebook.ipynb") py_file = tmpdir.join("notebook.py") cfg_file.write("formats: 'ipynb,py'\n") nbformat.write(new_notebook(), str(nb_file)) jupytext([str(nb_file), "--sync"]) assert nb_file.isfile() assert py_file.isfile() nb = nbformat.read(nb_file, as_version=4) assert "jupytext" not in nb.metadata def test_formats(tmpdir): tmpdir.join(".jupytext").write( '''# Default pairing formats = "ipynb,py"''' ) test = tmpdir.join("test.py") test.write("1 + 1\n") jupytext([str(test), "--sync"]) assert tmpdir.join("test.ipynb").isfile() def test_formats_with_suffix(tmpdir): tmpdir.join(".jupytext").write('formats = "ipynb,.nb.py"') test = tmpdir.join("test.py") test.write("1 + 1\n") test_nb = tmpdir.join("test.nb.py") test_nb.write("1 + 1\n") jupytext([str(test), "--sync"]) assert not tmpdir.join("test.ipynb").isfile() jupytext([str(test_nb), "--sync"]) assert tmpdir.join("test.ipynb").isfile() def test_formats_does_not_apply_to_config_file(tmpdir): config = tmpdir.join(".jupytext.py") config.write('c.formats = "ipynb,py"') test = tmpdir.join("test.py") test.write("1 + 1\n") jupytext([str(test), str(config), "--sync"]) assert tmpdir.join("test.ipynb").isfile() assert not tmpdir.join(".jupytext.ipynb").isfile() def test_preferred_jupytext_formats_save(tmpdir): tmpdir.join(".jupytext.yml").write("preferred_jupytext_formats_save: jl:percent") tmp_ipynb = tmpdir.join("notebook.ipynb") tmp_jl = tmpdir.join("notebook.jl") nb = new_notebook(cells=[new_code_cell("1 + 1")], metadata={"jupytext": {"formats": "ipynb,jl"}}) write(nb, str(tmp_ipynb)) jupytext([str(tmp_ipynb), "--sync"]) with open(str(tmp_jl)) as stream: text_jl = stream.read() # Parse the YAML header metadata, _, _, _ = header_to_metadata_and_cell(text_jl.splitlines(), "#", "") assert metadata["jupytext"]["formats"] == "ipynb,jl:percent" @pytest.mark.parametrize( "config", [ # Way 1: preferred_jupytext_formats_save + formats """preferred_jupytext_formats_save: "python//py:percent" formats: "ipynb,python//py" """, # Way 2: formats "formats: ipynb,python//py:percent", ], ) def test_save_using_preferred_and_default_format(config, tmpdir): tmpdir.join(".jupytext.yml").write(config) tmp_ipynb = tmpdir.join("notebook.ipynb") tmp_py = tmpdir.join("python").join("notebook.py") nb = new_notebook(cells=[new_code_cell("1 + 1")]) write(nb, str(tmp_ipynb)) jupytext([str(tmp_ipynb), "--sync"]) # read py file nb_py = read(str(tmp_py)) assert nb_py.metadata["jupytext"]["text_representation"]["format_name"] == "percent" def test_hide_notebook_metadata(tmpdir, no_jupytext_version_number): tmpdir.join(".jupytext").write("hide_notebook_metadata = true") tmp_ipynb = tmpdir.join("notebook.ipynb") tmp_md = tmpdir.join("notebook.md") nb = new_notebook(cells=[new_code_cell("1 + 1")], metadata={"jupytext": {"formats": "ipynb,md"}}) write(nb, str(tmp_ipynb)) jupytext([str(tmp_ipynb), "--sync"]) with open(str(tmp_md)) as stream: text_md = stream.read() compare( text_md, """ ```python 1 + 1 ``` """, ) def test_cli_config_on_windows_issue_629(tmpdir): cfg_file = tmpdir.join("jupytext.yml") cfg_file.write( """formats: "notebooks///ipynb,scripts///py:percent" notebook_metadata_filter: "jupytext" """ ) tmpdir.mkdir("scripts").join("test.py").write("# %%\n 1+1\n") jupytext(["--sync", str(tmpdir.join("scripts").join("*.py"))]) assert tmpdir.join("notebooks").join("test.ipynb").exists() def test_sync_config_does_not_create_formats_metadata(tmpdir, cwd_tmpdir, python_notebook): tmpdir.join("jupytext.yml").write( """formats: "ipynb,py:percent" """ ) write(python_notebook, "test.ipynb") jupytext(["--sync", "test.ipynb"]) nb = read("test.py") assert "formats" not in nb.metadata["jupytext"] def test_multiple_formats_771(tmpdir, cwd_tmpdir, python_notebook): tmpdir.join("jupytext.toml").write( """formats = "notebooks///ipynb,notebooks///py,scripts///py:percent" """ ) notebooks_dir = tmpdir.mkdir("notebooks") scripts_dir = tmpdir.join("scripts") write(python_notebook, str(notebooks_dir.join("notebook.ipynb"))) jupytext(["--sync", "notebooks/notebook.ipynb"]) assert notebooks_dir.join("notebook.py").isfile() assert scripts_dir.join("notebook.py").isfile() notebooks_dir.join("module.py").write("1 + 1\n") jupytext(["--sync", "notebooks/module.py"]) assert notebooks_dir.join("module.ipynb").isfile() assert scripts_dir.join("module.py").isfile() ================================================ FILE: tests/functional/cli/test_source_is_newer.py ================================================ """ Here we test the --check-source-is-newer option of the jupytext CLI """ import os from jupytext import cli from jupytext import write import pytest def test_check_source_is_newer_when_using_jupytext_to(tmp_path, python_notebook): tmp_ipynb = tmp_path / "notebook.ipynb" tmp_py = tmp_path / "notebook.py" write(python_notebook, tmp_ipynb, fmt="ipynb") # First, we convert the .ipynb to .py cli.jupytext([str(tmp_ipynb), "--to", "py", "--check-source-is-newer"]) assert tmp_py.exists() # Now, we modify the .py file so that it is more recent than the .ipynb file text = tmp_py.read_text() + "\n# A new comment" tmp_py.write_text(text) # We can convert the .py to .ipynb because the .py is more recent than the .ipynb cli.jupytext([str(tmp_py), "--to", "ipynb", "--check-source-is-newer"]) # We modify the .ipynb file so that it is more recent than the .py file text = tmp_ipynb.read_text().replace("A new comment", "Another new comment") tmp_ipynb.write_text(text) # Now, trying to convert the .py to .ipynb raises an error because the .py is older than the .ipynb with pytest.raises(ValueError, match=r"Source .*notebook\.py.* is older than destination .*notebook\.ipynb.*"): cli.jupytext([str(tmp_py), "--to", "ipynb", "--check-source-is-newer"]) def test_check_source_is_newer_when_using_jupytext_sync(tmp_path, python_notebook): tmp_ipynb = tmp_path / "notebook.ipynb" tmp_py = tmp_path / "notebook.py" write(python_notebook, tmp_ipynb, fmt="ipynb") # First, we turn the notebook into a paired notebook cli.jupytext([str(tmp_ipynb), "--set-formats", "ipynb,py", "--check-source-is-newer"]) assert tmp_py.exists() # Running sync on the .py file works as .py is always more recent after a --sync operation cli.jupytext([str(tmp_py), "--sync", "--check-source-is-newer"]) # Make .ipynb slightly older again to ensure .py is newer stat = os.stat(tmp_ipynb) os.utime(tmp_ipynb, (stat.st_atime, stat.st_mtime - 1)) # Now, trying to sync the .ipynb to .py raises an error because .ipynb is older than .py with pytest.raises(ValueError, match=r"Source .*notebook\.ipynb.* is older than paired file .*notebook\.py.*"): cli.jupytext([str(tmp_ipynb), "--sync", "--check-source-is-newer"]) # We modify the .ipynb file so that it is more recent than the .py file text = tmp_ipynb.read_text().replace("A short notebook", "A short notebook with a modification") tmp_ipynb.write_text(text) # Make .py slightly older to ensure .ipynb is newer stat = os.stat(tmp_py) os.utime(tmp_py, (stat.st_atime, stat.st_mtime - 1)) # Now, trying to sync the .py to .ipynb raises an error because the .py is older than the .ipynb with pytest.raises(ValueError, match=r"Source .*notebook\.py.* is older than paired file .*notebook\.ipynb.*"): cli.jupytext([str(tmp_py), "--sync", "--check-source-is-newer"]) # Running sync on the .ipynb file works as .ipynb is now more recent than .py cli.jupytext([str(tmp_ipynb), "--sync", "--check-source-is-newer"]) ================================================ FILE: tests/functional/cli/test_synchronous_changes.py ================================================ """ These tests ensure that Jupytext raises an error when a file loaded by Jupytext changes while Jupytext is running. To make the simultaneous change occur in the tests, we monkey-patch the function `create_prefix_dir` which is called just before writing the file back to disk. """ from jupytext import cli from jupytext import write import pytest def test_jupytext_sync_raises_on_synchronous_edits(tmp_path, python_notebook, monkeypatch): (tmp_path / "jupytext.toml").write_text("""formats = "ipynb,py" """) tmp_py = tmp_path / "notebook.py" tmp_ipynb = tmp_path / "notebook.ipynb" write(python_notebook, tmp_py, fmt="py:percent") def edit_py_file(path): text = tmp_py.read_text() + "\n# A new comment" tmp_py.write_text(text) # The print statements help to see which Jupytext actions correspond to which test print("Testing a synchronous edit on a .py file that does not have a .ipynb counterpart") monkeypatch.setattr(cli, "_callback_on_lazy_write", edit_py_file) with pytest.raises( cli.SynchronousModificationError, match=r"The file .*notebook\.py.* was modified while Jupytext was running" ): cli.jupytext([str(tmp_py), "--sync"]) assert not tmp_ipynb.exists() print("Testing the normal sync command that creates the .ipynb file") monkeypatch.setattr(cli, "_callback_on_lazy_write", None) cli.jupytext([str(tmp_py), "--sync"]) assert tmp_ipynb.exists() print("Testing a synchronous edit on a .py file that does have a .ipynb counterpart") monkeypatch.setattr(cli, "_callback_on_lazy_write", edit_py_file) with pytest.raises( cli.SynchronousModificationError, match=r"The file .*notebook\.py.* was modified while Jupytext was running" ): cli.jupytext([str(tmp_py), "--sync"]) print("Testing a synchronous deletion of the .ipynb file") def rm_ipynb_file(path): tmp_ipynb.unlink() monkeypatch.setattr(cli, "_callback_on_lazy_write", rm_ipynb_file) with pytest.raises( cli.SynchronousModificationError, match=r"The file .*notebook\.ipynb.* was deleted while Jupytext was running" ): cli.jupytext([str(tmp_py), "--sync"]) assert not tmp_ipynb.exists() print("Testing a synchronous creation of the .ipynb file") def create_ipynb_file(path): tmp_ipynb.write_text("{}") monkeypatch.setattr(cli, "_callback_on_lazy_write", create_ipynb_file) with pytest.raises( cli.SynchronousModificationError, match=r"The file .*notebook\.ipynb.* was created while Jupytext was running" ): cli.jupytext([str(tmp_py), "--sync"]) def test_jupytext_to_raises_on_synchronous_edits(tmp_path, python_notebook, monkeypatch): tmp_py = tmp_path / "notebook.py" tmp_ipynb = tmp_path / "notebook.ipynb" write(python_notebook, tmp_py, fmt="py:percent") def edit_py_file(path): text = tmp_py.read_text() + "\n# A new comment" tmp_py.write_text(text) # The print statements help to see which Jupytext actions correspond to which test print("Testing a synchronous edit on a .py file") monkeypatch.setattr(cli, "_callback_on_lazy_write", edit_py_file) with pytest.raises( cli.SynchronousModificationError, match=r"The file .*notebook\.py.* was modified while Jupytext was running" ): cli.jupytext([str(tmp_py), "--to", "ipynb"]) assert not tmp_ipynb.exists() print("Testing the normal to command that creates the .ipynb file") monkeypatch.setattr(cli, "_callback_on_lazy_write", None) cli.jupytext([str(tmp_py), "--to", "ipynb"]) assert tmp_ipynb.exists() print("Testing a synchronous edit on a .py file that is not paired to a .ipynb file") monkeypatch.setattr(cli, "_callback_on_lazy_write", edit_py_file) # This one works as the .py file is not paired, so it is not read cli.jupytext([str(tmp_ipynb), "--to", "py"]) print("Turning the .py file into a paired notebook") monkeypatch.setattr(cli, "_callback_on_lazy_write", None) cli.jupytext([str(tmp_ipynb), "--set-formats", "ipynb,py"]) print("Testing a synchronous edit on a paired .py file") monkeypatch.setattr(cli, "_callback_on_lazy_write", edit_py_file) with pytest.raises( cli.SynchronousModificationError, match=r"The file .*notebook\.py.* was modified while Jupytext was running" ): cli.jupytext([str(tmp_py), "--to", "ipynb"]) ================================================ FILE: tests/functional/config/test_config.py ================================================ import os from pathlib import Path from contextlib import contextmanager import pytest from jupytext.config import ( find_jupytext_configuration_file, load_jupytext_configuration_file, notebook_formats, ) from jupytext.jupytext import load_jupytext_config, read @contextmanager def change_dir(path): """Context manager to temporarily change directory.""" old_cwd = os.getcwd() try: os.chdir(path) yield finally: os.chdir(old_cwd) @pytest.fixture def temp_folder_tree(tmp_path): """ Fixture that creates a temporary folder tree. tmp_path is a pytest built-in fixture that auto-cleans up. """ # Create folder structure (tmp_path / "subdir").mkdir() # Create some files (tmp_path / "jupytext.toml").write_text("") (tmp_path / "subdir" / "notebook.ipynb").write_text("") return tmp_path def test_issue_1440(temp_folder_tree): """Test that jupytext finds the config file even in parent of cwd""" notebook = Path("notebook.ipynb") notebook_str = str(notebook) expected_toml = str(temp_folder_tree / "jupytext.toml") with change_dir(temp_folder_tree / "subdir"): assert notebook.exists() config_file_from_path = find_jupytext_configuration_file(notebook) assert config_file_from_path == expected_toml config_file_from_str = find_jupytext_configuration_file(notebook_str) assert config_file_from_str == expected_toml def test_find_jupytext_configuration_file(tmpdir): nested = tmpdir.mkdir("nested") # Start with no configuration assert find_jupytext_configuration_file(str(nested)) is None # Configuration file in the parent directory root_config = tmpdir.join("jupytext.yml") root_config.write("\n") assert os.path.samefile(find_jupytext_configuration_file(str(tmpdir)), str(root_config)) assert os.path.samefile(find_jupytext_configuration_file(str(nested)), str(root_config)) # Local pyproject file pyproject_config = nested.join("pyproject.toml") pyproject_config.write("[tool.jupytext]\n") assert os.path.samefile(find_jupytext_configuration_file(str(tmpdir)), str(root_config)) assert os.path.samefile(find_jupytext_configuration_file(str(nested)), str(pyproject_config)) # Local configuration file local_config = nested.join(".jupytext") local_config.write("\n") assert os.path.samefile(find_jupytext_configuration_file(str(tmpdir)), str(root_config)) assert os.path.samefile(find_jupytext_configuration_file(str(nested)), str(local_config)) def test_jupytext_py_is_not_a_configuration_file(tmpdir): jupytext_py = tmpdir.join("jupytext.py") jupytext_py.write("# Not a config file!") assert find_jupytext_configuration_file(str(tmpdir)) is None dot_jupytext_py = tmpdir.join(".jupytext.py") dot_jupytext_py.write("# This is a config file!") assert find_jupytext_configuration_file(str(tmpdir)) == str(dot_jupytext_py) @pytest.mark.parametrize( "config_file", [ "pyproject.toml", "jupytext", "jupytext.toml", "jupytext.yml", "jupytext.json", "jupytext.py", ], ) def test_load_jupytext_configuration_file(tmpdir, config_file): full_config_path = tmpdir.join(config_file) if config_file == "pyproject.toml": full_config_path.write( """[tool.jupytext] formats = "ipynb,py:percent" notebook_metadata_filter = "all" cell_metadata_filter = "all" """ ) elif config_file.endswith(("jupytext", ".toml")): full_config_path.write( """formats = "ipynb,py:percent" notebook_metadata_filter = "all" cell_metadata_filter = "all" """ ) elif config_file.endswith(".yml"): full_config_path.write( """formats: ipynb,py:percent notebook_metadata_filter: all cell_metadata_filter: all """ ) elif config_file.endswith(".json"): full_config_path.write( """{"formats": "ipynb,py:percent", "notebook_metadata_filter": "all", "cell_metadata_filter": "all" } """ ) elif config_file.endswith(".py"): full_config_path.write( """c.formats = "ipynb,py:percent" c.notebook_metadata_filter = "all" c.cell_metadata_filter = "all" """ ) config = load_jupytext_configuration_file(str(full_config_path)) assert config.formats == ["ipynb,py:percent"] assert config.notebook_metadata_filter == "all" assert config.cell_metadata_filter == "all" @pytest.mark.parametrize( "content_toml,formats_short_form", [ ( """# always pair ipynb notebooks to py:percent files formats = "ipynb,py:percent" """, "ipynb,py:percent", ), ( """# always pair ipynb notebooks to py:percent files formats = "ipynb,py:percent" """, "ipynb,py:percent", ), ( """# Pair notebooks in subfolders of 'notebooks' to scripts in subfolders of 'scripts' [formats] "notebooks/" = "ipynb" "scripts/" = "py:percent" """, "notebooks///ipynb,scripts///py:percent", ), ( """# Pair notebooks in subfolders of 'notebooks' to scripts in subfolders of 'scripts' [formats] "notebooks" = "ipynb" "scripts" = "py:percent" """, "notebooks///ipynb,scripts///py:percent", ), ( """# Pair local notebooks to scripts in 'notebooks_py' and md files in 'notebooks_md' [formats] "" = "ipynb" "notebooks_py" = "py:percent" "notebooks_md" = "md:myst" """, "ipynb,notebooks_py///py:percent,notebooks_md///md:myst", ), ], ) def test_jupytext_formats(tmpdir, content_toml, formats_short_form): jupytext_toml = tmpdir.join("jupytext.toml") jupytext_toml.write(content_toml) config = load_jupytext_configuration_file(str(jupytext_toml)) assert config.formats == [formats_short_form] def test_deprecated_formats_cause_warning(tmpdir, content_toml="default_jupytext_formats = 'ipynb,md'"): jupytext_toml = tmpdir.join("jupytext.toml") jupytext_toml.write(content_toml) config = load_jupytext_configuration_file(str(jupytext_toml)) with pytest.warns(FutureWarning, match="use 'formats'"): assert config.default_formats(str(tmpdir.join("test.md"))) == "ipynb,md" @pytest.mark.parametrize( "option_name", ["notebook_metadata_filter", "cell_metadata_filter", "cell_markers"], ) def test_deprecated_options_cause_warning(tmpdir, option_name): jupytext_toml = tmpdir.join("jupytext.toml") jupytext_toml.write(f"default_{option_name} = 'value'") config = load_jupytext_configuration_file(str(jupytext_toml)) fmt = {} with pytest.warns(FutureWarning, match=f"use '{option_name}'"): config.set_default_format_options(fmt) assert fmt[option_name] == "value" def test_simple_py_file_is_not_paired(tmp_path): py_file = tmp_path / "simple.py" py_file.write_text('print("Hello, world!")') config_file = tmp_path / "jupytext.toml" config_file.write_text('formats = "ipynb,py:percent"') notebook = read(str(py_file)) config_file = load_jupytext_config(str(config_file)) formats = notebook_formats(notebook, config_file, str(py_file)) assert formats == [{"extension": ".py", "format_name": "light"}], formats def test_pairing_groups(tmp_path): """Test list-based formats for subset-specific pairing""" jupytext_toml = tmp_path / "jupytext.toml" jupytext_toml.write_text(""" [[formats]] "notebooks/tutorials/" = "ipynb" "docs/tutorials/" = "md" "scripts/tutorials/" = "py:percent" [[formats]] "notebooks/" = "ipynb" "scripts/" = "py:percent" """) config = load_jupytext_configuration_file(str(jupytext_toml)) # Formats should be a list of str assert isinstance(config.formats, list) assert len(config.formats) == 2 assert all(isinstance(f, str) for f in config.formats) # Test that default_formats returns the correct formats based on path # Tutorial notebook should match first format (tutorials) tutorial_notebook = str(tmp_path / "notebooks" / "tutorials" / "getting_started.ipynb") assert ( config.default_formats(tutorial_notebook) == "notebooks/tutorials///ipynb,docs/tutorials///md,scripts/tutorials///py:percent" ) # Regular notebook should match second format (main) regular_notebook = str(tmp_path / "notebooks" / "hello.ipynb") assert config.default_formats(regular_notebook) == "notebooks///ipynb,scripts///py:percent" def test_pairing_groups_multiple_groups(tmp_path): """Test multiple format sets with list-based formats""" jupytext_toml = tmp_path / "jupytext.toml" jupytext_toml.write_text(""" [[formats]] "notebooks/tutorials/" = "ipynb" "docs/tutorials/" = "md" [[formats]] "notebooks/examples/" = "ipynb" "docs/examples/" = "md:myst" [[formats]] "notebooks/" = "ipynb" "scripts/" = "py:percent" """) config = load_jupytext_configuration_file(str(jupytext_toml)) # Check formats is a list of dicts assert isinstance(config.formats, list) assert len(config.formats) == 3 # Test that the correct format is selected based on path (first match wins) tutorial_notebook = str(tmp_path / "notebooks" / "tutorials" / "intro.ipynb") assert config.default_formats(tutorial_notebook) == "notebooks/tutorials///ipynb,docs/tutorials///md" example_notebook = str(tmp_path / "notebooks" / "examples" / "demo.ipynb") assert config.default_formats(example_notebook) == "notebooks/examples///ipynb,docs/examples///md:myst" # Regular notebook should use the last (default) format regular_notebook = str(tmp_path / "notebooks" / "regular.ipynb") assert config.default_formats(regular_notebook) == "notebooks///ipynb,scripts///py:percent" def test_formats_list_without_default(tmp_path): """Test list-based formats without a default catchall""" jupytext_toml = tmp_path / "jupytext.toml" jupytext_toml.write_text(""" [[formats]] "notebooks/tutorials/" = "ipynb" "docs/tutorials/" = "md" """) config = load_jupytext_configuration_file(str(jupytext_toml)) # Formats should be a list assert isinstance(config.formats, list) assert len(config.formats) == 1 # Matching notebook should work tutorial_notebook = str(tmp_path / "notebooks" / "tutorials" / "getting_started.ipynb") assert config.default_formats(tutorial_notebook) == "notebooks/tutorials///ipynb,docs/tutorials///md" # Non-matching notebook should return None other_notebook = str(tmp_path / "notebooks" / "other.ipynb") assert config.default_formats(other_notebook) is None def test_formats_list_yaml(tmp_path): """Test list-based formats with YAML config""" jupytext_yml = tmp_path / "jupytext.yml" jupytext_yml.write_text(""" formats: - notebooks/tutorials/: ipynb docs/tutorials/: md - notebooks/: ipynb scripts/: py:percent """) config = load_jupytext_configuration_file(str(jupytext_yml)) # Formats should be a list assert isinstance(config.formats, list) assert len(config.formats) == 2 def test_formats_list_json(tmp_path): """Test list-based formats with JSON config""" jupytext_json = tmp_path / "jupytext.json" jupytext_json.write_text("""{ "formats": [ { "notebooks/tutorials/": "ipynb", "docs/tutorials/": "md" }, { "notebooks/": "ipynb", "scripts/": "py:percent" } ] } """) config = load_jupytext_configuration_file(str(jupytext_json)) # Formats should be a list assert isinstance(config.formats, list) assert len(config.formats) == 2 def test_formats_semicolon_separated(tmp_path): """Test semicolon-separated format strings""" jupytext_toml = tmp_path / "jupytext.toml" jupytext_toml.write_text(""" formats = "notebooks///ipynb,scripts///py:percent;ipynb,py:percent" """) config = load_jupytext_configuration_file(str(jupytext_toml)) # Formats should be split into a list assert isinstance(config.formats, list) assert len(config.formats) == 2 assert config.formats[0] == "notebooks///ipynb,scripts///py:percent" assert config.formats[1] == "ipynb,py:percent" # Test that the correct format is selected based on path notebook_in_notebooks = str(tmp_path / "notebooks" / "test.ipynb") assert config.default_formats(notebook_in_notebooks) == "notebooks///ipynb,scripts///py:percent" notebook_elsewhere = str(tmp_path / "test.ipynb") assert config.default_formats(notebook_elsewhere) == "ipynb,py:percent" def test_formats_toml_list_of_strings(tmp_path): """Test TOML list with string format specifications""" jupytext_toml = tmp_path / "jupytext.toml" jupytext_toml.write_text(""" formats = [ "notebooks///ipynb,scripts///py:percent", "ipynb,py:percent" ] """) config = load_jupytext_configuration_file(str(jupytext_toml)) # Formats should be a list assert isinstance(config.formats, list) assert len(config.formats) == 2 assert config.formats[0] == "notebooks///ipynb,scripts///py:percent" assert config.formats[1] == "ipynb,py:percent" # Test that the correct format is selected based on path notebook_in_notebooks = str(tmp_path / "notebooks" / "test.ipynb") assert config.default_formats(notebook_in_notebooks) == "notebooks///ipynb,scripts///py:percent" notebook_elsewhere = str(tmp_path / "test.ipynb") assert config.default_formats(notebook_elsewhere) == "ipynb,py:percent" ================================================ FILE: tests/functional/contents_manager/test_async_and_sync_contents_manager_are_in_sync.py ================================================ from pathlib import Path import pytest from black import FileMode, format_str from jupytext.async_contentsmanager import __file__ as async_contentsmanager_file from jupytext.async_pairs import __file__ as async_pairs_file from jupytext.sync_contentsmanager import __file__ as sync_contentsmanager_file from jupytext.sync_pairs import __file__ as sync_pairs_file def generate_sync_code_from_async_code(async_code: str) -> str: # No async methods sync_code = async_code.replace("async def", "def") # Don't await sync_code = sync_code.replace("await ", "") # Rename the contents manager sync_code = sync_code.replace("AsyncLargeFileManager", "LargeFileManager") sync_code = sync_code.replace("AsyncJupytextContentsManager", "SyncJupytextContentsManager") sync_code = sync_code.replace("AsyncTextFileContentsManager", "TextFileContentsManager") sync_code = sync_code.replace("asynchronous", "synchronous") sync_code = sync_code.replace("async_", "sync_") # Add a header sync_code = f'''""" This file is automatically generated by tests/functional/contents_manager/test_async_and_sync_contents_manager_are_in_sync.py Do not edit this file manually. """ {sync_code}''' sync_code = format_str(sync_code, mode=FileMode()) return sync_code @pytest.mark.parametrize( "async_file, sync_file", [ (async_contentsmanager_file, sync_contentsmanager_file), (async_pairs_file, sync_pairs_file), ], ) def test_async_and_sync_files_are_in_sync(async_file, sync_file): async_code = Path(async_file).read_text() sync_code = generate_sync_code_from_async_code(async_code) actual_sync_code = Path(sync_file).read_text() try: assert actual_sync_code == sync_code except AssertionError: Path(sync_file).write_text(sync_code) raise ================================================ FILE: tests/functional/docs/test_changelog.py ================================================ import re import sys from pathlib import Path import pytest from jupytext.version import __version__ def replace_issue_number_with_links(text): return re.sub( r"([^\[-])#([0-9]+)", r"\1[#\2](https://github.com/mwouts/jupytext/issues/\2)", text, ) @pytest.mark.parametrize( "input,output", [ ( "Issue #535", "Issue [#535](https://github.com/mwouts/jupytext/issues/535)", ), ( "Multiline\ntext (#123)", "Multiline\ntext ([#123](https://github.com/mwouts/jupytext/issues/123))", ), ( "(#123) and [Another-project-#535](https://custom_url)", "([#123](https://github.com/mwouts/jupytext/issues/123)) and [Another-project-#535](https://custom_url)", ), ], ) def test_replace_issue_numbers_with_links(input, output): assert replace_issue_number_with_links(input) == output @pytest.mark.skipif(sys.version_info < (3, 5), reason="'PosixPath' object has no attribute 'read_text'") def test_update_changelog(): changelog_file = Path(__file__).parent.parent.parent.parent / "CHANGELOG.md" cur_text = changelog_file.read_text() new_text = replace_issue_number_with_links(cur_text) if cur_text != new_text: changelog_file.write_text(new_text) # pragma: no cover def test_version_matches_changelog(): root_path = Path(__file__).parent.parent.parent.parent changelog_file = root_path / "CHANGELOG.md" # Read version from version.py current_version = __version__ # Read first version from CHANGELOG.md changelog_text = changelog_file.read_text() prev_line = "" for line in changelog_text.splitlines(): if not line.startswith("--------"): prev_line = line continue changelog_version = prev_line.split("(")[0].strip() assert current_version == changelog_version, ( f"Version mismatch: version.py has {current_version}, but CHANGELOG.md has {changelog_version}" ) return raise ValueError("No version found in CHANGELOG.md") def test_version_pep440_compliance(): pep440_regex = r"^(?:(?:0|[1-9]\d*)\.){2}(?:0|[1-9]\d*)(?:[abc]|rc)?(?:\d+)?(?:\.post\d+)?(?:\.dev\d+)?$" assert re.match(pep440_regex, __version__), f"Version {__version__} is not PEP 440 compliant" ================================================ FILE: tests/functional/docs/test_doc_files_are_notebooks.py ================================================ from pathlib import Path import pytest from jupytext import read def documentation_files(): for path in (Path(__file__).parent / "../../../docs").iterdir(): if path.suffix == ".md": yield path @pytest.mark.parametrize( "doc_file", documentation_files(), ids=[doc_file.stem for doc_file in documentation_files()], ) def test_doc_files_are_notebooks(doc_file): nb = read(doc_file) # count how many cell types counts = {"markdown": 0, "raw": 0, "code": 0} for cell in nb.cells: counts[cell.cell_type] += 1 assert counts["raw"] <= 1 ================================================ FILE: tests/functional/metadata/test_metadata_filter.py ================================================ from copy import deepcopy import pytest from nbformat.v4.nbbase import new_code_cell, new_notebook from jupytext import reads, writes from jupytext.cli import jupytext as jupytext_cli from jupytext.compare import compare, compare_notebooks from jupytext.metadata_filter import filter_metadata, metadata_filter_as_dict def to_dict(keys): return {key: None for key in keys} @pytest.mark.parametrize( "metadata_filter_string,metadata_filter_dict", [ ( "all, -widgets,-varInspector", {"additional": "all", "excluded": ["widgets", "varInspector"]}, ), ("toc", {"additional": ["toc"]}), ("+ toc", {"additional": ["toc"]}), ("preserve,-all", {"additional": ["preserve"], "excluded": "all"}), ( "ExecuteTime, autoscroll, -hide_output", {"additional": ["ExecuteTime", "autoscroll"], "excluded": ["hide_output"]}, ), ], ) def test_string_to_dict_conversion(metadata_filter_string, metadata_filter_dict): assert metadata_filter_as_dict(metadata_filter_string) == metadata_filter_dict def test_metadata_filter_as_dict(): assert metadata_filter_as_dict(True) == metadata_filter_as_dict("all") assert metadata_filter_as_dict(False) == metadata_filter_as_dict("-all") assert metadata_filter_as_dict({"excluded": "all"}) == metadata_filter_as_dict("-all") def test_metadata_filter_default(): assert filter_metadata(to_dict(["technical", "user", "preserve"]), None, "-technical") == to_dict(["user", "preserve"]) assert filter_metadata(to_dict(["technical", "user", "preserve"]), None, "preserve,-all") == to_dict(["preserve"]) def test_metadata_filter_user_plus_default(): assert filter_metadata(to_dict(["technical", "user", "preserve"]), "-user", "-technical") == to_dict(["preserve"]) assert filter_metadata(to_dict(["technical", "user", "preserve"]), "all,-user", "-technical") == to_dict( ["preserve", "technical"] ) assert filter_metadata(to_dict(["technical", "user", "preserve"]), "user", "preserve,-all") == to_dict( ["user", "preserve"] ) def test_metadata_filter_user_overrides_default(): assert filter_metadata(to_dict(["technical", "user", "preserve"]), "all,-user", "-technical") == to_dict( ["technical", "preserve"] ) assert filter_metadata(to_dict(["technical", "user", "preserve"]), "user,-all", "preserve") == to_dict(["user"]) def test_negative_cell_metadata_filter(): assert filter_metadata(to_dict(["exectime"]), "-linesto", "-exectime") == to_dict([]) def test_cell_metadata_filter_is_updated(): text = """--- jupyter: jupytext: cell_metadata_filter: -all --- ```{r cache=FALSE} 1+1 ``` """ nb = reads(text, "Rmd") assert nb.metadata["jupytext"]["cell_metadata_filter"] == "cache,-all" text2 = writes(nb, "Rmd") assert text.splitlines()[-3:] == text2.splitlines()[-3:] def test_notebook_metadata_all(): nb = new_notebook( metadata={ "user_metadata": [1, 2, 3], "jupytext": {"notebook_metadata_filter": "all"}, } ) text = writes(nb, "md") assert "user_metadata" in text def test_notebook_metadata_none(): nb = new_notebook(metadata={"jupytext": {"notebook_metadata_filter": "-all"}}) text = writes(nb, "md") assert "---" not in text def test_filter_nested_metadata(): metadata = {"I": {"1": {"a": 1, "b": 2}}} assert filter_metadata(metadata, "I", "-all") == {"I": {"1": {"a": 1, "b": 2}}} assert filter_metadata(metadata, "-I") == {} assert filter_metadata(metadata, "I.1.a", "-all") == {"I": {"1": {"a": 1}}} assert filter_metadata(metadata, "-I.1.b") == {"I": {"1": {"a": 1}}} assert filter_metadata(metadata, "-I.1.b", "I") == {"I": {"1": {"a": 1}}} # That one is not supported yet # assert filter_metadata(metadata, 'I.1.a', '-I') == {'I': {'1': {'a': 1}}} def test_filter_out_execution_metadata(): nb = new_notebook( cells=[ new_code_cell( "1 + 1", metadata={ "execution": { "iopub.execute_input": "2020-10-12T19:13:45.306603Z", "iopub.status.busy": "2020-10-12T19:13:45.306233Z", "iopub.status.idle": "2020-10-12T19:13:45.316103Z", "shell.execute_reply": "2020-10-12T19:13:45.315429Z", "shell.execute_reply.started": "2020-10-12T19:13:45.306577Z", } }, ) ] ) text = writes(nb, fmt="py:percent") assert "execution" not in text def test_default_config_has_priority_over_current_metadata( tmpdir, text="""# %% some_metadata_key=5 1 + 1 """, ): py_file = tmpdir.join("notebook.py") py_file.write(text) cfg_file = tmpdir.join("jupytext.toml") cfg_file.write( """cell_metadata_filter = "-some_metadata_key" """ ) jupytext_cli([str(py_file), "--to", "py"]) assert ( py_file.read() == """# %% 1 + 1 """ ) @pytest.mark.requires_myst def test_metadata_filter_in_notebook_757(): md = """--- jupytext: cell_metadata_filter: all,-hidden,-heading_collapsed notebook_metadata_filter: all,-language_info,-toc,-jupytext.text_representation.jupytext_version,-jupytext.text_representation.format_version text_representation: extension: .md format_name: myst kernelspec: display_name: Python 3 language: python name: python3 nbhosting: title: 'Exercice: Taylor' --- ```python 1 + 1 ``` """ # noqa nb = reads(md, fmt="md:myst") assert nb.metadata["jupytext"]["notebook_metadata_filter"] == ",".join( [ "all", "-language_info", "-toc", "-jupytext.text_representation.jupytext_version", "-jupytext.text_representation.format_version", ] ) md2 = writes(nb, fmt="md:myst") compare(md2, md) for fmt in ["py:light", "py:percent", "md"]: text = writes(nb, fmt=fmt) nb2 = reads(text, fmt=fmt) compare_notebooks(nb2, nb, fmt=fmt) ref_metadata = deepcopy(nb.metadata) del ref_metadata["jupytext"]["text_representation"] del nb2.metadata["jupytext"]["text_representation"] compare(nb2.metadata, ref_metadata) ================================================ FILE: tests/functional/metadata/test_metadata_filters_from_config.py ================================================ import nbformat import pytest import yaml from nbformat.v4.nbbase import new_code_cell, new_markdown_cell, new_notebook from jupytext.cli import jupytext as jupytext_cli from jupytext.compare import compare, compare_notebooks from jupytext.header import _JUPYTER_METADATA_NAMESPACE def test_metadata_filters_from_config(tmpdir): cfg_file = tmpdir.join("jupytext.toml") nb_file = tmpdir.join("notebook.ipynb") md_file = tmpdir.join("notebook.md") cfg_file.write( """notebook_metadata_filter = "-all" cell_metadata_filter = "-all" """ ) nb = new_notebook( cells=[new_markdown_cell("A markdown cell")], metadata={ "kernelspec": { "display_name": "Python [conda env:.conda-week1]", "language": "python", "name": "conda-env-.conda-week1-py", }, "language_info": { "codemirror_mode": {"name": "ipython", "version": 3}, "file_extension": ".py", "mimetype": "text/x-python", "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", "version": "3.8.3", }, "nbsphinx": {"execute": "never"}, }, ) nbformat.write(nb, str(nb_file)) jupytext_cli([str(nb_file), "--to", "md"]) md = md_file.read() compare(md, "A markdown cell\n") jupytext_cli([str(md_file), "--to", "notebook", "--update"]) nb2 = nbformat.read(str(nb_file), as_version=4) compare_notebooks(nb2, nb) @pytest.mark.requires_myst def test_root_level_metadata_filters_from_config(tmpdir): cfg_file = tmpdir.join("jupytext.toml") nb_file = tmpdir.join("notebook.ipynb") md_file = tmpdir.join("notebook.md") cfg_file.write( """root_level_metadata_filter = "-all" """ ) nb = new_notebook( cells=[new_code_cell("1 + 1")], metadata={ "language_info": { "name": "python", "pygments_lexer": "ipython3", }, }, ) nbformat.write(nb, str(nb_file)) jupytext_cli([str(nb_file), "--to", "md:myst"]) header = next(yaml.safe_load_all(md_file.read())) assert list(header) == [_JUPYTER_METADATA_NAMESPACE] jupytext_cli([str(md_file), "--to", "notebook", "--update"]) nb2 = nbformat.read(str(nb_file), as_version=4) compare_notebooks(nb2, nb) ================================================ FILE: tests/functional/others/invalid_file_896.md ================================================ --- jupytext: formats: ipynb,md:myst text_representation: extension: .md format_name: myst format_version: 0.13 jupytext_version: 1.11.5 kernelspec: display_name: Python 3 (ipykernel) language: python name: python3 --- Et voil! ================================================ FILE: tests/functional/others/test_active_cells.py ================================================ import pytest from nbformat import NotebookNode import jupytext from jupytext.compare import compare, compare_cells HEADER = { ".py": """# --- # jupyter: # jupytext: # main_language: python # --- """, ".R": """# --- # jupyter: # jupytext: # main_language: python # --- """, ".md": """--- jupyter: jupytext: main_language: python --- """, ".Rmd": """--- jupyter: jupytext: main_language: python --- """, } ACTIVE_ALL = { ".py": """# %% active="ipynb,py,R,Rmd" # This cell is active in all extensions """, ".Rmd": """```{python active="ipynb,py,R,Rmd"} # This cell is active in all extensions ``` """, ".md": """```python active="ipynb,py,R,Rmd" # This cell is active in all extensions ``` """, ".R": """# %% active="ipynb,py,R,Rmd" # This cell is active in all extensions """, ".ipynb": { "cell_type": "code", "source": "# This cell is active in all extensions", "metadata": {"active": "ipynb,py,R,Rmd"}, "execution_count": None, "outputs": [], }, } def check_active_cell(ext, active_dict): text = ("" if ext == ".py" else HEADER[ext]) + active_dict[ext] nb = jupytext.reads(text, ext) assert len(nb.cells) == 1 compare(jupytext.writes(nb, ext), text) cell = NotebookNode(active_dict[".ipynb"]) compare_cells(nb.cells, [cell], compare_ids=False) @pytest.mark.parametrize("ext", [".Rmd", ".md", ".py", ".R"]) def test_active_all(ext, no_jupytext_version_number): check_active_cell(ext, ACTIVE_ALL) ACTIVE_IPYNB = { ".py": """# %% active="ipynb" # # This cell is active only in ipynb # %matplotlib inline """, ".Rmd": """```{python active="ipynb", eval=FALSE} # This cell is active only in ipynb %matplotlib inline ``` """, ".md": """```python active="ipynb" # This cell is active only in ipynb %matplotlib inline ``` """, ".R": """# %% active="ipynb" # # This cell is active only in ipynb # %matplotlib inline """, ".ipynb": { "cell_type": "code", "source": "# This