Repository: jktr/matplotlib-backend-kitty Branch: master Commit: cbe4fe231d75 Files: 5 Total size: 12.5 KB Directory structure: gitextract_81kwwsd_/ ├── .gitignore ├── LICENSE ├── README.md ├── matplotlib-backend-kitty/ │ └── __init__.py └── pyproject.toml ================================================ FILE CONTENTS ================================================ ================================================ FILE: .gitignore ================================================ .pyc __pycache__ dist/ *.egg-info/ ================================================ FILE: LICENSE ================================================ Creative Commons Legal Code CC0 1.0 Universal CREATIVE COMMONS CORPORATION IS NOT A LAW FIRM AND DOES NOT PROVIDE LEGAL SERVICES. DISTRIBUTION OF THIS DOCUMENT DOES NOT CREATE AN ATTORNEY-CLIENT RELATIONSHIP. CREATIVE COMMONS PROVIDES THIS INFORMATION ON AN "AS-IS" BASIS. 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Affirmer understands and acknowledges that Creative Commons is not a party to this document and has no duty or obligation with respect to this CC0 or use of the Work. ================================================ FILE: README.md ================================================ # matplotlib-backend-kitty This python module allows you to use your [kitty terminal](https://github.com/kovidgoyal/kitty) to show the plots generated by python's [matplotlib](https://github.com/matplotlib/matplotlib). For other terminals, the similar [notcurses backend](https://github.com/jktr/matplotlib-backend-notcurses) may also be of interest. To install this one, do one of the following - `$ pip install --user matplotlib-backend-kitty` - clone this repo into your python's `site-packages` directory - clone this repo and add the parent directory to `sys.path` or `$PYTHONPATH` Then, configure matplotlib to use the module by either setting the environment variable `MPLBACKEND` to `module://matplotlib-backend-kitty` or by initializing matplotlib as follows. ```python import matplotlib matplotlib.use('module://matplotlib-backend-kitty') import matplotlib.pyplot as plt ``` If you've installed this module correctly, you can now use the following sample code to draw a plot in your terminal. ``` $ export MPLBACKEND='module://matplotlib-backend-kitty' $ python >>> n = 10000 >>> df = pd.DataFrame({'x': np.random.randn(n), 'y': np.random.randn(n)}) >>> df.plot.hexbin(x='x', y='y', gridsize=20) ``` If you set your matplotlib to interactive mode via `matplotlib.pyplot.ion()` or by running an interactive python shell like `python` or `ipython`, non-empty figures are drawn on construction where possible. This allows you to use pandas' `plot()` calls directly, without calling `plt.show()`, and still enables you to manually construct and `plt.show()`. If your matplotlib is in non-interactive mode, you can construct your figures as usual, and then call `plt.show()` to render them to your terminal. This works both from scripts and from a repl. Figures are resized to the size of your terminal by default. If you'd rather control the sizing of figures manually, set the `MPLBACKEND_KITTY_SIZING` environment variable to `manual`. Internally, this backend is somewhat based on matplotlib's IPython support: it's a hybrid of image and GUI backend types. It works by using matplotlib's `Agg` backend to render the plot, and then calls kitty's `icat` to place the rendered image on your terminal. This means that plotting works as expected, but the image drawn to your terminal isn't interactive and animations aren't supported. ================================================ FILE: matplotlib-backend-kitty/__init__.py ================================================ # SPDX-License-Identifier: CC0-1.0 import os import sys from io import BytesIO from subprocess import run from matplotlib import interactive, is_interactive from matplotlib._pylab_helpers import Gcf from matplotlib.backend_bases import (_Backend, FigureManagerBase) from matplotlib.backends.backend_agg import FigureCanvasAgg # XXX heuristic for interactive repl if hasattr(sys, 'ps1') or sys.flags.interactive: interactive(True) class FigureManagerICat(FigureManagerBase): @classmethod def _run(cls, *cmd): def f(*args, output=True, **kwargs): if output: kwargs['capture_output'] = True kwargs['text'] = True r = run(cmd + args, **kwargs) if output: return r.stdout.rstrip() return f def show(self): icat = __class__._run('kitty', '+kitten', 'icat') if os.environ.get('MPLBACKEND_KITTY_SIZING', 'automatic') != 'manual': tput = __class__._run('tput') # gather terminal dimensions rows = int(tput('lines')) px = icat('--print-window-size') px = list(map(int, px.split('x'))) # account for post-display prompt scrolling # 3 line shift for [\n, >>] after the figure px[1] -= int(3*(px[1]/rows)) # resize figure to terminal size & aspect ratio dpi = self.canvas.figure.dpi self.canvas.figure.set_size_inches((px[0] / dpi, px[1] / dpi)) with BytesIO() as buf: self.canvas.figure.savefig(buf, format='png') icat('--align', 'left', output=False, input=buf.getbuffer()) class FigureCanvasICat(FigureCanvasAgg): manager_class = FigureManagerICat @_Backend.export class _BackendICatAgg(_Backend): FigureCanvas = FigureCanvasICat FigureManager = FigureManagerICat # Noop function instead of None signals that # this is an "interactive" backend mainloop = lambda: None # XXX: `draw_if_interactive` isn't really intended for # on-shot rendering. We run the risk of being called # on a figure that isn't completely rendered yet, so # we skip draw calls for figures that we detect as # not being fully initialized yet. Our heuristic for # that is the presence of axes on the figure. @classmethod def draw_if_interactive(cls): manager = Gcf.get_active() if is_interactive() and manager.canvas.figure.get_axes(): cls.show() @classmethod def show(cls, *args, **kwargs): _Backend.show(*args, **kwargs) Gcf.destroy_all() ================================================ FILE: pyproject.toml ================================================ [project] name = "matplotlib-backend-kitty" version = "2.1.2" description = "show matplotlib plots directly in your kitty terminal" readme = "README.md" classifiers = [ "Programming Language :: Python :: 3", "License :: CC0 1.0 Universal (CC0 1.0) Public Domain Dedication", "Framework :: Matplotlib", "Topic :: Terminals", ] dependencies = [ "matplotlib" ] [project.urls] "Homepage" = "https://github.com/jktr/matplotlib-backend-kitty" "Bug Tracker" = "https://github.com/jktr/matplotlib-backend-kitty/issues" [build-system] requires = [ "setuptools>=61.0" ] build-backend = "setuptools.build_meta" [tool.setuptools.packages.find] where = [ "." ]