[ { "path": ".gitignore", "content": "*.egg-info\n.DS_Store\n__pycache__\nbuild\ndist\nnode_modules\n.ipynb_checkpoints\n" }, { "path": "Examples/1_HelloWorld/HelloWorld.ipynb", "content": "{\n \"cells\": [\n {\n \"cell_type\": \"markdown\",\n \"metadata\": {},\n \"source\": [\n \"# Hello World\\n\",\n \"\\n\",\n \"Adding a text element to a Notebook output cell using plain JavaScript\"\n ]\n },\n {\n \"cell_type\": \"code\",\n \"execution_count\": null,\n \"metadata\": {},\n \"outputs\": [],\n \"source\": [\n \"from notebookjs import execute_js\"\n ]\n },\n {\n \"cell_type\": \"markdown\",\n \"metadata\": {},\n \"source\": [\n \"### Writing the js function\"\n ]\n },\n {\n \"cell_type\": \"code\",\n \"execution_count\": null,\n \"metadata\": {},\n \"outputs\": [],\n \"source\": [\n \"helloworld_js = \\\"\\\"\\\"\\n\",\n \"function helloworld(div_id, data){\\n\",\n \" document.querySelector(div_id).textContent=data.text;\\n\",\n \"}\\n\",\n \"\\\"\\\"\\\"\"\n ]\n },\n {\n \"cell_type\": \"markdown\",\n \"metadata\": {},\n \"source\": [\n \"### Running the code\"\n ]\n },\n {\n \"cell_type\": \"code\",\n \"execution_count\": null,\n \"metadata\": {},\n \"outputs\": [],\n \"source\": [\n \"execute_js(helloworld_js, \\\"helloworld\\\", {\\\"text\\\": \\\"Hello World\\\"})\"\n ]\n }\n ],\n \"metadata\": {\n \"kernelspec\": {\n \"display_name\": \"Python 3\",\n \"language\": \"python\",\n \"name\": \"python3\"\n },\n \"language_info\": {\n \"codemirror_mode\": {\n \"name\": \"ipython\",\n \"version\": 3\n },\n \"file_extension\": \".py\",\n \"mimetype\": \"text/x-python\",\n \"name\": \"python\",\n \"nbconvert_exporter\": \"python\",\n \"pygments_lexer\": \"ipython3\",\n \"version\": \"3.8.5\"\n }\n },\n \"nbformat\": 4,\n \"nbformat_minor\": 4\n}\n" }, { "path": "Examples/2_SimpleD3_Circle/SimpleD3_Circle.ipynb", "content": "{\n \"cells\": [\n {\n \"cell_type\": \"markdown\",\n \"metadata\": {},\n \"source\": [\n \"# Simple D3 Circle\\n\",\n \"\\n\",\n \"This notebook shows how to load D3js from an URL and draw a simple circle in a notebook\"\n ]\n },\n {\n \"cell_type\": \"code\",\n \"execution_count\": null,\n \"metadata\": {},\n \"outputs\": [],\n \"source\": [\n \"from notebookjs import execute_js\"\n ]\n },\n {\n \"cell_type\": \"markdown\",\n \"metadata\": {},\n \"source\": [\n \"### Setting up the JavaScript libraries\\n\",\n \"\\n\",\n \"We are using two JavaScript libraries: D3 and a local \\\"draw_circle_lib\\\" library.\\n\",\n \"\\n\",\n \"- D3 is loaded from the web (notebookJS takes care of downloading files from URLs). \\n\",\n \"\\n\",\n \"- draw_circle_lib is loaded from a local file.\\n\",\n \"\\n\",\n \"**Note that we are using D3 V3.**\\n\",\n \"More recent versions of D3 use ES6 and cannot be directly loaded in the notebook script tag. We recommend using a javascript build tool such as babel + webpack to use more modern libraries.\"\n ]\n },\n {\n \"cell_type\": \"code\",\n \"execution_count\": null,\n \"metadata\": {},\n \"outputs\": [],\n \"source\": [\n \"with open(\\\"./draw_circle_lib.js\\\", \\\"r\\\") as f:\\n\",\n \" draw_circle_lib = f.read()\\n\",\n \" \\n\",\n \"d3_lib_url = \\\"https://d3js.org/d3.v3.min.js\\\"\"\n ]\n },\n {\n \"cell_type\": \"markdown\",\n \"metadata\": {},\n \"source\": [\n \"This is the D3 function to draw a circle: \"\n ]\n },\n {\n \"cell_type\": \"code\",\n \"execution_count\": null,\n \"metadata\": {},\n \"outputs\": [],\n \"source\": [\n \"print(draw_circle_lib)\"\n ]\n },\n {\n \"cell_type\": \"markdown\",\n \"metadata\": {},\n \"source\": [\n \"### Running the code\"\n ]\n },\n {\n \"cell_type\": \"code\",\n \"execution_count\": null,\n \"metadata\": {},\n \"outputs\": [],\n \"source\": [\n \"execute_js([d3_lib_url, draw_circle_lib], \\\"draw_circle\\\", {\\\"color\\\": \\\"#4682B4\\\"})\"\n ]\n },\n {\n \"cell_type\": \"code\",\n \"execution_count\": null,\n \"metadata\": {},\n \"outputs\": [],\n \"source\": []\n }\n ],\n \"metadata\": {\n \"kernelspec\": {\n \"display_name\": \"Python 3\",\n \"language\": \"python\",\n \"name\": \"python3\"\n },\n \"language_info\": {\n \"codemirror_mode\": {\n \"name\": \"ipython\",\n \"version\": 3\n },\n \"file_extension\": \".py\",\n \"mimetype\": \"text/x-python\",\n \"name\": \"python\",\n \"nbconvert_exporter\": \"python\",\n \"pygments_lexer\": \"ipython3\",\n \"version\": \"3.8.5\"\n }\n },\n \"nbformat\": 4,\n \"nbformat_minor\": 4\n}\n" }, { "path": "Examples/2_SimpleD3_Circle/draw_circle_lib.js", "content": "function draw_circle(id, data){\n d3.select(id)\n .append(\"div\")\n .style(\"width\", \"50px\")\n .style(\"height\", \"50px\")\n .style(\"background-color\", data.color)\n .style(\"border-radius\", \"50px\")\n}" }, { "path": "Examples/3_RadialBarChart/RadialBarChart.ipynb", "content": "{\n \"cells\": [\n {\n \"cell_type\": \"markdown\",\n \"metadata\": {},\n \"source\": [\n \"# Radial Bar Chart\\n\",\n \"\\n\",\n \"We port the Radial Bar Chart implemented in D3 to a Jupyter Notebook.