cell is active only in ipynb\n%matplotlib inline", "metadata": {"active": "ipynb"}, "execution_count": None, "outputs": [], }, } @pytest.mark.parametrize("ext", [".Rmd", ".md", ".py", ".R"]) def test_active_ipynb(ext, no_jupytext_version_number): check_active_cell(ext, ACTIVE_IPYNB) ACTIVE_IPYNB_RMD_USING_TAG = { ".py": """# %% tags=["active-ipynb-Rmd"] # # This cell is active only in ipynb and Rmd # %matplotlib inline """, ".Rmd": """```{python tags=c("active-ipynb-Rmd")} # This cell is active only in ipynb and Rmd # %matplotlib inline ``` """, ".md": """```python tags=["active-ipynb-Rmd"] # This cell is active only in ipynb and Rmd %matplotlib inline ``` """, ".R": """# %% tags=["active-ipynb-Rmd"] # # This cell is active only in ipynb and Rmd # %matplotlib inline """, ".ipynb": { "cell_type": "code", "source": "# This cell is active only in ipynb and Rmd\n%matplotlib inline", "metadata": {"tags": ["active-ipynb-Rmd"]}, "execution_count": None, "outputs": [], }, } @pytest.mark.parametrize("ext", [".Rmd", ".md", ".py", ".R"]) def test_active_ipynb_rmd_using_tags(ext, no_jupytext_version_number): check_active_cell(ext, ACTIVE_IPYNB_RMD_USING_TAG) ACTIVE_IPYNB_RSPIN = { ".R": """#+ active="ipynb", eval=FALSE # # This cell is active only in ipynb # 1 + 1 """, ".ipynb": { "cell_type": "code", "source": "# This cell is active only in ipynb\n1 + 1", "metadata": {"active": "ipynb"}, "execution_count": None, "outputs": [], }, } def test_active_ipynb_rspin(no_jupytext_version_number): nb = jupytext.reads(ACTIVE_IPYNB_RSPIN[".R"], "R:spin") assert len(nb.cells) == 1 compare(jupytext.writes(nb, "R:spin"), ACTIVE_IPYNB_RSPIN[".R"]) cell = NotebookNode(ACTIVE_IPYNB_RSPIN[".ipynb"]) compare_cells(nb.cells, [cell], compare_ids=False) ACTIVE_PY_IPYNB = { ".py": """# %% active="ipynb,py" # This cell is active in py and ipynb extensions """, ".Rmd": """```{python active="ipynb,py", eval=FALSE} # This cell is active in py and ipynb extensions ``` """, ".md": """```python active="ipynb,py" # This cell is active in py and ipynb extensions ``` """, ".R": """# %% active="ipynb,py" # # This cell is active in py and ipynb extensions """, ".ipynb": { "cell_type": "code", "source": "# This cell is active in py and ipynb extensions", "metadata": {"active": "ipynb,py"}, "execution_count": None, "outputs": [], }, } @pytest.mark.parametrize("ext", [".Rmd", ".md", ".py", ".R"]) def test_active_py_ipynb(ext, no_jupytext_version_number): check_active_cell(ext, ACTIVE_PY_IPYNB) ACTIVE_PY_R_IPYNB = { ".py": """# %% active="ipynb,py,R" # This cell is active in py, R and ipynb extensions """, ".Rmd": """```{python active="ipynb,py,R", eval=FALSE} # This cell is active in py, R and ipynb extensions ``` """, ".R": """# %% active="ipynb,py,R" # This cell is active in py, R and ipynb extensions """, ".ipynb": { "cell_type": "code", "source": "# This cell is active in py, R and ipynb extensions", "metadata": {"active": "ipynb,py,R"}, "execution_count": None, "outputs": [], }, } @pytest.mark.parametrize("ext", [".Rmd", ".py", ".R"]) def test_active_py_r_ipynb(ext, no_jupytext_version_number): check_active_cell(ext, ACTIVE_PY_R_IPYNB) ACTIVE_RMD = { ".py": """# %% active="Rmd" # # This cell is active in Rmd only """, ".Rmd": """```{python active="Rmd"} # This cell is active in Rmd only ``` """, ".R": """# %% active="Rmd" # # This cell is active in Rmd only """, ".ipynb": { "cell_type": "raw", "source": "# This cell is active in Rmd only", "metadata": {"active": "Rmd"}, }, } @pytest.mark.parametrize("ext", [".Rmd", ".py", ".R"]) def test_active_rmd(ext, no_jupytext_version_number): check_active_cell(ext, ACTIVE_RMD) ACTIVE_NOT_INCLUDE_RMD = { ".py": """# %% tags=["remove_cell"] active="Rmd" # # This cell is active in Rmd only """, ".Rmd": """```{python include=FALSE, active="Rmd"} # This cell is active in Rmd only ``` """, ".R": """# %% tags=["remove_cell"] active="Rmd" # # This cell is active in Rmd only """, ".ipynb": { "cell_type": "raw", "source": "# This cell is active in Rmd only", "metadata": {"active": "Rmd", "tags": ["remove_cell"]}, }, } @pytest.mark.parametrize("ext", [".Rmd", ".py", ".R"]) def test_active_not_include_rmd(ext, no_jupytext_version_number): check_active_cell(ext, ACTIVE_NOT_INCLUDE_RMD) def test_active_cells_from_py_percent( text="""# %% active="py" print('should only be displayed in py file') # %% tags=["active-py"] print('should only be displayed in py file') # %% active="ipynb" # print('only in jupyter') """, ): """Example taken from https://github.com/mwouts/jupytext/issues/477""" nb = jupytext.reads(text, "py:percent") assert nb.cells[0].cell_type == "raw" assert nb.cells[1].cell_type == "raw" assert nb.cells[2].cell_type == "code" assert nb.cells[2].source == "print('only in jupyter')" text2 = jupytext.writes(nb, "py:percent") compare(text2, text) def test_comments_work_in_active_cells_from_py_percent_1131( text="""# %% tags=["active-py"] # this is a comment """, ): nb = jupytext.reads(text, "py:percent") assert nb.cells[0].cell_type == "raw" assert nb.cells[0].source == "# this is a comment" text2 = jupytext.writes(nb, "py:percent") compare(text2, text) def test_comments_work_in_active_cells_from_py_light_1131( text="""# + tags=["active-py"] # this is a comment """, ): nb = jupytext.reads(text, "py:light") assert nb.cells[0].cell_type == "raw" assert nb.cells[0].source == "# this is a comment" text2 = jupytext.writes(nb, "py:light") compare(text2, text) def test_comments_plus_code_work_in_active_cells_from_py_percent_1131( text="""# %% tags=["active-py"] # this is a comment 1 + 1 """, ): nb = jupytext.reads(text, "py:percent") assert nb.cells[0].cell_type == "raw" assert nb.cells[0].source == "# this is a comment\n1 + 1" text2 = jupytext.writes(nb, "py:percent") compare(text2, text) def test_comments_plus_code_work_in_active_cells_from_py_light_1131( text="""# + tags=["active-py"] # this is a comment 1 + 1 """, ): nb = jupytext.reads(text, "py:light") assert nb.cells[0].cell_type == "raw" assert nb.cells[0].source == "# this is a comment\n1 + 1" text2 = jupytext.writes(nb, "py:light") compare(text2, text) def test_active_cells_from_py_light( text="""# + active="py" print('should only be displayed in py file') # + tags=["active-py"] print('should only be displayed in py file') # + active="ipynb" # print('only in jupyter') """, ): """Example adapted from https://github.com/mwouts/jupytext/issues/477""" nb = jupytext.reads(text, "py:light") assert nb.cells[0].cell_type == "raw" assert nb.cells[1].cell_type == "raw" assert nb.cells[2].cell_type == "code" assert nb.cells[2].source == "print('only in jupyter')" text2 = jupytext.writes(nb, "py") compare(text2, text) ================================================ FILE: tests/functional/others/test_auto_ext.py ================================================ import pytest from jupytext import read, reads, writes from jupytext.formats import JupytextFormatError, auto_ext_from_metadata def test_auto_in_fmt(ipynb_py_R_file): nb = read(ipynb_py_R_file) auto_ext = auto_ext_from_metadata(nb.metadata) fmt = auto_ext[1:] + ":percent" text = writes(nb, "auto:percent") assert "auto" not in text nb2 = reads(text, fmt) assert nb2.metadata["jupytext"]["text_representation"]["extension"] assert nb2.metadata["jupytext"]["text_representation"]["format_name"] == "percent" del nb.metadata["language_info"] del nb.metadata["kernelspec"] with pytest.raises(JupytextFormatError): writes(nb, "auto:percent") def test_auto_from_kernelspecs_works(ipynb_file): nb = read(ipynb_file) language_info = nb.metadata.pop("language_info") expected_ext = language_info.get("file_extension") if not expected_ext: pytest.skip("No file_extension in language_info") if expected_ext == ".r": expected_ext = ".R" elif expected_ext == ".fs": expected_ext = ".fsx" elif expected_ext == ".C": # ROOT-flavored C++ notebooks have a .C extension in the language_info, see PR #1384 expected_ext = ".cpp" auto_ext = auto_ext_from_metadata(nb.metadata) if auto_ext == ".sage": pytest.skip("Sage notebooks have Python in their language_info metadata, see #727") assert auto_ext == expected_ext def test_auto_in_formats(ipynb_py_R_jl_file): if any(pattern in ipynb_py_R_jl_file for pattern in ["plotly", "julia"]): pytest.skip() nb = read(ipynb_py_R_jl_file) nb.metadata["jupytext"] = {"formats": "ipynb,auto:percent"} fmt = auto_ext_from_metadata(nb.metadata)[1:] + ":percent" expected_formats = "ipynb," + fmt text = writes(nb, "ipynb") assert "auto" not in text nb2 = reads(text, "ipynb") assert nb2.metadata["jupytext"]["formats"] == expected_formats text = writes(nb, "auto:percent") assert "auto" not in text nb2 = reads(text, fmt) assert nb2.metadata["jupytext"]["formats"] == expected_formats del nb.metadata["language_info"] del nb.metadata["kernelspec"] with pytest.raises(JupytextFormatError): writes(nb, "ipynb") with pytest.raises(JupytextFormatError): writes(nb, "auto:percent") ================================================ FILE: tests/functional/others/test_cell_markers.py ================================================ from nbformat.v4.nbbase import new_raw_cell from jupytext import reads, writes from jupytext.cli import jupytext def test_set_cell_markers_cli(tmpdir, cwd_tmpdir): tmpdir.join("test.py").write("# %% [markdown]\n# A Markdown cell\n") jupytext(["--format-options", 'cell_markers="""', "test.py"]) py = tmpdir.join("test.py").read() assert py.endswith('# %% [markdown]\n"""\nA Markdown cell\n"""\n') def test_add_cell_to_script_with_cell_markers( no_jupytext_version_number, py='''# --- # jupyter: # jupytext: # formats: py:percent # cell_markers: '"""' # --- ''', ): nb = reads(py, fmt="py:percent") nb.cells = [new_raw_cell("A raw cell")] py2 = writes(nb, fmt="py:percent") assert py2.endswith( '''# %% [raw] """ A raw cell """ ''' ) ================================================ FILE: tests/functional/others/test_cell_metadata.py ================================================ import pytest from nbformat.v4.nbbase import new_code_cell, new_markdown_cell import jupytext from jupytext.cell_metadata import ( _IGNORE_CELL_METADATA, RMarkdownOptionParsingError, is_valid_metadata_key, metadata_to_rmd_options, metadata_to_text, parse_key_equal_value, parse_rmd_options, rmd_options_to_metadata, text_to_metadata, try_eval_metadata, ) from jupytext.combine import combine_inputs_with_outputs from jupytext.compare import compare, compare_notebooks from jupytext.metadata_filter import filter_metadata def r_options_language_metadata(): yield from [ ("r", "R", {}), ( 'r plot_1, dpi=72, fig.path="fig_path/"', "R", {"name": "plot_1", "dpi": 72, "fig.path": "fig_path/"}, ), ( 'r plot_1, bool=TRUE, fig.path="fig_path/"', "R", {"name": "plot_1", "bool": True, "fig.path": "fig_path/"}, ), ("r echo=FALSE", "R", {"tags": ["remove_input"]}), ("r plot_1, echo=TRUE", "R", {"name": "plot_1", "echo": True}), ( "python echo=if a==5 then TRUE else FALSE", "python", {"echo": "#R_CODE#if a==5 then TRUE else FALSE"}, ), ( 'python noname, tags=c("a", "b", "c"), echo={sum(a+c(1,2))>1}', "python", { "name": "noname", "tags": ["a", "b", "c"], "echo": "#R_CODE#{sum(a+c(1,2))>1}", }, ), ('python active="ipynb,py"', "python", {"active": "ipynb,py"}), ( 'python include=FALSE, active="Rmd"', "python", {"active": "Rmd", "tags": ["remove_cell"]}, ), ( 'r chunk_name, include=FALSE, active="Rmd"', "R", {"name": "chunk_name", "active": "Rmd", "tags": ["remove_cell"]}, ), ('python tags=c("parameters")', "python", {"tags": ["parameters"]}), ] @pytest.mark.parametrize("options,language, metadata", r_options_language_metadata()) def test_parse_rmd_options(options, language, metadata): compare(rmd_options_to_metadata(options), (language, metadata)) @pytest.mark.parametrize("options,language, metadata", r_options_language_metadata()) def test_build_options(options, language, metadata): compare(metadata_to_rmd_options(*(language, metadata)), options) @pytest.mark.parametrize("options,language, metadata", r_options_language_metadata()) def test_build_options_random_order(options, language, metadata): # Older python has no respect for order... # assert to_chunk_options(metadata) == options def split_and_strip(opt): {o.strip() for o in opt.split(",")} assert split_and_strip(metadata_to_rmd_options(*(language, metadata))) == split_and_strip(options) @pytest.mark.parametrize("options", ["a={)", "name, name2", "a=}", "b=]", "c=["]) def test_parsing_error(options): with pytest.raises(RMarkdownOptionParsingError): parse_rmd_options(options) def test_ignore_metadata(): metadata = {"trusted": True, "tags": ["remove_input"]} metadata = filter_metadata(metadata, None, _IGNORE_CELL_METADATA) assert metadata_to_rmd_options("R", metadata) == "r echo=FALSE" def test_filter_metadata(): assert filter_metadata({"scrolled": True}, None, _IGNORE_CELL_METADATA) == {} def test_try_eval_metadata(): metadata = {"list": 'list("a",5)', "c": "c(1,2,3)"} try_eval_metadata(metadata, "list") try_eval_metadata(metadata, "c") assert metadata == {"list": ["a", 5], "c": [1, 2, 3]} def test_language_no_metadata(text="python", value=("python", {})): compare(text_to_metadata(text), value) assert metadata_to_text(*value) == text.strip() def test_only_metadata(text='key="value"', value=("", {"key": "value"})): compare(text_to_metadata(text), value) assert metadata_to_text(*value) == text def test_only_metadata_2(text='key="value"', value=("", {"key": "value"})): compare(text_to_metadata(text, allow_title=True), value) assert metadata_to_text(*value) == text def test_no_language(text=".class", value=("", {".class": None})): compare(text_to_metadata(text), value) assert metadata_to_text(*value) == text def test_language_metadata_no_space(text='python{"a":1}', value=("python", {"a": 1})): compare(text_to_metadata(text), value) assert metadata_to_text(*value) == "python a=1" def test_title_no_metadata(text="title", value=("title", {})): compare(text_to_metadata(text, allow_title=True), value) assert metadata_to_text(*value) == text.strip() def test_simple_metadata( text='python string="value" number=1.0 array=["a", "b"]', value=("python", {"string": "value", "number": 1.0, "array": ["a", "b"]}), ): compare(text_to_metadata(text), value) assert metadata_to_text(*value) == text def test_simple_metadata_with_spaces( text='python string = "value" number = 1.0 array = ["a", "b"]', value=("python", {"string": "value", "number": 1.0, "array": ["a", "b"]}), ): compare(text_to_metadata(text), value) assert metadata_to_text(*value) == 'python string="value" number=1.0 array=["a", "b"]' def test_title_and_relax_json( text="cell title string='value' number=1.0 array=['a', \"b\"]", value=("cell title", {"string": "value", "number": 1.0, "array": ["a", "b"]}), ): compare(text_to_metadata(text, allow_title=True), value) assert metadata_to_text(*value) == 'cell title string="value" number=1.0 array=["a", "b"]' def test_title_and_json_dict( text='cell title {"string": "value", "number": 1.0, "array": ["a", "b"]}', value=("cell title", {"string": "value", "number": 1.0, "array": ["a", "b"]}), ): compare(text_to_metadata(text, allow_title=True), value) assert metadata_to_text(*value) == 'cell title string="value" number=1.0 array=["a", "b"]' @pytest.mark.parametrize("allow_title", [True, False]) def test_attribute(allow_title): text = ".class" value = ("", {".class": None}) compare(text_to_metadata(text, allow_title), value) assert metadata_to_text(*value) == text def test_language_and_attribute(text="python .class", value=("python", {".class": None})): compare(text_to_metadata(text), value) assert metadata_to_text(*value) == text def test_title_and_attribute(text="This is my title. .class", value=("This is my title.", {".class": None})): compare(text_to_metadata(text, allow_title=True), value) assert metadata_to_text(*value) == text def test_values_with_equal_signs_inside(text='python string="value=5"', value=("python", {"string": "value=5"})): compare(text_to_metadata(text), value) assert metadata_to_text(*value) == text def test_incorrectly_encoded(text="this is an incorrect expression d={{4 b=3"): value = text_to_metadata(text, allow_title=True) assert metadata_to_text(*value) == text def test_incorrectly_encoded_json(text='this is an incorrect expression {"d": "}'): value = text_to_metadata(text, allow_title=True) assert metadata_to_text(*value) == text def test_parse_key_value(): assert parse_key_equal_value("key='value' key2=5.0") == { "key": "value", "key2": 5.0, } def test_parse_key_value_key(): assert parse_key_equal_value("key='value' key2") == { "key": "value", "key2": None, } @pytest.mark.parametrize("key", ["ok", "also.ok", "all_right_55", "not,ok", "unexpected,key"]) def test_is_valid_metadata_key(key): assert is_valid_metadata_key(key) == ("," not in key) @pytest.fixture() def notebook_with_unsupported_key_in_metadata(python_notebook): nb = python_notebook nb.cells.append(new_markdown_cell("text", metadata={"unexpected,key": True})) return nb def test_unsupported_key_in_metadata(notebook_with_unsupported_key_in_metadata, fmt_with_cell_metadata): """Notebook metadata that can't be parsed in text notebook cannot go to the text file, but it should still remain available in the ipynb file for paired notebooks.""" with pytest.warns( UserWarning, match="The following metadata cannot be exported to the text notebook", ): text = jupytext.writes(notebook_with_unsupported_key_in_metadata, fmt_with_cell_metadata) assert "unexpected" not in text nb_text = jupytext.reads(text, fmt=fmt_with_cell_metadata) nb = combine_inputs_with_outputs(nb_text, notebook_with_unsupported_key_in_metadata, fmt=fmt_with_cell_metadata) assert nb.cells[-1].metadata == {"unexpected,key": True} @pytest.fixture() def notebook_with_collapsed_cell(python_notebook): nb = python_notebook nb.cells.append(new_markdown_cell("## Data", metadata={"jp-MarkdownHeadingCollapsed": True})) return nb def test_notebook_with_collapsed_cell(notebook_with_collapsed_cell, fmt_with_cell_metadata): text = jupytext.writes(notebook_with_collapsed_cell, fmt_with_cell_metadata) assert "MarkdownHeadingCollapsed" in text nb = jupytext.reads(text, fmt=fmt_with_cell_metadata) compare_notebooks(nb, notebook_with_collapsed_cell, fmt=fmt_with_cell_metadata) def test_empty_tags_are_not_saved_in_text_notebooks(no_jupytext_version_number, python_notebook, fmt="py:percent"): nb = python_notebook nb.cells.append(new_code_cell(metadata={"tags": []})) text = jupytext.writes(nb, fmt=fmt) assert "tags" not in text nb_text = jupytext.reads(text, fmt=fmt) nb2 = combine_inputs_with_outputs(nb_text, nb, fmt=fmt) assert nb2.cells[-1].metadata["tags"] == [] ================================================ FILE: tests/functional/others/test_cell_tags_are_preserved.py ================================================ import pytest from nbformat.v4.nbbase import new_code_cell, new_markdown_cell from jupytext import reads, writes from jupytext.formats import formats_with_support_for_cell_metadata, is_myst_available @pytest.fixture() def notebook_with_tags(python_notebook): nb = python_notebook nb.cells = [ new_code_cell("1 + 1", metadata={"tags": ["tag1"]}), new_markdown_cell("some text", metadata={"tags": ["tag2"]}), ] return nb @pytest.mark.parametrize("fmt", ["py:percent", "py:light", "md:markdown", "md:myst", "Rmd:rmarkdown"]) def test_main_formats_support_cell_metadata(fmt): if fmt == "md:myst" and not is_myst_available(): pytest.skip("myst is not available") assert fmt in set(formats_with_support_for_cell_metadata()) def test_tags_are_preserved(notebook_with_tags, fmt_with_cell_metadata): text = writes(notebook_with_tags, fmt_with_cell_metadata) nb = reads(text, fmt_with_cell_metadata) assert nb.cells[0]["metadata"]["tags"] == ["tag1"] assert nb.cells[1]["metadata"]["tags"] == ["tag2"] ================================================ FILE: tests/functional/others/test_cells.py ================================================ import pytest from nbformat.v4.nbbase import new_markdown_cell from jupytext.cell_reader import ( LightScriptCellReader, RMarkdownCellReader, paragraph_is_fully_commented, uncomment, ) from jupytext.cell_to_text import RMarkdownCellExporter @pytest.mark.parametrize( "lines", [ "# text", """# # %%R # # comment # 1 + 1 # 2 + 2 """, ], ) def test_paragraph_is_fully_commented(lines): assert paragraph_is_fully_commented(lines.splitlines(), comment="#", main_language="python") def test_paragraph_is_not_fully_commented(lines="# text\nnot fully commented out"): assert not paragraph_is_fully_commented(lines.splitlines(), comment="#", main_language="python") def test_uncomment(): assert uncomment(["# line one", "#line two", "line three"], "#") == [ "line one", "line two", "line three", ] assert uncomment(["# line one", "#line two", "line three"], "") == [ "# line one", "#line two", "line three", ] def test_text_to_code_cell(): text = """```{python} 1+2+3 ``` """ lines = text.splitlines() cell, pos = RMarkdownCellReader().read(lines) assert cell.cell_type == "code" assert cell.source == "1+2+3" assert cell.metadata == {"language": "python"} assert lines[pos:] == [] def test_text_to_code_cell_empty_code(): text = """```{python} ``` """ lines = text.splitlines() cell, pos = RMarkdownCellReader().read(lines) assert cell.cell_type == "code" assert cell.source == "" assert cell.metadata == {"language": "python"} assert lines[pos:] == [] def test_text_to_code_cell_empty_code_no_blank_line(): text = """```{python} ``` """ lines = text.splitlines() cell, pos = RMarkdownCellReader().read(lines) assert cell.cell_type == "code" assert cell.source == "" assert cell.metadata == {"language": "python"} assert lines[pos:] == [] def test_text_to_markdown_cell(): text = """This is a markdown cell ```{python} 1+2+3 ``` """ lines = text.splitlines() cell, pos = RMarkdownCellReader().read(lines) assert cell.cell_type == "markdown" assert cell.source == "This is\na markdown cell" assert cell.metadata == {} assert pos == 3 def test_text_to_markdown_no_blank_line(): text = """This is a markdown cell ```{python} 1+2+3 ``` """ lines = text.splitlines() cell, pos = RMarkdownCellReader().read(lines) assert cell.cell_type == "markdown" assert cell.source == "This is\na markdown cell" assert cell.metadata == {"lines_to_next_cell": 0} assert pos == 2 def test_text_to_markdown_two_blank_line(): text = """ ```{python} 1+2+3 ``` """ lines = text.splitlines() cell, pos = RMarkdownCellReader().read(lines) assert cell.cell_type == "markdown" assert cell.source == "" assert cell.metadata == {} assert pos == 2 def test_text_to_markdown_one_blank_line(): text = """ ```{python} 1+2+3 ``` """ lines = text.splitlines() cell, pos = RMarkdownCellReader().read(lines) assert cell.cell_type == "markdown" assert cell.source == "" assert cell.metadata == {"lines_to_next_cell": 0} assert pos == 1 def test_empty_markdown_to_text(): cell = new_markdown_cell(source="") text = RMarkdownCellExporter(cell, "python").cell_to_text() assert text == [""] def test_text_to_cell_py(): text = "1+1\n" lines = text.splitlines() cell, pos = LightScriptCellReader().read(lines) assert cell.cell_type == "code" assert cell.source == "1+1" assert cell.metadata == {} assert pos == 1 def test_text_to_cell_py2(): text = """def f(x): return x+1""" lines = text.splitlines() cell, pos = LightScriptCellReader().read(lines) assert cell.cell_type == "code" assert cell.source == """def f(x):\n return x+1""" assert cell.metadata == {} assert pos == 2 def test_code_to_cell(): text = """def f(x): return x+1""" lines = text.splitlines() cell, pos = LightScriptCellReader().read(lines) assert cell.cell_type == "code" assert cell.source == """def f(x):\n return x+1""" assert cell.metadata == {} assert pos == 2 def test_uncomment_ocaml(): assert uncomment(["(* ## *)"], "(*", "*)") == ["##"] assert uncomment(["(*##*)"], "(*", "*)") == ["##"] ================================================ FILE: tests/functional/others/test_combine.py ================================================ from copy import deepcopy import pytest from jupyter_server.utils import ensure_async from nbformat.v4.nbbase import new_code_cell, new_markdown_cell, new_notebook import jupytext from jupytext.combine import combine_inputs_with_outputs from jupytext.compare import compare, compare_notebooks def test_combine(): nb_source = new_notebook( cells=[ new_markdown_cell("Markdown text"), new_code_cell("a=3"), new_code_cell("a+1"), new_code_cell("a+1"), new_markdown_cell("Markdown text"), new_code_cell("a+2"), ] ) nb_outputs = new_notebook( cells=[ new_markdown_cell("Markdown text"), new_code_cell("a=3"), new_code_cell("a+1"), new_code_cell("a+2"), new_markdown_cell("Markdown text"), ] ) nb_outputs.cells[2].outputs = ["4"] nb_outputs.cells[3].outputs = ["5"] nb_source = combine_inputs_with_outputs(nb_source, nb_outputs) assert nb_source.cells[2].outputs == ["4"] assert nb_source.cells[3].outputs == [] assert nb_source.cells[5].outputs == ["5"] @pytest.mark.asyncio async def test_read_text_and_combine_with_outputs(tmpdir, cm): tmp_ipynb = "notebook.ipynb" tmp_script = "notebook.py" with open(str(tmpdir.join(tmp_script)), "w") as fp: fp.write( """# --- # jupyter: # jupytext_formats: ipynb,py:light # --- 1+1 2+2 3+3 """ ) with open(str(tmpdir.join(tmp_ipynb)), "w") as fp: fp.write( """{ "cells": [ { "cell_type": "code", "execution_count": 1, "metadata": {}, "outputs": [ { "data": { "text/plain": [ "2" ] }, "execution_count": 1, "metadata": {}, "output_type": "execute_result" } ], "source": [ "1+1" ] }, { "cell_type": "code", "execution_count": 3, "metadata": {}, "outputs": [ { "data": { "text/plain": [ "6" ] }, "execution_count": 3, "metadata": {}, "output_type": "execute_result" } ], "source": [ "3+3" ] } ], "metadata": {}, "nbformat": 4, "nbformat_minor": 2 } """ ) # create contents manager cm.root_dir = str(tmpdir) # load notebook from script model = await ensure_async(cm.get(tmp_script)) nb = model["content"] assert nb.cells[0]["source"] == "1+1" assert nb.cells[1]["source"] == "2+2" assert nb.cells[2]["source"] == "3+3" # No output for the second cell, which is not in the ipynb assert nb.cells[0]["outputs"] assert not nb.cells[1]["outputs"] assert nb.cells[2]["outputs"] assert len(nb.cells) == 3 def test_combine_stable(ipynb_file): nb_org = jupytext.read(ipynb_file) nb_source = deepcopy(nb_org) nb_outputs = deepcopy(nb_org) for cell in nb_source.cells: cell.outputs = [] nb_source = combine_inputs_with_outputs(nb_source, nb_outputs) compare_notebooks(nb_source, nb_org) def test_combine_reorder(): nb_source = new_notebook( cells=[ new_markdown_cell("Markdown text"), new_code_cell("1+1"), new_code_cell("2+2"), new_code_cell("3+3"), new_markdown_cell("Markdown text"), new_code_cell("4+4"), ] ) nb_outputs = new_notebook( cells=[ new_markdown_cell("Markdown text"), new_code_cell("2+2"), new_code_cell("4+4"), new_code_cell("1+1"), new_code_cell("3+3"), new_markdown_cell("Markdown text"), ] ) nb_outputs.cells[1].outputs = ["4"] nb_outputs.cells[2].outputs = ["8"] nb_outputs.cells[3].outputs = ["2"] nb_outputs.cells[4].outputs = ["6"] nb_source = combine_inputs_with_outputs(nb_source, nb_outputs) assert nb_source.cells[1].outputs == ["2"] assert nb_source.cells[2].outputs == ["4"] assert nb_source.cells[3].outputs == ["6"] assert nb_source.cells[5].outputs == ["8"] def test_combine_split(): nb_source = new_notebook(cells=[new_code_cell("1+1"), new_code_cell("2+2")]) nb_outputs = new_notebook(cells=[new_code_cell("1+1\n2+2")]) nb_outputs.cells[0].outputs = ["4"] nb_source = combine_inputs_with_outputs(nb_source, nb_outputs) assert nb_source.cells[0].outputs == [] assert nb_source.cells[1].outputs == ["4"] def test_combine_refactor(): nb_source = new_notebook(cells=[new_code_cell("a=1"), new_code_cell("a+1"), new_code_cell("a+2")]) nb_outputs = new_notebook(cells=[new_code_cell("b=1"), new_code_cell("b+1"), new_code_cell("b+2")]) nb_outputs.cells[1].outputs = ["2"] nb_outputs.cells[2].outputs = ["3"] nb_source = combine_inputs_with_outputs(nb_source, nb_outputs) assert nb_source.cells[0].outputs == [] assert nb_source.cells[1].outputs == ["2"] assert nb_source.cells[2].outputs == ["3"] def test_combine_attachments(): nb_source = new_notebook(cells=[new_markdown_cell("![image.png](attachment:image.png)")]) nb_outputs = new_notebook( cells=[ new_markdown_cell( "![image.png](attachment:image.png)", attachments={"image.png": {"image/png": "SOME_LONG_IMAGE_CODE...=="}}, ) ] ) nb_source = combine_inputs_with_outputs(nb_source, nb_outputs) compare(nb_source, nb_outputs) ================================================ FILE: tests/functional/others/test_custom_cell_magics.py ================================================ import nbformat from nbformat.v4.nbbase import new_code_cell, new_notebook from jupytext.cli import jupytext as jupytext_cli from jupytext.compare import compare_notebooks from jupytext.languages import _JUPYTER_LANGUAGES_LOWER_AND_UPPER def test_custom_cell_magics( tmpdir, nb=new_notebook( cells=[ new_code_cell("%%sql -o tables -q\n SHOW TABLES"), new_code_cell( """%%configure -f {"executorMemory": "3072M", "executorCores": 4, "numExecutors":10}""" ), new_code_cell("%%local\na=1"), ] ), ): cfg_file = tmpdir.join("jupytext.toml") nb_file = tmpdir.join("notebook.ipynb") py_file = tmpdir.join("notebook.py") cfg_file.write('custom_cell_magics = "configure,local"') assert "configure" not in _JUPYTER_LANGUAGES_LOWER_AND_UPPER assert "logs" not in _JUPYTER_LANGUAGES_LOWER_AND_UPPER nbformat.write(nb, str(nb_file)) jupytext_cli([str(nb_file), "--to", "py"]) py = py_file.read() for line in py.splitlines(): if line: assert line.startswith("# "), line jupytext_cli([str(py_file), "--to", "notebook"]) nb2 = nbformat.read(str(nb_file), as_version=4) compare_notebooks(nb2, nb) ================================================ FILE: tests/functional/others/test_doxygen.py ================================================ import nbformat import pytest import jupytext from jupytext.cli import jupytext as jupytext_cli from jupytext.compare import compare, compare_notebooks from jupytext.doxygen import doxygen_to_markdown, markdown_to_doxygen SAMPLE_MARKDOWN = """A latex formula $$1+1$$, another one $$2+2 $$ An inline formula $3+3$ """ SAMPLE_DOXYGEN = """A latex formula \\f[1+1\\f], another one \\f[2+2 \\f] An inline formula \\f$3+3\\f$ """ def test_markdown_to_doxygen(): compare(markdown_to_doxygen(SAMPLE_MARKDOWN), SAMPLE_DOXYGEN) def test_doxygen_to_markdown(): compare(doxygen_to_markdown(SAMPLE_DOXYGEN), SAMPLE_MARKDOWN) @pytest.mark.parametrize( "latex,doxygen", [ ("$$", "$$"), ("$1+1$", "\\f$1+1\\f$"), ("$1\\$ $", "\\f$1\\$ \\f$"), ("$$2+2$$", "\\f[2+2\\f]"), ("$$2+2$$ then $$3+3$$", "\\f[2+2\\f] then \\f[3+3\\f]"), ("$$2+2\n$$", "\\f[2+2\n\\f]"), ("$$1\\$+2\\$=3\\$$$", "\\f[1\\$+2\\$=3\\$\\f]"), ], ) def test_simple_equations_to_doxygen_and_back(latex, doxygen): assert markdown_to_doxygen(latex) == doxygen assert doxygen_to_markdown(doxygen) == latex def test_doxygen_equation_markers(tmpdir): cfg_file = tmpdir.join("jupytext.toml") nb_file = tmpdir.join("notebook.ipynb") md_file = tmpdir.join("notebook.md") cfg_file.write("hide_notebook_metadata = true\ndoxygen_equation_markers = true") nb = jupytext.reads(SAMPLE_MARKDOWN, "md") del nb.metadata["jupytext"] nbformat.write(nb, str(nb_file)) jupytext_cli([str(nb_file), "--to", "md"]) md = md_file.read() # Doxygen equation markers assert "$$" not in md assert "\\f[" in md assert "\\f]" in md assert "\\f$" in md assert "\\f$" in md # Metadata hidden assert md.startswith("", ""]] # language is not inserted by nbconvert md_expected = ["```" if line.startswith("```") else line for line in md_expected] # nbconvert inserts no empty line after the YAML header (which is in a Raw cell) md_expected = "\n".join(md_expected).replace("---\n\n", "---\n") + "\n" # an extra blank line is inserted before code cells md_nbconvert = md_nbconvert.replace("\n\n```", "\n```") jupytext.compare.compare(md_nbconvert, md_expected) @pytest.mark.requires_nbconvert def test_jupytext_markdown_similar_to_nbconvert(ipynb_py_R_jl_file): """Test that the nbconvert export for a notebook matches Jupytext's one""" if "magic" in ipynb_py_R_jl_file or "html" in ipynb_py_R_jl_file: pytest.skip() nb = jupytext.read(ipynb_py_R_jl_file) # Remove cell outputs and metadata for cell in nb.cells: if "outputs" in cell: cell.outputs = [] if "metadata" in cell: cell.metadata = {} md_jupytext = jupytext.writes(nb, fmt="md") import nbconvert md_nbconvert, _ = nbconvert.export(nbconvert.MarkdownExporter, nb) # our expectations # nbconvert file has no YAML header md_jupytext_lines = md_jupytext.splitlines() _, _, raw_cell, pos = header_to_metadata_and_cell(md_jupytext_lines, "", "") md_jupytext = "\n".join(md_jupytext_lines[pos:]) + "\n" if raw_cell is not None: md_jupytext = raw_cell.source + "\n\n" + md_jupytext # region comments are not in nbconvert md_jupytext = md_jupytext.replace("\n", "").replace("\n", "") # Jupytext uses HTML comments to keep track of raw cells md_jupytext = ( md_jupytext.replace("\n\n", "").replace("\n", "").replace("\n\n", "") ) # nbconvert file may start with an empty line md_jupytext = md_jupytext.lstrip("\n") md_nbconvert = md_nbconvert.lstrip("\n") # Jupytext may not always have two blank lines between cells like Jupyter nbconvert md_jupytext = md_jupytext.replace("\n\n\n", "\n\n") md_nbconvert = md_nbconvert.replace("\n\n\n", "\n\n") jupytext.compare.compare(md_nbconvert, md_jupytext) ================================================ FILE: tests/functional/round_trip/test_mirror.py ================================================ """Here we generate mirror representation of py, Rmd and ipynb files as py or ipynb, and make sure that these representations minimally change on new releases. """ import os import re import pytest from nbformat.v4.nbbase import new_notebook import jupytext from jupytext.compare import ( assert_conversion_same_as_mirror, compare_notebooks, create_mirror_file_if_missing, ) from jupytext.formats import auto_ext_from_metadata from jupytext.languages import _SCRIPT_EXTENSIONS def test_create_mirror_file_if_missing(tmpdir, no_jupytext_version_number): py_file = str(tmpdir.join("notebook.py")) assert not os.path.isfile(py_file) create_mirror_file_if_missing(py_file, new_notebook(), "py") assert os.path.isfile(py_file) """--------------------------------------------------------------------------------- Part I: ipynb -> fmt -> ipynb ---------------------------------------------------------------------------------""" def test_ipynb_to_percent(ipynb_file, no_jupytext_version_number): assert_conversion_same_as_mirror(ipynb_file, "auto:percent", "ipynb_to_percent") def test_ipynb_to_hydrogen(ipynb_file, no_jupytext_version_number): assert_conversion_same_as_mirror(ipynb_file, "auto:hydrogen", "ipynb_to_hydrogen") def test_ipynb_to_light(ipynb_to_light, no_jupytext_version_number): assert_conversion_same_as_mirror(ipynb_to_light, "auto:light", "ipynb_to_script") @pytest.mark.requires_marimo def test_ipynb_to_marimo(marimo_compatible_ipynb, no_jupytext_version_number): assert_conversion_same_as_mirror( marimo_compatible_ipynb, "auto:marimo", "ipynb_to_marimo", ) def test_ipynb_to_md(ipynb_file, no_jupytext_version_number): assert_conversion_same_as_mirror(ipynb_file, "md", "ipynb_to_md") def test_ipynb_to_Rmd(ipynb_file, no_jupytext_version_number): assert_conversion_same_as_mirror(ipynb_file, "Rmd", "ipynb_to_Rmd") @pytest.mark.requires_myst def test_ipynb_to_myst(ipynb_file, no_jupytext_version_number): if re.match(r".*(html-demo|julia_functional_geometry|xcpp_by_quantstack).*", ipynb_file): pytest.skip() assert_conversion_same_as_mirror(ipynb_file, "md:myst", "ipynb_to_myst") """--------------------------------------------------------------------------------- Part II: text -> ipynb -> text ---------------------------------------------------------------------------------""" def test_script_to_ipynb(script_to_ipynb, no_jupytext_version_number): assert_conversion_same_as_mirror(script_to_ipynb, "ipynb:light", "script_to_ipynb") def test_percent_to_ipynb(percent_file, no_jupytext_version_number): assert_conversion_same_as_mirror(percent_file, "ipynb:percent", "script_to_ipynb") def test_hydrogen_to_ipynb(hydrogen_file, no_jupytext_version_number): assert_conversion_same_as_mirror(hydrogen_file, "ipynb:hydrogen", "script_to_ipynb") def test_spin_to_ipynb(r_spin_file, no_jupytext_version_number): assert_conversion_same_as_mirror(r_spin_file, "ipynb:spin", "script_to_ipynb") @pytest.mark.requires_marimo def test_marimo_to_ipynb(marimo_file, no_jupytext_version_number): assert_conversion_same_as_mirror(marimo_file, "ipynb:marimo", "script_to_ipynb") def test_md_to_ipynb(md_file, no_jupytext_version_number): assert_conversion_same_as_mirror(md_file, "ipynb", "md_to_ipynb") @pytest.mark.requires_myst def test_myst_file_has_myst_format(myst_file): with open(myst_file) as f: text = f.read() fmt = jupytext.guess_format(text, ".md") assert fmt == ("myst", {}) @pytest.mark.requires_myst def test_myst_to_ipynb(myst_file, no_jupytext_version_number): assert_conversion_same_as_mirror(myst_file, "ipynb:myst", "myst_to_ipynb") """--------------------------------------------------------------------------------- Part III: More specific round trip tests ---------------------------------------------------------------------------------""" def test_ipynb_to_percent_to_light(ipynb_file): nb = jupytext.read(ipynb_file) pct = jupytext.writes(nb, "auto:percent") auto_ext = auto_ext_from_metadata(nb.metadata) comment = _SCRIPT_EXTENSIONS[auto_ext]["comment"] lgt = ( pct.replace(comment + " %%\n", comment + " +\n") .replace(comment + " %% ", comment + " + ") .replace( comment + " format_name: percent", comment + " format_name: light", ) ) nb2 = jupytext.reads(lgt, auto_ext) compare_notebooks(nb2, nb) def test_ipynb_to_python_vim(ipynb_py_file, no_jupytext_version_number): assert_conversion_same_as_mirror( ipynb_py_file, {"extension": ".py", "cell_markers": "{{{,}}}"}, "ipynb_to_script_vim_folding_markers", ) def test_ipynb_to_python_vscode(ipynb_py_file, no_jupytext_version_number): assert_conversion_same_as_mirror( ipynb_py_file, {"extension": ".py", "cell_markers": "region,endregion"}, "ipynb_to_script_vscode_folding_markers", ) def test_ipynb_to_r_light(ipynb_R_file, no_jupytext_version_number): assert_conversion_same_as_mirror(ipynb_R_file, ".low.r:light", "ipynb_to_script") def test_ipynb_to_r_percent(ipynb_R_file, no_jupytext_version_number): assert_conversion_same_as_mirror(ipynb_R_file, ".low.r:percent", "ipynb_to_percent") def test_ipynb_to_R_spin(ipynb_R_file, no_jupytext_version_number): assert_conversion_same_as_mirror(ipynb_R_file, "R:spin", "ipynb_to_spin") def test_ipynb_to_r_spin(ipynb_R_file, no_jupytext_version_number): assert_conversion_same_as_mirror(ipynb_R_file, ".low.r:spin", "ipynb_to_spin") @pytest.mark.parametrize("extension", ("ss", "scm")) def test_ipynb_to_scheme_light(ipynb_scheme_file, extension, no_jupytext_version_number): assert_conversion_same_as_mirror(ipynb_scheme_file, f"{extension}:light", "ipynb_to_script") @pytest.mark.parametrize("extension", ("ss", "scm")) def test_ipynb_to_scheme_percent(ipynb_scheme_file, extension, no_jupytext_version_number): assert_conversion_same_as_mirror(ipynb_scheme_file, f"{extension}:percent", "ipynb_to_percent") ================================================ FILE: tests/functional/round_trip/test_myst_header.py ================================================ import pytest from nbformat.v4.nbbase import new_notebook, new_raw_cell from jupytext import reads, writes from jupytext.compare import compare, compare_notebooks from jupytext.config import load_jupytext_configuration_file from jupytext.header import _JUPYTER_METADATA_NAMESPACE from jupytext.myst import dump_yaml_blocks @pytest.mark.requires_myst def test_myst_header_is_stable_1247_using_inline_filter( md="""--- jupytext: formats: md:myst notebook_metadata_filter: -jupytext.text_representation.jupytext_version,settings,mystnb text_representation: extension: .md format_name: myst format_version: 0.13 kernelspec: display_name: Python 3 (ipykernel) language: python name: python3 mystnb: execution_mode: 'off' settings: output_matplotlib_strings: remove --- """, ): nb = reads(md, fmt="md") md2 = writes(nb, fmt="md") compare(md2, md) @pytest.mark.requires_myst def test_myst_header_is_stable_1247_using_config( jupytext_toml_content="""notebook_metadata_filter = "-jupytext.text_representation.jupytext_version,settings,mystnb" """, md="""--- jupytext: formats: md:myst text_representation: extension: .md format_name: myst format_version: 0.13 kernelspec: display_name: Python 3 (ipykernel) language: python name: python3 mystnb: execution_mode: 'off' settings: output_matplotlib_strings: remove --- """, ): config = load_jupytext_configuration_file("jupytext.toml", jupytext_toml_content) nb = reads(md, fmt="md", config=config) md2 = writes(nb, fmt="md", config=config) compare(md2, md) @pytest.mark.requires_myst def test_myst_frontmatter_metadata_combo(no_jupytext_version_number): # --- # foo: bar # jupyter: <- subkeys become notebook metadata # lorem: ipsum # --- frontmatter = {"foo": "bar"} metadata = {"lorem": "ipsum"} md = dump_yaml_blocks( {**frontmatter, _JUPYTER_METADATA_NAMESPACE: metadata}, compact=False, ) config = load_jupytext_configuration_file( "jupytext.toml", "\n".join( ( 'notebook_metadata_filter = "all,-jupytext"', 'root_level_metadata_filter = "-all"', ) ), ) actual_nb = reads(md, fmt="md:myst", config=config) expected_nb = new_notebook( metadata=metadata, cells=[ new_raw_cell(dump_yaml_blocks(frontmatter, compact=False).strip()), ], ) compare_notebooks(actual_nb, expected_nb) # { # "cells": [ # { # "cell_type": "raw", # "source": "---\nfoo: bar\n---", <- merge with metadata in frontmatter # ... # } # ], # "metadata": {"foo": "baz"}, # ... # } actual_md = writes(actual_nb, fmt="md:myst", config=config) expected_md = md compare(actual_md, expected_md) ================================================ FILE: tests/functional/round_trip/test_read_all_py.py ================================================ import jupytext from jupytext.compare import compare def test_identity_source_write_read(py_file): with open(py_file) as fp: py = fp.read() nb = jupytext.reads(py, "py") py2 = jupytext.writes(nb, "py") compare(py2, py) ================================================ FILE: tests/functional/round_trip/test_rmd_to_ipynb.py ================================================ import jupytext from jupytext.compare import compare def test_identity_write_read(rmd_file, no_jupytext_version_number): """Test that writing the notebook with ipynb, and read again, yields identity""" with open(rmd_file) as fp: rmd = fp.read() nb = jupytext.reads(rmd, "Rmd") rmd2 = jupytext.writes(nb, "Rmd") compare(rmd2, rmd) def test_two_blank_lines_as_cell_separator(): rmd = """Some markdown text And a new cell """ nb = jupytext.reads(rmd, "Rmd") assert len(nb.cells) == 2 assert nb.cells[0].cell_type == "markdown" assert nb.cells[1].cell_type == "markdown" assert nb.cells[0].source == "Some markdown\ntext" assert nb.cells[1].source == "And a new cell" ================================================ FILE: tests/functional/simple_notebooks/test_ipynb_to_R.py ================================================ import nbformat import pytest import jupytext from jupytext.compare import compare_notebooks @pytest.mark.parametrize("ext", [".r", ".R"]) def test_identity_source_write_read(ipynb_R_file, ext): """ Test that writing the notebook with R, and read again, is the same as removing outputs """ with open(ipynb_R_file) as fp: nb1 = nbformat.read(fp, as_version=4) R = jupytext.writes(nb1, ext) nb2 = jupytext.reads(R, ext) compare_notebooks(nb2, nb1) ================================================ FILE: tests/functional/simple_notebooks/test_ipynb_to_myst.py ================================================ import json import unittest.mock as mock from textwrap import dedent import pytest from jupyter_server.utils import ensure_async from nbformat.v4.nbbase import new_notebook from tornado.web import HTTPError import jupytext from jupytext.cli import jupytext as jupytext_cli from jupytext.compare import compare from jupytext.formats import ( JupytextFormatError, get_format_implementation, guess_format, ) from jupytext.myst import ( CODE_DIRECTIVE, MystMetadataParsingError, matches_mystnb, myst_extensions, myst_to_notebook, ) @pytest.mark.requires_myst def test_bad_notebook_metadata(): """Test exception raised if notebook metadata cannot be parsed.""" with pytest.raises(MystMetadataParsingError): myst_to_notebook( dedent( """\ --- {{a --- """ ) ) @pytest.mark.requires_myst def test_bad_code_metadata(): """Test exception raised if cell metadata cannot be parsed.""" with pytest.raises(MystMetadataParsingError): myst_to_notebook( dedent( """\ ```{0} --- {{a --- ``` """ ).format(CODE_DIRECTIVE) ) @pytest.mark.requires_myst def test_bad_markdown_metadata(): """Test exception raised if markdown metadata cannot be parsed.""" with pytest.raises(MystMetadataParsingError): myst_to_notebook( dedent( """\ +++ {{a """ ) ) @pytest.mark.requires_myst def test_bad_markdown_metadata2(): """Test exception raised if markdown metadata is not a dict.""" with pytest.raises(MystMetadataParsingError): myst_to_notebook( dedent( """\ +++ [1, 2] """ ) ) @pytest.mark.requires_myst def test_matches_mystnb(): assert matches_mystnb("") is False assert matches_mystnb("```{code-cell}\n```") is False assert matches_mystnb("---\njupytext: true\n---") is False for ext in myst_extensions(no_md=True): assert matches_mystnb("", ext=ext) is True text = dedent( """\ --- {{a --- ```{code-cell} :b: {{c ``` """ ) assert matches_mystnb(text) is True text = dedent( """\ --- jupyter: jupytext: text_representation: format_name: myst extension: .md --- """ ) assert matches_mystnb(text) is True text = dedent( """\ --- jupytext: text_representation: format_name: myst extension: .md --- """ ) assert matches_mystnb(text) is True text = dedent( """\ --- a: 1 --- > ```{code-cell} ``` """ ) assert matches_mystnb(text) is True assert guess_format(text, ".md") == ("myst", {}) def test_not_installed(): with mock.patch("jupytext.formats.JUPYTEXT_FORMATS", return_value=[]): with pytest.raises(JupytextFormatError): get_format_implementation(".myst") @pytest.mark.requires_myst def test_add_source_map(): notebook = myst_to_notebook( dedent( """\ --- a: 1 --- abc +++ def ```{0} --- b: 2 --- c = 3 ``` xyz """ ).format(CODE_DIRECTIVE), add_source_map=True, ) assert notebook.metadata.source_map == [3, 5, 7, 12] PLEASE_INSTALL_MYST = "The MyST Markdown format requires .*" @pytest.mark.requires_no_myst def test_meaningfull_error_write_myst_missing(tmpdir): nb_file = tmpdir.join("notebook.ipynb") jupytext.write(new_notebook(), str(nb_file)) with pytest.raises(ImportError, match=PLEASE_INSTALL_MYST): jupytext_cli([str(nb_file), "--to", "md:myst"]) @pytest.mark.asyncio @pytest.mark.requires_no_myst async def test_meaningfull_error_open_myst_missing(tmpdir, cm): md_file = tmpdir.join("notebook.md") md_file.write( """--- jupytext: text_representation: extension: '.md' format_name: myst kernelspec: display_name: Python 3 language: python name: python3 --- 1 + 1 """ ) with pytest.raises(ImportError, match=PLEASE_INSTALL_MYST): jupytext_cli([str(md_file), "--to", "ipynb"]) cm.root_dir = str(tmpdir) with pytest.raises(HTTPError, match=PLEASE_INSTALL_MYST): await ensure_async(cm.get("notebook.md")) @pytest.mark.asyncio @pytest.mark.requires_myst @pytest.mark.parametrize("language_info", ["none", "std", "no_pygments_lexer"]) async def test_myst_representation_same_cli_or_contents_manager(tmpdir, cwd_tmpdir, cm, notebook_with_outputs, language_info): """This test gives some information on #759. As of Jupytext 1.11.1, in the MyST Markdown format, the code cells have an ipython3 lexer when the notebook "language_info" metadata has "ipython3" as the pygments_lexer. This information comes from the kernel and ATM it is not clear how the user can choose to include it or not in the md file.""" nb = notebook_with_outputs if language_info != "none": nb["metadata"]["language_info"] = { "codemirror_mode": {"name": "ipython", "version": 3}, "file_extension": ".py", "mimetype": "text/x-python", "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", "version": "3.7.3", } if language_info == "no_pygments_lexer": del nb["metadata"]["language_info"]["pygments_lexer"] # Writing the notebook with the Python API text_api = jupytext.writes(nb, fmt="md:myst") # How do code cells look like? code_cells = {line for line in text_api.splitlines() if line.startswith("```{code-cell")} if language_info == "std": assert code_cells == {"```{code-cell} ipython3"} else: assert code_cells == {"```{code-cell}"} # We get the same file with the command line jupytext tmpdir.mkdir("cli").join("notebook.ipynb").write(json.dumps(nb)) jupytext_cli(["--to", "md:myst", "cli/notebook.ipynb"]) text_cli = tmpdir.join("cli").join("notebook.md").read() compare(text_cli, text_api) # Or with the contents manager cm.formats = "ipynb,md:myst" cm.root_dir = str(tmpdir.mkdir("contents_manager")) await ensure_async(cm.save(model=dict(content=nb, type="notebook"), path="notebook.ipynb")) text_cm = tmpdir.join("contents_manager").join("notebook.md").read() compare(text_cm, text_api) ================================================ FILE: tests/functional/simple_notebooks/test_ipynb_to_py.py ================================================ import nbformat import jupytext from jupytext.compare import compare_notebooks def test_identity_source_write_read(ipynb_py_file): """Test that writing the notebook with jupytext, and read again, is the same as removing outputs""" with open(ipynb_py_file) as fp: nb1 = nbformat.read(fp, as_version=4) py = jupytext.writes(nb1, "py") nb2 = jupytext.reads(py, "py") compare_notebooks(nb2, nb1) ================================================ FILE: tests/functional/simple_notebooks/test_ipynb_to_rmd.py ================================================ import nbformat import jupytext from jupytext.compare import compare_notebooks def test_identity_source_write_read(ipynb_py_R_jl_file): """Test that writing the notebook with rmd, and read again, is the same as removing outputs""" with open(ipynb_py_R_jl_file) as fp: nb1 = nbformat.read(fp, as_version=4) rmd = jupytext.writes(nb1, "Rmd") nb2 = jupytext.reads(rmd, "Rmd") compare_notebooks(nb2, nb1, "Rmd") ================================================ FILE: tests/functional/simple_notebooks/test_knitr_spin.py ================================================ import jupytext def test_jupytext_same_as_knitr_spin(r_spin_file, tmpdir): nb = jupytext.read(r_spin_file) rmd_jupytext = jupytext.writes(nb, "Rmd") # Rmd file generated with spin(hair='R/spin.R', knit=FALSE) rmd_file = r_spin_file.replace("R_spin", "Rmd").replace(".R", ".Rmd") with open(rmd_file) as fp: rmd_spin = fp.read() assert rmd_spin == rmd_jupytext ================================================ FILE: tests/functional/simple_notebooks/test_read_dotnet_try_markdown.py ================================================ import jupytext from jupytext.cell_metadata import parse_key_equal_value from jupytext.compare import compare def test_parse_metadata(): assert parse_key_equal_value("--key value --key-2 .\\a\\b.cs") == { "incorrectly_encoded_metadata": "--key value --key-2 .\\a\\b.cs" } def test_parse_double_hyphen_metadata(): assert parse_key_equal_value("--key1 value1 --key2 value2") == { "incorrectly_encoded_metadata": "--key1 value1 --key2 value2" } def test_read_dotnet_try_markdown( md="""This is a dotnet/try Markdown file, inspired from this [post](https://devblogs.microsoft.com/dotnet/creating-interactive-net-documentation/) ``` cs --region methods --source-file .\\myapp\\Program.cs --project .\\myapp\\myapp.csproj var name ="Rain"; Console.WriteLine($"Hello {name.ToUpper()}!"); ``` """, ): # Read the notebook nb = jupytext.reads(md, fmt=".md") assert nb.metadata["jupytext"]["main_language"] == "csharp" assert len(nb.cells) == 2 assert nb.cells[0].cell_type == "markdown" assert nb.cells[1].cell_type == "code" assert ( nb.cells[1].source == """var name ="Rain"; Console.WriteLine($"Hello {name.ToUpper()}!");""" ) compare( nb.cells[1].metadata, { "language": "cs", "incorrectly_encoded_metadata": "--region methods --source-file .\\myapp\\Program.cs --project .\\myapp\\myapp.csproj", # noqa: E501 }, ) # Round trip to Markdown md2 = jupytext.writes(nb, "md") compare(md2, md.replace("``` cs", "```cs")) ================================================ FILE: tests/functional/simple_notebooks/test_read_empty_text_notebook.py ================================================ import pytest from nbformat.notebooknode import NotebookNode import jupytext from jupytext.formats import NOTEBOOK_EXTENSIONS from jupytext.myst import is_myst_available, myst_extensions from jupytext.quarto import is_quarto_available @pytest.mark.parametrize("ext", sorted(set(NOTEBOOK_EXTENSIONS) - {".ipynb"})) def test_read_empty_text_notebook(ext, tmp_path): if ext == ".qmd" and not is_quarto_available(min_version="0.2.0"): pytest.skip("quarto is not available") if ext in myst_extensions(no_md=True) and not is_myst_available(): pytest.skip("MyST is not available") empty_nb = (tmp_path / "notebook").with_suffix(ext) empty_nb.touch() nb = jupytext.read(empty_nb) assert isinstance(nb, NotebookNode) assert not nb.cells ================================================ FILE: tests/functional/simple_notebooks/test_read_folding_markers.py ================================================ import jupytext from jupytext.compare import compare # region Folding markers as cell boundaries # region Sub-region with metadata {"key": "value"} def test_mark_cell_with_vim_folding_markers( script="""# This is a markdown cell # {{{ And this is a foldable code region with metadata {"key": "value"} a = 1 b = 2 c = 3 # }}} """, ): nb = jupytext.reads(script, "py") assert nb.metadata["jupytext"]["cell_markers"] == "{{{,}}}" assert len(nb.cells) == 2 assert nb.cells[0].cell_type == "markdown" assert nb.cells[0].source == "This is a markdown cell" assert nb.cells[1].cell_type == "code" assert nb.cells[1].source == "a = 1\n\nb = 2\n\nc = 3" assert nb.cells[1].metadata == { "title": "And this is a foldable code region with metadata", "key": "value", } script2 = jupytext.writes(nb, "py") compare(script2, script) # endregion def test_mark_cell_with_vscode_pycharm_folding_markers( script="""# This is a markdown cell # region And this is a foldable code region with metadata {"key": "value"} a = 1 b = 2 c = 3 # endregion """, ): nb = jupytext.reads(script, "py") assert len(nb.cells) == 2 assert nb.cells[0].cell_type == "markdown" assert nb.cells[0].source == "This is a markdown cell" assert nb.cells[1].cell_type == "code" assert nb.cells[1].source == "a = 1\n\nb = 2\n\nc = 3" assert nb.cells[1].metadata == { "title": "And this is a foldable code region with metadata", "key": "value", } script2 = jupytext.writes(nb, "py") compare(script2, script) def test_mark_cell_with_no_title_and_inner_region( script="""# This is a markdown cell # region {"key": "value"} a = 1 # region An inner region b = 2 # endregion def f(x): return x + 1 # endregion d = 4 """, ): nb = jupytext.reads(script, "py") assert nb.cells[0].cell_type == "markdown" assert nb.cells[0].source == "This is a markdown cell" assert nb.cells[1].cell_type == "code" assert nb.cells[1].source == '# region {"key": "value"}\na = 1' assert nb.cells[2].cell_type == "code" assert nb.cells[2].metadata["title"] == "An inner region" assert nb.cells[2].source == "b = 2" assert nb.cells[3].cell_type == "code" assert nb.cells[3].source == "def f(x):\n return x + 1" assert nb.cells[4].cell_type == "code" assert nb.cells[4].source == "# endregion" assert nb.cells[5].cell_type == "code" assert nb.cells[5].source == "d = 4" assert len(nb.cells) == 6 script2 = jupytext.writes(nb, "py") compare(script2, script) # endregion def test_adjacent_regions( script="""# region global # region innermost a = 1 b = 2 # endregion # endregion """, ): nb = jupytext.reads(script, "py") assert len(nb.cells) == 3 assert nb.cells[0].cell_type == "code" assert nb.cells[0].source == "# region global" assert nb.cells[1].cell_type == "code" assert nb.cells[1].source == "a = 1\n\nb = 2" assert nb.cells[2].cell_type == "code" assert nb.cells[2].source == "# endregion" script2 = jupytext.writes(nb, "py") compare(script2, script) def test_indented_markers_are_ignored( script="""# region global # region indented a = 1 b = 2 # endregion # endregion """, ): nb = jupytext.reads(script, "py") assert len(nb.cells) == 1 assert nb.cells[0].cell_type == "code" script2 = jupytext.writes(nb, "py") compare(script2, script) ================================================ FILE: tests/functional/simple_notebooks/test_read_incomplete_rmd.py ================================================ import jupytext def test_incomplete_header( rmd="""--- title: Incomplete header ```{python} 1+1 ``` """, ): nb = jupytext.reads(rmd, "Rmd") assert len(nb.cells) == 2 assert nb.cells[0].cell_type == "markdown" assert nb.cells[0].source == "---\ntitle: Incomplete header" assert nb.cells[1].cell_type == "code" assert nb.cells[1].source == "1+1" def test_code_in_markdown_block( rmd="""```{python} a = 1 b = 2 a + b ``` ```python '''Code here goes to a Markdown cell''' '''even if we have two blank lines above''' ``` ```{bash} ls -l ``` """, ): nb = jupytext.reads(rmd, "Rmd") assert len(nb.cells) == 3 assert nb.cells[0].cell_type == "code" assert nb.cells[0].source == "a = 1\nb = 2\na + b" assert nb.cells[1].cell_type == "markdown" assert ( nb.cells[1].source == """```python '''Code here goes to a Markdown cell''' '''even if we have two blank lines above''' ```""" ) assert nb.cells[2].cell_type == "code" assert nb.cells[2].source == "%%bash\nls -l" def test_unterminated_header( rmd="""--- title: Unterminated header ```{python} 1+3 ``` some text ```{r} 1+4 ``` ```{python not_terminated} 1+5 """, ): nb = jupytext.reads(rmd, "Rmd") assert len(nb.cells) == 5 assert nb.cells[0].cell_type == "markdown" assert nb.cells[0].source == "---\ntitle: Unterminated header" assert nb.cells[1].cell_type == "code" assert nb.cells[1].source == "1+3" assert nb.cells[2].cell_type == "markdown" assert nb.cells[2].source == "some text" assert nb.cells[3].cell_type == "code" assert nb.cells[3].source == "%%R\n1+4" assert nb.cells[4].cell_type == "code" assert nb.cells[4].metadata == {"name": "not_terminated"} assert nb.cells[4].source == "1+5" ================================================ FILE: tests/functional/simple_notebooks/test_read_simple_R.py ================================================ import pytest import jupytext from jupytext.compare import compare @pytest.mark.parametrize("ext", [".r", ".R"]) def test_read_simple_file( ext, rnb="""#' --- #' title: Simple file #' --- #' Here we have some text #' And below we have some R code f <- function(x) { x + 1 } h <- function(y) y + 1 """, ): nb = jupytext.reads(rnb, ext) assert len(nb.cells) == 4 assert nb.cells[0].cell_type == "raw" assert nb.cells[0].source == "---\ntitle: Simple file\n---" assert nb.cells[1].cell_type == "markdown" assert nb.cells[1].source == "Here we have some text\nAnd below we have some R code" assert nb.cells[2].cell_type == "code" compare( nb.cells[2].source, """f <- function(x) { x + 1 }""", ) assert nb.cells[3].cell_type == "code" compare( nb.cells[3].source, """h <- function(y) y + 1""", ) rnb2 = jupytext.writes(nb, ext) compare(rnb2, rnb) @pytest.mark.parametrize("ext", [".r", ".R"]) def test_read_less_simple_file( ext, rnb="""#' --- #' title: Less simple file #' --- #' Here we have some text #' And below we have some R code # This is a comment about function f f <- function(x) { return(x+1)} # And a comment on h h <- function(y) { return(y-1) } """, ): nb = jupytext.reads(rnb, ext) assert len(nb.cells) == 4 assert nb.cells[0].cell_type == "raw" assert nb.cells[0].source == "---\ntitle: Less simple file\n---" assert nb.cells[1].cell_type == "markdown" assert nb.cells[1].source == "Here we have some text\nAnd below we have some R code" assert nb.cells[2].cell_type == "code" compare( nb.cells[2].source, """# This is a comment about function f f <- function(x) { return(x+1)}""", ) assert nb.cells[3].cell_type == "code" compare( nb.cells[3].source, """# And a comment on h h <- function(y) { return(y-1) }""", ) rnb2 = jupytext.writes(nb, ext) compare(rnb2, rnb) @pytest.mark.parametrize("ext", [".r", ".R"]) def test_no_space_after_code( ext, rnb="""# -*- coding: utf-8 -*- #' Markdown cell f <- function(x) { return(x+1) } #' And a new cell, and non ascii contênt """, ): nb = jupytext.reads(rnb, ext) assert len(nb.cells) == 3 assert nb.cells[0].cell_type == "markdown" assert nb.cells[0].source == "Markdown cell" assert nb.cells[1].cell_type == "code" assert ( nb.cells[1].source == """f <- function(x) { return(x+1) }""" ) assert nb.cells[2].cell_type == "markdown" assert nb.cells[2].source == "And a new cell, and non ascii contênt" rnb2 = jupytext.writes(nb, ext) compare(rnb2, rnb) @pytest.mark.parametrize("ext", [".r", ".R"]) def test_read_write_script( ext, rnb="""#!/usr/bin/env Rscript # coding=utf-8 print('Hello world') """, ): nb = jupytext.reads(rnb, ext) rnb2 = jupytext.writes(nb, ext) compare(rnb2, rnb) @pytest.mark.parametrize("ext", [".r", ".R"]) def test_escape_start_pattern( ext, rnb="""#' The code start pattern '#+' can #' appear in code and markdown cells. #' In markdown cells it is escaped like here: #' #+ fig.width=12 # In code cells like this one, it is also escaped # #+ cell_name language="python" 1 + 1 """, ): nb = jupytext.reads(rnb, ext) assert len(nb.cells) == 3 assert nb.cells[0].cell_type == "markdown" assert nb.cells[1].cell_type == "markdown" assert nb.cells[2].cell_type == "code" assert ( nb.cells[1].source == """In markdown cells it is escaped like here: #+ fig.width=12""" ) assert ( nb.cells[2].source == """# In code cells like this one, it is also escaped #+ cell_name language="python" 1 + 1""" ) rnb2 = jupytext.writes(nb, ext) compare(rnb2, rnb) @pytest.mark.parametrize("ext", [".r", ".R"]) def test_read_simple_r( ext, text="""# This is a very simple R file # I expect to get three cells here. # # The first one is markdown. The two others # are code cells cars plot(cars) """, ): nb = jupytext.reads(text, ext) assert len(nb.cells) == 3 assert nb.cells[0].cell_type == "markdown" assert nb.cells[1].cell_type == "code" assert nb.cells[2].cell_type == "code" assert nb.cells[1].source == "cars" assert nb.cells[2].source == "plot(cars)" text2 = jupytext.writes(nb, ext) compare(text2, text) ================================================ FILE: tests/functional/simple_notebooks/test_read_simple_clojure.py ================================================ import jupytext from jupytext.compare import compare def test_read_simple_file( script=""";; --- ;; title: Simple file ;; --- ;; Here we have some text ;; And below we have some code ((fn [] (println "Hello World"))) """, ): nb = jupytext.reads(script, "clj") assert len(nb.cells) == 3 assert nb.cells[0].cell_type == "raw" assert nb.cells[0].source == "---\ntitle: Simple file\n---" assert nb.cells[1].cell_type == "markdown" assert nb.cells[1].source == "Here we have some text\nAnd below we have some code" assert nb.cells[2].cell_type == "code" compare( nb.cells[2].source, """((fn [] (println "Hello World")))""", ) script2 = jupytext.writes(nb, "clj") compare(script2, script) ================================================ FILE: tests/functional/simple_notebooks/test_read_simple_csharp.py ================================================ import pytest import jupytext from jupytext.compare import compare @pytest.mark.parametrize("lang", ["cs", "c#", "csharp"]) def test_simple_cs(lang): source = """// A Hello World! program in C#. Console.WriteLine("Hello World!"); """ md = """```{lang} {source} ``` """.format(lang=lang, source=source) nb = jupytext.reads(md, "md") assert nb.metadata["jupytext"]["main_language"] == "csharp" assert len(nb.cells) == 1 assert nb.cells[0].cell_type == "code" cs = jupytext.writes(nb, "cs") assert source in cs if lang != "csharp": assert cs.startswith(f'// %% language="{lang}"') md2 = jupytext.writes(nb, "md") compare(md2, md) @pytest.mark.parametrize("lang", ["cs", "c#", "csharp"]) def test_csharp_magics(no_jupytext_version_number, lang): md = """```{lang} #!html Hello! ``` """.format(lang=lang) nb = jupytext.reads(md, "md") nb.metadata["jupytext"].pop("notebook_metadata_filter") nb.metadata["jupytext"].pop("cell_metadata_filter") assert nb.metadata["jupytext"]["main_language"] == "csharp" assert len(nb.cells) == 1 assert nb.cells[0].cell_type == "code" cs = jupytext.writes(nb, "cs") assert all(line.startswith("//") for line in cs.splitlines()), cs md2 = jupytext.writes(nb, "md") md_expected = """--- jupyter: jupytext: main_language: csharp --- ```html Hello! ``` """ compare(md2, md_expected) def test_read_html_cell_from_md(no_jupytext_version_number): md = """--- jupyter: jupytext: main_language: csharp --- ```html Hello! ``` """ nb = jupytext.reads(md, "md") assert len(nb.cells) == 1 assert nb.cells[0].cell_type == "code" compare(nb.cells[0].source, "#!html\nHello!") md2 = jupytext.writes(nb, "md") compare(md2, md) ================================================ FILE: tests/functional/simple_notebooks/test_read_simple_go.py ================================================ import jupytext from jupytext.compare import compare def test_read_simple_file( go="""// -*- coding: utf-8 -*- // --- // jupyter: // kernelspec: // display_name: Go (gonb) // language: go // name: gonb // --- // A notebook that use [GoNB](https://github.com/janpfeifer/gonb) // the code below comes from [tutorial.ipynb](https://github.com/janpfeifer/gonb/blob/main/examples/tutorial.ipynb) func main() { fmt.Printf("Hello World!") } """, ): nb = jupytext.reads(go, "go:light") assert len(nb.cells) == 3 assert nb.cells[0].cell_type == "markdown" assert nb.cells[1].cell_type == "markdown" assert nb.cells[2].cell_type == "code" def test_read_go_notebook_with_percent_percent_and_arguments( go="""// %% [markdown] // # Square Function // // Defines a function $f(x) = x^2$ // %% func Square(x float64) float64 { return x*x } // %% [markdown] // # Examples // // ## Example A: $x = 3$ // %% var x = flag.Float64("x", 0.0, "value of x to feed f(x)") //gonb:%% -x=3 fmt.Printf("Square(%g)=%g\n", *x, Square(*x)) // %% [markdown] // ## Example B: $x = 4$ // %% //gonb:%% -x=4 fmt.Printf("Square(%g)=%g\n", *x, Square(*x)) """, ): nb = jupytext.reads(go, "go") for cell in nb.cells: assert "gonb" not in cell.source, cell.source go2 = jupytext.writes(nb, "go") compare(go2, go) def test_read_go_notebook_with_magic_main( go="""// %% package square // %% [markdown] // # Defining a $x^2$ function // It returns x*x. // %% func Square(x float64) float64 { return x * x } // %% [markdown] // # Examples // // ## Example A: $x = 3$ // %% var x = flag.Float64("x", 0.0, "Value of x") func example() { fmt.Printf("Square(%g)=%g\n", *x, Square(*x)) } // %main example -x=3 // %% [markdown] // ## Example B: $x = 4$ // %% // %main example -x=4 """, ): nb = jupytext.reads(go, "go") for cell in nb.cells: assert "gonb" not in cell.source, cell.source go2 = jupytext.writes(nb, "go") compare(go2, go) def test_commented_magic( go="""// %% // This is a commented magic // //gonb:%% // %% [markdown] // This is a commented magic in a markdown cell // // //gonb:%% """, ): nb = jupytext.reads(go, "go") assert len(nb.cells) == 2 assert nb.cells[0].cell_type == "code" assert ( nb.cells[0].source == """// This is a commented magic // %%""" ) assert nb.cells[1].cell_type == "markdown" assert ( nb.cells[1].source == """This is a commented magic in a markdown cell // %%""" ) go2 = jupytext.writes(nb, "go") compare(go2, go) def test_magic_commands_are_commented( go="""// %% // !*rm -f go.work && go work init && go work use . ${HOME}/Projects/gopjrt // %goworkfix // %env LD_LIBRARY_PATH=/usr/local/lib """, ): nb = jupytext.reads(go, "go:percent") assert len(nb.cells) == 1 assert nb.cells[0].cell_type == "code" assert ( nb.cells[0].source == """!*rm -f go.work && go work init && go work use . ${HOME}/Projects/gopjrt %goworkfix %env LD_LIBRARY_PATH=/usr/local/lib""" ) go2 = jupytext.writes(nb, "go") compare(go2, go) ================================================ FILE: tests/functional/simple_notebooks/test_read_simple_groovy.py ================================================ import jupytext from jupytext.compare import compare def test_read_simple_file( script="""// --- // title: Simple file // --- // Here we have some text // And below we have some code println("Hello World") """, ): nb = jupytext.reads(script, "groovy") assert len(nb.cells) == 3 assert nb.cells[0].cell_type == "raw" assert nb.cells[0].source == "---\ntitle: Simple file\n---" assert nb.cells[1].cell_type == "markdown" assert nb.cells[1].source == "Here we have some text\nAnd below we have some code" assert nb.cells[2].cell_type == "code" assert nb.cells[2].source == """println("Hello World")""" script2 = jupytext.writes(nb, "groovy") compare(script2, script) ================================================ FILE: tests/functional/simple_notebooks/test_read_simple_hydrogen.py ================================================ import jupytext from jupytext.compare import compare def test_read_simple_file( script="""# --- # title: Simple file # --- # %% [markdown] # This is a markdown cell # %% [raw] # This is a raw cell # %%% sub-cell title # This is a sub-cell # %%%% sub-sub-cell title # This is a sub-sub-cell # %% And now a code cell 1 + 2 + 3 + 4 5 6 %%pylab inline 7 """, ): nb = jupytext.reads(script, "py:hydrogen") assert len(nb.cells) == 6 assert nb.cells[0].cell_type == "raw" assert nb.cells[0].source == "---\ntitle: Simple file\n---" assert nb.cells[1].cell_type == "markdown" assert nb.cells[1].source == "This is a markdown cell" assert nb.cells[2].cell_type == "raw" assert nb.cells[2].source == "This is a raw cell" assert nb.cells[3].cell_type == "code" assert nb.cells[3].source == "# This is a sub-cell" assert nb.cells[3].metadata["title"] == "sub-cell title" assert nb.cells[4].cell_type == "code" assert nb.cells[4].source == "# This is a sub-sub-cell" assert nb.cells[4].metadata["title"] == "sub-sub-cell title" assert nb.cells[5].cell_type == "code" compare( nb.cells[5].source, """1 + 2 + 3 + 4 5 6 %%pylab inline 7""", ) assert nb.cells[5].metadata == {"title": "And now a code cell"} script2 = jupytext.writes(nb, "py:hydrogen") compare(script2, script) def test_read_cell_with_metadata( script="""# %% a code cell with parameters {"tags": ["parameters"]} a = 3 """, ): nb = jupytext.reads(script, "py:hydrogen") assert len(nb.cells) == 1 assert nb.cells[0].cell_type == "code" assert nb.cells[0].source == "a = 3" assert nb.cells[0].metadata == { "title": "a code cell with parameters", "tags": ["parameters"], } script2 = jupytext.writes(nb, "py:hydrogen") compare(script2, script) def test_read_nbconvert_script( script=""" # coding: utf-8 # A markdown cell # In[1]: %pylab inline import pandas as pd pd.options.display.max_rows = 6 pd.options.display.max_columns = 20 # Another markdown cell # In[2]: 1 + 1 # Again, a markdown cell # In[33]: 2 + 2 # 3 + 3 """, ): assert jupytext.formats.guess_format(script, ".py")[0] == "hydrogen" nb = jupytext.reads(script, ".py") assert len(nb.cells) == 5 def test_read_remove_blank_lines( script="""# %% import pandas as pd # %% Display a data frame df = pd.DataFrame({'A': [1, 2], 'B': [3, 4]}, index=pd.Index(['x0', 'x1'], name='x')) df # %% Pandas plot {"tags": ["parameters"]} df.plot(kind='bar') # %% sample class class MyClass: pass # %% a function def f(x): return 42 * x """, ): nb = jupytext.reads(script, "py") assert len(nb.cells) == 5 for i in range(5): assert nb.cells[i].cell_type == "code" assert not nb.cells[i].source.startswith("\n") assert not nb.cells[i].source.endswith("\n") script2 = jupytext.writes(nb, "py:hydrogen") compare(script2, script) def test_no_crash_on_square_bracket( script="""# %% In [2] print('Hello') """, ): nb = jupytext.reads(script, "py") script2 = jupytext.writes(nb, "py:hydrogen") compare(script2, script) def test_nbconvert_cell( script="""# In[2]: print('Hello') """, ): nb = jupytext.reads(script, "py") script2 = jupytext.writes(nb, "py:hydrogen") expected = """# %% print('Hello') """ compare(script2, expected) def test_nbformat_v3_nbpy_cell( script="""# print('Hello') """, ): nb = jupytext.reads(script, "py") script2 = jupytext.writes(nb, "py:hydrogen") expected = """# %% print('Hello') """ compare(script2, expected) ================================================ FILE: tests/functional/simple_notebooks/test_read_simple_ipynb.py ================================================ import nbformat from nbformat.v4.nbbase import new_notebook import jupytext from jupytext.compare import compare def test_save_ipynb_with_jupytext_has_final_newline(tmpdir): nb = new_notebook() file_jupytext = str(tmpdir.join("jupytext.ipynb")) file_nbformat = str(tmpdir.join("nbformat.ipynb")) jupytext.write(nb, file_jupytext) with open(file_nbformat, "w") as fp: nbformat.write(nb, fp) with open(file_jupytext) as fp: text_jupytext = fp.read() with open(file_nbformat) as fp: text_nbformat = fp.read() compare(text_jupytext, text_nbformat) ================================================ FILE: tests/functional/simple_notebooks/test_read_simple_java.py ================================================ import jupytext from jupytext.compare import compare def test_read_simple_file( script="""// --- // title: Simple file // --- // Here we have some text // And below we have some code System.out.println("Hello World"); """, ): nb = jupytext.reads(script, "java") assert len(nb.cells) == 3 assert nb.cells[0].cell_type == "raw" assert nb.cells[0].source == "---\ntitle: Simple file\n---" assert nb.cells[1].cell_type == "markdown" assert nb.cells[1].source == "Here we have some text\nAnd below we have some code" assert nb.cells[2].cell_type == "code" assert nb.cells[2].source == """System.out.println("Hello World");""" script2 = jupytext.writes(nb, "java") compare(script2, script) ================================================ FILE: tests/functional/simple_notebooks/test_read_simple_julia.py ================================================ import jupytext from jupytext.compare import compare def test_read_simple_file( julia='''""" cube(x) Compute the cube of `x`, ``x^3``. # Examples ```jldoctest julia> cube(2) 8 ``` """ function cube(x) x^3 end cube(x) # And a markdown comment ''', ): nb = jupytext.reads(julia, "jl") assert nb.metadata["jupytext"]["main_language"] == "julia" assert len(nb.cells) == 3 assert nb.cells[0].cell_type == "code" assert ( nb.cells[0].source == '''""" cube(x) Compute the cube of `x`, ``x^3``. # Examples ```jldoctest julia> cube(2) 8 ``` """ function cube(x) x^3 end''' ) assert nb.cells[1].cell_type == "code" assert nb.cells[1].source == "cube(x)" assert nb.cells[2].cell_type == "markdown" compare(nb.cells[2].source, "And a markdown comment") julia2 = jupytext.writes(nb, "jl") compare(julia2, julia) ================================================ FILE: tests/functional/simple_notebooks/test_read_simple_markdown.py ================================================ from nbformat.v4.nbbase import ( new_code_cell, new_markdown_cell, new_notebook, new_raw_cell, ) import jupytext from jupytext.combine import combine_inputs_with_outputs from jupytext.compare import compare, compare_cells, compare_notebooks def test_read_mostly_py_markdown_file( markdown="""--- title: Simple file --- ```python import numpy as np x = np.arange(0, 2*math.pi, eps) ``` ```python x = np.arange(0,1,eps) y = np.abs(x)-.5 ``` This is a Markdown cell ``` # followed by a code cell with no language info ``` ``` # another code cell # with two blank lines ``` And the same markdown cell continues this is a raw cell ```R ls() ``` ```R cat(stringi::stri_rand_lipsum(3), sep='\n\n') ``` """, ): nb = jupytext.reads(markdown, "md") assert nb.metadata["jupytext"]["main_language"] == "python" compare_cells( nb.cells, [ new_raw_cell("---\ntitle: Simple file\n---"), new_code_cell("import numpy as np\nx = np.arange(0, 2*math.pi, eps)"), new_code_cell("x = np.arange(0,1,eps)\ny = np.abs(x)-.5"), new_markdown_cell( """This is a Markdown cell ``` # followed by a code cell with no language info ``` ``` # another code cell # with two blank lines ``` And the same markdown cell continues""" ), new_raw_cell("this is a raw cell"), new_code_cell("%%R\nls()"), new_code_cell("%%R\ncat(stringi::stri_rand_lipsum(3), sep='\n\n')"), ], compare_ids=False, ) markdown2 = jupytext.writes(nb, "md") compare(markdown2, markdown) def test_read_md_and_markdown_regions( markdown="""Some text A long cell Another long cell """, ): nb = jupytext.reads(markdown, "md") assert nb.metadata["jupytext"]["main_language"] == "python" compare_cells( nb.cells, [ new_markdown_cell("Some text"), new_markdown_cell( """A long cell""", metadata={"region_name": "md"}, ), new_markdown_cell( """Another long cell""", metadata={"region_name": "markdown"}, ), ], compare_ids=False, ) markdown2 = jupytext.writes(nb, "md") compare(markdown2, markdown) def test_read_mostly_R_markdown_file( markdown="""```R ls() ``` ```R cat(stringi::stri_rand_lipsum(3), sep='\n\n') ``` """, ): nb = jupytext.reads(markdown, "md") assert nb.metadata["jupytext"]["main_language"] == "R" compare_cells( nb.cells, [ new_code_cell("ls()"), new_code_cell("cat(stringi::stri_rand_lipsum(3), sep='\n\n')"), ], compare_ids=False, ) markdown2 = jupytext.writes(nb, "md") compare(markdown2, markdown) def