\\n\",\n \"Code adapted from https://bl.ocks.org/AntonOrlov/6b42d8676943cc933f48a43a7c7e5b6c\"\n ]\n },\n {\n \"cell_type\": \"markdown\",\n \"metadata\": {},\n \"source\": [\n \"### Loading the radial bar chart code. \\n\",\n \"\\n\",\n \"We load both js and css scripts\"\n ]\n },\n {\n \"cell_type\": \"code\",\n \"execution_count\": null,\n \"metadata\": {},\n \"outputs\": [],\n \"source\": [\n \"d3_lib_url = \\\"https://d3js.org/d3.v3.min.js\\\"\\n\",\n \"\\n\",\n \"with open(\\\"radial_bar.css\\\", \\\"r\\\") as f:\\n\",\n \" radial_bar_css = f.read()\\n\",\n \" \\n\",\n \"with open (\\\"radial_bar_lib.js\\\", \\\"r\\\") as f:\\n\",\n \" radial_bar_lib = f.read()\"\n ]\n },\n {\n \"cell_type\": \"markdown\",\n \"metadata\": {},\n \"source\": [\n \"### Loading data\"\n ]\n },\n {\n \"cell_type\": \"code\",\n \"execution_count\": null,\n \"metadata\": {},\n \"outputs\": [],\n \"source\": [\n \"import pandas as pd\\n\",\n \"energy = pd.read_csv(\\\"energy.csv\\\")\"\n ]\n },\n {\n \"cell_type\": \"markdown\",\n \"metadata\": {},\n \"source\": [\n \"### Plotting the bar chart \\n\",\n \"\\n\",\n \"Radial Bar Chart of energy consumption over five months\"\n ]\n },\n {\n \"cell_type\": \"code\",\n \"execution_count\": null,\n \"metadata\": {},\n \"outputs\": [],\n \"source\": [\n \"from notebookjs import execute_js\\n\",\n \"execute_js(library_list=[d3_lib_url, radial_bar_lib], main_function=\\\"radial_bar\\\", \\n\",\n \" data_dict=energy.to_dict(orient=\\\"records\\\"), css_list=[radial_bar_css])\"\n ]\n },\n {\n \"cell_type\": \"code\",\n \"execution_count\": null,\n \"metadata\": {},\n \"outputs\": [],\n \"source\": []\n }\n ],\n \"metadata\": {\n \"kernelspec\": {\n \"display_name\": \"Python 3\",\n \"language\": \"python\",\n \"name\": \"python3\"\n },\n \"language_info\": {\n \"codemirror_mode\": {\n \"name\": \"ipython\",\n \"version\": 3\n },\n \"file_extension\": \".py\",\n \"mimetype\": \"text/x-python\",\n \"name\": \"python\",\n \"nbconvert_exporter\": \"python\",\n \"pygments_lexer\": \"ipython3\",\n \"version\": \"3.8.5\"\n }\n },\n \"nbformat\": 4,\n \"nbformat_minor\": 4\n}\n" }, { "path": "Examples/3_RadialBarChart/energy.csv", "content": "name,value\nJan,432\nFeb,340\nMar,382\nApr,398\nMay,410" }, { "path": "Examples/3_RadialBarChart/radial_bar.css", "content": "body {\n font: 12px sans-serif;\n}\n\nsvg {\n margin: 0px auto;\n display: block;\n}\n\npath.arc {\n opacity: 0.9;\n transition: opacity 0.5s;\n}\n\npath.arc:hover {\n opacity: 0.7;\n}\n\n.axis line, .axis circle {\n stroke: #cccccc;\n stroke-width: 1px\n}\n\n.axis circle {\n fill: none;\n}\n\n.r.axis text {\n text-anchor: end\n}\n\n.tooltip {\n position: absolute;\n display: none;\n background: rgba(0, 0, 0, 0.6);\n border-radius: 3px;\n box-shadow: -3px 3px 15px #888;\n color: white;\n padding: 6px;\n}" }, { "path": "Examples/3_RadialBarChart/radial_bar_lib.js", "content": "function radial_bar(div_id, data){\n // Radial Bar Chart\n \n // Code adapted from: https://bl.ocks.org/AntonOrlov/6b42d8676943cc933f48a43a7c7e5b6c\n // We have changed the data loading lines (to receive the parameter data) and ported the code to D3 V3.\n \n const width = 960,\n height = 500,\n chartRadius = height / 2 - 40;\n\n const color = d3.scale.category10();\n\n let svg = d3.select(div_id).append('svg')\n .attr('width', width)\n .attr('height', height)\n .append('g')\n .attr('transform', 'translate(' + width / 2 + ',' + height / 2 + ')');\n\n let tooltip = d3.select('body').append('div')\n .attr('class', 'tooltip');\n\n const PI = Math.PI,\n arcMinRadius = 10,\n arcPadding = 10,\n labelPadding = -5,\n numTicks = 10;\n\n\n let scale = d3.scale.linear()\n .domain([0, d3.max(data, d => d.value) * 1.1])\n .range([0, 2 * PI]);\n\n let ticks = scale.ticks(numTicks).slice(0, -1);\n let keys = data.map((d, i) => d.name);\n //number of arcs\n const numArcs = keys.length;\n const arcWidth = (chartRadius - arcMinRadius - numArcs * arcPadding) / numArcs;\n\n let arc = d3.svg.arc()\n .innerRadius((d, i) => getInnerRadius(i))\n .outerRadius((d, i) => getOuterRadius(i))\n .startAngle(0)\n .endAngle((d, i) => scale(d))\n\n let radialAxis = svg.append('g')\n .attr('class', 'r axis')\n .selectAll('g')\n .data(data)\n .enter().append('g');\n\n radialAxis.append('circle')\n .attr('r', (d, i) => getOuterRadius(i) + arcPadding);\n\n radialAxis.append('text')\n .attr('x', labelPadding)\n .attr('y', (d, i) => -getOuterRadius(i) + arcPadding)\n .text(d => d.name);\n\n let axialAxis = svg.append('g')\n .attr('class', 'a axis')\n .selectAll('g')\n .data(ticks)\n .enter().append('g')\n .attr('transform', d => 'rotate(' + (rad2deg(scale(d)) - 90) + ')');\n\n axialAxis.append('line')\n .attr('x2', chartRadius);\n\n axialAxis.append('text')\n .attr('x', chartRadius + 10)\n .style('text-anchor', d => (scale(d) >= PI && scale(d) < 2 * PI ? 'end' : null))\n .attr('transform', d => 'rotate(' + (90 - rad2deg(scale(d))) + ',' + (chartRadius + 10) + ',0)')\n .text(d => d);\n\n //data arcs\n let arcs = svg.append('g')\n .attr('class', 'data')\n .selectAll('path')\n .data(data)\n .enter().append('path')\n .attr('class', 'arc')\n .style('fill', (d, i) => color(i))\n\n arcs.transition()\n .delay((d, i) => i * 200)\n .duration(1000)\n .attrTween('d', arcTween);\n\n arcs.on('mousemove', showTooltip)\n arcs.on('mouseout', hideTooltip)\n\n\n function arcTween(d, i) {\n let interpolate = d3.interpolate(0, d.value);\n return t => arc(interpolate(t), i);\n }\n\n function showTooltip(d) {\n tooltip.style('left', (d3.event.pageX + 10) + 'px')\n .style('top', (d3.event.pageY - 25) + 'px')\n .style('display', 'inline-block')\n .html(d.value);\n }\n\n function hideTooltip() {\n tooltip.style('display', 'none');\n }\n\n function rad2deg(angle) {\n return angle * 180 / PI;\n }\n\n function getInnerRadius(index) {\n return arcMinRadius + (numArcs - (index + 1)) * (arcWidth + arcPadding);\n }\n\n function getOuterRadius(index) {\n return getInnerRadius(index) + arcWidth;\n }\n}\n" }, { "path": "Examples/4_Bidirectional_Comm/Bar_Chart_Bidirectional_Comm.ipynb", "content": "{\n \"cells\": [\n {\n \"cell_type\": \"markdown\",\n \"metadata\": {},\n \"source\": [\n \"# Bar chart example with bidirectional communication\"\n ]\n },\n {\n \"cell_type\": \"code\",\n \"execution_count\": null,\n \"metadata\": {},\n \"outputs\": [],\n \"source\": [\n \"from notebookjs import execute_js\"\n ]\n },\n {\n \"cell_type\": \"markdown\",\n \"metadata\": {},\n \"source\": [\n \"### Loading libraries\"\n ]\n },\n {\n \"cell_type\": \"code\",\n \"execution_count\": null,\n \"metadata\": {},\n \"outputs\": [],\n \"source\": [\n \"d3_lib_url = \\\"https://d3js.org/d3.v3.min.js\\\"\\n\",\n \"\\n\",\n \"with open(\\\"bar_chart_lib.js\\\", \\\"r\\\") as f:\\n\",\n \" bar_chart_lib = f.read()\"\n ]\n },\n {\n \"cell_type\": \"markdown\",\n \"metadata\": {},\n \"source\": [\n \"### The bar chart displays the array data in order\"\n ]\n },\n {\n \"cell_type\": \"code\",\n \"execution_count\": null,\n \"metadata\": {},\n \"outputs\": [],\n \"source\": [\n \"data_dict = {\\n\",\n \" \\\"array\\\": [1,2,3]\\n\",\n \"}\\n\",\n \"execute_js(library_list=[d3_lib_url, bar_chart_lib], main_function=\\\"bar_chart\\\", data_dict=data_dict)\"\n ]\n },\n {\n \"cell_type\": \"markdown\",\n \"metadata\": {},\n \"source\": [\n \"### Set up data update callback\"\n ]\n },\n {\n \"cell_type\": \"code\",\n \"execution_count\": null,\n \"metadata\": {},\n \"outputs\": [],\n \"source\": [\n \"import random\\n\",\n \"\\n\",\n \"def random_array(data):\\n\",\n \" # Makes an array of random numbers\\n\",\n \" n = data[\\\"n\\\"]\\n\",\n \" return {'array': [random.random() for x in range(n)]}\\n\",\n \"\\n\",\n \"callbacks = {'random_array': random_array}\"\n ]\n },\n {\n \"cell_type\": \"markdown\",\n \"metadata\": {},\n \"source\": [\n \"### Update the bar chart every 2 seconds using callback\"\n ]\n },\n {\n \"cell_type\": \"code\",\n \"execution_count\": null,\n \"metadata\": {},\n \"outputs\": [],\n \"source\": [\n \"update_func_js = \\\"\\\"\\\"\\n\",\n \"function set_update(div_id, _){ \\n\",\n \" comm = new CommAPI(\\\"random_array\\\", (data) => {\\n\",\n \" d3.select(div_id).selectAll(\\\"*\\\").remove();\\n\",\n \" bar_chart(div_id, data);\\n\",\n \" });\\n\",\n \" comm.call({n: 5})\\n\",\n \" setInterval(function(){ comm.call({n: 5}) }, 2000);\\n\",\n \"}\\n\",\n \"\\\"\\\"\\\"\\n\",\n \"\\n\",\n \"execute_js(library_list=[d3_lib_url, bar_chart_lib, update_func_js], main_function=\\\"set_update\\\", callbacks=callbacks)\"\n ]\n },\n {\n \"cell_type\": \"code\",\n \"execution_count\": null,\n \"metadata\": {},\n \"outputs\": [],\n \"source\": []\n }\n ],\n \"metadata\": {\n \"kernelspec\": {\n \"display_name\": \"Python 3\",\n \"language\": \"python\",\n \"name\": \"python3\"\n },\n \"language_info\": {\n \"codemirror_mode\": {\n \"name\": \"ipython\",\n \"version\": 3\n },\n \"file_extension\": \".py\",\n \"mimetype\": \"text/x-python\",\n \"name\": \"python\",\n \"nbconvert_exporter\": \"python\",\n \"pygments_lexer\": \"ipython3\",\n \"version\": \"3.8.5\"\n }\n },\n \"nbformat\": 4,\n \"nbformat_minor\": 4\n}\n" }, { "path": "Examples/4_Bidirectional_Comm/bar_chart_lib.js", "content": "function bar_chart(div_id, data_dict){\n const data = data_dict.array;\n const div = d3.select(div_id)\n const height = data.length * 20;\n \n const scaleY = d3.scale.ordinal()\n .domain(d3.range(data.length))\n .rangeRoundBands([0, height], .1);\n const scaleX = d3.scale.linear()\n .domain(d3.extent(data))\n .range([1, 120]);\n \n const svg = div.append(\"svg\")\n .style(\"width\", \"120px\")\n .style(\"height\", height+\"px\");\n \n svg.selectAll(\"rect\")\n .data(data)\n .enter()\n .append(\"rect\")\n .attr(\"x\", 0)\n .attr(\"y\", (d, i) => scaleY(i))\n .attr(\"width\", d => scaleX(d))\n .attr(\"height\", scaleY.rangeBand());\n}\n" }, { "path": "Examples/5_Webpack_BaseballAnnotator_Bidirectional/BaseballAnnotator.ipynb", "content": "{\n \"cells\": [\n {\n \"cell_type\": \"markdown\",\n \"metadata\": {},\n \"source\": [\n \"# Baseball Visualizer and Annotator - Bidirectional communication\"\n ]\n },\n {\n \"cell_type\": \"markdown\",\n \"metadata\": {},\n \"source\": [\n \"This visualization shows an interactive chart that displays baseball game trajectories. The user can control the progress of the play using a slider. Furthermore, the user can select a player or the ball to edit its trajectory (either clicking on the field, or using the button \\\"Clear trajectory\\\"). Visualization based on the paper HistoryTracker (Ono et al, 2019).\"\n ]\n },\n {\n \"cell_type\": \"markdown\",\n \"metadata\": {},\n \"source\": [\n \"### Loading code bundle (built with Webpack)\\n\",\n \"\\n\",\n \"Source code for the bundle is in BaseballVisualizer/js.\\n\",\n \"\\n\",\n \"To build the library from scratch, run\\n\",\n \"\\n\",\n \"```\\n\",\n \"cd BaseballVisualizer\\n\",\n \"npm install\\n\",\n \"npm run build\\n\",\n \"```\"\n ]\n },\n {\n \"cell_type\": \"code\",\n \"execution_count\": null,\n \"metadata\": {},\n \"outputs\": [],\n \"source\": [\n \"with open(\\\"BaseballVisualizer/build/baseballvisualizer.js\\\", \\\"r\\\") as f:\\n\",\n \" code_bundle = f.read()\"\n ]\n },\n {\n \"cell_type\": \"markdown\",\n \"metadata\": {},\n \"source\": [\n \"### Loading the data (baseball play trajectory in CSV)\"\n ]\n },\n {\n \"cell_type\": \"code\",\n \"execution_count\": null,\n \"metadata\": {},\n \"outputs\": [],\n \"source\": [\n \"import pandas as pd\\n\",\n \"play_csv = pd.read_csv(\\\"./BaseballVisualizer/play_annotated.csv\\\")\\n\",\n \"data_dict = {'tracking': play_csv.to_json(orient=\\\"records\\\")}\"\n ]\n },\n {\n \"cell_type\": \"markdown\",\n \"metadata\": {},\n \"source\": [\n \"### Setting up callback\\n\",\n \"\\n\",\n \"The callback function will set the received_trajectory variable when the user clicks the button \\\"Submit\\\"\"\n ]\n },\n {\n \"cell_type\": \"code\",\n \"execution_count\": null,\n \"metadata\": {},\n \"outputs\": [],\n \"source\": [\n \"received_trajectory = None\\n\",\n \"\\n\",\n \"def receive_trajectory(data):\\n\",\n \" global received_trajectory \\n\",\n \" received_trajectory = data['trajectory']\\n\",\n \" return {\\\"received\\\": True}\\n\",\n \" \\n\",\n \"callbacks = {'submit_trajectory': receive_trajectory}\"\n ]\n },\n {\n \"cell_type\": \"markdown\",\n \"metadata\": {},\n \"source\": [\n \"In javascript, the callback call is done in BaseballVisualizer/js/TrajectoryAnnotator.js\\n\",\n \"\\n\",\n \"```Javascript\\n\",\n \"function submitTrajectoryToServer(tracking){\\n\",\n \" const alert_sent = ()=>{alert(\\\"Trajectory sent to Jupyter Notebook.