test_read_markdown_file_no_language( markdown="""``` ls ``` ``` echo 'Hello World' ``` """, ): nb = jupytext.reads(markdown, "md") markdown2 = jupytext.writes(nb, "md") compare(markdown2, markdown) def test_read_julia_notebook( markdown="""```julia 1 + 1 ``` """, ): nb = jupytext.reads(markdown, "md") assert nb.metadata["jupytext"]["main_language"] == "julia" assert len(nb.cells) == 1 assert nb.cells[0].cell_type == "code" markdown2 = jupytext.writes(nb, "md") compare(markdown2, markdown) def test_split_on_header( markdown="""A paragraph # H1 Header ## H2 Header Another paragraph """, ): fmt = {"extension": ".md", "split_at_heading": True} nb = jupytext.reads(markdown, fmt) assert nb.cells[0].source == "A paragraph" assert nb.cells[1].source == "# H1 Header" assert nb.cells[2].source == "## H2 Header\n\nAnother paragraph" assert len(nb.cells) == 3 markdown2 = jupytext.writes(nb, fmt) compare(markdown2, markdown) def test_split_on_header_after_two_blank_lines( markdown="""A paragraph # H1 Header """, ): fmt = {"extension": ".Rmd", "split_at_heading": True} nb = jupytext.reads(markdown, fmt) markdown2 = jupytext.writes(nb, fmt) compare(markdown2, markdown) def test_split_at_heading_in_metadata( markdown="""--- jupyter: jupytext: split_at_heading: true --- A paragraph # H1 Header """, nb_expected=new_notebook(cells=[new_markdown_cell("A paragraph"), new_markdown_cell("# H1 Header")]), ): nb = jupytext.reads(markdown, ".md") compare_notebooks(nb, nb_expected) def test_code_cell_with_metadata( markdown="""```python tags=["parameters"] a = 1 b = 2 ``` """, ): nb = jupytext.reads(markdown, "md") compare_cells( nb.cells, [new_code_cell(source="a = 1\nb = 2", metadata={"tags": ["parameters"]})], compare_ids=False, ) markdown2 = jupytext.writes(nb, "md") compare(markdown2, markdown) def test_raw_cell_with_metadata_json( markdown=""" raw content """, ): nb = jupytext.reads(markdown, "md") compare_cells( nb.cells, [new_raw_cell(source="raw content", metadata={"key": "value"})], compare_ids=False, ) markdown2 = jupytext.writes(nb, "md") compare(markdown2, markdown) def test_raw_cell_with_metadata( markdown=""" raw content """, ): nb = jupytext.reads(markdown, "md") compare_cells( nb.cells, [new_raw_cell(source="raw content", metadata={"key": "value"})], compare_ids=False, ) markdown2 = jupytext.writes(nb, "md") compare(markdown2, markdown) def test_read_raw_cell_markdown_version_1_1( markdown="""--- jupyter: jupytext: text_representation: extension: .md format_name: markdown format_version: '1.1' jupytext_version: 1.1.0 --- ```key="value" raw content ``` """, ): nb = jupytext.reads(markdown, "md") compare_cells( nb.cells, [new_raw_cell(source="raw content", metadata={"key": "value"})], compare_ids=False, ) md2 = jupytext.writes(nb, "md") assert "format_version: '1.1'" not in md2 def test_read_raw_cell_markdown_version_1_1_with_mimetype( header="""--- jupyter: jupytext: text_representation: extension: .md format_name: markdown format_version: '1.1' jupytext_version: 1.1.0-rc0 kernelspec: display_name: Python 3 language: python name: python3 --- """, markdown_11="""```raw_mimetype="text/restructuredtext" .. meta:: :description: Topic: Integrated Development Environments, Difficulty: Easy, Category: Tools :keywords: python, introduction, IDE, PyCharm, VSCode, Jupyter, recommendation, tools ``` """, markdown_12=""" .. meta:: :description: Topic: Integrated Development Environments, Difficulty: Easy, Category: Tools :keywords: python, introduction, IDE, PyCharm, VSCode, Jupyter, recommendation, tools """, ): nb = jupytext.reads(header + "\n" + markdown_11, "md") compare_cells( nb.cells, [ new_raw_cell( source=""".. meta:: :description: Topic: Integrated Development Environments, Difficulty: Easy, Category: Tools :keywords: python, introduction, IDE, PyCharm, VSCode, Jupyter, recommendation, tools""", metadata={"raw_mimetype": "text/restructuredtext"}, ) ], compare_ids=False, ) md2 = jupytext.writes(nb, "md") assert "format_version: '1.1'" not in md2 nb.metadata["jupytext"]["notebook_metadata_filter"] = "-all" md2 = jupytext.writes(nb, "md") compare(md2, markdown_12) def test_markdown_cell_with_metadata_json( markdown=""" A long markdown cell """, ): nb = jupytext.reads(markdown, "md") compare_cells( nb.cells, [new_markdown_cell(source="A long\n\n\nmarkdown cell", metadata={"key": "value"})], compare_ids=False, ) markdown2 = jupytext.writes(nb, "md") compare(markdown2, markdown) def test_markdown_cell_with_metadata( markdown=""" A long markdown cell """, ): nb = jupytext.reads(markdown, "md") compare_cells( nb.cells, [new_markdown_cell(source="A long\n\n\nmarkdown cell", metadata={"key": "value"})], compare_ids=False, ) markdown2 = jupytext.writes(nb, "md") compare(markdown2, markdown) def test_two_markdown_cells( markdown="""# A header A long markdown cell """, ): nb = jupytext.reads(markdown, "md") compare_cells( nb.cells, [ new_markdown_cell(source="# A header"), new_markdown_cell(source="A long\n\n\nmarkdown cell"), ], compare_ids=False, ) markdown2 = jupytext.writes(nb, "md") compare(markdown2, markdown) def test_combine_md_version_one(): markdown = """--- jupyter: jupytext: text_representation: extension: .md format_name: markdown format_version: '1.0' jupytext_version: 1.0.0 kernelspec: display_name: Python 3 language: python name: python3 --- A short markdown cell ``` a raw cell ``` ```python 1 + 1 ``` """ # notebook read from markdown file in version 1.0 nb_source = jupytext.reads(markdown, "md") # actual notebook has metadata nb_meta = jupytext.reads(markdown, "md") for cell in nb_meta.cells: cell.metadata = {"key": "value"} nb_source = combine_inputs_with_outputs(nb_source, nb_meta) for cell in nb_source.cells: assert cell.metadata == {"key": "value"}, cell.source def test_jupyter_cell_is_not_split(): text = """Here we have a markdown file with a jupyter code cell ```python 1 + 1 2 + 2 ``` the code cell should become a Jupyter cell. """ nb = jupytext.reads(text, "md") assert nb.cells[0].cell_type == "markdown" compare( nb.cells[0].source, """Here we have a markdown file with a jupyter code cell""", ) assert nb.cells[1].cell_type == "code" compare( nb.cells[1].source, """1 + 1 2 + 2""", ) assert nb.cells[2].cell_type == "markdown" compare(nb.cells[2].source, "the code cell should become a Jupyter cell.") assert len(nb.cells) == 3 def test_indented_code_is_not_split(): text = """Here we have a markdown file with an indented code cell 1 + 1 2 + 2 the code cell should not become a Jupyter cell, nor be split into two pieces.""" nb = jupytext.reads(text, "md") compare(nb.cells[0].source, text) assert nb.cells[0].cell_type == "markdown" assert len(nb.cells) == 1 def test_non_jupyter_code_is_not_split(): text = """Here we have a markdown file with a non-jupyter code cell ```{.python} 1 + 1 2 + 2 ``` the code cell should not become a Jupyter cell, nor be split into two pieces.""" nb = jupytext.reads(text, "md") compare(nb.cells[0].source, text) assert nb.cells[0].cell_type == "markdown" assert len(nb.cells) == 1 def test_read_markdown_idl( no_jupytext_version_number, text="""--- jupyter: kernelspec: display_name: IDL [conda env:gdl] * language: IDL name: conda-env-gdl-idl --- # A sample IDL Markdown notebook ```idl a = 1 ``` """, ): nb = jupytext.reads(text, "md") assert len(nb.cells) == 2 assert nb.cells[1].cell_type == "code" assert nb.cells[1].source == "a = 1" text2 = jupytext.writes(nb, "md") compare(text2, text) def test_read_markdown_IDL( no_jupytext_version_number, text="""--- jupyter: kernelspec: display_name: IDL [conda env:gdl] * language: IDL name: conda-env-gdl-idl --- # A sample IDL Markdown notebook ```IDL a = 1 ``` """, ): nb = jupytext.reads(text, "md") assert len(nb.cells) == 2 assert nb.cells[1].cell_type == "code" assert nb.cells[1].source == "a = 1" text2 = jupytext.writes(nb, "md") compare(text2, text) def test_inactive_cell( text="""```python active="md" # This becomes a raw cell in Jupyter ``` """, expected=new_notebook(cells=[new_raw_cell("# This becomes a raw cell in Jupyter", metadata={"active": "md"})]), ): nb = jupytext.reads(text, "md") compare_notebooks(nb, expected) text2 = jupytext.writes(nb, "md") compare(text2, text) def test_inactive_cell_using_tag( text="""```python tags=["active-md"] # This becomes a raw cell in Jupyter ``` """, expected=new_notebook(cells=[new_raw_cell("# This becomes a raw cell in Jupyter", metadata={"tags": ["active-md"]})]), ): nb = jupytext.reads(text, "md") compare_notebooks(nb, expected) text2 = jupytext.writes(nb, "md") compare(text2, text) def test_inactive_cell_using_noeval( text="""This is text ```python .noeval # This is python code. # It should not become a code cell ``` """, ): expected = new_notebook(cells=[new_markdown_cell(text[:-1])]) nb = jupytext.reads(text, "md") compare_notebooks(nb, expected) text2 = jupytext.writes(nb, "md") compare(text2, text) def test_noeval_followed_by_code_works( text="""```python .noeval # Not a code cell in Jupyter ``` ```python 1 + 1 ``` """, expected=new_notebook( cells=[ new_markdown_cell( """```python .noeval # Not a code cell in Jupyter ```""" ), new_code_cell("1 + 1"), ] ), ): nb = jupytext.reads(text, "md") compare_notebooks(nb, expected) text2 = jupytext.writes(nb, "md") compare(text2, text) def test_markdown_cell_with_code_works( nb=new_notebook( cells=[ new_markdown_cell( """```python 1 + 1 ```""" ) ] ), ): text = jupytext.writes(nb, "md") nb2 = jupytext.reads(text, "md") compare_notebooks(nb2, nb) def test_markdown_cell_with_noeval_code_works( nb=new_notebook( cells=[ new_markdown_cell( """```python .noeval 1 + 1 ```""" ) ] ), ): text = jupytext.writes(nb, "md") nb2 = jupytext.reads(text, "md") compare_notebooks(nb2, nb) def test_two_markdown_cell_with_code_works( nb=new_notebook( cells=[ new_markdown_cell( """```python 1 + 1 ```""" ), new_markdown_cell( """```python 2 + 2 ```""" ), ] ), ): text = jupytext.writes(nb, "md") nb2 = jupytext.reads(text, "md") compare_notebooks(nb2, nb) def test_two_markdown_cell_with_no_language_code_works( nb=new_notebook( cells=[ new_markdown_cell( """``` 1 + 1 ```""" ), new_markdown_cell( """``` 2 + 2 ```""" ), ] ), ): text = jupytext.writes(nb, "md") nb2 = jupytext.reads(text, "md") compare_notebooks(nb2, nb) def test_markdown_cell_with_code_inside_multiline_string_419( text='''```python readme = """ above ```python x = 2 ``` below """ ``` ''', ): """A code cell containing triple backticks is converted to a code cell encapsulated with four backticks""" nb = jupytext.reads(text, "md") compare(jupytext.writes(nb, "md"), "`" + text[:-1] + "`\n") assert len(nb.cells) == 1 def test_notebook_with_python3_magic( no_jupytext_version_number, nb=new_notebook( metadata={ "kernelspec": { "display_name": "Python 3", "language": "python", "name": "python3", } }, cells=[ new_code_cell("%%python2\na = 1\nprint a"), new_code_cell("%%python3\nb = 2\nprint(b)"), ], ), text="""--- jupyter: kernelspec: display_name: Python 3 language: python name: python3 --- ```python2 a = 1 print a ``` ```python3 b = 2 print(b) ``` """, ): md = jupytext.writes(nb, "md") compare(md, text) nb2 = jupytext.reads(md, "md") compare_notebooks(nb2, nb) def test_update_metadata_filter( no_jupytext_version_number, org="""--- jupyter: kernelspec: display_name: Python 3 language: python name: python3 extra: key: value --- """, target="""--- jupyter: extra: key: value jupytext: notebook_metadata_filter: extra kernelspec: display_name: Python 3 language: python name: python3 --- """, ): nb = jupytext.reads(org, "md") text = jupytext.writes(nb, "md") compare(text, target) def test_update_metadata_filter_2( no_jupytext_version_number, org="""--- jupyter: jupytext: notebook_metadata_filter: -extra kernelspec: display_name: Python 3 language: python name: python3 extra: key: value --- """, target="""--- jupyter: jupytext: notebook_metadata_filter: -extra kernelspec: display_name: Python 3 language: python name: python3 --- """, ): nb = jupytext.reads(org, "md") text = jupytext.writes(nb, "md") compare(text, target) def test_custom_metadata( no_jupytext_version_number, nb=new_notebook( metadata={ "author": "John Doe", "title": "Some serious math", "jupytext": {"notebook_metadata_filter": "title,author"}, "kernelspec": { "display_name": "Python 3", "language": "python", "name": "python3", }, } ), md="""--- jupyter: author: John Doe jupytext: notebook_metadata_filter: title,author kernelspec: display_name: Python 3 language: python name: python3 title: Some serious math --- """, ): """Here we test the addition of custom metadata, cf. https://github.com/mwouts/jupytext/issues/469""" md2 = jupytext.writes(nb, "md") compare(md2, md) nb2 = jupytext.reads(md, "md") compare_notebooks(nb2, nb) def test_hide_notebook_metadata( no_jupytext_version_number, nb=new_notebook( metadata={ "jupytext": {"hide_notebook_metadata": True}, "kernelspec": { "display_name": "Python 3", "language": "python", "name": "python3", }, } ), md=""" """, ): """Test the hide_notebook_metadata option""" md2 = jupytext.writes(nb, "md") compare(md2, md) nb2 = jupytext.reads(md, "md") compare_notebooks(nb2, nb) def test_notebook_with_empty_header_1070( md="""--- --- This file has empty frontmatter. """, ): nb = jupytext.reads(md, fmt="md:markdown") md2 = jupytext.writes(nb, "md") compare(md2, md) nb2 = jupytext.reads(md, "md") compare_notebooks(nb2, nb) ================================================ FILE: tests/functional/simple_notebooks/test_read_simple_matlab.py ================================================ from nbformat.v4.nbbase import new_code_cell, new_notebook import jupytext from jupytext.compare import compare, compare_notebooks def test_hide_code_tag( no_jupytext_version_number, nb=new_notebook( metadata={"jupytext": {"main_language": "matlab"}}, cells=[new_code_cell("1 + 1", metadata={"tags": ["hide_code"]})], ), text="""% %% tags=["hide_code"] 1 + 1 """, ): text2 = jupytext.writes(nb, "m") compare(text2, text) nb2 = jupytext.reads(text, "m") compare_notebooks(nb2, nb) def test_hide_code_tag_percent_format( no_jupytext_version_number, nb=new_notebook( metadata={"jupytext": {"main_language": "matlab"}}, cells=[new_code_cell("1 + 1", metadata={"tags": ["hide_code"]})], ), text="""% %% tags=["hide_code"] 1 + 1 """, ): text2 = jupytext.writes(nb, "m:percent") compare(text2, text) nb2 = jupytext.reads(text, "m:percent") compare_notebooks(nb2, nb) ================================================ FILE: tests/functional/simple_notebooks/test_read_simple_nomarker.py ================================================ import os import pytest from nbformat.v4.nbbase import new_code_cell, new_markdown_cell, new_notebook from jupytext import reads, write, writes from jupytext.cli import jupytext as jupytext_cli from jupytext.combine import combine_inputs_with_outputs from jupytext.compare import compare def test_write_reload_simple_notebook(): nb1 = new_notebook( cells=[ new_markdown_cell("A markdown cell", metadata={"md": "value"}), new_code_cell("1 + 1"), new_markdown_cell("A markdown cell", metadata={"md": "value"}), new_code_cell( """def f(x): return x""", metadata={"md": "value"}, ), new_markdown_cell("A markdown cell", metadata={"md": "value"}), new_code_cell( """def g(x): return x def h(x): return x """, metadata={"md": "value"}, ), ] ) text = writes(nb1, "py:nomarker") nb2 = reads(text, "py:nomarker") nb2 = combine_inputs_with_outputs(nb2, nb1, "py:nomarker") nb2.metadata.pop("jupytext") assert len(nb2.cells) == 7 nb1.cells = nb1.cells[:5] nb2.cells = nb2.cells[:5] compare(nb2, nb1) with pytest.warns(DeprecationWarning, match="nomarker"): text = writes(nb2, "py:bare") with pytest.warns(DeprecationWarning, match="nomarker"): nb3 = reads(text, "py:bare") with pytest.warns(DeprecationWarning, match="nomarker"): nb3 = combine_inputs_with_outputs(nb3, nb2, "py:bare") nb3.metadata.pop("jupytext") compare(nb3, nb2) def test_jupytext_cli_bare(tmpdir): tmp_py = str(tmpdir.join("test.py")) tmp_ipynb = str(tmpdir.join("test.ipynb")) write(new_notebook(cells=[new_code_cell("1 + 1")]), tmp_ipynb) with pytest.warns(DeprecationWarning, match="nomarker"): jupytext_cli([tmp_ipynb, "--to", "py:bare"]) assert os.path.isfile(tmp_py) ================================================ FILE: tests/functional/simple_notebooks/test_read_simple_ocaml.py ================================================ from nbformat.v4.nbbase import new_code_cell, new_markdown_cell, new_notebook import jupytext from jupytext.compare import compare, compare_notebooks def test_read_simple_code( no_jupytext_version_number, ml="""(* %% *) let sum x y = x + y """, nb=new_notebook( cells=[ new_code_cell("""let sum x y = x + y"""), ] ), ): nb2 = jupytext.reads(ml, "ml:percent") compare_notebooks(nb2, nb) ml2 = jupytext.writes(nb, "ml:percent") compare(ml2, ml) def test_read_simple_markdown( no_jupytext_version_number, ml="""(* %% [markdown] *) (* # Example of an OCaml notebook *) """, nb=new_notebook( cells=[ new_markdown_cell("# Example of an OCaml notebook"), ] ), ): nb2 = jupytext.reads(ml, "ml:percent") compare_notebooks(nb2, nb) ml2 = jupytext.writes(nb, "ml:percent") compare(ml2, ml) ================================================ FILE: tests/functional/simple_notebooks/test_read_simple_percent.py ================================================ import os import pytest from jupyter_server.utils import ensure_async from nbformat.v4.nbbase import ( new_code_cell, new_markdown_cell, new_notebook, new_raw_cell, ) import jupytext from jupytext.compare import compare, compare_notebooks, notebook_model def test_read_simple_file( script="""# --- # title: Simple file # --- # %% [markdown] # This is a markdown cell # %% [md] # This is also a markdown cell # %% [raw] # This is a raw cell # %%% sub-cell title # This is a sub-cell # %%%% sub-sub-cell title # This is a sub-sub-cell # %% And now a code cell 1 + 2 + 3 + 4 5 6 # %%magic # this is a commented magic, not a cell 7 """, ): nb = jupytext.reads(script, "py:percent") compare_notebooks( new_notebook( cells=[ new_raw_cell("---\ntitle: Simple file\n---"), new_markdown_cell("This is a markdown cell"), new_markdown_cell("This is also a markdown cell", metadata={"region_name": "md"}), new_raw_cell("This is a raw cell"), new_code_cell( "# This is a sub-cell", metadata={"title": "sub-cell title", "cell_depth": 1}, ), new_code_cell( "# This is a sub-sub-cell", metadata={"title": "sub-sub-cell title", "cell_depth": 2}, ), new_code_cell( """1 + 2 + 3 + 4 5 6 %%magic # this is a commented magic, not a cell 7""", metadata={"title": "And now a code cell"}, ), ] ), nb, ) script2 = jupytext.writes(nb, "py:percent") compare(script2, script) def test_read_cell_with_metadata( script="""# %% a code cell with parameters {"tags": ["parameters"]} a = 3 """, ): nb = jupytext.reads(script, "py:percent") assert len(nb.cells) == 1 assert nb.cells[0].cell_type == "code" assert nb.cells[0].source == "a = 3" assert nb.cells[0].metadata == { "title": "a code cell with parameters", "tags": ["parameters"], } script2 = jupytext.writes(nb, "py:percent") compare(script2, script) def test_read_nbconvert_script( script=""" # coding: utf-8 # A markdown cell # In[1]: import pandas as pd pd.options.display.max_rows = 6 pd.options.display.max_columns = 20 # Another markdown cell # In[2]: 1 + 1 # Again, a markdown cell # In[33]: 2 + 2 # 3 + 3 """, ): assert jupytext.formats.guess_format(script, ".py")[0] == "percent" nb = jupytext.reads(script, ".py") assert len(nb.cells) == 5 def test_read_remove_blank_lines( script="""# %% import pandas as pd # %% Display a data frame df = pd.DataFrame({'A': [1, 2], 'B': [3, 4]}, index=pd.Index(['x0', 'x1'], name='x')) df # %% Pandas plot {"tags": ["parameters"]} df.plot(kind='bar') # %% sample class class MyClass: pass # %% a function def f(x): return 42 * x """, ): nb = jupytext.reads(script, "py") assert len(nb.cells) == 5 for i in range(5): assert nb.cells[i].cell_type == "code" assert not nb.cells[i].source.startswith("\n") assert not nb.cells[i].source.endswith("\n") script2 = jupytext.writes(nb, "py:percent") compare(script2, script) def test_no_crash_on_square_bracket( script="""# %% In [2] print('Hello') """, ): nb = jupytext.reads(script, "py") script2 = jupytext.writes(nb, "py:percent") compare(script2, script) def test_nbconvert_cell( script="""# In[2]: print('Hello') """, ): nb = jupytext.reads(script, "py") script2 = jupytext.writes(nb, "py:percent") expected = """# %% print('Hello') """ compare(script2, expected) def test_nbformat_v3_nbpy_cell( script="""# print('Hello') """, ): nb = jupytext.reads(script, "py") script2 = jupytext.writes(nb, "py:percent") expected = """# %% print('Hello') """ compare(script2, expected) def test_multiple_empty_cells(): nb = new_notebook( cells=[new_code_cell(), new_code_cell(), new_code_cell()], metadata={"jupytext": {"notebook_metadata_filter": "-all"}}, ) text = jupytext.writes(nb, "py:percent") expected = """# %% # %% # %% """ compare(text, expected) nb2 = jupytext.reads(text, "py:percent") nb2.metadata = nb.metadata compare_notebooks(nb2, nb) def test_first_cell_markdown_191(): text = """# %% [markdown] # Docstring # %% from math import pi # %% [markdown] # Another markdown cell """ nb = jupytext.reads(text, "py") assert nb.cells[0].cell_type == "markdown" assert nb.cells[1].cell_type == "code" assert nb.cells[2].cell_type == "markdown" def test_multiline_comments_in_markdown_1(): text = """# %% [markdown] ''' a long cell ''' """ nb = jupytext.reads(text, "py") assert len(nb.cells) == 1 assert nb.cells[0].cell_type == "markdown" assert nb.cells[0].source == "a\nlong\ncell" py = jupytext.writes(nb, "py") compare(py, text) def test_multiline_comments_in_markdown_2(): text = '''# %% [markdown] """ a long cell """ ''' nb = jupytext.reads(text, "py") assert len(nb.cells) == 1 assert nb.cells[0].cell_type == "markdown" assert nb.cells[0].source == "a\nlong\ncell" py = jupytext.writes(nb, "py") compare(py, text) def test_multiline_comments_format_option(): text = '''# %% [markdown] """ a long cell """ ''' nb = new_notebook( cells=[new_markdown_cell("a\nlong\ncell")], metadata={"jupytext": {"cell_markers": '"""', "notebook_metadata_filter": "-all"}}, ) py = jupytext.writes(nb, "py:percent") compare(py, text) def test_multiline_comments_in_raw_cell(): text = '''# %% [raw] """ some text """ ''' nb = jupytext.reads(text, "py") assert len(nb.cells) == 1 assert nb.cells[0].cell_type == "raw" assert nb.cells[0].source == "some\ntext" py = jupytext.writes(nb, "py") compare(py, text) def test_multiline_comments_in_markdown_cell_no_line_return(): text = '''# %% [markdown] """a long cell""" ''' nb = jupytext.reads(text, "py") assert len(nb.cells) == 1 assert nb.cells[0].cell_type == "markdown" assert nb.cells[0].source == "a\nlong\ncell" def test_multiline_comments_in_markdown_cell_is_robust_to_additional_cell_marker(): text = '''# %% [markdown] """ some text, and a fake cell marker # %% [raw] """ ''' nb = jupytext.reads(text, "py") assert len(nb.cells) == 1 assert nb.cells[0].cell_type == "markdown" assert nb.cells[0].source == "some text, and a fake cell marker\n# %% [raw]" py = jupytext.writes(nb, "py") compare(py, text) @pytest.mark.asyncio async def test_cell_markers_option_in_contents_manager(tmpdir, cm): tmp_ipynb = tmpdir / "notebook.ipynb" tmp_py = tmpdir / "notebook.py" cm.root_dir = str(tmpdir) nb = new_notebook( cells=[new_code_cell("1 + 1"), new_markdown_cell("a\nlong\ncell")], metadata={ "jupytext": { "formats": "ipynb,py:percent", "notebook_metadata_filter": "-all", "cell_markers": "'''", } }, ) await ensure_async(cm.save(model=notebook_model(nb), path="notebook.ipynb")) assert os.path.isfile(tmp_ipynb) assert os.path.isfile(tmp_py) with open(tmp_py) as fp: text = fp.read() compare( text, """# %% 1 + 1 # %% [markdown] ''' a long cell ''' """, ) nb2 = jupytext.read(tmp_py) compare_notebooks(nb, nb2) @pytest.mark.asyncio async def test_cell_markers_in_config(tmpdir, python_notebook, cm): (tmpdir / "jupytext.toml").write('''cell_markers = '"""'\n''') cm.root_dir = str(tmpdir) nb = python_notebook nb.metadata["jupytext"] = {"formats": "ipynb,py:percent"} await ensure_async(cm.save(model=notebook_model(nb), path="notebook.ipynb")) text = (tmpdir / "notebook.py").read() assert ( '''# %% [markdown] """ A short notebook """ ''' in text ) nb2 = jupytext.read(tmpdir / "notebook.py") compare_notebooks(nb, nb2) @pytest.mark.asyncio async def test_cell_markers_in_contents_manager(tmpdir, cm): tmp_ipynb = tmpdir / "notebook.ipynb" tmp_py = tmpdir / "notebook.py" cm.root_dir = str(tmpdir) cm.cell_markers = "'''" nb = new_notebook( cells=[new_code_cell("1 + 1"), new_markdown_cell("a\nlong\ncell")], metadata={ "jupytext": { "formats": "ipynb,py:percent", "notebook_metadata_filter": "-all", } }, ) await ensure_async(cm.save(model=notebook_model(nb), path="notebook.ipynb")) assert os.path.isfile(tmp_ipynb) assert os.path.isfile(tmp_py) with open(tmp_py) as fp: text = fp.read() compare( text, """# %% 1 + 1 # %% [markdown] ''' a long cell ''' """, ) nb2 = jupytext.read(tmp_py) compare_notebooks(nb, nb2) @pytest.mark.asyncio async def test_cell_markers_in_contents_manager_does_not_impact_light_format(tmpdir, cm): tmp_ipynb = tmpdir / "notebook.ipynb" tmp_py = tmpdir / "notebook.py" cm.root_dir = str(tmpdir) cm.cell_markers = "'''" nb = new_notebook( cells=[new_code_cell("1 + 1"), new_markdown_cell("a\nlong\ncell")], metadata={ "jupytext": { "formats": "ipynb,py:light", "notebook_metadata_filter": "-all", } }, ) with pytest.warns(UserWarning, match="Ignored cell markers"): await ensure_async(cm.save(model=notebook_model(nb), path="notebook.ipynb")) assert os.path.isfile(tmp_ipynb) assert os.path.isfile(tmp_py) with open(tmp_py) as fp: text = fp.read() compare( text, """1 + 1 # a # long # cell """, ) nb2 = jupytext.read(tmp_py) compare_notebooks(nb, nb2) def test_single_triple_quote_works( no_jupytext_version_number, text='''# --- # jupyter: # jupytext: # cell_markers: '"""' # formats: ipynb,py:percent # text_representation: # extension: .py # format_name: percent # --- # %% print("hello") ''', notebook=new_notebook(cells=[new_code_cell('print("hello")')]), ): compare_notebooks(jupytext.reads(text, "py"), notebook) def test_docstring_with_quadruple_quote( nb=new_notebook( cells=[ new_code_cell( '''def fun_1(df): """" docstring starting with 4 double quotes and ending with 3 """ return df''' ), new_code_cell( '''def fun_2(df): """ docstring """ return df''' ), ] ), ): """Reproduces https://github.com/mwouts/jupytext/issues/460""" py = jupytext.writes(nb, "py:percent") nb2 = jupytext.reads(py, "py") compare_notebooks(nb2, nb) def test_cell_marker_has_same_indentation_as_code( text="""# %% if __name__ == '__main__': print(1) # %% # INDENTED COMMENT print(2) """, nb_expected=new_notebook( cells=[ new_code_cell( """if __name__ == '__main__': print(1)""" ), new_code_cell( """ # INDENTED COMMENT print(2)""" ), ] ), ): """The cell marker should have the same indentation as the first code line. See issue #562""" nb_actual = jupytext.reads(text, fmt="py:percent") compare_notebooks(nb_actual, nb_expected) text_actual = jupytext.writes(nb_actual, fmt="py:percent") compare(text_actual, text) @pytest.mark.parametrize("space_in_gonb", [False, True]) def test_read_simple_gonb_cell_with_double_percent( space_in_gonb, go_percent="""// --- // jupyter: // kernelspec: // display_name: Go (gonb) // language: go // name: gonb // --- // %% //gonb:%% fmt.Printf("Hello World!") """, ): """The cell marker should have the same indentation as the first code line. See issue #562""" if space_in_gonb: go_percent = go_percent.replace("//gonb:%%", "// gonb:%%") nb = jupytext.reads(go_percent, fmt="go:percent") assert len(nb.cells) == 1 (cell,) = nb.cells assert cell.cell_type == "code", cell.cell_type assert ( cell.source == """%% fmt.Printf("Hello World!")""" ) def test_write_simple_gonb_cell_with_double_percent( no_jupytext_version_number, go_percent="""// --- // jupyter: // kernelspec: // display_name: Go (gonb) // language: go // name: gonb // --- // %% //gonb:%% fmt.Printf("Hello World!") """, ): """The cell marker should have the same indentation as the first code line. See issue #562""" nb = jupytext.reads(go_percent, fmt="go:percent") go = jupytext.writes(nb, fmt="go:percent") compare(go, go_percent) ================================================ FILE: tests/functional/simple_notebooks/test_read_simple_python.py ================================================ import pytest from nbformat.v4.nbbase import ( new_code_cell, new_markdown_cell, new_notebook, new_raw_cell, ) import jupytext from jupytext.compare import compare, compare_notebooks def test_read_simple_file( pynb="""# --- # title: Simple file # --- # Here we have some text # And below we have some python code def f(x): return x+1 def h(y): return y-1 """, ): nb = jupytext.reads(pynb, "py") assert len(nb.cells) == 4 assert nb.cells[0].cell_type == "raw" assert nb.cells[0].source == "---\ntitle: Simple file\n---" assert nb.cells[1].cell_type == "markdown" assert nb.cells[1].source == "Here we have some text\nAnd below we have some python code" assert nb.cells[2].cell_type == "code" compare( nb.cells[2].source, """def f(x): return x+1""", ) assert nb.cells[3].cell_type == "code" compare( nb.cells[3].source, """def h(y): return y-1""", ) pynb2 = jupytext.writes(nb, "py") compare(pynb2, pynb) def test_read_less_simple_file( pynb="""# --- # title: Less simple file # --- # Here we have some text # And below we have some python code # This is a comment about function f def f(x): return x+1 # And a comment on h def h(y): return y-1 """, ): nb = jupytext.reads(pynb, "py") assert len(nb.cells) == 4 assert nb.cells[0].cell_type == "raw" assert nb.cells[0].source == "---\ntitle: Less simple file\n---" assert nb.cells[1].cell_type == "markdown" assert nb.cells[1].source == "Here we have some text\nAnd below we have some python code" assert nb.cells[2].cell_type == "code" compare( nb.cells[2].source, "# This is a comment about function f\ndef f(x):\n return x+1", ) assert nb.cells[3].cell_type == "code" compare(nb.cells[3].source, """# And a comment on h\ndef h(y):\n return y-1""") pynb2 = jupytext.writes(nb, "py") compare(pynb2, pynb) def test_indented_comment( text="""def f(): return 1 # f returns 1 def g(): return 2 # h returns 3 def h(): return 3 """, ref=new_notebook( cells=[ new_code_cell( """def f(): return 1 # f returns 1""" ), new_code_cell("def g():\n return 2"), new_code_cell("# h returns 3\ndef h():\n return 3"), ] ), ): nb = jupytext.reads(text, "py") compare_notebooks(nb, ref) py = jupytext.writes(nb, "py") compare(py, text) def test_non_pep8( text="""def f(): return 1 def g(): return 2 def h(): return 3 """, ref=new_notebook( cells=[ new_code_cell( "def f():\n return 1\ndef g():\n return 2", metadata={"lines_to_next_cell": 1}, ), new_code_cell("def h():\n return 3"), ] ), ): nb = jupytext.reads(text, "py") compare_notebooks(nb, ref) py = jupytext.writes(nb, "py") compare(py, text) def test_read_non_pep8_file( pynb="""# --- # title: Non-pep8 file # --- # This file is non-pep8 as the function below has # two consecutive blank lines in its body def f(x): return x+1 """, ): nb = jupytext.reads(pynb, "py") assert len(nb.cells) == 3 assert nb.cells[0].cell_type == "raw" assert nb.cells[0].source == "---\ntitle: Non-pep8 file\n---" assert nb.cells[1].cell_type == "markdown" assert nb.cells[1].source == "This file is non-pep8 as the function below has\ntwo consecutive blank lines in its body" assert nb.cells[2].cell_type == "code" compare(nb.cells[2].source, "def f(x):\n\n\n return x+1") pynb2 = jupytext.writes(nb, "py") compare(pynb2, pynb) def test_read_cell_two_blank_lines( pynb="""# --- # title: cell with two consecutive blank lines # --- # + a = 1 a + 2 """, ): nb = jupytext.reads(pynb, "py") assert len(nb.cells) == 2 assert nb.cells[0].cell_type == "raw" assert nb.cells[0].source == "---\ntitle: cell with two consecutive blank lines\n---" assert nb.cells[1].cell_type == "code" assert nb.cells[1].source == "a = 1\n\n\na + 2" pynb2 = jupytext.writes(nb, "py") compare(pynb2, pynb) def test_read_cell_explicit_start( pynb=""" import pandas as pd # + def data(): return pd.DataFrame({'A': [0, 1]}) data() """, ): nb = jupytext.reads(pynb, "py") pynb2 = jupytext.writes(nb, "py") compare(pynb2, pynb) def test_read_complex_cells( pynb="""import pandas as pd # + def data(): return pd.DataFrame({'A': [0, 1]}) data() # + def data2(): return pd.DataFrame({'B': [0, 1]}) data2() # + # Finally we have a cell with only comments # This cell should remain a code cell and not get converted # to markdown # + {"endofcell": "--"} # This cell has an enumeration in it that should not # match the endofcell marker! # - item 1 # - item 2 # - # -- """, ): nb = jupytext.reads(pynb, "py") assert len(nb.cells) == 5 assert nb.cells[0].cell_type == "code" assert nb.cells[1].cell_type == "code" assert nb.cells[2].cell_type == "code" assert nb.cells[3].cell_type == "code" assert nb.cells[4].cell_type == "code" assert ( nb.cells[3].source == """# Finally we have a cell with only comments # This cell should remain a code cell and not get converted # to markdown""" ) assert ( nb.cells[4].source == """# This cell has an enumeration in it that should not # match the endofcell marker! # - item 1 # - item 2 # -""" ) pynb2 = jupytext.writes(nb, "py") compare(pynb2, pynb) def test_read_prev_function( pynb="""def test_read_cell_explicit_start_end(pynb=''' import pandas as pd # + def data(): return pd.DataFrame({'A': [0, 1]}) data() '''): nb = jupytext.reads(pynb, 'py') pynb2 = jupytext.writes(nb, 'py') compare(pynb2, pynb) """, ): nb = jupytext.reads(pynb, "py") pynb2 = jupytext.writes(nb, "py") compare(pynb2, pynb) def test_read_cell_with_one_blank_line_end( pynb="""import pandas """, ): nb = jupytext.reads(pynb, "py") assert len(nb.cells) == 1 pynb2 = jupytext.writes(nb, "py") compare(pynb2, pynb) def test_read_code_cell_fully_commented( pynb="""# + # This is a code cell that # only contains comments """, ): nb = jupytext.reads(pynb, "py") assert len(nb.cells) == 1 assert nb.cells[0].cell_type == "code" assert ( nb.cells[0].source == """# This is a code cell that # only contains comments""" ) pynb2 = jupytext.writes(nb, "py") compare(pynb2, pynb) def test_file_with_two_blank_line_end( pynb="""import pandas """, ): nb = jupytext.reads(pynb, "py") pynb2 = jupytext.writes(nb, "py") compare(pynb2, pynb) def test_one_blank_lines_after_endofcell( pynb="""# + # This is a code cell with explicit end of cell 1 + 1 2 + 2 # - # This cell is a cell with implicit start 1 + 1 """, ): nb = jupytext.reads(pynb, "py") assert len(nb.cells) == 2 assert nb.cells[0].cell_type == "code" assert ( nb.cells[0].source == """# This is a code cell with explicit end of cell 1 + 1 2 + 2""" ) assert nb.cells[1].cell_type == "code" assert ( nb.cells[1].source == """# This cell is a cell with implicit start 1 + 1""" ) pynb2 = jupytext.writes(nb, "py") compare(pynb2, pynb) def test_two_cells_with_explicit_start( pynb="""# + # Cell one 1 + 1 1 + 1 # + # Cell two 2 + 2 2 + 2 """, ): nb = jupytext.reads(pynb, "py") assert len(nb.cells) == 2 assert nb.cells[0].cell_type == "code" assert ( nb.cells[0].source == """# Cell one 1 + 1 1 + 1""" ) assert nb.cells[1].cell_type == "code" assert ( nb.cells[1].source == """# Cell two 2 + 2 2 + 2""" ) pynb2 = jupytext.writes(nb, "py") compare(pynb2, pynb) def test_escape_start_pattern( pynb="""# The code start pattern '# +' can # appear in code and markdown cells. # In markdown cells it is escaped like here: # # + {"sample_metadata": "value"} # In code cells like this one, it is also escaped # # + {"sample_metadata": "value"} 1 + 1 """, ): nb = jupytext.reads(pynb, "py") assert len(nb.cells) == 3 assert nb.cells[0].cell_type == "markdown" assert nb.cells[1].cell_type == "markdown" assert nb.cells[2].cell_type == "code" assert ( nb.cells[1].source == """In markdown cells it is escaped like here: # + {"sample_metadata": "value"}""" ) assert ( nb.cells[2].source == """# In code cells like this one, it is also escaped # + {"sample_metadata": "value"} 1 + 1""" ) pynb2 = jupytext.writes(nb, "py") compare(pynb2, pynb) def test_dictionary_with_blank_lines_not_broken( pynb="""# This is a markdown cell, and below # we have a long dictionary with blank lines # inside it dictionary = { 'a': 'A', 'b': 'B', # and the end 'z': 'Z'} """, ): nb = jupytext.reads(pynb, "py") assert len(nb.cells) == 2 assert nb.cells[0].cell_type == "markdown" assert nb.cells[1].cell_type == "code" assert ( nb.cells[0].source == """This is a markdown cell, and below we have a long dictionary with blank lines inside it""" ) assert ( nb.cells[1].source == """dictionary = { 'a': 'A', 'b': 'B', # and the end 'z': 'Z'}""" ) pynb2 = jupytext.writes(nb, "py") compare(pynb2, pynb) def test_isolated_cell_with_magic( pynb="""# --- # title: cell with isolated jupyter magic # --- # A magic command included in a markdown # paragraph is code # # %matplotlib inline # a code block may start with # a magic command, like this one: # %matplotlib inline # or that one # %matplotlib inline 1 + 1 """, ): nb = jupytext.reads(pynb, "py") assert len(nb.cells) == 6 assert nb.cells[0].cell_type == "raw" assert nb.cells[0].source == "---\ntitle: cell with isolated jupyter magic\n---" assert nb.cells[1].cell_type == "code" assert nb.cells[2].cell_type == "markdown" assert nb.cells[3].cell_type == "code" assert nb.cells[3].source == "%matplotlib inline" assert nb.cells[4].cell_type == "markdown" assert nb.cells[5].cell_type == "code" assert nb.cells[5].source == "%matplotlib inline\n1 + 1" pynb2 = jupytext.writes(nb, "py") compare(pynb2, pynb) def test_ipython_help_are_commented_297( text="""# This is a markdown cell # that ends with a question: float? # The next cell is also a markdown cell, # because it has no code marker: # float? # + # float? # + # float?? # + # Finally a question in a code # # cell? """, nb=new_notebook( cells=[ new_markdown_cell("This is a markdown cell\nthat ends with a question: float?"), new_markdown_cell("The next cell is also a markdown cell,\nbecause it has no code marker:"), new_markdown_cell("float?"), new_code_cell("float?"), new_code_cell("float??"), new_code_cell("# Finally a question in a code\n# cell?"), ] ), ): nb2 = jupytext.reads(text, "py") compare_notebooks(nb2, nb) text2 = jupytext.writes(nb2, "py") compare(text2, text) def test_questions_in_unmarked_cells_are_not_uncommented_297( text="""# This cell has no explicit marker # question? 1 + 2 """, nb=new_notebook( cells=[ new_code_cell( "# This cell has no explicit marker\n# question?\n1 + 2", metadata={"comment_questions": False}, ) ] ), ): nb2 = jupytext.reads(text, "py") compare_notebooks(nb2, nb) text2 = jupytext.writes(nb2, "py") compare(text2, text) def test_read_multiline_comment( pynb="""'''This is a multiline comment with "quotes", 'single quotes' # and comments and line breaks and it ends here''' 1 + 1 """, ): nb = jupytext.reads(pynb, "py") assert len(nb.cells) == 2 assert nb.cells[0].cell_type == "code" assert ( nb.cells[0].source == """'''This is a multiline comment with "quotes", 'single quotes' # and comments and line breaks and it ends here'''""" ) assert nb.cells[1].cell_type == "code" assert nb.cells[1].source == "1 + 1" pynb2 = jupytext.writes(nb, "py") compare(pynb2, pynb) def test_no_space_after_code( pynb="""# -*- coding: utf-8 -*- # Markdown cell def f(x): return x+1 # And a new cell, and non ascii contênt """, ): nb = jupytext.reads(pynb, "py") assert len(nb.cells) == 3 assert nb.cells[0].cell_type == "markdown" assert nb.cells[0].source == "Markdown cell" assert nb.cells[1].cell_type == "code" assert nb.cells[1].source == "def f(x):\n return x+1" assert nb.cells[2].cell_type == "markdown" assert nb.cells[2].source == "And a new cell, and non ascii contênt" pynb2 = jupytext.writes(nb, "py") compare(pynb2, pynb) def test_read_write_script( pynb="""#!/usr/bin/env python # coding=utf-8 print('Hello world') """, ): nb = jupytext.reads(pynb, "py") pynb2 = jupytext.writes(nb, "py") compare(pynb2, pynb) def test_read_write_script_with_metadata_241( no_jupytext_version_number, pynb="""#!/usr/bin/env python3 # -*- coding: utf-8 -*- # --- # jupyter: # jupytext: # text_representation: # extension: .py # format_name: light # kernelspec: # display_name: Python 3 # language: python # name: python3 # --- a = 2 a + 1 """, ): nb = jupytext.reads(pynb, "py") assert "executable" in nb.metadata["jupytext"] assert "encoding" in nb.metadata["jupytext"] pynb2 = jupytext.writes(nb, "py") compare(pynb2, pynb) def test_notebook_blank_lines( script="""# + # This is a comment # followed by two variables a = 3 b = 4 # - # New cell is a variable c = 5 # + # Now we have two functions def f(x): return x + x def g(x): return x + x + x # - # A commented block that is two lines away # from previous cell # A function again def h(x): return x + 1 # variable d = 6 """, ): notebook = jupytext.reads(script, "py") assert len(notebook.cells) >= 6 for cell in notebook.cells: lines = cell.source.splitlines() if len(lines) != 1: assert lines[0], cell.source assert lines[-1], cell.source script2 = jupytext.writes(notebook, "py") compare(script2, script) def test_notebook_two_blank_lines_before_next_cell( script="""# + # This is cell with a function def f(x): return 4 # + # Another cell c = 5 def g(x): return 6 # + # Final cell 1 + 1 """, ): notebook = jupytext.reads(script, "py") assert len(notebook.cells) == 3 for cell in notebook.cells: lines = cell.source.splitlines() if len(lines) != 1: assert lines[0] assert lines[-1] script2 = jupytext.writes(notebook, "py") compare(script2, script) def test_notebook_one_blank_line_between_cells( script="""# + 1 + 1 2 + 2 # + 3 + 3 4 + 4 # + 5 + 5 def g(x): return 6 # + 7 + 7 def h(x): return 8 # + def i(x): return 9 10 + 10 # + def j(x): return 11 12 + 12 """, ): notebook = jupytext.reads(script, "py") for cell in notebook.cells: lines = cell.source.splitlines() assert lines[0] assert lines[-1] assert not cell.metadata, cell.source script2 = jupytext.writes(notebook, "py") compare(script2, script) def test_notebook_with_magic_and_bash_cells( script="""# This is a test for issue #181 # %load_ext line_profiler # !head -4 data/president_heights.csv """, ): notebook = jupytext.reads(script, "py") for cell in notebook.cells: lines = cell.source.splitlines() assert lines[0] assert lines[-1] assert not cell.metadata, cell.source script2 = jupytext.writes(notebook, "py") compare(script2, script) def test_notebook_no_line_to_next_cell( nb=new_notebook( cells=[ new_markdown_cell("Markdown cell #1"), new_code_cell("%load_ext line_profiler"), new_markdown_cell("Markdown cell #2"), new_code_cell("%lprun -f ..."), new_markdown_cell("Markdown cell #3"), new_code_cell("# And a function!\ndef f(x):\n return 5"), ] ), ): script = jupytext.writes(nb, "py") nb2 = jupytext.reads(script, "py") nb2.metadata.pop("jupytext") compare_notebooks(nb2, nb) def test_notebook_one_blank_line_before_first_markdown_cell( script=""" # This is a markdown cell 1 + 1 """, ): notebook = jupytext.reads(script, "py") script2 = jupytext.writes(notebook, "py") compare(script2, script) assert len(notebook.cells) == 3 for cell in notebook.cells: lines = cell.source.splitlines() if len(lines): assert lines[0] assert lines[-1] def test_read_markdown_cell_with_triple_quote_307( script="""# This script test that commented triple quotes ''' # do not impede the correct identification of Markdown cells # Here is Markdown cell number 2 ''' """, ): notebook = jupytext.reads(script, "py") assert len(notebook.cells) == 2 assert notebook.cells[0].cell_type == "markdown" assert ( notebook.cells[0].source == """This script test that commented triple quotes ''' do not impede the correct identification of Markdown cells""" ) assert notebook.cells[1].cell_type == "markdown" assert notebook.cells[1].source == "Here is Markdown cell number 2 '''" script2 = jupytext.writes(notebook, "py") compare(script2, script) def test_read_explicit_markdown_cell_with_triple_quote_307( script="""# {{{ [md] {"special": "metadata"} # some text ''' # }}} print('hello world') # {{{ [md] {"special": "metadata"} # more text ''' # }}} """, ): notebook = jupytext.reads(script, "py") assert len(notebook.cells) == 3 assert notebook.cells[0].cell_type == "markdown" assert notebook.cells[0].source == "some text '''" assert notebook.cells[1].cell_type == "code" assert notebook.cells[1].source == "print('hello world')" assert notebook.cells[2].cell_type == "markdown" assert notebook.cells[2].source == "more text '''" script2 = jupytext.writes(notebook, "py") compare(script2, script) def test_round_trip_markdown_cell_with_magic(): notebook = new_notebook( cells=[new_markdown_cell("IPython has magic commands like\n%quickref")], metadata={"jupytext": {"main_language": "python"}}, ) text = jupytext.writes(notebook, "py") notebook2 = jupytext.reads(text, "py") compare_notebooks(notebook2, notebook) def test_round_trip_python_with_js_cell(): notebook = new_notebook( cells=[ new_code_cell( """import notebook.nbextensions notebook.nbextensions.install_nbextension('index.js', user=True)""" ), new_code_cell( """%%javascript Jupyter.utils.load_extensions('jupytext')""" ), ] ) text = jupytext.writes(notebook, "py") notebook2 = jupytext.reads(text, "py") compare_notebooks(notebook2, notebook) def test_round_trip_python_with_js_cell_no_cell_metadata(): notebook = new_notebook( cells=[ new_code_cell( """import notebook.nbextensions notebook.nbextensions.install_nbextension('index.js', user=True)""" ), new_code_cell( """%%javascript Jupyter.utils.load_extensions('jupytext')""" ), ], metadata={ "jupytext": { "notebook_metadata_filter": "-all", "cell_metadata_filter": "-all", } }, ) text = jupytext.writes(notebook, "py") notebook2 = jupytext.reads(text, "py") compare_notebooks(notebook2, notebook) def test_raw_with_metadata( text="""# + key="value" active="" # Raw cell # # Commented line """, notebook=new_notebook(cells=[new_raw_cell("Raw cell\n# Commented line", metadata={"key": "value"})]), ): nb2 = jupytext.reads(text, "py") compare_notebooks(nb2, notebook) text2 = jupytext.writes(nb2, "py") compare(text2, text) def test_raw_with_metadata_2( no_jupytext_version_number, text="""# + [raw] key="value" # Raw cell # # Commented line """, notebook=new_notebook(cells=[new_raw_cell("Raw cell\n# Commented line", metadata={"key": "value"})]), ): nb2 = jupytext.reads(text, "py") compare_notebooks(nb2, notebook) def test_markdown_with_metadata( text="""# + [markdown] key="value" # Markdown cell """, notebook=new_notebook(cells=[new_markdown_cell("Markdown cell", metadata={"key": "value"})]), ): nb2 = jupytext.reads(text, "py") compare_notebooks(nb2, notebook) text2 = jupytext.writes(nb2, "py") compare(text2, text) def test_multiline_comments_in_markdown_1(): text = """# + [markdown] ''' a long cell ''' """ nb = jupytext.reads(text, "py") assert len(nb.cells) == 1 assert nb.cells[0].cell_type == "markdown" assert nb.cells[0].source == "a\nlong\ncell" py = jupytext.writes(nb, "py") compare(py, text) def test_multiline_comments_in_markdown_2(): text = '''# + [markdown] """ a long cell """ ''' nb = jupytext.reads(text, "py") assert len(nb.cells) == 1 assert nb.cells[0].cell_type == "markdown" assert nb.cells[0].source == "a\nlong\ncell" py = jupytext.writes(nb, "py") compare(py, text) def test_multiline_comments_in_raw_cell(): text = '''# + active="" """ some text """ ''' nb = jupytext.reads(text, "py") assert len(nb.cells) == 1 assert nb.cells[0].cell_type == "raw" assert nb.cells[0].source == "some\ntext" py = jupytext.writes(nb, "py") compare(py, text) def test_multiline_comments_in_markdown_cell_no_line_return(): text = '''# + [md] """a long cell""" ''' nb = jupytext.reads(text, "py") assert len(nb.cells) == 1 assert nb.cells[0].cell_type == "markdown" assert nb.cells[0].source == "a\nlong\ncell" def test_multiline_comments_in_markdown_cell_is_robust_to_additional_cell_marker(): text = '''# + [md] """ some text, and a fake cell marker # + [raw] """ ''' nb = jupytext.reads(text, "py") assert len(nb.cells) == 1 assert nb.cells[0].cell_type == "markdown" assert nb.cells[0].source == "some text, and a fake cell marker\n# + [raw]" py = jupytext.writes(nb, "py") compare(py, text) def test_active_tag( text="""# + tags=["active-py"] interpreter = 'python' # + tags=["active-ipynb"] # interpreter = 'ipython' """, ref=new_notebook( cells=[ new_raw_cell("interpreter = 'python'", metadata={"tags": ["active-py"]}), new_code_cell("interpreter = 'ipython'", metadata={"tags": ["active-ipynb"]}), ] ), ): nb = jupytext.reads(text, "py") compare_notebooks(nb, ref) py = jupytext.writes(nb, "py") compare(py, text) def test_indented_bash_command( no_jupytext_version_number, nb=new_notebook( cells=[ new_code_cell( """try: !echo jo pass except: pass""" ) ] ), text="""try: # !echo jo pass except: pass """, ): """Reproduces https://github.com/mwouts/jupytext/issues/437""" py = jupytext.writes(nb, "py:light") compare(py, text) nb2 = jupytext.reads(py, "py") compare_notebooks(nb2, nb) def test_two_raw_cells_are_preserved(nb=new_notebook(cells=[new_raw_cell("---\nX\n---"), new_raw_cell("Y")])): """Test the pattern described at https://github.com/mwouts/jupytext/issues/466""" py = jupytext.writes(nb, "py") nb2 = jupytext.reads(py, "py") compare_notebooks(nb2, nb) def test_no_metadata_on_multiline_decorator( text="""import pytest @pytest.mark.parametrize( "arg", [ 'a', 'b', 'c' ], ) def test_arg(arg): assert isinstance(arg, str) """, ): """Applying black on the code of jupytext 1.4.2 turns some pytest parameters into multi-lines ones, and causes a few failures in test_pep8.py:test_no_metadata_when_py_is_pep8""" nb = jupytext.reads(text, "py") assert len(nb.cells) == 2 for cell in nb.cells: assert cell.cell_type == "code" assert nb.cells[0].source == "import pytest" assert nb.cells[0].metadata == {} @pytest.mark.parametrize( "script,cell", [ ( """if True: # # !rm file 1 # !rm file 2 """, """if True: # !rm file 1 !rm file 2""", ), ( """# + if True: # help? # ?help # # ?help # # help? """, """if True: help? ?help # ?help # help?""", ), ], ) def test_indented_magic_commands(script, cell): nb = jupytext.reads(script, "py") assert len(nb.cells) == 1 assert nb.cells[0].cell_type == "code" compare(nb.cells[0].source, cell) assert nb.cells[0].metadata == {} compare(jupytext.writes(nb, "py"), script) ================================================ FILE: tests/functional/simple_notebooks/test_read_simple_rmd.py ================================================ import re from time import sleep import nbformat import pytest from nbformat.v4.nbbase import ( new_code_cell, new_markdown_cell, new_notebook, new_raw_cell, ) import jupytext from jupytext.cli import jupytext as jupytext_cli from jupytext.compare import compare, compare_cells, compare_notebooks def test_read_mostly_py_rmd_file( rmd="""--- title: Simple file --- ```{python, echo=TRUE} import numpy as np x = np.arange(0, 2*math.pi, eps) ``` ```{python, echo=TRUE} x = np.arange(0,1,eps) y = np.abs(x)-.5 ``` ```{r} ls() ``` ```{r, results="asis", magic_args="-i x"} cat(stringi::stri_rand_lipsum(3), sep='\n\n') ``` """, ): nb = jupytext.reads(rmd, "Rmd") compare_cells( nb.cells, [ new_raw_cell("---\ntitle: Simple file\n---"), new_code_cell( "import numpy as np\nx = np.arange(0, 2*math.pi, eps)", metadata={"echo": True}, ), new_code_cell("x = np.arange(0,1,eps)\ny = np.abs(x)-.5", metadata={"echo": True}), new_code_cell("%%R\nls()"), new_code_cell( "%%R -i x\ncat(stringi::stri_rand_lipsum(3), sep='\n\n')", metadata={"results": "asis"}, ), ], compare_ids=False, ) rmd2 = jupytext.writes(nb, "Rmd") rmd2 = re.sub(r"```{r ", "```{r, ", rmd2) rmd2 = re.sub(r"```{python ", "```{python, ", rmd2) compare(rmd2, rmd) def test_markdown_cell_with_code_works( nb=new_notebook( cells=[ new_markdown_cell( """```python 1 + 1 ```""" ) ] ), ): text = jupytext.writes(nb, "Rmd") nb2 = jupytext.reads(text, "Rmd") compare_notebooks(nb2, nb) def test_two_markdown_cell_with_code_works( nb=new_notebook( cells=[ new_markdown_cell( """```python 1 + 1 ```""" ), new_markdown_cell( """```python 2 + 2 ```""" ), ] ), ): text = jupytext.writes(nb, "Rmd") nb2 = jupytext.reads(text, "Rmd") compare_notebooks(nb2, nb) def test_tags_in_rmd( rmd="""--- jupyter: jupytext: text_representation: extension: .Rmd format_name: rmarkdown format_version: '1.1' jupytext_version: 1.2.3 --- ```{python tags=c("parameters")} p = 1 ``` """, nb=new_notebook(cells=[new_code_cell("p = 1", metadata={"tags": ["parameters"]})]), ): nb2 = jupytext.reads(rmd, "Rmd") compare_notebooks(nb2, nb) def round_trip_cell_metadata(cell_metadata): nb = new_notebook( metadata={"jupytext": {"main_language": "python"}}, cells=[new_code_cell("1 + 1", metadata=cell_metadata)], ) text = jupytext.writes(nb, "Rmd") nb2 = jupytext.reads(text, "Rmd") compare_notebooks(nb2, nb) def test_comma_in_metadata(cell_metadata={"a": "b, c"}): round_trip_cell_metadata(cell_metadata) def test_dict_in_metadata(cell_metadata={"a": {"b": "c"}}): round_trip_cell_metadata(cell_metadata) def test_list_in_metadata(cell_metadata={"d": ["e"]}): round_trip_cell_metadata(cell_metadata) @pytest.mark.parametrize("root_level_metadata_as_raw_cell", [True, False]) def test_root_level_metadata_as_raw_cell( tmpdir, root_level_metadata_as_raw_cell, rmd="""--- author: R Markdown document author title: R Markdown notebook title --- ```{r} 1 + 1 ``` """, ): nb_file = tmpdir.join("notebook.ipynb") rmd_file = tmpdir.join("notebook.Rmd") cfg_file = tmpdir.join("jupytext.toml") cfg_file.write("root_level_metadata_as_raw_cell = {}".format("true" if root_level_metadata_as_raw_cell else "false")) rmd_file.write(rmd) jupytext_cli([str(rmd_file), "--to", "ipynb"]) nb = nbformat.read(str(nb_file), as_version=4) if root_level_metadata_as_raw_cell: compare_cells( nb.cells, [ new_raw_cell( """--- author: R Markdown document author title: R Markdown notebook title ---""" ), new_code_cell("1 + 1"), ], compare_ids=False, ) else: compare_cells(nb.cells, [new_code_cell("1 + 1")], compare_ids=False) assert nb.metadata["jupytext"]["root_level_metadata"] == { "title": "R Markdown notebook title", "author": "R Markdown document author", } # Writing back to Rmd should preserve the original document jupytext_cli([str(nb_file), "--to", "Rmd"]) compare(rmd_file.read(), rmd) def test_pair_rmd_file_with_cell_tags_and_options(tmpdir, cwd_tmpdir, no_jupytext_version_number): rmd = """```{r plot_1, dpi=72} plot(3:30) ``` """ rmd_file = tmpdir.join("test.Rmd") rmd_file.write(rmd) # Pair Rmd with ipynb jupytext_cli(["--set-formats", "ipynb,Rmd", "test.Rmd"]) # Wait so that ipynb will be more recent sleep(0.2) # Modify the ipynb file nb_file = tmpdir.join("test.ipynb") nb = nbformat.read(nb_file, as_version=4) nb.cells[0].source = "plot(4:40)" nb_file.write(nbformat.writes(nb)) # Sync the two files jupytext_cli(["--sync", "test.Rmd"]) # Remove the header rmd2 = rmd_file.read() rmd2 = rmd2.rsplit("---\n\n")[1] # The new code chunk has the new code, and options are still there compare(rmd2, rmd.replace("3", "4")) def test_apostrophe_in_parameter_1079( rmd="""```{python some-name, param="Problem's"} a = 1 ``` """, ): nb = jupytext.reads(rmd, fmt="Rmd") rmd2 = jupytext.writes(nb, fmt="Rmd") compare(rmd2, rmd) nb2 = jupytext.reads(rmd, fmt="Rmd") compare_notebooks(nb2, nb) @pytest.mark.parametrize("line", [" #'''", "a = 2 #'''"]) def test_commented_triple_quote_1060(line): rmd = f"""```{{python}} {line} ``` ```{{python}} # Another cell ``` """ nb = jupytext.reads(rmd, fmt="Rmd") assert nb.cells[0].source == line rmd2 = jupytext.writes(nb, fmt="Rmd") compare(rmd2, rmd) nb2 = jupytext.reads(rmd, fmt="Rmd") compare_notebooks(nb2, nb) def test_bibliography_in_rmd( rmd="""Issue #1161 The bibliography section below should not become a code cell ```{bibliography} ``` ```{r} 6 ``` """, ): nb = jupytext.reads(rmd, fmt="Rmd") assert len(nb.cells) == 2, nb.cells assert nb.cells[0].cell_type == "markdown" assert nb.cells[1].cell_type == "code" assert nb.cells[1].source == "6" rmd2 = jupytext.writes(nb, fmt="Rmd") compare(rmd2, rmd) def test_non_language_code_fence(): """ This test reproduces the example from issue #1429 """ rmd = """# A title ```{index} equations ``` Some text. ```{python} a = 10 ``` """ nb = jupytext.reads(rmd, fmt="Rmd") assert len(nb.cells) == 2, nb.cells assert nb.cells[0].cell_type == "markdown" assert nb.cells[1].cell_type == "code" assert nb.cells[1].source == "a = 10" rmd2 = jupytext.writes(nb, fmt="Rmd") compare(rmd2, rmd) ================================================ FILE: tests/functional/simple_notebooks/test_read_simple_rust.py ================================================ from nbformat.v4.nbbase import new_code_cell, new_markdown_cell, new_notebook import jupytext from jupytext.compare import compare, compare_notebooks def test_read_magics(text="// :vars\n"): nb = jupytext.reads(text, "rs") compare_notebooks(nb, new_notebook(cells=[new_code_cell(":vars")])) compare(jupytext.writes(nb, "rs"), text) def test_read_simple_file( text="""println!("Hello world"); eprintln!("Hello error"); format!("Hello {}", "world") // A Function pub fn fib(x: i32) -> i32 { if x <= 2 {0} else {fib(x - 2) + fib(x - 1)} } // This is a // Markdown cell // This is a magic instruction // :vars // This is a rust identifier ::std::mem::drop """, ): nb = jupytext.reads(text, "rs") compare_notebooks( nb, new_notebook( cells=[ new_code_cell( """println!("Hello world"); eprintln!("Hello error"); format!("Hello {}", "world")""" ), new_code_cell( """// A Function pub fn fib(x: i32) -> i32 { if x <= 2 {0} else {fib(x - 2) + fib(x - 1)} }""" ), new_markdown_cell("This is a\nMarkdown cell"), new_code_cell( """// This is a magic instruction :vars""" ), new_code_cell( """// This is a rust identifier ::std::mem::drop""" ), ] ), ) compare(jupytext.writes(nb, "rs"), text) def test_read_write_script_with_metadata_241( no_jupytext_version_number, rsnb="""#!/usr/bin/env scriptisto // --- // jupyter: // jupytext: // text_representation: // extension: .rs // format_name: light // kernelspec: // display_name: Rust // language: rust // name: rust // --- let mut a: i32 = 2; a += 1; """, ): nb = jupytext.reads(rsnb, "rs") assert "executable" in nb.metadata["jupytext"] rsnb2 = jupytext.writes(nb, "rs") compare(rsnb, rsnb2) ================================================ FILE: tests/functional/simple_notebooks/test_read_simple_scheme.py ================================================ import jupytext from jupytext.compare import compare def test_read_simple_file( script=""";; --- ;; title: Simple file ;; --- ;; Here we have some text ;; And below we have some code (define a 35) """, ): for file_extension in ("ss", "scm"): nb = jupytext.reads(script, file_extension) assert len(nb.cells) == 3 assert nb.cells[0].cell_type == "raw" assert nb.cells[0].source == "---\ntitle: Simple file\n---" assert nb.cells[1].cell_type == "markdown" assert nb.cells[1].source == "Here we have some text\nAnd below we have some code" assert nb.cells[2].cell_type == "code" compare(nb.cells[2].source, "(define a 35)") script2 = jupytext.writes(nb, file_extension) compare(script2, script) ================================================ FILE: tests/functional/simple_notebooks/test_read_simple_sphinx.py ================================================ import jupytext from jupytext.compare import compare def test_read_simple_file( script='''# -*- coding: utf-8 -*- """ This is a markdown cell """ 1 + 2 + 3 + 4 5 6 "" 7 ################################# # Another markdown cell def f(x): """Sample docstring""" return 4 ''', ): nb = jupytext.reads(script, "py:sphinx") assert nb.cells[0].cell_type == "code" assert nb.cells[0].source == "%matplotlib inline" assert nb.cells[1].cell_type == "markdown" assert nb.cells[1].source == "This is a markdown cell" assert nb.cells[2].cell_type == "code" compare( nb.cells[2].source, """1 + 2 + 3 + 4 5 6""", ) assert nb.cells[3].cell_type == "code" assert nb.cells[3].source == "7" assert nb.cells[4].cell_type == "markdown" assert nb.cells[4].source == "Another markdown cell" assert nb.cells[5].cell_type == "code" assert ( nb.cells[5].source == '''def f(x): """Sample docstring""" return 4''' ) assert len(nb.cells) == 6 script2 = jupytext.writes(nb, "py:sphinx") compare(script2, script) def test_read_more_complex_file( script="""'''This is a markdown cell''' 1 + 2 + 3 + 4 5 6 ''' Another markdown cell''' ################################# # A third one ''' Another markdown cell''' 1 + 2 + 3 + 4 # ################################ # A fifth one '''And a last one ''' """, ): nb = jupytext.reads(script, "py:sphinx") assert nb.cells[0].cell_type == "code" assert nb.cells[0].source == "%matplotlib inline" assert nb.cells[1].cell_type == "markdown" assert nb.cells[1].source == "This is a markdown cell" assert nb.cells[2].cell_type == "code" compare( nb.cells[2].source, """1 + 2 + 3 + 4 5 6""", ) assert nb.cells[3].cell_type == "markdown" assert nb.cells[3].source == "Another markdown cell" assert nb.cells[4].cell_type == "markdown" assert nb.cells[4].source == "A third one" assert nb.cells[5].cell_type == "markdown" assert nb.cells[5].source == "Another markdown cell" assert nb.cells[6].cell_type == "code" assert nb.cells[6].source == "1 + 2 + 3 + 4" assert nb.cells[7].cell_type == "markdown" assert nb.cells[7].source == "A fifth one" assert nb.cells[8].cell_type == "markdown" assert nb.cells[8].source == "And a last one" assert len(nb.cells) == 9 def test_read_empty_code_cell( script='''""" Markdown cell """ ''', ): nb = jupytext.reads(script, "py:sphinx") assert nb.cells[0].cell_type == "code" assert nb.cells[0].source == "%matplotlib inline" assert nb.cells[1].cell_type == "markdown" assert nb.cells[1].source == "Markdown cell" assert nb.cells[2].cell_type == "code" assert nb.cells[2].source == "" assert len(nb.cells) == 3 assert jupytext.writes(nb, "py:sphinx") == script ================================================ FILE: tests/integration/cli/test_cli_pipe.py ================================================ import pytest from jupytext.cli import jupytext @pytest.mark.requires_myst @pytest.mark.requires_black def test_cli_black_myst( tmp_path, no_jupytext_version_number, text="""--- jupytext: formats: md:myst text_representation: extension: .md format_name: myst format_version: 0.13 kernelspec: display_name: Python 3 (ipykernel) language: python name: python3 --- # Quantum yield efficiency of photosynthesis ```{code-cell} python # I'm some code x = 1 ``` """, ): tmp_md = tmp_path / "notebook.md" tmp_md.write_text(text) jupytext(["--pipe", "black", str(tmp_md)]) assert tmp_md.read_text() == text ================================================ FILE: tests/integration/cli/test_execute.py ================================================ import shutil from io import StringIO from unittest import mock import pytest from jupytext import read, reads from jupytext.cli import jupytext from jupytext.version import __version__ @pytest.mark.requires_user_kernel_python3 @pytest.mark.requires_nbconvert @pytest.mark.skip_on_windows def test_pipe_nbconvert_execute(tmpdir): tmp_ipynb = str(tmpdir.join("notebook.ipynb")) tmp_py = str(tmpdir.join("notebook.py")) with open(tmp_py, "w") as fp: fp.write( """1 + 2 """ ) jupytext( args=[ tmp_py, "--to", "ipynb", "--pipe-fmt", "ipynb", "--pipe", "jupyter nbconvert --stdin --stdout --to notebook --execute", ] ) nb = read(tmp_ipynb) assert len(nb.cells) == 1 assert nb.cells[0].outputs[0]["data"] == {"text/plain": "3"} @pytest.mark.requires_user_kernel_python3 @pytest.mark.requires_nbconvert @pytest.mark.skip_on_windows def test_pipe_nbconvert_execute_sync(tmpdir): tmp_ipynb = str(tmpdir.join("notebook.ipynb")) tmp_py = str(tmpdir.join("notebook.py")) with open(tmp_py, "w") as fp: fp.write( """1 + 2 """ ) jupytext( args=[ tmp_py, "--set-formats", "py,ipynb", "--sync", "--pipe-fmt", "ipynb", "--pipe", "jupyter nbconvert --stdin --stdout --to notebook --execute", ] ) nb = read(tmp_ipynb) assert len(nb.cells) == 1 assert nb.cells[0].outputs[0]["data"] == {"text/plain": "3"} @pytest.mark.requires_user_kernel_python3 @pytest.mark.requires_nbconvert @pytest.mark.skip_on_windows def test_execute(tmpdir, caplog, capsys): tmp_ipynb = str(tmpdir.join("notebook.ipynb")) tmp_py = str(tmpdir.join("notebook.py")) with open(tmp_py, "w") as fp: fp.write( """1 + 2 """ ) jupytext(args=[tmp_py, "--to", "ipynb", "--execute"]) nb = read(tmp_ipynb) assert len(nb.cells) == 1 assert nb.cells[0].outputs[0]["data"] == {"text/plain": "3"} @pytest.mark.requires_user_kernel_python3 @pytest.mark.requires_nbconvert def test_execute_readme_ok(tmpdir): tmp_md = str(tmpdir.join("notebook.md")) with open(tmp_md, "w") as fp: fp.write( """ A readme with correct instructions ```python 1 + 2 ``` """ ) jupytext(args=[tmp_md, "--execute"]) @pytest.mark.requires_user_kernel_python3 @pytest.mark.requires_nbconvert @pytest.mark.skip_on_windows def test_execute_readme_not_ok(tmpdir): tmp_md = str(tmpdir.join("notebook.md")) with open(tmp_md, "w") as fp: fp.write( """ A readme with incorrect instructions (a is not defined) ```python a + 1 ``` """ ) import nbconvert with pytest.raises(nbconvert.preprocessors.execute.CellExecutionError, match="is not defined"): jupytext(args=[tmp_md, "--execute"]) @pytest.mark.requires_user_kernel_python3 @pytest.mark.requires_nbconvert @pytest.mark.skip_on_windows def test_execute_sync(tmpdir, caplog, capsys): tmp_ipynb = str(tmpdir.join("notebook.ipynb")) tmp_py = str(tmpdir.join("notebook.py")) with open(tmp_py, "w") as fp: fp.write( """1 + 2 """ ) jupytext(args=[tmp_py, "--set-formats", "py,ipynb", "--sync", "--execute"]) nb = read(tmp_ipynb) assert len(nb.cells) == 1 assert nb.cells[0].outputs[0]["data"] == {"text/plain": "3"} @pytest.mark.requires_nbconvert @pytest.mark.requires_ir_kernel @pytest.mark.skip_on_windows def test_execute_r(tmpdir, caplog, capsys): # pragma: no cover tmp_ipynb = str(tmpdir.join("notebook.ipynb")) tmp_md = str(tmpdir.join("notebook.md")) with open(tmp_md, "w") as fp: fp.write( """```r 1 + 2 + 3 ``` """ ) jupytext(args=[tmp_md, "--to", "ipynb", "--execute"]) nb = read(tmp_ipynb) assert len(nb.cells) == 1 assert nb.cells[0].outputs[0]["data"]["text/markdown"] == "6" @pytest.mark.requires_user_kernel_python3 @pytest.mark.requires_nbconvert @pytest.mark.skip_on_windows def test_execute_in_subfolder(tmpdir, caplog, capsys): subfolder = tmpdir.mkdir("subfolder") tmp_csv = str(subfolder.join("inputs.csv")) tmp_py = str(subfolder.join("notebook.py")) tmp_ipynb = str(subfolder.join("notebook.ipynb")) with open(tmp_csv, "w") as fp: fp.write("1\n2\n") with open(tmp_py, "w") as fp: fp.write( """import ast with open('inputs.csv') as fp: text = fp.read() sum(ast.literal_eval(line) for line in text.splitlines()) """ ) jupytext(args=[tmp_py, "--to", "ipynb", "--execute"]) nb = read(tmp_ipynb) assert len(nb.cells) == 3 assert nb.cells[2].outputs[0]["data"] == {"text/plain": "3"} tmp2_py = str(tmpdir.mkdir("another_folder").join("notebook.py")) tmp2_ipynb = str(tmpdir.join("another_folder", "notebook.ipynb")) shutil.copy(tmp_py, tmp2_py) # Executing without run-path fails import nbconvert with pytest.raises( nbconvert.preprocessors.execute.CellExecutionError, match="No such file or directory: 'inputs.csv'", ): jupytext(args=[tmp2_py, "--to", "ipynb", "--execute"]) # Raise if folder does not exists with pytest.raises(ValueError, match="is not a valid path"): jupytext(args=[tmp2_py, "--to", "ipynb", "--run-path", "wrong_path"]) # Execute in full path jupytext(args=[tmp2_py, "--to", "ipynb", "--run-path", str(subfolder)]) nb = read(tmp2_ipynb) assert len(nb.cells) == 3 assert nb.cells[2].outputs[0]["data"] == {"text/plain": "3"} # Execute in path relative to notebook dir jupytext(args=[tmp2_py, "--to", "ipynb", "--run-path", "../subfolder"]) nb = read(tmp2_ipynb) assert len(nb.cells) == 3 assert nb.cells[2].outputs[0]["data"] == {"text/plain": "3"} @pytest.fixture() def sample_md_notebook(): """This is a sample md notebook with an outdated version of Jupytext and no kernel information, to test #908""" return """--- jupyter: jupytext: text_representation: extension: .md format_name: markdown format_version: '1.1' jupytext_version: 1.1.0 --- ```python 1 + 1 ``` """ @pytest.mark.requires_user_kernel_python3 def test_execute_text_file_does_update_the_metadata(sample_md_notebook, tmp_path): md_file = tmp_path / "nb.md" md_file.write_text(sample_md_notebook) jupytext([str(md_file), "--execute"]) new_md_text = md_file.read_text() assert __version__ in new_md_text assert "kernelspec" in new_md_text @pytest.mark.requires_user_kernel_python3 def test_cat_execute_does_not_update_the_metadata(sample_md_notebook, tmp_path): md_file = tmp_path / "nb.md" md_file.write_text(sample_md_notebook) # read md notebook on stdin - this does the same as # cat notebook.md | jupytext --execute with open(md_file) as fp, mock.patch("sys.stdin", fp): jupytext(["--execute"]) new_md_text = md_file.read_text() assert __version__ not in new_md_text assert "kernelspec" not in new_md_text @pytest.mark.requires_user_kernel_python3 @pytest.mark.skip_on_windows @pytest.mark.filterwarnings("ignore") def test_utf8_out_331(capsys, caplog): py = "from IPython.core.display import HTML; HTML(u'\xd7')" with mock.patch("sys.stdin", StringIO(py)): jupytext(["--to", "ipynb", "--execute", "-"]) out, err = capsys.readouterr() assert err == "" nb = reads(out, "ipynb") assert len(nb.cells) == 1 print(nb.cells[0].outputs) assert nb.cells[0].outputs[0]["data"]["text/html"] == "\xd7" ================================================ FILE: tests/integration/contents_manager/test_cm_config.py ================================================ import logging import os import sys import unittest.mock as mock import pytest from jupyter_server.utils import ensure_async from nbformat import read from nbformat.v4.nbbase import new_code_cell, new_markdown_cell, new_notebook from tornado.web import HTTPError import jupytext from jupytext.compare import compare_cells, notebook_model SAMPLE_NOTEBOOK = new_notebook(cells=[new_markdown_cell("A Markdown cell"), new_code_cell("# A code cell\n1 + 1")]) pytestmark = pytest.mark.asyncio async def test_local_config_overrides_cm_config(tmpdir, cm): cm.root_dir = str(tmpdir) cm.formats = "ipynb,py" nested = tmpdir.mkdir("nested") with open(str(nested.join("jupytext.yml")), "w") as fp: fp.write("formats: ''\n") await ensure_async(cm.save(notebook_model(SAMPLE_NOTEBOOK), "notebook.ipynb")) assert os.path.isfile(str(tmpdir.join("notebook.ipynb"))) assert os.path.isfile(str(tmpdir.join("notebook.py"))) await ensure_async(cm.save(notebook_model(SAMPLE_NOTEBOOK), "nested/notebook.ipynb")) assert os.path.isfile(str(nested.join("notebook.ipynb"))) assert not os.path.isfile(str(nested.join("notebook.py"))) async def test_config_file_is_called_just_once(tmpdir, cm, n=2): cm.root_dir = str(tmpdir) tmpdir.join("jupytext.toml").write("") nb_files = [str(tmpdir.join(f"notebook{i}.ipynb")) for i in range(n)] for nb_file in nb_files: jupytext.write(SAMPLE_NOTEBOOK, nb_file) mock_config = mock.MagicMock(return_value=None) with mock.patch("jupytext.sync_contentsmanager.load_jupytext_configuration_file", mock_config): with mock.patch( "jupytext.async_contentsmanager.load_jupytext_configuration_file", mock_config, ): for i in range(n): await ensure_async(cm.get(f"notebook{i}.ipynb", content=False)) # Listing the contents should not call the config more than once assert mock_config.call_count == 1 async def test_pairing_through_config_leaves_ipynb_unmodified(tmpdir, cm): cm.root_dir = str(tmpdir) cfg_file = tmpdir.join("jupytext.yml") nb_file = tmpdir.join("notebook.ipynb") py_file = tmpdir.join("notebook.py") cfg_file.write("formats: 'ipynb,py'\n") await ensure_async(cm.save(notebook_model(SAMPLE_NOTEBOOK), "notebook.ipynb")) assert nb_file.isfile() assert py_file.isfile() nb = read(nb_file, as_version=4) assert "jupytext" not in nb.metadata @pytest.mark.parametrize( "cfg_file,cfg_text", [ # Should be false, not False ("jupytext.toml", "hide_notebook_metadata = False"), ("jupytext.toml", 'hide_notebook_metadata = "False"'), ("jupytext.toml", "not_a_jupytext_option = true"), ("pyproject.toml", "[tool.jupytext]\nnot_a_jupytext_option = true"), ("jupytext.json", '{"notebook_metadata_filter":"-all",}'), ], ) @pytest.mark.filterwarnings( r"ignore:Passing (unrecognized|unrecoginized) arguments " r"to super\(JupytextConfiguration\).__init__" ) async def test_incorrect_config_message(tmpdir, cfg_file, cfg_text, cm): cm.root_dir = str(tmpdir) tmpdir.join(cfg_file).write(cfg_text) tmpdir.join("empty.ipynb").write("{}") expected_message = f"The Jupytext configuration file .*{cfg_file} is incorrect" with pytest.raises(HTTPError, match=expected_message): await ensure_async(cm.get("empty.ipynb", type="notebook", content=False)) with pytest.raises(HTTPError, match=expected_message): await ensure_async(cm.save(notebook_model(SAMPLE_NOTEBOOK), "notebook.ipynb")) async def test_global_config_file(tmpdir, cm): cm_dir = tmpdir.join("cm_dir").mkdir() cm.root_dir = str(cm_dir) tmpdir.join("jupytext.toml").write('formats = "ipynb,Rmd"') def fake_global_config_directory(): return [str(tmpdir)] with mock.patch( "jupytext.config.global_jupytext_configuration_directories", fake_global_config_directory, ): nb = new_notebook(cells=[new_code_cell("1+1")]) model = notebook_model(nb) await ensure_async(cm.save(model, "notebook.ipynb")) assert {model["path"] for model in (await ensure_async(cm.get("/", content=True)))["content"]} == { "notebook.ipynb", "notebook.Rmd", } @pytest.mark.skipif( sys.platform.startswith("win"), reason="AttributeError: 'LocalPath' object has no attribute 'mksymlinkto'", ) async def test_paired_files_and_symbolic_links(tmpdir, cm): """We test that we don't get issues when pairing files into folders that are symbolic links""" actual = tmpdir.mkdir("actual_files") actual_notebooks = actual.mkdir("notebooks") actual_scripts = actual.mkdir("scripts") # Open the contents manager in another dir jupyter_dir = tmpdir.mkdir("jupyter_dir") cm.root_dir = str(jupyter_dir) # Create sym links to the notebook/script folders jupyter_dir.join("link_to_notebooks").mksymlinkto(actual_notebooks) jupyter_dir.join("link_to_scripts").mksymlinkto(actual_scripts) # Pair the notebooks in the linked folders jupyter_dir.join("jupytext.toml").write('formats = "link_to_notebooks///ipynb,link_to_scripts///py:percent"') # Save a notebook await ensure_async(cm.save(notebook_model(SAMPLE_NOTEBOOK), "link_to_notebooks/notebook.ipynb")) # This creates two files in the destinations folders assert actual_notebooks.join("notebook.ipynb").isfile() assert actual_scripts.join("notebook.py").isfile() # Re-open the notebook (here, the text version) await ensure_async(cm.get("link_to_scripts/notebook.py")) # Update the text version jupyter_dir.join("link_to_scripts").join("notebook.py").write_text("# %%\n3 + 3\n", encoding="utf-8") # Reload and make sure that we get the updated notebook model = await ensure_async(cm.get("link_to_notebooks/notebook.ipynb")) nb = model["content"] compare_cells(nb.cells, [new_code_cell("3 + 3")], compare_ids=False) async def test_metadata_filter_from_config_has_precedence_over_notebook_metadata(tmpdir, cwd_tmpdir, cm, python_notebook): python_notebook.metadata["jupytext"] = {"notebook_metadata_filter": "-all"} tmpdir.join("jupytext.toml").write('notebook_metadata_filter = "all"') cm.root_dir = str(tmpdir) await ensure_async(cm.save(notebook_model(python_notebook), "test.py")) py = tmpdir.join("test.py").read() assert "notebook_metadata_filter: all" in py async def test_test_no_text_representation_metadata_in_ipynb_900(tmpdir, python_notebook, cm): tmpdir.join("jupytext.toml").write('formats = "ipynb,py:percent"\n') # create a test notebook and save it in Jupyter nb = python_notebook cm.root_dir = str(tmpdir) await ensure_async(cm.save(dict(type="notebook", content=nb), "test.ipynb")) # Assert that "text_representation" is in the Jupytext metadata #900 assert "text_representation" in tmpdir.join("test.py").read() # But not in the ipynb notebook assert "text_representation" not in tmpdir.join("test.ipynb").read() # modify the ipynb file in Jupyter # Reload the notebook nb = (await ensure_async(cm.get("test.ipynb")))["content"] nb.cells.append(new_markdown_cell("A new cell")) await ensure_async(cm.save(dict(type="notebook", content=nb), "test.ipynb")) # The text representation metadata is in the py file assert "text_representation" in tmpdir.join("test.py").read() # But not in the ipynb notebook assert "text_representation" not in tmpdir.join("test.ipynb").read() async def test_cm_config_no_log(cwd_tmp_path, tmp_path, caplog, cm): cm.root_dir = str(tmp_path) config = 'cm_config_log_level="none"' (tmp_path / "jupytext.toml").write_text(config) (tmp_path / "nb1.py").write_text("# %%") (tmp_path / "subfolder").mkdir() (tmp_path / "subfolder" / "jupytext.toml").write_text(config) (tmp_path / "subfolder" / "nb2.py").write_text("# %%") caplog.set_level(logging.DEBUG) await ensure_async(cm.get("nb1.py", type="notebook", content=False)) await ensure_async(cm.get("nb1.py", type="notebook", content=True)) await ensure_async(cm.get("subfolder/nb2.py", type="notebook", content=False)) await ensure_async(cm.get("subfolder/nb2.py", type="notebook", content=True)) assert "Jupytext configuration file" not in caplog.text async def test_cm_config_log_only_if_changed(cwd_tmp_path, tmp_path, caplog, cm): cm.root_dir = str(tmp_path) config = "" (tmp_path / "jupytext.toml").write_text(config) (tmp_path / "nb1.py").write_text("# %%") (tmp_path / "subfolder").mkdir() (tmp_path / "subfolder" / "jupytext.toml").write_text(config) (tmp_path / "subfolder" / "nb2.py").write_text("# %%") caplog.set_level(logging.INFO) await ensure_async(cm.get("nb1.py", type="notebook", content=False)) assert "Jupytext configuration file" in caplog.text caplog.clear() # Same notebook, same config => no log await ensure_async(cm.get("nb1.py", type="notebook", content=True)) assert "Jupytext configuration file" not in caplog.text # Same notebook, config changed => log (tmp_path / "jupytext.toml").write_text('formats="ipynb,py:percent"') await ensure_async(cm.get("nb1.py", type="notebook", content=True)) assert "Jupytext configuration file" in caplog.text caplog.clear() # Different folder, different config await ensure_async(cm.get("subfolder/nb2.py", type="notebook", content=False)) assert "Jupytext configuration file" in caplog.text caplog.clear() # Same config as previously => no log await ensure_async(cm.get("subfolder/nb2.py", type="notebook", content=False)) assert "Jupytext configuration file" not in caplog.text ================================================ FILE: tests/integration/contents_manager/test_contentsmanager.py ================================================ import inspect import os import re import shutil import time import pytest from jupyter_server.utils import ensure_async from nbformat.v4.nbbase import new_code_cell, new_markdown_cell, new_notebook from tornado.web import HTTPError import jupytext from jupytext.cli import jupytext as jupytext_cli from jupytext.compare import compare, compare_notebooks, notebook_model from jupytext.formats import auto_ext_from_metadata, read_format_from_metadata from jupytext.header import header_to_metadata_and_cell from jupytext.jupytext import read, write, writes from jupytext.kernels import kernelspec_from_language pytestmark = pytest.mark.asyncio async def test_rename(tmpdir, cm): org_file = str(tmpdir.join("notebook.ipynb")) new_file = str(tmpdir.join("new.ipynb")) jupytext.write(new_notebook(), org_file) cm.root_dir = str(tmpdir) await ensure_async(cm.rename_file("notebook.ipynb", "new.ipynb")) assert os.path.isfile(new_file) assert not os.path.isfile(org_file) async def test_rename_inconsistent_path(tmpdir, cm): org_file = str(tmpdir.join("notebook_suffix.ipynb")) new_file = str(tmpdir.join("new.ipynb")) jupytext.write(new_notebook(metadata={"jupytext": {"formats": "_suffix.ipynb"}}), org_file) cm.root_dir = str(tmpdir) # Read notebook, and learn about its format model = await ensure_async(cm.get("notebook_suffix.ipynb")) assert model["content"]["metadata"]["jupytext"]["formats"] == "_suffix.ipynb" # Since #1414 the notebook can be moved await ensure_async(cm.rename_file("notebook_suffix.ipynb", "new.ipynb")) assert os.path.isfile(new_file) assert not os.path.isfile(org_file) # The new notebook is unchanged new_model = await ensure_async(cm.get("new.ipynb")) compare_notebooks(new_model["content"], model["content"]) async def test_pair_unpair_notebook(tmpdir, cm): tmp_ipynb = "notebook.ipynb" tmp_md = "notebook.md" nb = new_notebook( metadata={ "kernelspec": { "display_name": "Python3", "language": "python", "name": "python3", } }, cells=[ new_code_cell( "1 + 1", outputs=[ { "data": {"text/plain": ["2"]}, "execution_count": 1, "metadata": {}, "output_type": "execute_result", } ], ) ], ) cm.root_dir = str(tmpdir) # save notebook await ensure_async(cm.save(model=notebook_model(nb), path=tmp_ipynb)) assert not os.path.isfile(str(tmpdir.join(tmp_md))) # pair notebook nb["metadata"]["jupytext"] = {"formats": "ipynb,md"} await ensure_async(cm.save(model=notebook_model(nb), path=tmp_ipynb)) assert os.path.isfile(str(tmpdir.join(tmp_md))) # reload and get outputs nb2 = (await ensure_async(cm.get(tmp_md)))["content"] compare_notebooks(nb, nb2) # unpair and save as md del nb["metadata"]["jupytext"] await ensure_async(cm.save(model=notebook_model(nb), path=tmp_md)) nb2 = (await ensure_async(cm.get(tmp_md)))["content"] # we get no outputs here compare_notebooks(nb, nb2, compare_outputs=False) assert len(nb2.cells[0]["outputs"]) == 0 async def test_load_save_rename(ipynb_py_R_jl_file, cm, tmpdir): tmp_ipynb = "notebook.ipynb" tmp_rmd = "notebook.Rmd" cm.formats = "ipynb,Rmd" cm.root_dir = str(tmpdir) cm.delete_to_trash = False # open ipynb, save Rmd, reopen nb = jupytext.read(ipynb_py_R_jl_file) await ensure_async(cm.save(model=notebook_model(nb), path=tmp_rmd)) nb_rmd = await ensure_async(cm.get(tmp_rmd)) compare_notebooks(nb_rmd["content"], nb, "Rmd") # save ipynb await ensure_async(cm.save(model=notebook_model(nb), path=tmp_ipynb)) # rename_file ipynb await ensure_async(cm.rename_file(tmp_ipynb, "new.ipynb")) assert not os.path.isfile(str(tmpdir.join(tmp_ipynb))) assert not os.path.isfile(str(tmpdir.join(tmp_rmd))) assert os.path.isfile(str(tmpdir.join("new.ipynb"))) assert os.path.isfile(str(tmpdir.join("new.Rmd"))) # delete one file, test that we can still read and rename_file it await ensure_async(cm.delete("new.Rmd")) assert not os.path.isfile(str(tmpdir.join("new.Rmd"))) model = await ensure_async(cm.get("new.ipynb", content=False)) assert "last_modified" in model await ensure_async(cm.save(model=notebook_model(nb), path="new.ipynb")) assert os.path.isfile(str(tmpdir.join("new.Rmd"))) await ensure_async(cm.delete("new.Rmd")) await ensure_async(cm.rename_file("new.ipynb", tmp_ipynb)) assert os.path.isfile(str(tmpdir.join(tmp_ipynb))) assert not os.path.isfile(str(tmpdir.join(tmp_rmd))) assert not os.path.isfile(str(tmpdir.join("new.ipynb"))) assert not os.path.isfile(str(tmpdir.join("new.Rmd"))) async def test_save_load_paired_md_notebook(ipynb_py_R_jl_file, cm, tmpdir): tmp_ipynb = "notebook.ipynb" tmp_md = "notebook.md" cm.root_dir = str(tmpdir) # open ipynb, save with cm, reopen nb = jupytext.read(ipynb_py_R_jl_file) nb.metadata["jupytext"] = {"formats": "ipynb,md"} await ensure_async(cm.save(model=notebook_model(nb), path=tmp_ipynb)) nb_md = await ensure_async(cm.get(tmp_md)) compare_notebooks(nb_md["content"], nb, "md") assert nb_md["content"].metadata["jupytext"]["formats"] == "ipynb,md" async def test_pair_plain_script(percent_file, cm, tmpdir, caplog): tmp_py = "notebook.py" tmp_ipynb = "notebook.ipynb" cm.root_dir = str(tmpdir) # open py file, pair, save with cm nb = jupytext.read(percent_file) nb.metadata["jupytext"]["formats"] = "ipynb,py:hydrogen" await ensure_async(cm.save(model=notebook_model(nb), path=tmp_py)) # assert "'Include Metadata' is off" in caplog.text assert os.path.isfile(str(tmpdir.join(tmp_py))) assert os.path.isfile(str(tmpdir.join(tmp_ipynb))) # Make sure we've not changed the script with open(percent_file) as fp: script = fp.read() with open(str(tmpdir.join(tmp_py))) as fp: script2 = fp.read() compare(script2, script) # reopen py file with the cm nb2 = (await ensure_async(cm.get(tmp_py)))["content"] compare_notebooks(nb2, nb) assert nb2.metadata["jupytext"]["formats"] == "ipynb,py:hydrogen" # remove the pairing and save del nb.metadata["jupytext"]["formats"] await ensure_async(cm.save(model=notebook_model(nb), path=tmp_py)) # reopen py file with the cm nb2 = (await ensure_async(cm.get(tmp_py)))["content"] compare_notebooks(nb2, nb) assert "formats" not in nb2.metadata["jupytext"] async def test_load_save_rename_nbpy(ipynb_py_file, cm, tmpdir): tmp_ipynb = "notebook.ipynb" tmp_nbpy = "notebook.nb.py" cm.formats = "ipynb,.nb.py" cm.root_dir = str(tmpdir) # open ipynb, save nb.py, reopen nb = jupytext.read(ipynb_py_file) await ensure_async(cm.save(model=notebook_model(nb), path=tmp_nbpy)) nbpy = await ensure_async(cm.get(tmp_nbpy)) compare_notebooks(nbpy["content"], nb) # save ipynb await ensure_async(cm.save(model=notebook_model(nb), path=tmp_ipynb)) # rename_file nbpy await ensure_async(cm.rename_file(tmp_nbpy, "new.nb.py")) assert not os.path.isfile(str(tmpdir.join(tmp_ipynb))) assert not os.path.isfile(str(tmpdir.join(tmp_nbpy))) assert os.path.isfile(str(tmpdir.join("new.ipynb"))) assert os.path.isfile(str(tmpdir.join("new.nb.py"))) # rename_file to a non-matching pattern with pytest.raises(HTTPError): await ensure_async(cm.rename_file(tmp_nbpy, "suffix_missing.py")) async def test_load_save_py_freeze_metadata(python_file, cm, tmpdir): if "light" in python_file: pytest.skip() tmp_nbpy = "notebook.py" cm.root_dir = str(tmpdir) # read original file with open(python_file) as fp: text_py = fp.read() # write to tmp_nbpy with open(str(tmpdir.join(tmp_nbpy)), "w") as fp: fp.write(text_py) # open and save notebook nb = (await ensure_async(cm.get(tmp_nbpy)))["content"] await ensure_async(cm.save(model=notebook_model(nb), path=tmp_nbpy)) with open(str(tmpdir.join(tmp_nbpy))) as fp: text_py2 = fp.read() compare(text_py2, text_py) async def test_load_text_notebook(tmpdir, cm): cm.root_dir = str(tmpdir) nbpy = "text.py" with open(str(tmpdir.join(nbpy)), "w") as fp: fp.write("# %%\n1 + 1\n") py_model = await ensure_async(cm.get(nbpy, content=False)) assert py_model["type"] == "notebook" assert py_model["content"] is None py_model = await ensure_async(cm.get(nbpy, content=True)) assert py_model["type"] == "notebook" assert "cells" in py_model["content"] # The model returned by the CM should match that of a classical ipynb notebook nb_model = dict(type="notebook", content=new_notebook(cells=[new_markdown_cell("A cell")])) await ensure_async(cm.save(nb_model, "notebook.ipynb")) nb_model = await ensure_async(cm.get("notebook.ipynb", content=True)) for key in ["format", "mimetype", "type"]: assert nb_model[key] == py_model[key], key async def test_load_save_rename_notebook_with_dot(ipynb_py_file, cm, tmpdir): tmp_ipynb = "1.notebook.ipynb" tmp_nbpy = "1.notebook.py" cm.formats = "ipynb,py" cm.root_dir = str(tmpdir) # open ipynb, save nb.py, reopen nb = jupytext.read(ipynb_py_file) await ensure_async(cm.save(model=notebook_model(nb), path=tmp_nbpy)) nbpy = await ensure_async(cm.get(tmp_nbpy)) compare_notebooks(nbpy["content"], nb) # save ipynb await ensure_async(cm.save(model=notebook_model(nb), path=tmp_ipynb)) # rename_file py await ensure_async(cm.rename_file(tmp_nbpy, "2.new_notebook.py")) assert not os.path.isfile(str(tmpdir.join(tmp_ipynb))) assert not os.path.isfile(str(tmpdir.join(tmp_nbpy))) assert os.path.isfile(str(tmpdir.join("2.new_notebook.ipynb"))) assert os.path.isfile(str(tmpdir.join("2.new_notebook.py"))) async def test_load_save_rename_nbpy_default_config(ipynb_py_file, cm, tmpdir): tmp_ipynb = "notebook.ipynb" tmp_nbpy = "notebook.nb.py" cm.formats = "ipynb,.nb.py" cm.root_dir = str(tmpdir) # open ipynb, save nb.py, reopen nb = jupytext.read(ipynb_py_file) await ensure_async(cm.save(model=notebook_model(nb), path=tmp_nbpy)) nbpy = await ensure_async(cm.get(tmp_nbpy)) compare_notebooks(nbpy["content"], nb) # open ipynb nbipynb = await ensure_async(cm.get(tmp_ipynb)) compare_notebooks(nbipynb["content"], nb) # save ipynb await ensure_async(cm.save(model=notebook_model(nb), path=tmp_ipynb)) # rename_file notebook.nb.py to new.nb.py await ensure_async(cm.rename_file(tmp_nbpy, "new.nb.py")) assert not os.path.isfile(str(tmpdir.join(tmp_ipynb))) assert not os.path.isfile(str(tmpdir.join(tmp_nbpy))) assert os.path.isfile(str(tmpdir.join("new.ipynb"))) assert os.path.isfile(str(tmpdir.join("new.nb.py"))) # rename_file new.ipynb to notebook.ipynb await ensure_async(cm.rename_file("new.ipynb", tmp_ipynb)) assert os.path.isfile(str(tmpdir.join(tmp_ipynb))) assert os.path.isfile(str(tmpdir.join(tmp_nbpy))) assert not os.path.isfile(str(tmpdir.join("new.ipynb"))) assert not os.path.isfile(str(tmpdir.join("new.nb.py"))) async def test_load_save_rename_non_ascii_path(ipynb_py_file, cm, tmpdir): tmp_ipynb = "notebôk.ipynb" tmp_nbpy = "notebôk.nb.py" cm.formats = "ipynb,.nb.py" tmpdir = "" + str(tmpdir) cm.root_dir = tmpdir # open ipynb, save nb.py, reopen nb = jupytext.read(ipynb_py_file) await ensure_async(cm.save(model=notebook_model(nb), path=tmp_nbpy)) nbpy = await ensure_async(cm.get(tmp_nbpy)) compare_notebooks(nbpy["content"], nb) # open ipynb nbipynb = await ensure_async(cm.get(tmp_ipynb)) compare_notebooks(nbipynb["content"], nb) # save ipynb await ensure_async(cm.save(model=notebook_model(nb), path=tmp_ipynb)) # rename_file notebôk.nb.py to nêw.nb.py await ensure_async(cm.rename_file(tmp_nbpy, "nêw.nb.py")) assert not os.path.isfile(os.path.join(tmpdir, tmp_ipynb)) assert not os.path.isfile(os.path.join(tmpdir, tmp_nbpy)) assert os.path.isfile(os.path.join(tmpdir, "nêw.ipynb")) assert os.path.isfile(os.path.join(tmpdir, "nêw.nb.py")) # rename_file nêw.ipynb to notebôk.ipynb await ensure_async(cm.rename_file("nêw.ipynb", tmp_ipynb)) assert os.path.isfile(os.path.join(tmpdir, tmp_ipynb)) assert os.path.isfile(os.path.join(tmpdir, tmp_nbpy)) assert not os.path.isfile(os.path.join(tmpdir, "nêw.ipynb")) assert not os.path.isfile(os.path.join(tmpdir, "nêw.nb.py")) async def test_outdated_text_notebook(python_notebook, cm, tmpdir): # 1. write py ipynb cm.formats = "py,ipynb" cm.outdated_text_notebook_margin = 0 cm.root_dir = str(tmpdir) # open ipynb, save py, reopen nb = python_notebook await ensure_async(cm.save(model=notebook_model(nb), path="notebook.py")) model_py = await ensure_async(cm.get("notebook.py", load_alternative_format=False)) model_ipynb = await ensure_async(cm.get("notebook.ipynb", load_alternative_format=False)) # 2. check that time of ipynb <= py assert model_ipynb["last_modified"] <= model_py["last_modified"] # 3. wait some time time.sleep(0.5) # 4. modify ipynb nb.cells.append(new_markdown_cell("New cell")) write(nb, str(tmpdir.join("notebook.ipynb"))) # 5. test error with pytest.raises(HTTPError): await ensure_async(cm.get("notebook.py")) # 6. test OK with cm.outdated_text_notebook_margin = 5.0 await ensure_async(cm.get("notebook.py")) # 7. test OK with cm.outdated_text_notebook_margin = float("inf") await ensure_async(cm.get("notebook.py")) async def test_outdated_text_notebook_no_diff_ok(tmpdir, cm, python_notebook): # 1. write py ipynb cm.formats = "py,ipynb" cm.outdated_text_notebook_margin = 0 cm.root_dir = str(tmpdir) # open ipynb, save py, reopen nb = python_notebook await ensure_async(cm.save(model=notebook_model(nb), path="notebook.py")) model_py = await ensure_async(cm.get("notebook.py", load_alternative_format=False)) model_ipynb = await ensure_async(cm.get("notebook.ipynb", load_alternative_format=False)) # 2. check that time of ipynb <= py assert model_ipynb["last_modified"] <= model_py["last_modified"] # 3. wait some time time.sleep(0.5) # 4. touch ipynb with open(tmpdir / "notebook.ipynb", "a"): os.utime(tmpdir / "notebook.ipynb", None) # 5. No error since both files correspond to the same notebook #799 await ensure_async(cm.get("notebook.py")) async def test_outdated_text_notebook_diff_is_shown(tmpdir, cm, python_notebook): # 1. write py ipynb cm.formats = "py,ipynb" cm.outdated_text_notebook_margin = 0 cm.root_dir = str(tmpdir) # open ipynb, save py, reopen nb = python_notebook nb.cells = [new_markdown_cell("Text version 1.0")] await ensure_async(cm.save(model=notebook_model(nb), path="notebook.py")) model_py = await ensure_async(cm.get("notebook.py", load_alternative_format=False)) model_ipynb = await ensure_async(cm.get("notebook.ipynb", load_alternative_format=False)) # 2. check that time of ipynb <= py assert model_ipynb["last_modified"] <= model_py["last_modified"] # 3. wait some time time.sleep(0.5) # 4. modify ipynb nb.cells = [new_markdown_cell("Text version 2.0")] jupytext.write(nb, str(tmpdir / "notebook.ipynb")) # 5. The diff is shown in the error with pytest.raises(HTTPError) as excinfo: await ensure_async(cm.get("notebook.py")) diff = excinfo.value.log_message diff = diff[diff.find("Differences") : diff.rfind("Please")] compare( # In the reference below, lines with a single space # have been stripped by the pre-commit hook diff.replace("\n \n", "\n\n"), """Differences (jupytext --diff notebook.py notebook.ipynb) are: --- notebook.py +++ notebook.ipynb @@ -13,5 +13,5 @@ # --- # %%%% [markdown] -# Text version 1.0 +# Text version 2.0 """, ) async def test_reload_notebook_after_jupytext_cli(python_notebook, cm, tmpdir): tmp_ipynb = str(tmpdir.join("notebook.ipynb")) tmp_nbpy = str(tmpdir.join("notebook.py")) cm.outdated_text_notebook_margin = 0 cm.root_dir = str(tmpdir) # write the paired notebook nb = python_notebook nb.metadata.setdefault("jupytext", {})["formats"] = "py,ipynb" await ensure_async(cm.save(model=notebook_model(nb), path="notebook.py")) assert os.path.isfile(tmp_ipynb) assert os.path.isfile(tmp_nbpy) # run jupytext CLI jupytext_cli([tmp_nbpy, "--to", "ipynb", "--update"]) # test reload nb1 = (await ensure_async(cm.get("notebook.py")))["content"] nb2 = (await ensure_async(cm.get("notebook.ipynb")))["content"] compare_notebooks(nb, nb1) compare_notebooks(nb, nb2) async def test_load_save_percent_format(percent_file, cm, tmpdir): tmp_py = "notebook.py" with open(percent_file) as stream: text_py = stream.read() with open(str(tmpdir.join(tmp_py)), "w") as stream: stream.write(text_py) cm.root_dir = str(tmpdir) # open python, save nb = (await ensure_async(cm.get(tmp_py)))["content"] del nb.metadata["jupytext"]["notebook_metadata_filter"] await ensure_async(cm.save(model=notebook_model(nb), path=tmp_py)) # compare the new file with original one with open(str(tmpdir.join(tmp_py))) as stream: text_py2 = stream.read() # do we find 'percent' in the header? header = text_py2[: -len(text_py)] assert any(["percent" in line for line in header.splitlines()]) # Remove the YAML header text_py2 = text_py2[-len(text_py) :] compare(text_py2, text_py) async def test_save_to_percent_format(ipynb_julia_file, cm, tmpdir): tmp_ipynb = "notebook.ipynb" tmp_jl = "notebook.jl" cm.root_dir = str(tmpdir) cm.preferred_jupytext_formats_save = "jl:percent" nb = jupytext.read(ipynb_julia_file) nb["metadata"]["jupytext"] = {"formats": "ipynb,jl"} # save to ipynb and jl await ensure_async(cm.save(model=notebook_model(nb), path=tmp_ipynb)) # read jl file with open(str(tmpdir.join(tmp_jl))) as stream: text_jl = stream.read() # Parse the YAML header metadata, _, _, _ = header_to_metadata_and_cell(text_jl.splitlines(), "#", "") assert metadata["jupytext"]["formats"] == "ipynb,jl:percent" async def test_save_using_preferred_and_default_format_170(ipynb_py_file, cm, tmpdir): nb = read(ipynb_py_file) # Way 0: preferred_jupytext_formats_save, no prefix + formats tmp_py = str(tmpdir.join("python/notebook.py")) cm.root_dir = str(tmpdir) cm.preferred_jupytext_formats_save = "py:percent" cm.formats = "ipynb,python//py" # save to ipynb and py await ensure_async(cm.save(model=notebook_model(nb), path="notebook.ipynb")) # read py file nb_py = read(tmp_py) assert nb_py.metadata["jupytext"]["text_representation"]["format_name"] == "percent" # Way 1: preferred_jupytext_formats_save + formats tmp_py = str(tmpdir.join("python/notebook.py")) cm.root_dir = str(tmpdir) cm.preferred_jupytext_formats_save = "python//py:percent" cm.formats = "ipynb,python//py" # save to ipynb and py await ensure_async(cm.save(model=notebook_model(nb), path="notebook.ipynb")) # read py file nb_py = read(tmp_py) assert nb_py.metadata["jupytext"]["text_representation"]["format_name"] == "percent" # Way 2: formats tmp_py = str(tmpdir.join("python/notebook.py")) cm.root_dir = str(tmpdir) cm.formats = "ipynb,python//py:percent" # save to ipynb and py await ensure_async(cm.save(model=notebook_model(nb), path="notebook.ipynb")) # read py file nb_py = read(tmp_py) assert nb_py.metadata["jupytext"]["text_representation"]["format_name"] == "percent" async def test_open_using_preferred_and_default_format_174(ipynb_py_file, cm, tmpdir): tmp_ipynb = str(tmpdir.join("notebook.ipynb")) tmp_py = str(tmpdir.join("python/notebook.py")) tmp_py2 = str(tmpdir.join("other/notebook.py")) os.makedirs(str(tmpdir.join("other"))) shutil.copyfile(ipynb_py_file, tmp_ipynb) cm.root_dir = str(tmpdir) cm.formats = "ipynb,python//py:percent" cm.notebook_metadata_filter = "all" cm.cell_metadata_filter = "all" # load notebook model = await ensure_async(cm.get("notebook.ipynb")) # save to ipynb and py await ensure_async(cm.save(model=model, path="notebook.ipynb")) assert os.path.isfile(tmp_py) os.remove(tmp_ipynb) # read py file model2 = await ensure_async(cm.get("python/notebook.py")) compare_notebooks(model2["content"], model["content"]) # move py file to the another folder shutil.move(tmp_py, tmp_py2) model2 = await ensure_async(cm.get("other/notebook.py")) compare_notebooks(model2["content"], model["content"]) await ensure_async(cm.save(model=model, path="other/notebook.py")) assert not os.path.isfile(tmp_ipynb) assert not os.path.isfile(str(tmpdir.join("other/notebook.ipynb"))) async def test_kernelspec_are_preserved(ipynb_py_file, cm, tmpdir): if "many hash" in ipynb_py_file: pytest.skip() tmp_ipynb = str(tmpdir.join("notebook.ipynb")) tmp_py = str(tmpdir.join("notebook.py")) shutil.copyfile(ipynb_py_file, tmp_ipynb) cm.root_dir = str(tmpdir) cm.formats = "ipynb,py" cm.notebook_metadata_filter = "-all" # load notebook model = await ensure_async(cm.get("notebook.ipynb")) model["content"].metadata["kernelspec"] = { "display_name": "Kernel name", "language": "python", "name": "custom", } # save to ipynb and py await ensure_async(cm.save(model=model, path="notebook.ipynb")) assert os.path.isfile(tmp_py) # read ipynb model2 = await ensure_async(cm.get("notebook.ipynb")) compare_notebooks(model2["content"], model["content"]) async def test_save_to_light_percent_sphinx_format(ipynb_py_file, cm, tmpdir): tmp_ipynb = "notebook.ipynb" tmp_lgt_py = "notebook.lgt.py" tmp_pct_py = "notebook.pct.py" tmp_spx_py = "notebook.spx.py" cm.root_dir = str(tmpdir) nb = jupytext.read(ipynb_py_file) nb["metadata"]["jupytext"] = {"formats": "ipynb,.pct.py:percent,.lgt.py:light,.spx.py:sphinx"} # save to ipynb and three python flavors await ensure_async(cm.save(model=notebook_model(nb), path=tmp_ipynb)) # read files with open(str(tmpdir.join(tmp_pct_py))) as stream: assert read_format_from_metadata(stream.read(), ".py") == "percent" with open(str(tmpdir.join(tmp_lgt_py))) as stream: assert read_format_from_metadata(stream.read(), ".py") == "light" with open(str(tmpdir.join(tmp_spx_py))) as stream: assert read_format_from_metadata(stream.read(), ".py") == "sphinx" model = await ensure_async(cm.get(path=tmp_pct_py)) compare_notebooks(model["content"], nb) model = await ensure_async(cm.get(path=tmp_lgt_py)) compare_notebooks(model["content"], nb) model = await ensure_async(cm.get(path=tmp_spx_py)) # (notebooks not equal as we insert %matplotlib inline in sphinx) model = await ensure_async(cm.get(path=tmp_ipynb)) compare_notebooks(model["content"], nb) async def test_pair_notebook_with_dot(ipynb_py_file, cm, tmpdir): # Reproduce issue #138 tmp_py = "file.5.1.py" tmp_ipynb = "file.5.1.ipynb" cm.root_dir = str(tmpdir) nb = jupytext.read(ipynb_py_file) nb["metadata"]["jupytext"] = {"formats": "ipynb,py:percent"} # save to ipynb and three python flavors await ensure_async(cm.save(model=notebook_model(nb), path=tmp_ipynb)) assert os.path.isfile(str(tmpdir.join(tmp_ipynb))) # read files with open(str(tmpdir.join(tmp_py))) as stream: assert read_format_from_metadata(stream.read(), ".py") == "percent" model = await ensure_async(cm.get(path=tmp_py)) assert model["name"] == "file.5.1.py" compare_notebooks(model["content"], nb) model = await ensure_async(cm.get(path=tmp_ipynb)) assert model["name"] == "file.5.1.ipynb" compare_notebooks(model["content"], nb) async def test_preferred_format_allows_to_read_others_format(python_notebook, cm, tmpdir): # 1. write py ipynb tmp_ipynb = "notebook.ipynb" tmp_nbpy = "notebook.py" cm.preferred_jupytext_formats_save = "py:light" cm.root_dir = str(tmpdir) # load notebook and save it using the cm nb = python_notebook nb["metadata"]["jupytext"] = {"formats": "ipynb,py"} await ensure_async(cm.save(model=notebook_model(nb), path=tmp_ipynb)) # Saving does not update the metadata, as 'save' makes a copy of the notebook # assert nb['metadata']['jupytext']['formats'] == 'ipynb,py:light' # Set preferred format for reading cm.preferred_jupytext_formats_read = "py:percent" # Read notebook model = await ensure_async(cm.get(tmp_nbpy)) # Check that format is explicit assert model["content"]["metadata"]["jupytext"]["formats"] == "ipynb,py:light" # Check contents compare_notebooks(model["content"], nb) # Change save format and save model["content"]["metadata"]["jupytext"]["formats"] == "ipynb,py" cm.preferred_jupytext_formats_save = "py:percent" await ensure_async(cm.save(model=notebook_model(nb), path=tmp_ipynb)) # Read notebook model = await ensure_async(cm.get(tmp_nbpy)) compare_notebooks(model["content"], nb) # Check that format is explicit assert model["content"]["metadata"]["jupytext"]["formats"] == "ipynb,py:percent" async def test_preferred_formats_read_auto(tmpdir, cm): tmp_py = "notebook.py" with open(str(tmpdir.join(tmp_py)), "w") as script: script.write( """# cell one 1 + 1 """ ) # create contents manager with default load format as percent cm.preferred_jupytext_formats_read = "auto:percent" cm.root_dir = str(tmpdir) # load notebook model = await ensure_async(cm.get(tmp_py)) # check that script is opened as percent assert "percent" == model["content"]["metadata"]["jupytext"]["text_representation"]["format_name"] async def test_save_in_auto_extension_global(ipynb_py_R_jl_file, cm, tmpdir): # load notebook nb = jupytext.read(ipynb_py_R_jl_file) auto_ext = auto_ext_from_metadata(nb.metadata) tmp_ipynb = "notebook.ipynb" tmp_script = "notebook" + auto_ext # create contents manager with default load format as percent cm.formats = "ipynb,auto" cm.preferred_jupytext_formats_save = "auto:percent" cm.root_dir = str(tmpdir) # save notebook await ensure_async(cm.save(model=notebook_model(nb), path=tmp_ipynb)) # check that text representation exists, and is in percent format with open(str(tmpdir.join(tmp_script))) as stream: assert read_format_from_metadata(stream.read(), auto_ext) == "percent" # reload and compare with original notebook model = await ensure_async(cm.get(path=tmp_script)) # saving should not create a format entry #95 assert "formats" not in model["content"].metadata.get("jupytext", {}) compare_notebooks(model["content"], nb) async def test_global_auto_pairing_works_with_empty_notebook(tmpdir, cm): nb = new_notebook() tmp_ipynb = str(tmpdir.join("notebook.ipynb")) tmp_py = str(tmpdir.join("notebook.py")) tmp_auto = str(tmpdir.join("notebook.auto")) # create contents manager with default load format as percent cm.formats = "ipynb,auto" cm.preferred_jupytext_formats_save = "auto:percent" cm.root_dir = str(tmpdir) # save notebook await ensure_async(cm.save(model=notebook_model(nb), path="notebook.ipynb")) # check that only the ipynb representation exists assert os.path.isfile(tmp_ipynb) assert not os.path.isfile(tmp_py) assert not os.path.isfile(tmp_auto) assert "notebook.ipynb" not in cm.paired_notebooks model = await ensure_async(cm.get(path="notebook.ipynb")) compare_notebooks(model["content"], nb) # add language information to the notebook nb.metadata["language_info"] = { "codemirror_mode": {"name": "ipython", "version": 3}, "file_extension": ".py", "mimetype": "text/x-python", "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", "version": "3.7.3", } # save again await ensure_async(cm.save(model=notebook_model(nb), path="notebook.ipynb")) # check that ipynb + py representations exists assert os.path.isfile(tmp_ipynb) assert os.path.isfile(tmp_py) assert not os.path.isfile(tmp_auto) assert len(cm.paired_notebooks["notebook.ipynb"]) == 2 # add a cell in the py file with open(tmp_py, "a") as fp: fp.write("# %%\n2+2\n") nb2 = (await ensure_async(cm.get(path="notebook.ipynb")))["content"] assert len(nb2.cells) == 1 assert nb2.cells[0].source == "2+2" async def test_save_in_auto_extension_global_with_format(ipynb_py_R_jl_file, cm, tmpdir): # load notebook nb = jupytext.read(ipynb_py_R_jl_file) auto_ext = auto_ext_from_metadata(nb.metadata) tmp_ipynb = "notebook.ipynb" tmp_script = "notebook" + auto_ext # create contents manager with default load format as percent cm.formats = "ipynb,auto:percent" cm.root_dir = str(tmpdir) # save notebook await ensure_async(cm.save(model=notebook_model(nb), path=tmp_ipynb)) # check that text representation exists, and is in percent format with open(str(tmpdir.join(tmp_script))) as stream: assert read_format_from_metadata(stream.read(), auto_ext) == "percent" # reload and compare with original notebook model = await ensure_async(cm.get(path=tmp_script)) # saving should not create a format entry #95 assert "formats" not in model["content"].metadata.get("jupytext", {}) compare_notebooks(model["content"], nb) async def test_save_in_auto_extension_local(ipynb_py_R_jl_file, cm, tmpdir): # load notebook nb = jupytext.read(ipynb_py_R_jl_file) nb.metadata.setdefault("jupytext", {})["formats"] = "ipynb,auto:percent" auto_ext = auto_ext_from_metadata(nb.metadata) tmp_ipynb = "notebook.ipynb" tmp_script = "notebook" + auto_ext # create contents manager with default load format as percent cm.root_dir = str(tmpdir) # save notebook await ensure_async(cm.save(model=notebook_model(nb), path=tmp_ipynb)) # check that text representation exists, and is in percent format with open(str(tmpdir.join(tmp_script))) as stream: assert read_format_from_metadata(stream.read(), auto_ext) == "percent" # reload and compare with original notebook model = await ensure_async(cm.get(path=tmp_script)) compare_notebooks(model["content"], nb) async def test_save_in_pct_and_lgt_auto_extensions(ipynb_py_R_jl_file, cm, tmpdir): # load notebook nb = jupytext.read(ipynb_py_R_jl_file) auto_ext = auto_ext_from_metadata(nb.metadata) tmp_ipynb = "notebook.ipynb" tmp_pct_script = "notebook.pct" + auto_ext tmp_lgt_script = "notebook.lgt" + auto_ext # create contents manager with default load format as percent cm.formats = "ipynb,.pct.auto,.lgt.auto" cm.preferred_jupytext_formats_save = ".pct.auto:percent,.lgt.auto:light" cm.root_dir = str(tmpdir) # save notebook await ensure_async(cm.save(model=notebook_model(nb), path=tmp_ipynb)) # check that text representation exists in percent format with open(str(tmpdir.join(tmp_pct_script))) as stream: assert read_format_from_metadata(stream.read(), auto_ext) == "percent" # check that text representation exists in light format with open(str(tmpdir.join(tmp_lgt_script))) as stream: assert read_format_from_metadata(stream.read(), auto_ext) == "light" async def test_metadata_filter_is_effective(ipynb_py_R_jl_file, cm, tmpdir): if re.match(r".*(magic|305).*", ipynb_py_R_jl_file): pytest.skip() nb = jupytext.read(ipynb_py_R_jl_file) tmp_ipynb = "notebook.ipynb" tmp_script = "notebook.py" # create contents manager cm.root_dir = str(tmpdir) # save notebook to tmpdir await ensure_async(cm.save(model=notebook_model(nb), path=tmp_ipynb)) # set config cm.formats = "ipynb,py" cm.notebook_metadata_filter = "jupytext,-all" cm.cell_metadata_filter = "-all" # load notebook nb = (await ensure_async(cm.get(tmp_ipynb)))["content"] assert nb.metadata["jupytext"]["cell_metadata_filter"] == "-all" assert nb.metadata["jupytext"]["notebook_metadata_filter"] == "jupytext,-all" # save notebook again await ensure_async(cm.save(model=notebook_model(nb), path=tmp_ipynb)) # read text version nb2 = jupytext.read(str(tmpdir.join(tmp_script))) # test no metadata assert set(nb2.metadata.keys()) <= {"jupytext", "kernelspec"} for cell in nb2.cells: assert not cell.metadata # read paired notebook nb3 = (await ensure_async(cm.get(tmp_script)))["content"] compare_notebooks(nb3, nb) async def test_no_metadata_added_to_scripts_139(tmpdir, cm): tmp_script = str(tmpdir.join("script.py")) text = """import os print('hello1') print('hello2') """ with open(tmp_script, "w") as fp: fp.write(text) # create contents manager cm.root_dir = str(tmpdir) # Andre's config #139 cm.freeze_metadata = True cm.notebook_metadata_filter = "-all" cm.cell_metadata_filter = "-lines_to_next_cell" # load notebook model = await ensure_async(cm.get("script.py")) # add cell metadata for cell in model["content"].cells: cell.metadata.update( { "ExecuteTime": { "start_time": "2019-02-06T11:53:21.208644Z", "end_time": "2019-02-06T11:53:21.213071Z", } } ) # save notebook await ensure_async(cm.save(model=model, path="script.py")) with open(tmp_script) as fp: compare(fp.read(), text) @pytest.mark.parametrize("ext", [".py", ".ipynb"]) async def test_local_format_can_deactivate_pairing(ipynb_py_file, cm, ext, tmpdir): """This is a test for #157: local format can be used to deactivate the global pairing""" nb = jupytext.read(ipynb_py_file) nb.metadata["jupytext_formats"] = ext[1:] # py or ipynb # create contents manager with default pairing cm.formats = "ipynb,py" cm.root_dir = str(tmpdir) # save notebook await ensure_async(cm.save(model=notebook_model(nb), path="notebook" + ext)) # check that only the text representation exists assert os.path.isfile(str(tmpdir.join("notebook.py"))) == (ext == ".py") assert os.path.isfile(str(tmpdir.join("notebook.ipynb"))) == (ext == ".ipynb") nb2 = (await ensure_async(cm.get("notebook" + ext)))["content"] compare_notebooks(nb2, nb) # resave, check again await ensure_async(cm.save(model=notebook_model(nb2), path="notebook" + ext)) assert os.path.isfile(str(tmpdir.join("notebook.py"))) == (ext == ".py") assert os.path.isfile(str(tmpdir.join("notebook.ipynb"))) == (ext == ".ipynb") nb3 = (await ensure_async(cm.get("notebook" + ext)))["content"] compare_notebooks(nb3, nb) async def test_global_pairing_allows_to_save_other_file_types(rmd_file, cm, tmpdir): """This is a another test for #157: local format can be used to deactivate the global pairing""" nb = jupytext.read(rmd_file) # create contents manager with default pairing cm.formats = "ipynb,py" cm.root_dir = str(tmpdir) # save notebook await ensure_async(cm.save(model=notebook_model(nb), path="notebook.Rmd")) # check that only the original file is saved assert os.path.isfile(str(tmpdir.join("notebook.Rmd"))) assert not os.path.isfile(str(tmpdir.join("notebook.py"))) assert not os.path.isfile(str(tmpdir.join("notebook.ipynb"))) nb2 = (await ensure_async(cm.get("notebook.Rmd")))["content"] compare_notebooks(nb2, nb) @pytest.mark.requires_user_kernel_python3 async def test_python_kernel_preserves_R_files(r_file, cm, tmpdir): """Opening a R file with a Jupyter server that has no R kernel should not modify the file""" tmp_r_file = str(tmpdir.join("script.R")) with open(r_file) as fp: script = fp.read() with open(tmp_r_file, "w") as fp: fp.write(script) # create contents manager cm.root_dir = str(tmpdir) # open notebook, set Python kernel and save model = await ensure_async(cm.get("script.R")) model["content"].metadata["kernelspec"] = kernelspec_from_language("python") await ensure_async(cm.save(model=model, path="script.R")) with open(tmp_r_file) as fp: script2 = fp.read() compare(script2, script) async def test_pair_notebook_in_another_folder(tmpdir, cm): cm.root_dir = str(tmpdir) os.makedirs(str(tmpdir.join("notebooks"))) tmp_ipynb = str(tmpdir.join("notebooks/notebook_name.ipynb")) tmp_py = str(tmpdir.join("scripts/notebook_name.py")) await ensure_async( cm.save( model=notebook_model( new_notebook(metadata={"jupytext": {"formats": "notebooks//ipynb,scripts//py"}}), ), path="notebooks/notebook_name.ipynb", ) ) assert os.path.isfile(tmp_ipynb) assert os.path.isfile(tmp_py) await ensure_async(cm.get("notebooks/notebook_name.ipynb")) await ensure_async(cm.get("scripts/notebook_name.py")) async def test_pair_notebook_in_dotdot_folder(tmpdir, cm): cm.root_dir = str(tmpdir) os.makedirs(str(tmpdir.join("notebooks"))) tmp_ipynb = str(tmpdir.join("notebooks/notebook_name.ipynb")) tmp_py = str(tmpdir.join("scripts/notebook_name.py")) await ensure_async( cm.save( model=notebook_model(new_notebook(metadata={"jupytext": {"formats": "ipynb,../scripts//py"}})), path="notebooks/notebook_name.ipynb", ) ) assert os.path.isfile(tmp_ipynb) assert os.path.isfile(tmp_py) await ensure_async(cm.get("notebooks/notebook_name.ipynb")) await ensure_async(cm.get("scripts/notebook_name.py")) async def test_split_at_heading_option(tmpdir, cm): text = """Markdown text # Header one ## Header two """ tmp_md = str(tmpdir.join("notebook.md")) with open(tmp_md, "w") as fp: fp.write(text) cm.root_dir = str(tmpdir) cm.split_at_heading = True nb = (await ensure_async(cm.get("notebook.md")))["content"] # Was rst to md conversion effective? assert nb.cells[0].source == "Markdown text" assert nb.cells[1].source == "# Header one" assert nb.cells[2].source == "## Header two" nb.metadata["jupytext"]["notebook_metadata_filter"] = "-all" text2 = writes(nb, "md") compare(text2, text) async def test_load_then_change_formats(tmpdir, cm): tmp_ipynb = str(tmpdir.join("nb.ipynb")) tmp_py = str(tmpdir.join("nb.py")) nb = new_notebook(metadata={"jupytext": {"formats": "ipynb,py:light"}}) write(nb, tmp_ipynb) cm.root_dir = str(tmpdir) model = await ensure_async(cm.get("nb.ipynb")) assert model["content"].metadata["jupytext"]["formats"] == "ipynb,py:light" await ensure_async(cm.save(model, path="nb.ipynb")) assert os.path.isfile(tmp_py) assert read(tmp_py).metadata["jupytext"]["formats"] == "ipynb,py:light" time.sleep(0.5) del model["content"].metadata["jupytext"]["formats"] await ensure_async(cm.save(model, path="nb.ipynb")) # test that we have not kept the 'ipynb/py' pairing info, and that we can read the ipynb await ensure_async(cm.get("nb.ipynb")) os.remove(tmp_py) model["content"].metadata.setdefault("jupytext", {})["formats"] = "ipynb,py:percent" await ensure_async(cm.save(model, path="nb.ipynb")) assert os.path.isfile(tmp_py) assert read(tmp_py).metadata["jupytext"]["formats"] == "ipynb,py:percent" os.remove(tmp_py) del model["content"].metadata["jupytext"]["formats"] await ensure_async(cm.save(model, path="nb.ipynb")) assert not os.path.isfile(tmp_py) async def test_set_then_change_formats(tmpdir, cm): tmp_py = str(tmpdir.join("nb.py")) nb = new_notebook(metadata={"jupytext": {"formats": "ipynb,py:light"}}) cm.root_dir = str(tmpdir) await ensure_async(cm.save(model=notebook_model(nb), path="nb.ipynb")) assert os.path.isfile(tmp_py) assert read(tmp_py).metadata["jupytext"]["formats"] == "ipynb,py:light" os.remove(tmp_py) nb.metadata["jupytext"]["formats"] = "ipynb,py:percent" await ensure_async(cm.save(model=notebook_model(nb), path="nb.ipynb")) assert os.path.isfile(tmp_py) assert read(tmp_py).metadata["jupytext"]["formats"] == "ipynb,py:percent" os.remove(tmp_py) del nb.metadata["jupytext"]["formats"] await ensure_async(cm.save(model=notebook_model(nb), path="nb.ipynb")) assert not os.path.isfile(tmp_py) async def test_set_then_change_auto_formats(tmpdir, cm, python_notebook): tmp_ipynb = str(tmpdir.join("nb.ipynb")) tmp_py = str(tmpdir.join("nb.py")) tmp_rmd = str(tmpdir.join("nb.Rmd")) nb = new_notebook(metadata=python_notebook.metadata) cm.root_dir = str(tmpdir) # Pair ipynb/py and save nb.metadata["jupytext"] = {"formats": "ipynb,auto:light"} await ensure_async(cm.save(model=notebook_model(nb), path="nb.ipynb")) assert "nb.py" in cm.paired_notebooks assert "nb.auto" not in cm.paired_notebooks assert os.path.isfile(tmp_py) assert read(tmp_ipynb).metadata["jupytext"]["formats"] == "ipynb,py:light" # Pair ipynb/Rmd and save time.sleep(0.5) nb.metadata["jupytext"] = {"formats": "ipynb,Rmd"} await ensure_async(cm.save(model=notebook_model(nb), path="nb.ipynb")) assert "nb.Rmd" in cm.paired_notebooks assert "nb.py" not in cm.paired_notebooks assert "nb.auto" not in cm.paired_notebooks assert os.path.isfile(tmp_rmd) assert read(tmp_ipynb).metadata["jupytext"]["formats"] == "ipynb,Rmd" await ensure_async(cm.get("nb.ipynb")) # Unpair and save time.sleep(0.5) del nb.metadata["jupytext"] await ensure_async(cm.save(model=notebook_model(nb), path="nb.ipynb")) assert "nb.Rmd" not in cm.paired_notebooks assert "nb.py" not in cm.paired_notebooks assert "nb.auto" not in cm.paired_notebooks await ensure_async(cm.get("nb.ipynb")) async def test_share_py_recreate_ipynb(tmpdir, cm, ipynb_py_R_jl_file): tmp_ipynb = str(tmpdir.join("nb.ipynb")) tmp_py = str(tmpdir.join("nb.py")) cm.root_dir = str(tmpdir) # set default py format cm.preferred_jupytext_formats_save = "py:percent" # every new file is paired cm.formats = "ipynb,py" # the text files don't need a YAML header cm.notebook_metadata_filter = "-all" cm.cell_metadata_filter = "-all" nb = read(ipynb_py_R_jl_file) model_ipynb = await ensure_async(cm.save(model=notebook_model(nb), path="nb.ipynb")) assert os.path.isfile(tmp_ipynb) assert os.path.isfile(tmp_py) os.remove(tmp_ipynb) # reopen and save nb.py model = await ensure_async(cm.get("nb.py")) await ensure_async(cm.save(model=model, path="nb.py")) # ipynb is re-created assert os.path.isfile(tmp_ipynb) # save time of ipynb is that of py file assert model_ipynb["last_modified"] == model["last_modified"] async def test_vim_folding_markers(tmpdir, cm): tmp_ipynb = str(tmpdir.join("nb.ipynb")) tmp_py = str(tmpdir.join("nb.py")) cm.root_dir = str(tmpdir) # Default Vim folding markers cm.cell_markers = "{{{,}}}" cm.formats = "ipynb,py:light" nb = new_notebook( cells=[ new_code_cell( """# region '''Sample cell with region markers''' '''End of the cell''' # end region""" ), new_code_cell("a = 1\n\n\nb = 1"), ] ) await ensure_async(cm.save(model=notebook_model(nb), path="nb.ipynb")) assert os.path.isfile(tmp_ipynb) assert os.path.isfile(tmp_py) nb2 = (await ensure_async(cm.get("nb.ipynb")))["content"] compare_notebooks(nb2, nb) nb3 = read(tmp_py) assert nb3.metadata["jupytext"]["cell_markers"] == "{{{,}}}" with open(tmp_py) as fp: text = fp.read() # Remove YAML header text = re.sub(re.compile(r"# ---.*# ---\n\n", re.DOTALL), "", text) compare( text, """# region '''Sample cell with region markers''' '''End of the cell''' # end region # {{{ a = 1 b = 1 # }}} """, ) async def test_vscode_pycharm_folding_markers(tmpdir, cm): tmp_ipynb = str(tmpdir.join("nb.ipynb")) tmp_py = str(tmpdir.join("nb.py")) cm.root_dir = str(tmpdir) # Default VScode/PyCharm folding markers cm.cell_markers = "region,endregion" cm.formats = "ipynb,py:light" nb = new_notebook( cells=[ new_code_cell( """# {{{ '''Sample cell with region markers''' '''End of the cell''' # }}}""" ), new_code_cell("a = 1\n\n\nb = 1"), ] ) await ensure_async(cm.save(model=notebook_model(nb), path="nb.ipynb")) assert os.path.isfile(tmp_ipynb) assert os.path.isfile(tmp_py) nb2 = (await ensure_async(cm.get("nb.ipynb")))["content"] compare_notebooks(nb2, nb) nb3 = read(tmp_py) assert nb3.metadata["jupytext"]["cell_markers"] == "region,endregion" with open(tmp_py) as fp: text = fp.read() # Remove YAML header text = re.sub(re.compile(r"# ---.*# ---\n\n", re.DOTALL), "", text) compare( text, """# {{{ '''Sample cell with region markers''' '''End of the cell''' # }}} # region a = 1 b = 1 # endregion """, ) async def test_open_file_with_cell_markers(tmpdir, cm): tmp_py = str(tmpdir.join("nb.py")) cm.root_dir = str(tmpdir) # Default VScode/PyCharm folding markers cm.cell_markers = "region,endregion" text = """# + # this is a unique code cell 1 + 1 2 + 2 """ with open(tmp_py, "w") as fp: fp.write(text) nb = (await ensure_async(cm.get("nb.py")))["content"] assert len(nb.cells) == 1 await ensure_async(cm.save(model=notebook_model(nb), path="nb.py")) with open(tmp_py) as fp: text2 = fp.read() expected = """# region # this is a unique code cell 1 + 1 2 + 2 # endregion """ compare(text2, expected) async def test_save_file_with_cell_markers(tmpdir, cm): tmp_py = str(tmpdir.join("nb.py")) cm.root_dir = str(tmpdir) # Default VScode/PyCharm folding markers cm.cell_markers = "region,endregion" text = """# + # this is a unique code cell 1 + 1 2 + 2 """ with open(tmp_py, "w") as fp: fp.write(text) nb = (await ensure_async(cm.get("nb.py")))["content"] assert len(nb.cells) == 1 await ensure_async(cm.save(model=notebook_model(nb), path="nb.py")) with open(tmp_py) as fp: text2 = fp.read() compare( text2, """# region # this is a unique code cell 1 + 1 2 + 2 # endregion """, ) nb2 = (await ensure_async(cm.get("nb.py")))["content"] compare_notebooks(nb2, nb) assert nb2.metadata["jupytext"]["cell_markers"] == "region,endregion" async def test_notebook_extensions(tmpdir, cm, cwd_tmpdir): nb = new_notebook() write(nb, "script.py") write(nb, "notebook.Rmd") write(nb, "notebook.ipynb") cm.root_dir = str(tmpdir) cm.notebook_extensions = "ipynb,Rmd" model = await ensure_async(cm.get("notebook.ipynb")) assert model["type"] == "notebook" model = await ensure_async(cm.get("notebook.Rmd")) assert model["type"] == "notebook" model = await ensure_async(cm.get("script.py")) assert model["type"] == "file" async def test_notebook_extensions_in_config(tmpdir, cm, cwd_tmpdir): nb = new_notebook() write(nb, "script.py") write(nb, "notebook.Rmd") write(nb, "notebook.ipynb") tmpdir.join("jupytext.toml").write("""notebook_extensions = ["ipynb", "Rmd"]""") cm.root_dir = str(tmpdir) model = await ensure_async(cm.get("notebook.ipynb")) assert model["type"] == "notebook" model = await ensure_async(cm.get("notebook.Rmd")) assert model["type"] == "notebook" model = await ensure_async(cm.get("script.py")) assert model["type"] == "file" async def test_invalid_config_in_cm(tmpdir, cm, cwd_tmpdir): nb = new_notebook() write(nb, "notebook.ipynb") tmpdir.join("pyproject.toml").write( """[tool.jupysql.SqlMagic] autopandas = False displaylimit = 1""" ) cm.root_dir = str(tmpdir) # list directory await ensure_async(cm.get("")) model = await ensure_async(cm.get("notebook.ipynb")) assert model["type"] == "notebook" async def test_download_file_318(tmpdir, cm): tmp_ipynb = str(tmpdir.join("notebook.ipynb")) tmp_py = str(tmpdir.join("notebook.py")) nb = new_notebook() nb.metadata["jupytext"] = {"formats": "ipynb,py"} write(nb, tmp_ipynb) write(nb, tmp_py) cm.root_dir = str(tmpdir) cm.notebook_extensions = "ipynb" model = await ensure_async(cm.get("notebook.ipynb", content=True, type=None, format=None)) assert model["type"] == "notebook" async def test_markdown_and_r_extensions(tmpdir, cm): tmp_r = str(tmpdir.join("script.r")) tmp_markdown = str(tmpdir.join("notebook.markdown")) nb = new_notebook() write(nb, tmp_r) write(nb, tmp_markdown) cm.root_dir = str(tmpdir) model = await ensure_async(cm.get("script.r")) assert model["type"] == "notebook" model = await ensure_async(cm.get("notebook.markdown")) assert model["type"] == "notebook" async def test_server_extension_issubclass(cm): class SubClassTextFileContentsManager(jupytext.TextFileContentsManager): pass assert not isinstance(SubClassTextFileContentsManager, jupytext.TextFileContentsManager) assert issubclass(SubClassTextFileContentsManager, jupytext.TextFileContentsManager) async def test_multiple_pairing(tmpdir, cm): """Test that multiple pairing works. Input cells are loaded from the most recent text representation among the paired ones""" tmp_ipynb = str(tmpdir.join("notebook.ipynb")) tmp_md = str(tmpdir.join("notebook.md")) tmp_py = str(tmpdir.join("notebook.py")) def nb(text): return new_notebook( cells=[new_markdown_cell(text)], metadata={"jupytext": {"formats": "ipynb,md,py"}}, ) cm.root_dir = str(tmpdir) await ensure_async(cm.save(model=notebook_model(nb("saved from cm")), path="notebook.ipynb")) compare_notebooks(jupytext.read(tmp_ipynb), nb("saved from cm")) compare_notebooks(jupytext.read(tmp_md), nb("saved from cm")) compare_notebooks(jupytext.read(tmp_py), nb("saved from cm")) jupytext.write(nb("md edited"), tmp_md) model = await ensure_async(cm.get("notebook.ipynb")) compare_notebooks(model["content"], nb("md edited")) await ensure_async(cm.save(model=model, path="notebook.ipynb")) compare_notebooks(jupytext.read(tmp_ipynb), nb("md edited")) compare_notebooks(jupytext.read(tmp_md), nb("md edited")) compare_notebooks(jupytext.read(tmp_py), nb("md edited")) jupytext.write(nb("py edited"), tmp_py) # Loading the md file give the content of that file model = await ensure_async(cm.get("notebook.md")) compare_notebooks(model["content"], nb("md edited")) # Loading the ipynb files gives the content of the most recent text file model = await ensure_async(cm.get("notebook.ipynb")) compare_notebooks(model["content"], nb("py edited")) await ensure_async(cm.save(model=model, path="notebook.ipynb")) compare_notebooks(jupytext.read(tmp_ipynb), nb("py edited")) compare_notebooks(jupytext.read(tmp_md), nb("py edited")) compare_notebooks(jupytext.read(tmp_py), nb("py edited")) model_ipynb = await ensure_async(cm.get("notebook.ipynb", content=False, load_alternative_format=False)) model_md = await ensure_async(cm.get("notebook.md", content=False, load_alternative_format=False)) model_py = await ensure_async(cm.get("notebook.py", content=False, load_alternative_format=False)) # ipynb is the oldest one, then py, then md # so that we read cell inputs from the py file assert model_ipynb["last_modified"] <= model_py["last_modified"] assert model_py["last_modified"] <= model_md["last_modified"] async def test_filter_jupytext_version_information_416(python_notebook, cm, tmpdir, cwd_tmpdir): cm.root_dir = str(tmpdir) cm.notebook_metadata_filter = "-jupytext.text_representation.jupytext_version" # load notebook notebook = python_notebook notebook.metadata["jupytext_formats"] = "ipynb,py" model = notebook_model(notebook) # save to ipynb and py await ensure_async(cm.save(model=model, path="notebook.ipynb")) assert os.path.isfile("notebook.py") # read py file with open("notebook.py") as fp: text = fp.read() assert "---" in text assert "jupytext:" in text assert "kernelspec:" in text assert "jupytext_version:" not in text @pytest.mark.requires_myst async def test_new_untitled(tmpdir, cm): cm.root_dir = str(tmpdir) # untitled is "Untitled" only when the locale is English #636 untitled, ext = (await ensure_async(cm.new_untitled(type="notebook")))["path"].split(".") assert untitled assert ext == "ipynb" # Jupytext related files assert (await ensure_async(cm.new_untitled(type="notebook", ext=".md")))["path"] == untitled + "1.md" assert (await ensure_async(cm.new_untitled(type="notebook", ext=".py")))["path"] == untitled + "2.py" assert (await ensure_async(cm.new_untitled(type="notebook", ext=".md:myst")))["path"] == untitled + "3.md" assert (await ensure_async(cm.new_untitled(type="notebook", ext=".py:percent")))["path"] == untitled + "4.py" assert (await ensure_async(cm.new_untitled(type="notebook", ext=".Rmd")))["path"] == untitled + "5.Rmd" # Test native formats that should not be changed by Jupytext and model should # not contain any Jupytext metadata neither file name should start with Uppercase for ext in [".py", ".md"]: model = await ensure_async(cm.new_untitled(type="file", ext=ext)) assert model["content"] is None assert model["path"] == f"untitled{ext}" assert (await ensure_async(cm.new_untitled(type="directory")))["path"] == "Untitled Folder" async def test_nested_prefix(tmpdir, cm): cm.root_dir = str(tmpdir) # save to ipynb and py nb = new_notebook( cells=[new_code_cell("1+1"), new_markdown_cell("Some text")], metadata={"jupytext": {"formats": "ipynb,nested/prefix//.py"}}, ) await ensure_async(cm.save(model=notebook_model(nb), path="notebook.ipynb")) assert tmpdir.join("nested").join("prefix").join("notebook.py").isfile() async def test_timestamp_is_correct_after_reload_978(tmp_path, cm, python_notebook): """Here we reproduce the conditions in Issue #978 and make sure no warning is generated""" nb = python_notebook nb.metadata["jupytext"] = {"formats": "ipynb,py:percent"} cm.root_dir = str(tmp_path) ipynb_py_R_jl_file = tmp_path / "nb.ipynb" py_file = tmp_path / "nb.py" # 1. Save the paired notebook await ensure_async(cm.save(notebook_model(nb), path="nb.ipynb")) assert ipynb_py_R_jl_file.exists() assert py_file.exists() # and reload to get the original timestamp org_model = await ensure_async(cm.get("nb.ipynb")) # 2. Edit the py file time.sleep(0.5) text = py_file.read_text() text = ( text + """ # %% # A new cell 2 + 2 """ ) py_file.write_text(text) # 3. Reload the paired notebook and make sure it has the modified content model = await ensure_async(cm.get("nb.ipynb")) nb = model["content"] assert "A new cell" in nb.cells[-1].source assert model["last_modified"] > org_model["last_modified"] async def test_move_paired_notebook_to_subdir_1059(tmp_path, cm, python_notebook): (tmp_path / "jupytext.toml").write_text('formats = "notebooks///ipynb,scripts///py:percent"\n') cm.root_dir = str(tmp_path) # create paired notebook (tmp_path / "notebooks").mkdir() await ensure_async(cm.save(notebook_model(python_notebook), path="notebooks/my_notebook.ipynb")) assert (tmp_path / "notebooks" / "my_notebook.ipynb").exists() assert (tmp_path / "scripts" / "my_notebook.py").exists() # move notebook (tmp_path / "notebooks" / "subdir").mkdir() await ensure_async(cm.rename_file("notebooks/my_notebook.ipynb", "notebooks/subdir/my_notebook.ipynb")) assert (tmp_path / "notebooks" / "subdir" / "my_notebook.ipynb").exists() assert (tmp_path / "scripts" / "subdir" / "my_notebook.py").exists() assert not (tmp_path / "notebooks" / "my_notebook.ipynb").exists() assert not (tmp_path / "scripts" / "my_notebook.py").exists() # check notebook content model = await ensure_async(cm.get("scripts/subdir/my_notebook.py")) nb = model["content"] compare_notebooks(nb, python_notebook, fmt="py:percent") def list_folder_contents(tmp_path): return [ str(file_path.relative_to(tmp_path)) for file_path in (tmp_path).rglob("*") if file_path.is_file() and ".ipynb_checkpoints" not in file_path.parts ] @pytest.mark.parametrize("copy", [False, True]) @pytest.mark.parametrize("config_file", [False, True]) async def test_move_paired_notebook_outside_of_notebook_dir_1414(tmp_path, cm, python_notebook, copy: bool, config_file: bool): cm.root_dir = str(tmp_path) nb = python_notebook if config_file: (tmp_path / "jupytext.toml").write_text('formats = "notebooks///ipynb,scripts///py:percent"\n') else: nb.metadata["jupytext"] = {"formats": ["notebooks///ipynb", "scripts///py:percent"]} # create paired notebook (tmp_path / "notebooks").mkdir() await ensure_async(cm.save(notebook_model(python_notebook), path="notebooks/my_notebook.ipynb")) assert (tmp_path / "notebooks" / "my_notebook.ipynb").exists() assert (tmp_path / "scripts" / "my_notebook.py").exists() folder_contents = list_folder_contents(tmp_path) assert len(folder_contents) == 2 + config_file, folder_contents # move notebook still within the config reach, but outside the notebooks folder if copy: await ensure_async(cm.copy("notebooks/my_notebook.ipynb", "my_notebook.ipynb")) else: await ensure_async(cm.rename_file("notebooks/my_notebook.ipynb", "my_notebook.ipynb")) assert (tmp_path / "notebooks" / "my_notebook.ipynb").exists() == copy assert (tmp_path / "scripts" / "my_notebook.py").exists() assert (tmp_path / "my_notebook.ipynb").exists() folder_contents = list_folder_contents(tmp_path) assert len(folder_contents) == 2 + copy + config_file, folder_contents # Open and save the notebook - this should create no additional file model = await ensure_async(cm.get("my_notebook.ipynb")) await ensure_async(cm.save(model=model, path="my_notebook.ipynb")) folder_contents = list_folder_contents(tmp_path) assert len(folder_contents) == 2 + copy + config_file, folder_contents async def test_move_paired_notebook_outside_of_pairing_config_1414(tmp_path, cm, python_notebook): (tmp_path / "within_config").mkdir() (tmp_path / "within_config" / "jupytext.toml").write_text('formats = "notebooks///ipynb,scripts///py:percent"\n') cm.root_dir = str(tmp_path) # create paired notebook (tmp_path / "within_config" / "notebooks").mkdir() await ensure_async( cm.save( notebook_model(python_notebook), path="within_config/notebooks/my_notebook.ipynb", ) ) assert (tmp_path / "within_config" / "notebooks" / "my_notebook.ipynb").exists() assert (tmp_path / "within_config" / "scripts" / "my_notebook.py").exists() folder_contents = list_folder_contents(tmp_path) assert len(folder_contents) == 3, folder_contents # move notebook still within the config reach, but outside the notebooks folder (tmp_path / "other").mkdir() await ensure_async(cm.rename_file("within_config/notebooks/my_notebook.ipynb", "other/my_notebook.ipynb")) assert not (tmp_path / "within_config" / "notebooks" / "my_notebook.ipynb").exists() assert (tmp_path / "other" / "my_notebook.ipynb").exists() assert (tmp_path / "within_config" / "scripts" / "my_notebook.py").exists() folder_contents = list_folder_contents(tmp_path) assert len(folder_contents) == 3, folder_contents # Open and save the notebook - this should create no additional file model = await ensure_async(cm.get("other/my_notebook.ipynb")) await ensure_async(cm.save(model=model, path="other/my_notebook.ipynb")) assert not (tmp_path / "within_config" / "notebooks" / "my_notebook.ipynb").exists() assert (tmp_path / "other" / "my_notebook.ipynb").exists() assert (tmp_path / "within_config" / "scripts" / "my_notebook.py").exists() folder_contents = list_folder_contents(tmp_path) assert len(folder_contents) == 3, folder_contents async def test_hash_changes_if_paired_file_is_edited(tmp_path, cm, python_notebook): # 1. write py ipynb if "require_hash" not in inspect.signature(cm.get).parameters: pytest.skip(reason="This JupytextContentsManager does not have a 'require_hash' parameter in cm.get") cm.formats = "ipynb,py:percent" cm.root_dir = str(tmp_path) # save ipynb nb = python_notebook nb_name = "notebook.ipynb" await ensure_async(cm.save(model=notebook_model(nb), path=nb_name)) org_model = await ensure_async(cm.get(nb_name, require_hash=True)) py_file = tmp_path / "notebook.py" text = py_file.read_text() assert "# %% [markdown]" in text.splitlines(), text # modify the timestamp of the paired file time.sleep(0.5) py_file.write_text(text) model = await ensure_async(cm.get(nb_name, require_hash=True)) # not sure why the hash changes on Windows? assert (model["hash"] == org_model["hash"]) or (os.name == "nt") # modify the paired file py_file.write_text(text + "\n# %%\n1 + 1\n") new_model = await ensure_async(cm.get(nb_name, require_hash=True)) assert new_model["hash"] != org_model["hash"] # the hash is for the pair (inputs first) model_from_py_file = await ensure_async(cm.get("notebook.py", require_hash=True)) assert model_from_py_file["hash"] == new_model["hash"] @pytest.mark.requires_myst async def test_metadata_stays_in_order_1368( tmp_path, cm, md="""--- jupytext: formats: md:myst notebook_metadata_filter: -jupytext.text_representation.jupytext_version text_representation: extension: .md format_name: myst format_version: 0.13 kernelspec: display_name: itables language: python name: itables --- A markdown cell """, ): cm.root_dir = str(tmp_path) (tmp_path / "nb.md").write_text(md) model = await ensure_async(cm.get(path="nb.md")) assert list(model["content"]["metadata"].keys()) == [ "jupytext", "kernelspec", ], "order must be preserved" await ensure_async(cm.save(model=model, path="nb.md")) compare((tmp_path / "nb.md").read_text(), md) @pytest.mark.requires_myst async def test_jupytext_orders_root_metadata( tmp_path, cm, md="""--- title: Quick test jupytext: formats: md:myst notebook_metadata_filter: -jupytext.text_representation.jupytext_version root_level_metadata_filter: -title text_representation: extension: .md format_name: myst format_version: 0.13 kernelspec: display_name: itables language: python name: itables --- A markdown cell """, ): cm.root_dir = str(tmp_path) (tmp_path / "nb.md").write_text(md) model = await ensure_async(cm.get(path="nb.md")) assert list(model["content"]["metadata"].keys()) == [ "jupytext", "kernelspec", ], "order must be preserved" # simulate jupyter changing the order of the metadata model["content"]["metadata"]["jupytext"] = model["content"]["metadata"].pop("jupytext") assert list(model["content"]["metadata"].keys()) == ["kernelspec", "jupytext"] await ensure_async(cm.save(model=model, path="nb.md")) compare((tmp_path / "nb.md").read_text(), md) @pytest.mark.parametrize("with_config", [False, True]) async def test_load_save_keeps_simple_python_file_unchanged(tmp_path, cm, with_config: bool): """Test that jupytext --sync on a simple Python file leaves it unchanged, even if a Jupytext configuration has formats=ipynb,py:percent """ cm.root_dir = str(tmp_path) if with_config: config_file = tmp_path / "jupytext.toml" config_file.write_text('formats = "ipynb,py:percent"') # Create a simple Python file without jupytext metadata py_file = tmp_path / "simple.py" py_content = '''#!/usr/bin/env python3 """A simple Python script""" def hello(): print("Hello, world!") if __name__ == "__main__": hello() ''' py_file.write_text(py_content) # Record original content original_content = py_file.read_text() # Open and save the file using our contents manager model = await ensure_async(cm.get(path="simple.py")) await ensure_async(cm.save(model=model, path="simple.py")) # Verify file is unchanged final_content = py_file.read_text() assert final_content == original_content, "File content should be unchanged" # Verify no additional files were created files_in_dir = list(tmp_path.iterdir()) if with_config: assert len(files_in_dir) == 2, f"Expected only 2 files, found: {[f.name for f in files_in_dir]}" assert set(files_in_dir) == {py_file, config_file} else: assert len(files_in_dir) == 1, f"Expected only 1 file, found: {[f.name for f in files_in_dir]}" assert files_in_dir[0] == py_file async def test_pairing_groups_in_contents_manager(tmp_path, cm, python_notebook): cm.root_dir = str(tmp_path) # With config file using list-based formats (tmp_path / "jupytext.toml").write_text( """ # Tutorial notebooks get paired to markdown docs [[formats]] "notebooks/tutorials/" = "ipynb" "docs/" = "md" # Main pairing: all other notebooks are paired with Python scripts [[formats]] "" = "ipynb,py:percent" """ ) cm = jupytext.TextFileContentsManager() cm.root_dir = str(tmp_path) (tmp_path / "notebooks").mkdir() await ensure_async(cm.save(model=notebook_model(python_notebook), path="notebooks/notebook.ipynb")) assert (tmp_path / "notebooks" / "notebook.ipynb").exists() assert (tmp_path / "notebooks" / "notebook.py").exists() assert not (tmp_path / "docs" / "notebook.md").exists() # A notebook under 'tutorials' is paired to md in the docs folder (tmp_path / "notebooks" / "tutorials").mkdir() await ensure_async(cm.save(model=notebook_model(python_notebook), path="notebooks/tutorials/notebook.ipynb")) assert (tmp_path / "notebooks" / "tutorials" / "notebook.ipynb").exists() assert not (tmp_path / "notebooks" / "tutorials" / "notebook.py").exists() assert (tmp_path / "docs" / "notebook.md").exists() ================================================ FILE: tests/integration/contents_manager/test_load_multiple.py ================================================ import pytest from jupyter_server.utils import ensure_async from nbformat.v4.nbbase import new_notebook from tornado.web import HTTPError import jupytext @pytest.mark.asyncio async def test_combine_same_version_ok(tmpdir, cm): tmp_ipynb = "notebook.ipynb" tmp_nbpy = "notebook.py" with open(str(tmpdir.join(tmp_nbpy)), "w") as fp: fp.write( """# --- # jupyter: # jupytext_formats: ipynb,py # jupytext_format_version: '1.2' # --- # New cell """ ) nb = new_notebook(metadata={"jupytext_formats": "ipynb,py"}) jupytext.write(nb, str(tmpdir.join(tmp_ipynb))) cm.formats = "ipynb,py" cm.root_dir = str(tmpdir) nb = await ensure_async(cm.get(tmp_ipynb)) cells = nb["content"]["cells"] assert len(cells) == 1 assert cells[0].cell_type == "markdown" assert cells[0].source == "New cell" @pytest.mark.asyncio async def test_combine_lower_version_raises(tmpdir, cm): tmp_ipynb = "notebook.ipynb" tmp_nbpy = "notebook.py" with open(str(tmpdir.join(tmp_nbpy)), "w") as fp: fp.write( """# --- # jupyter: # jupytext_formats: ipynb,py # jupytext_format_version: '0.0' # --- # New cell """ ) nb = new_notebook(metadata={"jupytext_formats": "ipynb,py"}) jupytext.write(nb, str(tmpdir.join(tmp_ipynb))) cm.formats = "ipynb,py" cm.root_dir = str(tmpdir) with pytest.raises(HTTPError): await ensure_async(cm.get(tmp_ipynb)) ================================================ FILE: tests/integration/jupytext_config/test_jupytext_config.py ================================================ from jupytext.cli import system def test_jupytext_config_cli(tmp_path): settings_file = tmp_path / "default_setting_overrides.json" system("jupytext-config", "-h") system( "jupytext-config", "--settings-file", str(settings_file), "set-default-viewer", "python", "markdown", ) assert "python" in (settings_file).read_text() assert "markdown" in system("jupytext-config", "--settings-file", settings_file, "list-default-viewer") system( "jupytext-config", "--settings-file", str(settings_file), "unset-default-viewer", "markdown", ) list_viewers = system("jupytext-config", "--settings-file", settings_file, "list-default-viewer") assert "python" in list_viewers assert "markdown" not in list_viewers ================================================ FILE: tests/unit/test_cell_id.py ================================================ from nbformat.v4.nbbase import new_code_cell, new_markdown_cell, new_raw_cell def test_cell_id_is_not_random(): assert new_code_cell().id == "cell-1" assert new_code_cell().id == "cell-2" assert new_markdown_cell().id == "cell-3" assert new_raw_cell().id == "cell-4" ================================================ FILE: tests/unit/test_compare.py ================================================ import pytest from nbformat.v4.nbbase import ( new_code_cell, new_markdown_cell, new_notebook, new_raw_cell, ) from jupytext.compare import ( NotebookDifference, compare, compare_cells, compare_notebooks, ) from jupytext.compare import test_round_trip_conversion as round_trip_conversion def notebook_metadata(): return { "kernelspec": { "display_name": "Python 3", "language": "python", "name": "python3", }, "language_info": { "codemirror_mode": {"name": "ipython", "version": 3}, "file_extension": ".py", "mimetype": "text/x-python", "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", "version": "3.7.3", }, "toc": { "base_numbering": 1, "nav_menu": {}, "number_sections": True, "sideBar": True, "skip_h1_title": False, "title_cell": "Table of Contents", "title_sidebar": "Contents", "toc_cell": False, "toc_position": {}, "toc_section_display": True, "toc_window_display": False, }, } @pytest.fixture() def notebook_expected(): return new_notebook( metadata=notebook_metadata(), cells=[ new_markdown_cell("First markdown cell", id="markdown-cell-one"), new_code_cell("1 + 1", id="code-cell-one"), new_markdown_cell("Second markdown cell", id="markdown-cell-two"), ], ) @pytest.fixture() def notebook_actual(): metadata = notebook_metadata() metadata["language_info"]["version"] = "3.6.8" return new_notebook( metadata=metadata, cells=[ new_markdown_cell("First markdown cell", id="markdown-cell-one"), new_code_cell("1 + 1", id="code-cell-one"), new_markdown_cell("Modified markdown cell", id="markdown-cell-two"), ], ) def test_compare_on_notebooks(notebook_actual, notebook_expected): with pytest.raises(AssertionError) as err: compare(notebook_actual, notebook_expected) assert ( str(err.value) == """ --- expected +++ actual @@ -18,7 +18,7 @@ "cell_type": "markdown", "id": "markdown-cell-two", "metadata": {}, - "source": "Second markdown cell" + "source": "Modified markdown cell" } ], "metadata": { @@ -37,7 +37,7 @@ "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", - "version": "3.7.3" + "version": "3.6.8" }, "toc": { "base_numbering": 1,""" ) def test_raise_on_different_metadata(): ref = new_notebook( metadata={ "kernelspec": { "language": "python", "name": "python", "display_name": "Python", } }, cells=[new_markdown_cell("Cell one")], ) test = new_notebook( metadata={"kernelspec": {"language": "R", "name": "R", "display_name": "R"}}, cells=[new_markdown_cell("Cell one")], ) with pytest.raises(NotebookDifference): compare_notebooks(test, ref, "md") @pytest.mark.parametrize("raise_on_first_difference", [True, False]) def test_raise_on_different_cell_type(raise_on_first_difference): ref = new_notebook(cells=[new_markdown_cell("Cell one"), new_code_cell("Cell two")]) test = new_notebook(cells=[new_markdown_cell("Cell one"), new_raw_cell("Cell two")]) with pytest.raises(NotebookDifference): compare_notebooks(test, ref, "md", raise_on_first_difference=raise_on_first_difference) @pytest.mark.parametrize("raise_on_first_difference", [True, False]) def test_raise_on_different_cell_content(raise_on_first_difference): ref = new_notebook(cells=[new_markdown_cell("Cell one"), new_code_cell("Cell two")]) test = new_notebook(cells=[new_markdown_cell("Cell one"), new_code_cell("Modified cell two")]) with pytest.raises(NotebookDifference): compare_notebooks(test, ref, "md", raise_on_first_difference=raise_on_first_difference) def test_raise_on_incomplete_markdown_cell(): ref = new_notebook(cells=[new_markdown_cell("Cell one\n\n\nsecond line")]) test = new_notebook(cells=[new_markdown_cell("Cell one")]) with pytest.raises(NotebookDifference): compare_notebooks(test, ref, "md") def test_does_raise_on_split_markdown_cell(): ref = new_notebook(cells=[new_markdown_cell("Cell one\n\n\nsecond line")]) test = new_notebook(cells=[new_markdown_cell("Cell one"), new_markdown_cell("second line")]) with pytest.raises(NotebookDifference): compare_notebooks(test, ref, "md") def test_raise_on_different_cell_metadata(): ref = new_notebook(cells=[new_code_cell("1+1")]) test = new_notebook(cells=[new_code_cell("1+1", metadata={"metakey": "value"})]) with pytest.raises(NotebookDifference): compare_notebooks(test, ref, "py:light") @pytest.mark.parametrize("raise_on_first_difference", [True, False]) def test_raise_on_different_cell_count(raise_on_first_difference): ref = new_notebook(cells=[new_code_cell("1")]) test = new_notebook(cells=[new_code_cell("1"), new_code_cell("2")]) with pytest.raises(NotebookDifference): compare_notebooks(test, ref, "py:light", raise_on_first_difference=raise_on_first_difference) with pytest.raises(NotebookDifference): compare_notebooks(ref, test, "py:light", raise_on_first_difference=raise_on_first_difference) def test_does_not_raise_on_blank_line_removed(): ref = new_notebook(cells=[new_code_cell("1+1\n ")]) test = new_notebook(cells=[new_code_cell("1+1")]) compare_notebooks(test, ref, "py:light") def test_strict_raise_on_blank_line_removed(): ref = new_notebook(cells=[new_code_cell("1+1\n")]) test = new_notebook(cells=[new_code_cell("1+1")]) with pytest.raises(NotebookDifference): compare_notebooks(test, ref, "py:light", allow_expected_differences=False) def test_dont_raise_on_different_outputs(): ref = new_notebook(cells=[new_code_cell("1+1")]) test = new_notebook( cells=[ new_code_cell( "1+1", outputs=[ { "data": {"text/plain": ["2"]}, "execution_count": 1, "metadata": {}, "output_type": "execute_result", } ], ) ] ) compare_notebooks(test, ref, "md") @pytest.mark.parametrize("raise_on_first_difference", [True, False]) def test_raise_on_different_outputs(raise_on_first_difference): ref = new_notebook(cells=[new_code_cell("1+1")]) test = new_notebook( cells=[ new_code_cell( "1+1", outputs=[ { "data": {"text/plain": ["2"]}, "execution_count": 1, "metadata": {}, "output_type": "execute_result", } ], ) ] ) with pytest.raises(NotebookDifference): compare_notebooks( test, ref, "md", raise_on_first_difference=raise_on_first_difference, compare_outputs=True, ) def test_test_round_trip_conversion(): notebook = new_notebook( cells=[ new_code_cell( "1+1", outputs=[ { "data": {"text/plain": ["2"]}, "execution_count": 1, "metadata": {}, "output_type": "execute_result", } ], ) ], metadata={"main_language": "python"}, ) round_trip_conversion(notebook, {"extension": ".py"}, update=True) def test_mutiple_cells_differ(): nb1 = new_notebook(cells=[new_code_cell(""), new_code_cell("2")]) nb2 = new_notebook(cells=[new_code_cell("1+1"), new_code_cell("2\n2")]) with pytest.raises(NotebookDifference) as exception_info: compare_notebooks(nb2, nb1, raise_on_first_difference=False) assert "Cells 1,2 differ" in exception_info.value.args[0] def test_cell_metadata_differ(): nb1 = new_notebook( cells=[ new_code_cell("1"), new_code_cell("2", metadata={"additional": "metadata1"}), ] ) nb2 = new_notebook( cells=[ new_code_cell("1"), new_code_cell("2", metadata={"additional": "metadata2"}), ] ) with pytest.raises(NotebookDifference) as exception_info: compare_notebooks(nb2, nb1, raise_on_first_difference=False) assert "Cell metadata 'additional' differ" in exception_info.value.args[0] def test_notebook_metadata_differ(): nb1 = new_notebook(cells=[new_code_cell("1"), new_code_cell("2")]) nb2 = new_notebook( cells=[new_code_cell("1"), new_code_cell("2")], metadata={ "kernelspec": { "language": "python", "name": "python", "display_name": "Python", } }, ) with pytest.raises(NotebookDifference) as exception_info: compare_notebooks(nb2, nb1, raise_on_first_difference=False) assert "Notebook metadata differ" in exception_info.value.args[0] def test_cell_ids_differ(): with pytest.raises(NotebookDifference, match="'id-one' != 'id-two'"): compare_cells([new_code_cell("1", id="id-one")], [new_code_cell("1", id="id-two")]) ================================================ FILE: tests/unit/test_escape_magics.py ================================================ import pytest from jupyter_server.utils import ensure_async from nbformat.v4.nbbase import new_code_cell, new_notebook import jupytext from jupytext.compare import compare, compare_notebooks, notebook_model from jupytext.magics import ( _PYTHON_MAGIC_ASSIGN, comment_magic, is_magic, uncomment_magic, unesc, ) def test_unesc(): assert unesc("# comment", "python") == "comment" assert unesc("#comment", "python") == "comment" assert unesc("comment", "python") == "comment" @pytest.mark.parametrize( "line", [ "%matplotlib inline", "#%matplotlib inline", "##%matplotlib inline", "%%HTML", "%autoreload", "%store", ], ) def test_escape(line): assert comment_magic([line]) == ["# " + line] assert uncomment_magic(comment_magic([line])) == [line] @pytest.mark.parametrize("line", ["@pytest.fixture"]) def test_escape_magic_only(line): assert comment_magic([line]) == [line] @pytest.mark.parametrize("line", ["%matplotlib inline #noescape"]) def test_force_noescape(line): assert comment_magic([line]) == [line] @pytest.mark.parametrize("line", ["%matplotlib inline #noescape"]) def test_force_noescape_with_gbl_esc_flag(line): assert comment_magic([line], global_escape_flag=True) == [line] @pytest.mark.parametrize("line", ["%matplotlib inline #escape"]) def test_force_escape_with_gbl_esc_flag(line): assert comment_magic([line], global_escape_flag=False) == ["# " + line] @pytest.mark.parametrize( "fmt,commented", zip( [ "md", "Rmd", "py:light", "py:percent", "py:sphinx", "R", "ss:light", "ss:percent", ], [False, True, True, True, True, True, True, True], ), ) def test_magics_commented_default(fmt, commented): nb = new_notebook(cells=[new_code_cell("%pylab inline")]) text = jupytext.writes(nb, fmt) assert ("%pylab inline" in text.splitlines()) != commented nb2 = jupytext.reads(text, fmt) if "sphinx" in fmt: nb2.cells = nb2.cells[1:] compare_notebooks(nb2, nb) @pytest.mark.parametrize( "fmt", ["md", "Rmd", "py:light", "py:percent", "py:sphinx", "R", "ss:light", "ss:percent"], ) def test_magics_are_commented(fmt): nb = new_notebook( cells=[new_code_cell("%pylab inline")], metadata={ "jupytext": { "comment_magics": True, "main_language": ("R" if fmt == "R" else "scheme" if fmt.startswith("ss") else "python"), } }, ) text = jupytext.writes(nb, fmt) assert "%pylab inline" not in text.splitlines() nb2 = jupytext.reads(text, fmt) if "sphinx" in fmt: nb2.cells = nb2.cells[1:] compare_notebooks(nb2, nb) @pytest.mark.parametrize( "fmt", ["md", "Rmd", "py:light", "py:percent", "py:sphinx", "R", "ss:light", "ss:percent"], ) def test_magics_are_not_commented(fmt): nb = new_notebook( cells=[new_code_cell("%pylab inline")], metadata={ "jupytext": { "comment_magics": False, "main_language": ("R" if fmt == "R" else "scheme" if fmt.startswith("ss") else "python"), } }, ) text = jupytext.writes(nb, fmt) assert "%pylab inline" in text.splitlines() nb2 = jupytext.reads(text, fmt) if "sphinx" in fmt: nb2.cells = nb2.cells[1:] compare_notebooks(nb2, nb) @pytest.mark.asyncio async def test_force_comment_using_contents_manager(tmpdir, cm): tmp_py = "notebook.py" cm.preferred_jupytext_formats_save = "py:percent" cm.root_dir = str(tmpdir) nb = new_notebook(cells=[new_code_cell("%pylab inline")]) await ensure_async(cm.save(model=notebook_model(nb), path=tmp_py)) with open(str(tmpdir.join(tmp_py))) as stream: assert "# %pylab inline" in stream.read().splitlines() cm.comment_magics = False await ensure_async(cm.save(model=notebook_model(nb), path=tmp_py)) with open(str(tmpdir.join(tmp_py))) as stream: assert "%pylab inline" in stream.read().splitlines() @pytest.mark.parametrize( "magic_cmd", [ "ls", "!ls", "ls -al", "!whoami", "# ls", "# mv a b", "! mkdir tmp", "!./script", "! ./script", "!./script args", "!./script.sh args", "! ./script.sh args", "!~/script.sh args", "! ~/script.sh args", "!../script.sh $ENV $USER", "! ../script.sh $ENV $USER", "!$HOME/script.sh $ENV $USER", "!/bin/sh $ENV $USER", "! /bin/sh $ENV $USER", r"! \bin\sh $ENV $USER", r"!\bin\sh $ENV $USER", "cat", "cat ", "cat hello.txt", "cat --option=value hello.txt", "!{x}", ], ) def test_comment_bash_commands_in_python(magic_cmd): assert comment_magic([magic_cmd]) == ["# " + magic_cmd] assert uncomment_magic(["# " + magic_cmd]) == [magic_cmd] @pytest.mark.parametrize( "not_magic_cmd", ["copy(a)", "copy.deepcopy", "cat = 3", "cat=5", "cat, other = 5,3", "cat(5)"], ) def test_do_not_comment_python_cmds(not_magic_cmd): assert comment_magic([not_magic_cmd]) == [not_magic_cmd] assert uncomment_magic([not_magic_cmd]) == [not_magic_cmd] @pytest.mark.parametrize("magic_cmd", ["ls", "!ls", "ls -al", "!whoami", "# ls", "# mv a b"]) def test_do_not_comment_bash_commands_in_R(magic_cmd): assert comment_magic([magic_cmd], language="R") == [magic_cmd] assert uncomment_magic([magic_cmd], language="R") == [magic_cmd] def test_markdown_image_is_not_magic(): assert is_magic("# !cmd", "python") assert not is_magic("# ![Image name](image.png", "python") def test_question_is_not_magic(): assert is_magic("float?", "python", explicitly_code=True) assert is_magic("# float?", "python", explicitly_code=True) assert not is_magic("# question: float?", "python", explicitly_code=True) def test_multiline_python_magic(no_jupytext_version_number): nb = new_notebook( cells=[ new_code_cell( """%load_ext watermark %watermark -u -n -t -z \\ -p jupytext -v def g(x): return x+1""" ) ] ) text = jupytext.writes(nb, "py:light") compare( text, """# + # %load_ext watermark # %watermark -u -n -t -z \\ # -p jupytext -v def g(x): return x+1 """, ) compare_notebooks(jupytext.reads(text, "py"), nb) def test_configure_magic(no_jupytext_version_number): nb = new_notebook( cells=[ new_code_cell( """%%configure -f \\ {"executorMemory": "3072M", "executorCores": 4, "numExecutors":10}""" ) ] ) text = jupytext.writes(nb, "py:light") compare( text, """# %%configure -f \\ # {"executorMemory": "3072M", "executorCores": 4, "numExecutors":10} """, ) compare_notebooks(jupytext.reads(text, "py"), nb) def test_indented_magic(): assert is_magic(" !rm file", "python") assert is_magic(" # !rm file", "python") assert is_magic(" %cd", "python") assert comment_magic([" !rm file"]) == [" # !rm file"] assert uncomment_magic([" # !rm file"]) == [" !rm file"] assert comment_magic([" %cd"]) == [" # %cd"] assert uncomment_magic([" # %cd"]) == [" %cd"] def test_magic_assign_781(): assert _PYTHON_MAGIC_ASSIGN.match("name = %magic") assert _PYTHON_MAGIC_ASSIGN.match("# name = %magic") assert not _PYTHON_MAGIC_ASSIGN.match("# not a name = %magic") assert not _PYTHON_MAGIC_ASSIGN.match("# 0name = %magic") assert is_magic("result = %sql SELECT * FROM quickdemo WHERE value > 25", "python") def test_magic_assign_816(): assert _PYTHON_MAGIC_ASSIGN.match("flake8_version = !flake8 --version") assert _PYTHON_MAGIC_ASSIGN.match("# flake8_version = !flake8 --version") assert _PYTHON_MAGIC_ASSIGN.match("name = %time 2+2") assert _PYTHON_MAGIC_ASSIGN.match("# name = %time 2+2") ================================================ FILE: tests/unit/test_formats.py ================================================ import pytest from jupyter_server.utils import ensure_async from nbformat.v4.nbbase import new_notebook import jupytext from jupytext.compare import compare from jupytext.formats import ( JupytextFormatError, divine_format, get_format_implementation, guess_format, long_form_multiple_formats, read_format_from_metadata, rearrange_jupytext_metadata, short_form_multiple_formats, update_jupytext_formats_metadata, validate_one_format, ) def test_guess_format_light(python_file): with open(python_file) as stream: assert guess_format(stream.read(), ext=".py")[0] == "light" def test_guess_format_percent(percent_file): with open(percent_file) as stream: assert guess_format(stream.read(), ext=".py")[0] == "percent" def test_guess_format_simple_percent( nb="""# %% print("hello world!") """, ): assert guess_format(nb, ext=".py")[0] == "percent" def test_guess_format_simple_percent_with_magic( nb="""# %% # %time print("hello world!") """, ): assert guess_format(nb, ext=".py")[0] == "percent" def test_guess_format_simple_hydrogen_with_magic( nb="""# %% %time print("hello world!") """, ): assert guess_format(nb, ext=".py")[0] == "hydrogen" def test_guess_format_sphinx(sphinx_file): with open(sphinx_file) as stream: assert guess_format(stream.read(), ext=".py")[0] == "sphinx" def test_guess_format_hydrogen(): text = """# %% cat hello.txt """ assert guess_format(text, ext=".py")[0] == "hydrogen" def test_divine_format(): assert divine_format('{"cells":[]}') == "ipynb" assert ( divine_format( """def f(x): x + 1""" ) == "py:light" ) assert ( divine_format( """# %% def f(x): x + 1 # %% def g(x): x + 2 """ ) == "py:percent" ) assert ( divine_format( """This is a markdown file with one code block ``` 1 + 1 ``` """ ) == "md" ) assert ( divine_format( """;; --- ;; jupyter: ;; jupytext: ;; text_representation: ;; extension: .ss ;; format_name: percent ;; ---""" ) == "ss:percent" ) def test_get_format_implementation(): assert get_format_implementation(".py").format_name == "light" assert get_format_implementation(".py", "percent").format_name == "percent" with pytest.raises(JupytextFormatError): get_format_implementation(".py", "wrong_format") def test_script_with_magics_not_percent( script="""# %%time 1 + 2""", ): assert guess_format(script, ".py")[0] == "light" def test_script_with_spyder_cell_is_percent( script="""#%% 1 + 2""", ): assert guess_format(script, ".py")[0] == "percent" def test_script_with_percent_cell_and_magic_is_hydrogen( script="""#%% %matplotlib inline """, ): assert guess_format(script, ".py")[0] == "hydrogen" def test_script_with_percent_cell_and_kernelspec( script="""# --- # jupyter: # kernelspec: # display_name: Python3 # language: python # name: python3 # --- # %% a = 1 """, ): assert guess_format(script, ".py")[0] == "percent" def test_script_with_spyder_cell_with_name_is_percent( script="""#%% cell name 1 + 2""", ): assert guess_format(script, ".py")[0] == "percent" def test_read_format_from_metadata( script="""--- jupyter: jupytext: formats: ipynb,pct.py:percent,lgt.py:light,spx.py:sphinx,md,Rmd text_representation: extension: .pct.py format_name: percent format_version: '1.1' jupytext_version: 0.8.0 ---""", ): assert read_format_from_metadata(script, ".Rmd") is None def test_update_jupytext_formats_metadata(): nb = new_notebook(metadata={"jupytext": {"formats": "py"}}) update_jupytext_formats_metadata(nb.metadata, "py:light") assert nb.metadata["jupytext"]["formats"] == "py:light" nb = new_notebook(metadata={"jupytext": {"formats": "ipynb,py"}}) update_jupytext_formats_metadata(nb.metadata, "py:light") assert nb.metadata["jupytext"]["formats"] == "ipynb,py:light" def test_decompress_formats(): assert long_form_multiple_formats("ipynb") == [{"extension": ".ipynb"}] assert long_form_multiple_formats("ipynb,md") == [ {"extension": ".ipynb"}, {"extension": ".md"}, ] assert long_form_multiple_formats("ipynb,py:light") == [ {"extension": ".ipynb"}, {"extension": ".py", "format_name": "light"}, ] assert long_form_multiple_formats(["ipynb", ".py:light"]) == [ {"extension": ".ipynb"}, {"extension": ".py", "format_name": "light"}, ] assert long_form_multiple_formats(".pct.py:percent") == [{"extension": ".py", "suffix": ".pct", "format_name": "percent"}] def test_compress_formats(): assert short_form_multiple_formats([{"extension": ".ipynb"}]) == "ipynb" assert short_form_multiple_formats("ipynb") == "ipynb" assert short_form_multiple_formats([{"extension": ".ipynb"}, {"extension": ".md"}]) == "ipynb,md" assert ( short_form_multiple_formats([{"extension": ".ipynb"}, {"extension": ".py", "format_name": "light"}]) == "ipynb,py:light" ) assert ( short_form_multiple_formats( [ {"extension": ".ipynb"}, {"extension": ".py", "format_name": "light"}, {"extension": ".md", "comment_magics": True}, ] ) == "ipynb,py:light,md" ) assert short_form_multiple_formats([{"extension": ".py", "suffix": ".pct", "format_name": "percent"}]) == ".pct.py:percent" def test_rearrange_jupytext_metadata(): metadata = {"nbrmd_formats": "ipynb,py"} rearrange_jupytext_metadata(metadata) compare(metadata, {"jupytext": {"formats": "ipynb,py"}}) metadata = {"jupytext_formats": "ipynb,py"} rearrange_jupytext_metadata(metadata) compare(metadata, {"jupytext": {"formats": "ipynb,py"}}) metadata = {"executable": "#!/bin/bash"} rearrange_jupytext_metadata(metadata) compare(metadata, {"jupytext": {"executable": "#!/bin/bash"}}) def test_rearrange_jupytext_metadata_metadata_filter(): metadata = { "jupytext": { "metadata_filter": { "notebook": {"additional": ["one", "two"], "excluded": "all"}, "cells": {"additional": "all", "excluded": ["three", "four"]}, } } } rearrange_jupytext_metadata(metadata) compare( metadata, { "jupytext": { "notebook_metadata_filter": "one,two,-all", "cell_metadata_filter": "all,-three,-four", } }, ) def test_rearrange_jupytext_metadata_add_dot_in_suffix(): metadata = { "jupytext": { "text_representation": {"jupytext_version": "0.8.6"}, "formats": "ipynb,pct.py,lgt.py", } } rearrange_jupytext_metadata(metadata) compare( metadata, { "jupytext": { "text_representation": {"jupytext_version": "0.8.6"}, "formats": "ipynb,.pct.py,.lgt.py", } }, ) def test_fix_139(): text = """# --- # jupyter: # jupytext: # metadata_filter: # cells: # additional: # - "lines_to_next_cell" # excluded: # - "all" # --- # + {"lines_to_next_cell": 2} 1 + 1 # - 1 + 1 """ nb = jupytext.reads(text, "py:light") text2 = jupytext.writes(nb, "py:light") assert "cell_metadata_filter: -all" in text2 assert "lines_to_next_cell" not in text2 def test_validate_one_format(): with pytest.raises(JupytextFormatError): validate_one_format("py:percent") with pytest.raises(JupytextFormatError): validate_one_format({"extension": "py", "format_name": "invalid"}) with pytest.raises(JupytextFormatError): validate_one_format({}) with pytest.raises(JupytextFormatError): validate_one_format({"extension": ".py", "unknown_option": True}) with pytest.raises(JupytextFormatError): validate_one_format({"extension": ".py", "comment_magics": "TRUE"}) def test_set_auto_ext(): with pytest.raises(ValueError): long_form_multiple_formats("ipynb,auto:percent", {}) @pytest.mark.requires_pandoc def test_pandoc_format_is_preserved(): formats_org = "ipynb,md,.pandoc.md:pandoc,py:light" long = long_form_multiple_formats(formats_org) formats_new = short_form_multiple_formats(long) compare(formats_new, formats_org) @pytest.mark.requires_myst def test_write_as_myst(tmpdir): """Inspired by https://github.com/mwouts/jupytext/issues/462""" nb = new_notebook() tmp_md = str(tmpdir.join("notebook.md")) jupytext.write(nb, tmp_md, fmt="myst") with open(tmp_md) as fp: md = fp.read() assert "myst" in md def test_write_raises_when_fmt_does_not_exists(tmpdir): """Inspired by https://github.com/mwouts/jupytext/issues/462""" nb = new_notebook() tmp_md = str(tmpdir.join("notebook.md")) with pytest.raises(JupytextFormatError): jupytext.write(nb, tmp_md, fmt="unknown_format") @pytest.mark.asyncio @pytest.mark.parametrize( "config_file,config_contents", [ ( "jupytext.toml", """# Always pair ipynb notebooks to md files formats = "ipynb,md" """, ), ( "jupytext.toml", """# Always pair ipynb notebooks to py:percent files formats = "ipynb,py:percent" """, ), ( "pyproject.toml", """[tool.jupytext] formats = "ipynb,py:percent" """, ), ( "jupytext.toml", """# Pair notebooks in subfolders of 'notebooks' to scripts in subfolders of 'scripts' formats = "notebooks///ipynb,scripts///py:percent" """, ), ( "jupytext.toml", """[formats] "notebooks/" = "ipynb" "scripts/" = "py:percent" """, ), ], ) async def test_configuration_examples_from_documentation(config_file, config_contents, python_notebook, tmp_path, cm): """Here we make sure that the config examples from https://jupytext.readthedocs.io/en/latest/config.html#configuring-paired-notebooks-globally just work """ (tmp_path / config_file).write_text(config_contents) cm.root_dir = str(tmp_path) # Save the notebook (tmp_path / "notebooks").mkdir() await ensure_async(cm.save(dict(type="notebook", content=python_notebook), "notebooks/nb.ipynb")) # Make sure that ipynb and text version are created assert (tmp_path / "notebooks" / "nb.ipynb").is_file() assert ( (tmp_path / "notebooks" / "nb.py").is_file() or (tmp_path / "notebooks" / "nb.md").is_file() or (tmp_path / "scripts" / "nb.py").is_file() ) ================================================ FILE: tests/unit/test_header.py ================================================ from nbformat.v4.nbbase import new_markdown_cell, new_notebook, new_raw_cell import jupytext from jupytext.compare import compare from jupytext.formats import get_format_implementation from jupytext.header import ( header_to_metadata_and_cell, metadata_and_cell_to_header, recursive_update, uncomment_line, ) def test_uncomment(): assert uncomment_line("# line one", "#") == "line one" assert uncomment_line("#line two", "#") == "line two" assert uncomment_line("#line two", "") == "#line two" def test_header_to_metadata_and_cell_blank_line(): text = """--- title: Sample header --- Header is followed by a blank line """ lines = text.splitlines() metadata, _, cell, pos = header_to_metadata_and_cell(lines, "", "") assert metadata == {} assert cell.cell_type == "raw" assert ( cell.source == """--- title: Sample header ---""" ) assert cell.metadata == {} assert lines[pos].startswith("Header is") def test_header_to_metadata_and_cell_no_blank_line(): text = """--- title: Sample header --- Header is not followed by a blank line """ lines = text.splitlines() metadata, _, cell, pos = header_to_metadata_and_cell(lines, "", "") assert metadata == {} assert cell.cell_type == "raw" assert ( cell.source == """--- title: Sample header ---""" ) assert cell.metadata == {"lines_to_next_cell": 0} assert lines[pos].startswith("Header is") def test_header_to_metadata_and_cell_metadata(): text = """--- title: Sample header jupyter: mainlanguage: python --- """ lines = text.splitlines() metadata, _, cell, pos = header_to_metadata_and_cell(lines, "", "") assert metadata == {"mainlanguage": "python"} assert cell.cell_type == "raw" assert ( cell.source == """--- title: Sample header ---""" ) assert cell.metadata == {"lines_to_next_cell": 0} assert pos == len(lines) def test_metadata_and_cell_to_header(no_jupytext_version_number): metadata = {"jupytext": {"mainlanguage": "python"}} nb = new_notebook(metadata=metadata, cells=[new_raw_cell(source="---\ntitle: Sample header\n---")]) header, lines_to_next_cell = metadata_and_cell_to_header( nb, metadata, get_format_implementation(".md"), {"extension": ".md"} ) assert ( "\n".join(header) == """--- title: Sample header jupyter: jupytext: mainlanguage: python ---""" ) assert nb.cells == [] assert lines_to_next_cell is None def test_metadata_and_cell_to_header2(no_jupytext_version_number): nb = new_notebook(cells=[new_markdown_cell(source="Some markdown\ntext")]) header, lines_to_next_cell = metadata_and_cell_to_header(nb, {}, get_format_implementation(".md"), {"extension": ".md"}) assert header == [] assert len(nb.cells) == 1 assert lines_to_next_cell is None def test_notebook_from_plain_script_has_metadata_filter( script="""print('Hello world") """, ): nb = jupytext.reads(script, ".py") assert nb.metadata.get("jupytext", {}).get("notebook_metadata_filter") == "-all" assert nb.metadata.get("jupytext", {}).get("cell_metadata_filter") == "-all" script2 = jupytext.writes(nb, ".py") compare(script2, script) def test_multiline_metadata( no_jupytext_version_number, notebook=new_notebook( metadata={ "multiline": """A multiline string with a blank line""", "jupytext": { "notebook_metadata_filter": "all", "text_representation": {"extension": ".md", "format_name": "markdown"}, }, } ), markdown="""--- jupyter: jupytext: notebook_metadata_filter: all text_representation: extension: .md format_name: markdown multiline: 'A multiline string with a blank line' --- """, ): actual = jupytext.writes(notebook, ".md") compare(actual, markdown) nb2 = jupytext.reads(markdown, ".md") compare(nb2, notebook) def test_header_in_html_comment(): text = """ """ lines = text.splitlines() metadata, _, cell, _ = header_to_metadata_and_cell(lines, "", "") assert metadata == {"title": "Sample header"} assert cell is None def test_header_to_html_comment(no_jupytext_version_number): metadata = {"jupytext": {"mainlanguage": "python"}} nb = new_notebook(metadata=metadata, cells=[]) header, lines_to_next_cell = metadata_and_cell_to_header( nb, metadata, get_format_implementation(".md"), {"extension": ".md", "hide_notebook_metadata": True}, ) compare( "\n".join(header), """""", ) def test_recusive_update(): assert recursive_update({0: {1: 2}}, {0: {1: 3}, 4: 5}) == {0: {1: 3}, 4: 5} assert recursive_update({0: {1: 2}}, {0: {1: 3}, 4: 5}, overwrite=False) == { 0: {1: 2}, 4: 5, } # the value of `None`` is a special case assert recursive_update({0: 1}, {0: None}) == {} assert recursive_update({0: 1}, {0: None}, overwrite=False) == {} ================================================ FILE: tests/unit/test_labconfig.py ================================================ import json import pytest from jupytext_config.labconfig import LabConfig @pytest.fixture() def sample_viewer_config(): return { "@jupyterlab/docmanager-extension:plugin": { "defaultViewers": { "markdown": "Jupytext Notebook", "myst": "Jupytext Notebook", "r-markdown": "Jupytext Notebook", "quarto": "Jupytext Notebook", "julia": "Jupytext Notebook", "python": "Jupytext Notebook", "r": "Jupytext Notebook", } } } @pytest.fixture() def sample_empty_viewer_config(): return {"@jupyterlab/docmanager-extension:plugin": {"defaultViewers": {}}} @pytest.fixture() def settings_file(tmp_path): return tmp_path / "default_setting_overrides.json" def test_read_config(settings_file, sample_viewer_config): (settings_file).write_text(json.dumps(sample_viewer_config)) labconfig = LabConfig(settings_file=settings_file).read() assert labconfig.config == sample_viewer_config def test_set_unset_default_viewers(settings_file, sample_viewer_config, sample_empty_viewer_config): labconfig = LabConfig(settings_file=settings_file) labconfig.set_default_viewers() assert labconfig.config == sample_viewer_config labconfig.unset_default_viewers() assert labconfig.config == sample_empty_viewer_config def test_write_config(settings_file, sample_viewer_config): labconfig = LabConfig(settings_file=settings_file) labconfig.set_default_viewers() labconfig.write() assert json.loads(settings_file.read_text()) == sample_viewer_config ================================================ FILE: tests/unit/test_markdown_in_code_cells.py ================================================ """Issue #712""" import pytest from nbformat.v4.nbbase import new_code_cell, new_notebook from jupytext import reads, writes from jupytext.cell_to_text import three_backticks_or_more from jupytext.compare import compare, compare_notebooks def test_three_backticks_or_more(): assert three_backticks_or_more([""]) == "```" assert three_backticks_or_more(["``"]) == "```" assert three_backticks_or_more(["```python"]) == "````" assert three_backticks_or_more(["```"]) == "````" assert three_backticks_or_more(["`````python"]) == "``````" assert three_backticks_or_more(["`````"]) == "``````" def test_triple_backticks_in_code_cell( no_jupytext_version_number, nb=new_notebook( metadata={"main_language": "python"}, cells=[ new_code_cell( '''a = """ ``` foo ``` """''' ) ], ), text='''--- jupyter: jupytext: main_language: python --- ````python a = """ ``` foo ``` """ ```` ''', ): actual_text = writes(nb, fmt="md") compare(actual_text, text) actual_nb = reads(text, fmt="md") compare_notebooks(actual_nb, nb) @pytest.mark.requires_myst def test_triple_backticks_in_code_cell_myst( no_jupytext_version_number, nb=new_notebook( metadata={"jupytext": {"default_lexer": "ipython3"}}, cells=[ new_code_cell( '''a = """ ``` foo ``` """''' ) ], ), text='''````{code-cell} ipython3 a = """ ``` foo ``` """ ```` ''', ): actual_text = writes(nb, fmt="md:myst") compare(actual_text, text) actual_nb = reads(text, fmt="md:myst") compare_notebooks(actual_nb, nb) def test_alternate_tree_four_five_backticks( no_jupytext_version_number, nb=new_notebook( metadata={"main_language": "python"}, cells=[ new_code_cell('a = """\n```\n"""'), new_code_cell("b = 2"), new_code_cell('c = """\n````\n"""'), ], ), text='''--- jupyter: jupytext: main_language: python --- ````python a = """ ``` """ ```` ```python b = 2 ``` `````python c = """ ```` """ ````` ''', ): actual_text = writes(nb, fmt="md") compare(actual_text, text) actual_nb = reads(text, fmt="md") compare_notebooks(actual_nb, nb) ================================================ FILE: tests/unit/test_paired_paths.py ================================================ import os import unittest.mock as mock import pytest import jupytext from jupytext.cli import jupytext as jupytext_cli from jupytext.compare import compare from jupytext.formats import ( long_form_multiple_formats, long_form_one_format, short_form_multiple_formats, ) from jupytext.paired_paths import ( InconsistentPath, base_path, base_path_and_adjusted_fmt, full_path, paired_paths, ) def test_simple_pair(): formats = long_form_multiple_formats("ipynb,py") expected_paths = ["notebook.ipynb", "notebook.py"] compare( paired_paths("notebook.ipynb", "ipynb", formats), list(zip(expected_paths, formats)), ) compare(paired_paths("notebook.py", "py", formats), list(zip(expected_paths, formats))) def test_base_path(): fmt = long_form_one_format("dir/prefix_/ipynb") assert base_path("dir/prefix_NAME.ipynb", fmt) == "NAME" with pytest.raises(InconsistentPath): base_path("dir/incorrect_prefix_NAME.ipynb", fmt) def test_base_path_dotdot(): fmt = long_form_one_format("../scripts//py") assert base_path("scripts/test.py", fmt=fmt) == "scripts/test" def test_full_path_dotdot(): fmt = long_form_one_format("../scripts//py") assert full_path("scripts/test", fmt=fmt) == "scripts/test.py" def test_base_path_in_tree_from_root(): fmt = long_form_one_format("scripts///py") assert base_path("scripts/subfolder/test.py", fmt=fmt) == "//subfolder/test" assert base_path("/scripts/subfolder/test.py", fmt=fmt) == "///subfolder/test" def test_base_path_in_tree_from_non_root(): fmt = long_form_one_format("scripts///py") assert base_path("/parent_folder/scripts/subfolder/test.py", fmt=fmt) == "/parent_folder///subfolder/test" def test_base_path_in_tree_from_non_root_no_subfolder(): nb_file = "/parent/notebooks/wrap_markdown.ipynb" formats = "notebooks///ipynb,scripts///py:percent" fmt = "notebooks///ipynb" assert base_path(nb_file, fmt) == "/parent///wrap_markdown" paired_paths(nb_file, fmt, formats) def test_full_path_in_tree_from_root(): fmt = long_form_one_format("notebooks///ipynb") assert full_path("//subfolder/test", fmt=fmt) == "notebooks/subfolder/test.ipynb" assert full_path("///subfolder/test", fmt=fmt) == "/notebooks/subfolder/test.ipynb" def test_full_path_in_tree_from_root_no_subfolder(): fmt = long_form_one_format("notebooks///ipynb") assert full_path("//test", fmt=fmt) == "notebooks/test.ipynb" assert full_path("///test", fmt=fmt) == "/notebooks/test.ipynb" def test_full_path_in_tree_from_non_root(): fmt = long_form_one_format("notebooks///ipynb") assert full_path("/parent_folder///subfolder/test", fmt=fmt) == "/parent_folder/notebooks/subfolder/test.ipynb" def test_paired_paths_windows(): nb_file = "C:\\Users\\notebooks\\notebooks\\subfolder\\nb.ipynb" formats = "notebooks///ipynb,scripts///py" with mock.patch("os.path.sep", "\\"): assert base_path(nb_file, "notebooks///ipynb") == "C:\\Users\\notebooks\\//subfolder\\nb" paired_paths(nb_file, "notebooks///ipynb", formats) def test_paired_paths_windows_no_subfolder(): nb_file = "C:\\Users\\notebooks\\notebooks\\nb.ipynb" formats = "notebooks///ipynb,scripts///py" with mock.patch("os.path.sep", "\\"): assert base_path(nb_file, "notebooks///ipynb") == "C:\\Users\\notebooks\\//nb" paired_paths(nb_file, "notebooks///ipynb", formats) def test_paired_paths_windows_relative(): """Test Windows pairing with relative paths and backslash as path separator, issue #1028""" nb_file = "C:\\notebooks\\example.ipynb" formats = "notebooks///ipynb,scripts///py:percent" with mock.patch("os.path.sep", "\\"): # Should not raise InconsistentPath paths = paired_paths(nb_file, "notebooks///ipynb", formats) # Verify the notebook path is in the paired paths path_list = [p[0] for p in paths] assert nb_file in path_list, f"Expected {nb_file} to be in paired paths {path_list}" # Verify both paths use backslashes on Windows assert paths[0][0] == "C:\\notebooks\\example.ipynb" assert paths[1][0] == "C:\\scripts\\example.py" @pytest.mark.parametrize("os_path_sep", ["\\", "/"]) def test_paired_path_dotdot_564(os_path_sep): main_path = os_path_sep.join(["examples", "tutorials", "colabs", "rigid_object_tutorial.ipynb"]) formats = "../nb_python//py:percent,../colabs//ipynb" with mock.patch("os.path.sep", os_path_sep): assert base_path(main_path, None, long_form_multiple_formats(formats)) == os_path_sep.join( ["examples", "tutorials", "colabs", "rigid_object_tutorial"] ) paired_paths(main_path, "ipynb", formats) def test_path_in_tree_limited_to_config_dir(tmpdir): root_nb_dir = tmpdir.mkdir("notebooks") nb_dir = root_nb_dir.mkdir("notebooks") src_dir = root_nb_dir.mkdir("scripts") other_dir = root_nb_dir.mkdir("other") formats = "notebooks///ipynb,scripts///py" fmt = long_form_multiple_formats(formats)[0] # Notebook in nested 'notebook' dir is paired notebook_in_nb_dir = nb_dir.join("subfolder").join("nb.ipynb") assert {path for (path, _) in paired_paths(str(notebook_in_nb_dir), fmt, formats)} == { str(notebook_in_nb_dir), str(src_dir.join("subfolder").join("nb.py")), } # Notebook in base 'notebook' dir is paired if no config file is found notebook_in_other_dir = other_dir.mkdir("subfolder").join("nb.ipynb") assert {path for (path, _) in paired_paths(str(notebook_in_other_dir), fmt, formats)} == { str(notebook_in_other_dir), str(tmpdir.join("scripts").join("other").join("subfolder").join("nb.py")), } # When a config file exists root_nb_dir.join("jupytext.toml").write("\n") # Notebook in nested 'notebook' dir is still paired assert {path for (path, _) in paired_paths(str(notebook_in_nb_dir), fmt, formats)} == { str(notebook_in_nb_dir), str(src_dir.join("subfolder").join("nb.py")), } # But the notebook in base 'notebook' dir is not paired any more alert = ( "Notebook directory '/other/subfolder' does not match prefix root 'notebooks'" if os.path.sep == "/" # we escape twice the backslash because pytest.raises matches it as a regular expression else "Notebook directory '\\\\other\\\\subfolder' does not match prefix root 'notebooks'" ) with pytest.raises(InconsistentPath, match=alert): paired_paths(str(notebook_in_other_dir), fmt, formats) def test_many_and_suffix(): formats = long_form_multiple_formats("ipynb,.pct.py,_lgt.py") expected_paths = ["notebook.ipynb", "notebook.pct.py", "notebook_lgt.py"] for fmt, path in zip(formats, expected_paths): compare(paired_paths(path, fmt, formats), list(zip(expected_paths, formats))) with pytest.raises(InconsistentPath): paired_paths("wrong_suffix.py", "py", formats) def test_prefix_and_suffix(): short_formats = ( "notebook_folder/notebook_prefix_/_notebook_suffix.ipynb," "script_folder//_in_percent_format.py:percent," "script_folder//_in_light_format.py" ) formats = long_form_multiple_formats(short_formats) assert short_form_multiple_formats(formats) == short_formats expected_paths = [ "parent/notebook_folder/notebook_prefix_NOTEBOOK_NAME_notebook_suffix.ipynb", "parent/script_folder/NOTEBOOK_NAME_in_percent_format.py", "parent/script_folder/NOTEBOOK_NAME_in_light_format.py", ] for fmt, path in zip(formats, expected_paths): compare(paired_paths(path, fmt, formats), list(zip(expected_paths, formats))) # without the parent folder expected_paths = [path[7:] for path in expected_paths] for fmt, path in zip(formats, expected_paths): compare(paired_paths(path, fmt, formats), list(zip(expected_paths, formats))) # Not the expected parent folder with pytest.raises(InconsistentPath): paired_paths( "script_folder_incorrect/NOTEBOOK_NAME_in_percent_format.py", formats[1], formats, ) # Not the expected suffix with pytest.raises(InconsistentPath): paired_paths("parent/script_folder/NOTEBOOK_NAME_in_LIGHT_format.py", formats[2], formats) # Not the expected extension with pytest.raises(InconsistentPath): paired_paths( "notebook_folder/notebook_prefix_NOTEBOOK_NAME_notebook_suffix.py", formats[0], formats, ) def test_prefix_on_root_174(): short_formats = "ipynb,python//py:percent" formats = long_form_multiple_formats(short_formats) assert short_form_multiple_formats(formats) == short_formats expected_paths = ["Untitled.ipynb", "python/Untitled.py"] for fmt, path in zip(formats, expected_paths): compare(paired_paths(path, fmt, formats), list(zip(expected_paths, formats))) def test_duplicated_paths(): formats = long_form_multiple_formats("ipynb,py:percent,py:light") with pytest.raises(InconsistentPath): paired_paths("notebook.ipynb", "ipynb", formats) @pytest.mark.asyncio async def test_cm_paired_paths(cm): cm.paired_notebooks = dict() three = "ipynb,py,md" cm.update_paired_notebooks("nb.ipynb", three) assert cm.paired_notebooks == {"nb." + fmt: (fmt, three) for fmt in three.split(",")} two = "ipynb,Rmd" cm.update_paired_notebooks("nb.ipynb", two) assert cm.paired_notebooks == {"nb." + fmt: (fmt, two) for fmt in two.split(",")} one = "ipynb" cm.update_paired_notebooks("nb.ipynb", one) assert cm.paired_notebooks == {} zero = "" cm.update_paired_notebooks("nb.ipynb", zero) assert cm.paired_notebooks == {} def test_paired_path_with_prefix( nb_file="scripts/test.py", fmt={"extension": ".py", "format_name": "percent"}, formats=[ {"extension": ".ipynb"}, {"prefix": "scripts/", "format_name": "percent", "extension": ".py"}, ], ): assert paired_paths(nb_file, fmt, formats) == [ ("test.ipynb", {"extension": ".ipynb"}), ( "scripts/test.py", {"prefix": "scripts/", "format_name": "percent", "extension": ".py"}, ), ] def test_paired_notebook_ipynb_root_scripts_in_folder_806(tmpdir, cwd_tmpdir, python_notebook): """In this test we pair a notebook with a script in a subfolder, and then do some natural operations like delete/recreate one of the paired files""" # Save sample notebook test_ipynb = tmpdir / "test.ipynb" jupytext.write(python_notebook, str(test_ipynb)) # Pair the notebook to a script in a subfolder jupytext_cli(["--set-formats", "ipynb,scripts//py:percent", "test.ipynb"]) assert (tmpdir / "scripts" / "test.py").exists() # Delete and then recreate the ipynb notebook using --to notebook test_ipynb.remove() jupytext_cli( [ "--to", "notebook", "--output", "test.ipynb", "scripts/test.py", ] ) assert test_ipynb.exists() # Delete and then recreate the ipynb notebook using --sync test_ipynb.remove() jupytext_cli( [ "--sync", "scripts/test.py", ] ) assert test_ipynb.exists() @pytest.mark.parametrize( "path, input_fmt, adjusted_fmt", [ ( "scripts/test.py", {"extension": ".py", "format_name": "percent", "prefix": "scripts//"}, {"extension": ".py", "format_name": "percent", "prefix": "scripts//"}, ), ( "test.py", {"extension": ".py", "format_name": "percent", "prefix": "scripts//"}, { "extension": ".py", "format_name": "percent", }, ), ( "test.py", {"extension": ".py", "format_name": "percent", "prefix": "prefix_"}, {"extension": ".py", "format_name": "percent"}, ), ], ) def test_paired_paths_and_adjusted_fmt(path, input_fmt, adjusted_fmt): base_path, actual_adjusted_fmt = base_path_and_adjusted_fmt(path, input_fmt) assert actual_adjusted_fmt == adjusted_fmt @pytest.mark.parametrize("os_sep", ["\\", "/"]) def test_base_path_os_sep(os_sep): fmt = "notebooks/tutorials///ipynb" root = ("" if os_sep == "/" else "C:") + os_sep path = root + os_sep.join(["notebooks", "tutorials", "subfolder", "notebook.ipynb"]) with mock.patch("os.path.sep", os_sep): assert base_path(path, fmt) == root + os_sep.join(["//subfolder", "notebook"]) ================================================ FILE: tests/unit/test_pep8.py ================================================ from nbformat.v4.nbbase import new_code_cell, new_notebook from jupytext import read, reads, writes from jupytext.compare import compare from jupytext.pep8 import ( cell_ends_with_code, cell_ends_with_function_or_class, cell_has_code, next_instruction_is_function_or_class, pep8_lines_between_cells, ) def test_next_instruction_is_function_or_class(): text = """@pytest.mark.parametrize('py_file', [py_file for py_file in list_notebooks('../src/jupytext') + list_notebooks('.') if py_file.endswith('.py')]) def test_no_metadata_when_py_is_pep8(py_file): pass """ assert next_instruction_is_function_or_class(text.splitlines()) def test_cell_ends_with_code(): assert not cell_ends_with_code([]) def test_cell_ends_with_function_or_class(): text = """class A: __init__(): '''A docstring with two lines or more''' self.a = 0 """ assert cell_ends_with_function_or_class(text.splitlines()) lines = ["#", "#"] assert not cell_ends_with_function_or_class(lines) text = """# two blank line after this class class A: pass # so we do not need to insert two blank lines below this cell """ assert not cell_ends_with_function_or_class(text.splitlines()) text = """# All lines # are commented""" assert not cell_ends_with_function_or_class(text.splitlines()) text = """# Two blank lines after function def f(x): return x # And a comment here""" assert not cell_ends_with_function_or_class(text.splitlines()) assert not cell_ends_with_function_or_class(["", "#"]) def test_pep8_lines_between_cells(): prev_lines = """a = a_long_instruction( over_two_lines=True)""".splitlines() next_lines = """def f(x): return x""".splitlines() assert cell_ends_with_code(prev_lines) assert next_instruction_is_function_or_class(next_lines) assert pep8_lines_between_cells(prev_lines, next_lines, ".py") == 2 def test_pep8_lines_between_cells_bis(): prev_lines = """def f(x): return x""".splitlines() next_lines = """# A markdown cell # An instruction a = 5 """.splitlines() assert cell_ends_with_function_or_class(prev_lines) assert cell_has_code(next_lines) assert pep8_lines_between_cells(prev_lines, next_lines, ".py") == 2 next_lines = """# A markdown cell # Only markdown here # And here """.splitlines() assert cell_ends_with_function_or_class(prev_lines) assert not cell_has_code(next_lines) assert pep8_lines_between_cells(prev_lines, next_lines, ".py") == 1 def test_pep8_lines_between_cells_ter(): prev_lines = ["from jupytext.cell_to_text import RMarkdownCellExporter"] next_lines = '''@pytest.mark.parametrize( "lines", [ "# text", """# # %%R # # comment # 1 + 1 # 2 + 2 """, ], ) def test_paragraph_is_fully_commented(lines): assert paragraph_is_fully_commented( lines.splitlines(), comment="#", main_language="python" )'''.splitlines() assert cell_ends_with_code(prev_lines) assert next_instruction_is_function_or_class(next_lines) assert pep8_lines_between_cells(prev_lines, next_lines, ".py") == 2 def test_pep8(): text = """import os path = os.path # code cell #1, with a comment on f def f(x): return x + 1 # markdown cell #1 # code cell #2 - an instruction a = 4 # markdown cell #2 # code cell #3 with a comment on g def g(x): return x + 1 # markdown cell #3 # the two lines are: # - right below the function/class # - below the last python paragraph (i.e. NOT ABOVE g) # code cell #4 x = 4 """ nb = reads(text, "py") for cell in nb.cells: assert not cell.metadata text2 = writes(nb, "py") compare(text2, text) def test_pep8_bis(): text = """# This is a markdown cell # a code cell def f(x): return x + 1 # And another markdown cell # Separated from f by just one line # As there is no code here """ nb = reads(text, "py") for cell in nb.cells: assert not cell.metadata text2 = writes(nb, "py") compare(text2, text) def test_no_metadata_when_py_is_pep8(py_file): """This test assumes that all Python files in the jupytext folder follow PEP8 rules""" nb = read(py_file) for i, cell in enumerate(nb.cells): if "title" in cell.metadata: cell.metadata.pop("title") # pragma: no cover if i == 0 and not cell.source: assert cell.metadata == {"lines_to_next_cell": 0}, py_file # pragma: no cover else: assert not cell.metadata, (py_file, cell.source) def test_notebook_ends_with_exactly_one_empty_line_682(): """(Issue #682) Steps to reproduce: Have a notebook that ends in a python code cell (with no empty lines at the end of the cell). run jupytext --to py:percent notebookWithCodeCell.ipynb. See that the generated python code file has two empty lines at the end. I would expect there to just be one new line.""" nb = new_notebook(cells=[new_code_cell("1+1")], metadata={"jupytext": {"main_language": "python"}}) py = writes(nb, "py:percent") assert py.endswith("1+1\n") ================================================ FILE: tests/unit/test_stringparser.py ================================================ from jupytext.stringparser import StringParser def test_long_string( text="""'''This is a multiline comment with "quotes", 'single quotes' # and comments and line breaks and it ends here''' 1 + 1 """, ): quoted = [] sp = StringParser("python") for i, line in enumerate(text.splitlines()): if sp.is_quoted(): quoted.append(i) sp.read_line(line) assert quoted == [1, 2, 3, 4, 5, 6] def test_single_chars( text="""'This is a single line comment''' 'and another one' # and comments "and line breaks" "and it ends here'''" 1 + 1 """, ): sp = StringParser("python") for line in text.splitlines(): assert not sp.is_quoted() sp.read_line(line) def test_long_string_with_four_quotes( text="""''''This is a multiline comment that starts with four quotes ''' 1 + 1 """, ): quoted = [] sp = StringParser("python") for i, line in enumerate(text.splitlines()): if sp.is_quoted(): quoted.append(i) sp.read_line(line) assert quoted == [1, 2] def test_long_string_ends_with_four_quotes( text="""'''This is a multiline comment that ends with four quotes '''' 1 + 1 """, ): quoted = [] sp = StringParser("python") for i, line in enumerate(text.splitlines()): if sp.is_quoted(): quoted.append(i) sp.read_line(line) assert quoted == [1, 2] ================================================ FILE: tools/absolute_links_in_readme.py ================================================ import re from pathlib import Path from hatchling.metadata.plugin.interface import MetadataHookInterface class AbsoluteLinksInReadme(MetadataHookInterface): """Hook that processes README.md to make relative links absolute.""" def update(self, metadata): """Process README.md when metadata is being prepared.""" readme_src_path = Path("README.md") readme_output_path = Path("build/README_with_absolute_links.md") base_url = "https://github.com/mwouts/jupytext/blob/main/" # Ensure the dist directory exists readme_output_path.parent.mkdir(exist_ok=True) self.convert_links(readme_src_path, readme_output_path, base_url) return metadata def convert_links(self, src_path, output_path, base_url): """Convert relative links in README.md to absolute links.""" print(f"Processing {src_path} to generate {output_path} with absolute links") content = src_path.read_text(encoding="utf-8") # Find markdown links that don't start with http:// or https:// pattern = re.compile(r"\[([^\]]+)\]\((?!http)([^)]+)\)") def replace_link(match): text, url = match.groups() if not url.startswith(("http://", "https://", "#")): url = base_url + url return f"[{text}]({url})" new_content = pattern.sub(replace_link, content) # Write the processed content to the output file output_path.parent.mkdir(exist_ok=True) output_path.write_text(new_content, encoding="utf-8") print(f"Generated {output_path} with absolute links")