\\\")};\\n\",\n \" let comm = new CommAPI(\\\"submit_trajectory\\\", alert_sent)\\n\",\n \"\\n\",\n \" // Send data\\n\",\n \" comm.call({'trajectory': tracking})\\n\",\n \"}\\n\",\n \"```\"\n ]\n },\n {\n \"cell_type\": \"markdown\",\n \"metadata\": {},\n \"source\": [\n \"### Rendering Visualization\"\n ]\n },\n {\n \"cell_type\": \"code\",\n \"execution_count\": null,\n \"metadata\": {},\n \"outputs\": [],\n \"source\": [\n \"from notebookjs import execute_js\\n\",\n \"\\n\",\n \"execute_js(library_list=code_bundle, \\n\",\n \" main_function=\\\"baseballvisualizer.renderBaseballAnnotator\\\", \\n\",\n \" data_dict=data_dict, \\n\",\n \" callbacks=callbacks)\"\n ]\n },\n {\n \"cell_type\": \"code\",\n \"execution_count\": null,\n \"metadata\": {},\n \"outputs\": [],\n \"source\": [\n \"received_trajectory\"\n ]\n },\n {\n \"cell_type\": \"code\",\n \"execution_count\": null,\n \"metadata\": {},\n \"outputs\": [],\n \"source\": []\n }\n ],\n \"metadata\": {\n \"kernelspec\": {\n \"display_name\": \"Python 3\",\n \"language\": \"python\",\n \"name\": \"python3\"\n },\n \"language_info\": {\n \"codemirror_mode\": {\n \"name\": \"ipython\",\n \"version\": 3\n },\n \"file_extension\": \".py\",\n \"mimetype\": \"text/x-python\",\n \"name\": \"python\",\n \"nbconvert_exporter\": \"python\",\n \"pygments_lexer\": \"ipython3\",\n \"version\": \"3.8.5\"\n }\n },\n \"nbformat\": 4,\n \"nbformat_minor\": 4\n}\n" }, { "path": "Examples/5_Webpack_BaseballAnnotator_Bidirectional/BaseballVisualizer/js/DraggableTimeline.js", "content": "import React from \"react\";\nimport PropTypes from 'prop-types';\nimport * as d3 from 'd3';\nimport Slider from 'rc-slider';\nimport 'rc-slider/assets/index.css';\n\nexport default class DraggableTimeline extends React.Component {\n shouldComponentUpdate(nextProps, nextState) {\n if (this.props.tracking === nextProps.tracking) {\n return false;\n }\n return true;\n }\n\n render () {\n const tracking = this.props.tracking;\n const annotatedPoints = {};\n\n tracking.forEach(({x, y, t}, idx) =>\n {\n annotatedPoints[t] = {};\n });\n\n const createSliderWithTooltip = Slider.createSliderWithTooltip;\n const SliderTP = createSliderWithTooltip(Slider);\n\n return (\n
\n {this.props.onDragTime(value)}}\n marks={annotatedPoints}\n activeDotStyle={{ borderColor: 'steelblue' }}\n dotStyle={{borderColor: 'steelblue' }}\n trackStyle={{ backgroundColor: 'steelblue' }}\n railStyle={{ backgroundColor: 'steelblue' }}\n width={this.props.width}\n />\n
\n );\n }\n}\n\nDraggableTimeline.propTypes = {\n width: PropTypes.number.isRequired,\n height: PropTypes.number.isRequired,\n tracking: PropTypes.array,\n playerHead: PropTypes.number,\n margin: PropTypes.object,\n onDragTime: PropTypes.func.isRequired,\n trackingDuration: PropTypes.number.isRequired,\n};\n\nDraggableTimeline.defaultProps = {\n width: 400,\n height: 10,\n margin: {top:10, bottom: 10, left: 10, right:10}\n};\n" }, { "path": "Examples/5_Webpack_BaseballAnnotator_Bidirectional/BaseballVisualizer/js/PlayDiagram.js", "content": "import React, { Component } from 'react';\nimport PropTypes from \"prop-types\";\nimport { mapFieldSVG, mapSVGField, constants, mapFieldSVGY, mapFieldSVGX, interpolatePositions } from './helpers';\nimport $ from \"jquery\";\nimport * as d3 from \"d3\";\nimport fieldsvg from \"./field.svg\";\n\nexport default class PlayDiagram extends Component {\n render() {\n let ball = null;\n\n let line = d3.line()\n .x((d) => {\n return mapFieldSVGX(d.x);\n })\n .y((d) => {\n return mapFieldSVGY(d.y);\n });\n\n const lineElems = [];\n const endElems = [];\n\n constants.gameElements.forEach( elem => {\n if (this.props.tracking && this.props.tracking[elem] && this.props.tracking[elem].length > 0){\n const tracking = this.props.tracking;\n const newTrackingElem = [];\n for (let i = 0; i < tracking[elem].length; ++i){\n if (tracking[elem][i].t > this.props.playUpTo){\n break;\n }\n newTrackingElem.push(tracking[elem][i]);\n }\n const lastPos = interpolatePositions(this.props.playUpTo, tracking[elem]);\n newTrackingElem.push( {...lastPos, t: this.props.playUpTo} );\n lineElems.push(\n );\n\n if (elem === this.props.annotationElem) {\n endElems.push();\n\n } else {\n endElems.push(\n \n );\n }\n }\n });\n return (\n {\n let container = $(\"#playDiagramBallSVG\").get(0).getBoundingClientRect();\n let x = evt.clientX - container.left;\n let y = evt.clientY - container.top;\n const scaleX = 250/this.props.width;\n const scaleY = 250/this.props.height;\n let mapped = mapSVGField([x * scaleX, y * scaleY]);\n this.props.onClick(mapped);\n }}>\n \n {lineElems}\n {endElems}\n {ball}\n \n );\n }\n}\n\nPlayDiagram.propTypes = {\n width: PropTypes.number.isRequired,\n height: PropTypes.number.isRequired,\n onClick: PropTypes.func,\n playUpTo: PropTypes.number,\n tracking: PropTypes.object,\n annotationElem: PropTypes.string\n};\n\nPlayDiagram.defaultProps = {\n width: 500,\n height: 500\n};\n" }, { "path": "Examples/5_Webpack_BaseballAnnotator_Bidirectional/BaseballVisualizer/js/TrajectoryAnnotator.js", "content": "import React, { Component } from 'react';\nimport PlayDiagram from './PlayDiagram';\nimport {interpolatePositions, constants, convert_data_format} from './helpers';\nimport {Container, Row, Col, Button} from 'react-bootstrap';\nimport 'rc-select/assets/index.less';\n\nimport DraggableTimeline from \"./DraggableTimeline\";\nimport PropTypes from 'prop-types';\n\nfunction submitTrajectoryToServer(tracking){\n const alert_sent = ()=>{alert(\"Trajectory sent to Jupyter Notebook.\")};\n let comm = new CommAPI(\"submit_trajectory\", alert_sent)\n\n // Send data\n comm.call({'trajectory': tracking})\n}\n\nfunction convertRawTrackingToTrajectory(rawTracking) {\n if (rawTracking === null) return [];\n let tracking = Object.create(null);\n constants.gameElements.forEach(element => {\n tracking[element] = [];\n for (let i = 0; i < rawTracking.length; ++i) {\n if (rawTracking[i][element + \"_x\"] !== null) {\n tracking[element].push({\n x: rawTracking[i][element + \"_x\"],\n y: rawTracking[i][element + \"_y\"],\n t: rawTracking[i][\"time_elapsed_sec\"]\n });\n }\n }\n });\n return tracking;\n}\n\nexport default class TrajectoryAnnotator extends Component {\n constructor(props){\n super(props);\n this.state = {\n tracking: convertRawTrackingToTrajectory(this.props.tracking),\n trackingDuration: this.props.tracking[this.props.tracking.length-1].time_elapsed_sec,\n playerHead: 0,\n curTracking: \"B\"\n };\n this.clickPlayDiagram = this.clickPlayDiagram.bind(this);\n }\n\n clickPlayDiagram(position) {\n const curTracking = this.state.curTracking;\n let newTracking = this.state.tracking[curTracking].filter(annotation => {\n return Math.abs(annotation.t - this.state.playerHead) > 1e-1;\n });\n newTracking.push({\n x: position[0],\n y: position[1],\n t: this.state.playerHead\n });\n const allTrackings = {\n ...this.state.tracking,\n };\n allTrackings[curTracking] = newTracking;\n this.setState({tracking: allTrackings});\n }\n\n render() {\n return (\n
\n Selected Position\n
\n {\n constants.gameElements.map((elem) => {\n return \n })\n }\n
\n \n {this.setState({playerHead: time})}}\n trackingDuration={this.state.trackingDuration}\n />\n\n {\n const originalDataFormat = convert_data_format(this.state.tracking);\n submitTrajectoryToServer(originalDataFormat);\n }}\n >\n Submit\n \n\n {\n let newTracking = {\n ...this.state.tracking\n };\n newTracking[this.state.curTracking] = [];\n this.setState({tracking: newTracking});\n }}\n >\n Clear trajectory\n \n
\n );\n }\n}\n\n\nTrajectoryAnnotator.propTypes = {\n tracking: PropTypes.arrayOf(PropTypes.object).isRequired\n};" }, { "path": "Examples/5_Webpack_BaseballAnnotator_Bidirectional/BaseballVisualizer/js/helpers.js", "content": "import {linear} from 'everpolate';\n\nexport const constants = {\n gameElements: [\"P\", \"B\", \"R@1\", \"R@2\", \"R@3\", \"1B\", \"2B\", \"3B\", \"SS\", \"LF\", \"CF\", \"RF\", \"C\",\n \"BALL\"],\n gameElementsDesc: {\n \"P\": \"Pitcher\",\n \"B\": \"Batter\",\n \"R@1\": \"Runner at first\",\n \"R@2\": \"Runner at second\",\n \"R@3\": \"Runner at third\",\n \"1B\": \"First baseman\",\n \"2B\": \"Second baseman\",\n \"3B\": \"Third baseman\",\n \"SS\": \"Shortstop\",\n \"LF\": \"Left fielder\",\n \"CF\": \"Center fielder\",\n \"RF\": \"Right fielder\",\n \"C\": \"Catcher\",\n \"BALL\": \"Ball\"\n },\n};\n\nconst input2ndBase = [0.0, 127.2792206],\n outputHomePlate = [125.2, 203.5],\n output2ndBase = [125.2, 150.8],\n inputScale = 1.0 / input2ndBase[1],\n outputScale = 1.0 / (output2ndBase[1] - outputHomePlate[1]);\n\nexport function mapFieldSVGX(x){\n const x2 = (((-x) * inputScale) / outputScale) + outputHomePlate[0];\n return x2;\n}\n\nexport function mapFieldSVGY(y){\n const y2 = (y * inputScale) / outputScale + outputHomePlate[1];\n return y2;\n}\n\nexport function mapFieldSVG([x, y]){\n const x2 = (((-x) * inputScale) / outputScale) + outputHomePlate[0];\n const y2 = (y * inputScale) / outputScale + outputHomePlate[1];\n return [x2, y2];\n}\n\nexport function mapSVGField([x2, y2]){\n const x = -((x2 - outputHomePlate[0]) * outputScale) / inputScale;\n const y = ((y2 - outputHomePlate[1]) * outputScale) / inputScale;\n return [x, y];\n}\n\nexport function interpolatePositions(tQuery, positions) {\n //positions: array of [{x, y, t}, ...]\n if (positions.length === 1){\n return {x: positions[0].x, y:positions[0].y};\n }\n positions.sort((a,b) => a.t - b.t);\n if (tQuery <= positions[0].t) {\n return {x: positions[0].x, y: positions[0].y}\n }\n if (tQuery >= positions[positions.length-1].t) {\n return {x: positions[positions.length-1].x, y: positions[positions.length-1].y}\n }\n const t = positions.map(p=>p.t);\n const x = positions.map(p=>p.x);\n const y = positions.map(p=>p.y);\n const mappedX = linear(tQuery, t, x);\n const mappedY = linear(tQuery, t, y);\n return {x: mappedX, y: mappedY};\n}\n\n\nexport function convert_data_format(tracking){\n let csvObj = {};\n constants.gameElements.forEach(elem => {\n tracking[elem].forEach( ({x, y, t}) => {\n if (!csvObj[t]) {\n csvObj[t] = {\"time_elapsed_sec\": t};\n constants.gameElements.forEach(ename => {\n csvObj[t][ename + \"_x\"] = null;\n csvObj[t][ename + \"_y\"] = null;\n })\n }\n csvObj[t][elem + \"_x\"] = x;\n csvObj[t][elem + \"_y\"] = y;\n });\n });\n const timeKeys = Object.keys(csvObj);\n timeKeys.sort((a, b) => a - b);\n const csvArray = [];\n timeKeys.forEach(key => {\n csvArray.push(csvObj[key]);\n });\n return csvArray;\n}" }, { "path": "Examples/5_Webpack_BaseballAnnotator_Bidirectional/BaseballVisualizer/js/index.js", "content": "import React from \"react\";\nimport ReactDOM from \"react-dom\";\nimport { select } from \"d3-selection\";\nimport TrajectoryAnnotator from \"./TrajectoryAnnotator\";\n\nexport function renderBaseballAnnotator(divName, data){\n\tReactDOM.render(\n\t\t\n\t\t, select(divName).node());\n}\n" }, { "path": "Examples/5_Webpack_BaseballAnnotator_Bidirectional/BaseballVisualizer/package.json", "content": "{\n \"name\": \"baseballvisualizer\",\n \"version\": \"1.0.0\",\n \"description\": \"library to plot and edit baseball trajectories\",\n \"main\": \"./js/index.js\",\n \"scripts\": {\n \"test\": \"echo \\\"Error: no test specified\\\" && exit 1\",\n \"build\": \"webpack\",\n \"start\": \"webpack-dev-server --progress --colors --content-base dist/\"\n },\n \"author\": \"Jorge Piazentin Ono\",\n \"license\": \"UNLICENSED\",\n \"devDependencies\": {\n \"@babel/core\": \"^7.12.9\",\n \"@babel/preset-env\": \"^7.12.7\",\n \"@babel/preset-react\": \"^7.12.7\",\n \"babel-loader\": \"^8.2.2\",\n \"css-loader\": \"^2.1.1\",\n \"file-loader\": \"^3.0.1\",\n \"less\": \"^4.0.0\",\n \"less-loader\": \"^7.1.0\",\n \"prop-types\": \"^15.6.2\",\n \"react\": \"^16.14.0\",\n \"react-dom\": \"^16.14.0\",\n \"style-loader\": \"^0.23.1\",\n \"url-loader\": \"^4.1.1\",\n \"webpack\": \"^4.44.2\",\n \"webpack-cli\": \"^3.3.11\",\n \"webpack-dev-server\": \"^3.11.0\",\n \"worker-loader\": \"^2.0.0\"\n },\n \"dependencies\": {\n \"@babel/polyfill\": \"^7.12.1\",\n \"@material-ui/core\": \"^4.11.2\",\n \"@material-ui/icons\": \"^4.11.2\",\n \"crossfilter2\": \"^1.5.4\",\n \"d3\": \"^6.3.1\",\n \"d3-array\": \"^2.9.0\",\n \"d3-axis\": \"^1.0.12\",\n \"d3-fetch\": \"^1.1.2\",\n \"d3-scale\": \"^2.2.2\",\n \"d3-scale-chromatic\": \"^1.3.3\",\n \"d3-selection\": \"^1.4.0\",\n \"d3-shape\": \"^1.3.7\",\n \"d3-transition\": \"^1.3.2\",\n \"d3-zoom\": \"^1.8.3\",\n \"dagre\": \"^0.8.4\",\n \"everpolate\": \"0.0.3\",\n \"install\": \"^0.12.2\",\n \"jquery\": \"^3.5.1\",\n \"lodash\": \"^4.17.20\",\n \"npm\": \"^7.3.0\",\n \"rc-checkbox\": \"^2.3.1\",\n \"rc-select\": \"^11.5.3\",\n \"rc-slider\": \"^9.6.5\",\n \"react-bootstrap\": \"^1.4.0\",\n \"react-redux\": \"^6.0.0\",\n \"react-select\": \"^2.4.1\",\n \"redux\": \"^4.0.1\",\n \"redux-thunk\": \"^2.3.0\",\n \"styled-components\": \"^5.2.1\"\n }\n}\n" }, { "path": "Examples/5_Webpack_BaseballAnnotator_Bidirectional/BaseballVisualizer/play_annotated.csv", "content": "time_elapsed_sec,P_x,P_y,B_x,B_y,R@1_x,R@1_y,R@2_x,R@2_y,R@3_x,R@3_y,1B_x,1B_y,2B_x,2B_y,3B_x,3B_y,SS_x,SS_y,LF_x,LF_y,CF_x,CF_y,RF_x,RF_y,C_x,C_y,BALL_x,BALL_y\n0.0,-1.0465815337,62.2709968754,-2.2541642719,-2.9384709841,,,,,,,,,,,-72.29396308400649,91.01148815468284,-59.010552964461894,136.89963220401873,,,,,,,-2.2541642719,-6.5612191986,,\n3.243,,,,,,,,,,,,,,,,,,,,,,,,,,,0.1207582738,62.7943023833\n3.443,,,,,,,,,,,,,,,,,,,,,,,,,,,-1.0868244643,8.453079167\n3.68,,,,,,,,,,,55.7098071589,96.0833135434,,,,,,,,,,,,,,,,\n3.98,,,-1.0465815337,-2.9384709841,,,,,,,,,,,,,,,,,,,,,,,,\n4.03,,,,,,,,,,,,,,,,,,,,,,,139.03301609056658,260.0730714943413,,,,\n4.44,,,,,,,,,,,,,,,,,,,,,-16.74515712954728,316.82946018694093,,,,,,\n4.47,,,,,,,,,,,,,,,,,,,-129.0503517766061,243.16691316037546,,,,,,,,\n4.88,,,,,,,,,,,,,,,,,-42.10439463049605,136.89963220401873,,,,,,,,,,\n5.493,,,,,,,,,,,,,,,,,,,,,,,,,,,31.5179094655,156.9857559583\n5.81,,,,,,,,,,,64.1628863259,81.5923206857,,,,,,,,,,,,,,,,\n6.34,,,,,,,,,,,,,,,,,,,,,,,128.16477144730283,217.8076756594267,,,,\n6.57,,,,,,,,,,,,,,,,,,,-102.48353153751694,233.50625125525212,,,,,,,,\n7.25,,,,,,,,,,,,,,,,,,,,,,,,,3.7837494188,-0.5233055079,,\n7.383,,,,,,,,,,,,,,,,,,,,,,,,,,,61.707477919,65.2094678596\n7.503,,,,,,,,,,,,,30.3103267273,156.9857559583,,,,,,,,,,,,,,\n8.8,,,,,,,,,,,,,,,,,,,,,-33.65131546351312,249.20482685107754,,,,,,\n8.81,,,,,,,,,,,,,,,,,-48.142308321198136,126.03138756075496,,,,,,,,,,\n8.85,3.7837494188,52.6103349703,,,,,,,,,,,,,,,,,-102.48353153751694,214.18492744500543,,,,,,,,\n8.89,,,62.9553035877,65.8937450899,,,,,,,64.1628863259,61.0634141373,,,,,,,,,,,131.78751966172408,180.37261077707376,,,,\n8.893,,,,,,,,,,,,,38.7634058943,153.3630077438,,,,,,,,,,,,,,\n" }, { "path": "Examples/5_Webpack_BaseballAnnotator_Bidirectional/BaseballVisualizer/webpack.config.js", "content": "const config = {\n entry: ['./js/index.js'],\n output: {\n path: __dirname + '/build',\n filename: 'baseballvisualizer.js',\n library: 'baseballvisualizer'\n },\n module: {\n rules: [\n {\n test: /\\.js$/,\n exclude: /node_modules/,\n loader: 'babel-loader',\n options: {\n presets: ['@babel/preset-env', '@babel/react']\n }\n },\n {\n test: /\\.css$/,\n use: [\n 'style-loader',\n 'css-loader'\n ]\n },\n {\n test: /\\.less$/,\n use: ['style-loader', 'css-loader', 'less-loader'],\n },\n {\n test: /\\.(jpg|png|svg)$/,\n loader: \"url-loader\",\n options: {\n limit: Infinity // everything\n }\n }\n ]\n },\n resolve: {\n extensions: ['.js']\n },\n devServer:{\n writeToDisk:true,\n hot:false,\n inline: false,\n },\n mode: 'development'\n};\nmodule.exports = config;\n" }, { "path": "Examples/6_HelloWorld_Bidirectional/HelloWorld_Bidirectional.ipynb", "content": "{\n \"cells\": [\n {\n \"cell_type\": \"markdown\",\n \"metadata\": {\n \"id\": \"IaxAGrTGttuV\"\n },\n \"source\": [\n \"# notebookJS Colab HelloWorld\\n\",\n \"\\n\",\n \"In this notebook, we show how to use notebookJS to run custom Javascript code. We also show how to send messages between Python and Javascript.\"\n ]\n },\n {\n \"cell_type\": \"code\",\n \"execution_count\": null,\n \"metadata\": {\n \"id\": \"vYD-yjPtn_ik\"\n },\n \"outputs\": [],\n \"source\": [\n \"!pip install notebookjs\"\n ]\n },\n {\n \"cell_type\": \"markdown\",\n \"metadata\": {\n \"id\": \"BjePMHoyt9TF\"\n },\n \"source\": [\n \"## Defining the JavaScript drawing function.\\n\",\n \"\\n\",\n \"The function requests a message to python every 1 second. The callback identifier is called *get_hello*\"\n ]\n },\n {\n \"cell_type\": \"code\",\n \"execution_count\": null,\n \"metadata\": {\n \"id\": \"10am7Nm9oCc9\"\n },\n \"outputs\": [],\n \"source\": [\n \"helloworld_js = \\\"\\\"\\\"\\n\",\n \"function helloworld(div_id, data){\\n\",\n \" comm = new CommAPI(\\\"get_hello\\\", (ret) => {\\n\",\n \" document.querySelector(div_id).textContent = ret.text;\\n\",\n \" });\\n\",\n \" setInterval(() => {comm.call({})}, 1000);\\n\",\n \" comm.call({});\\n\",\n \"}\\n\",\n \"\\\"\\\"\\\"\"\n ]\n },\n {\n \"cell_type\": \"markdown\",\n \"metadata\": {\n \"id\": \"zsXaw6XxuJF2\"\n },\n \"source\": [\n \"## Defining the Python callback\"\n ]\n },\n {\n \"cell_type\": \"code\",\n \"execution_count\": null,\n \"metadata\": {\n \"id\": \"L0ucikc4oIOW\"\n },\n \"outputs\": [],\n \"source\": [\n \"import random\\n\",\n \"def hello_world_random(data):\\n\",\n \" hello_world_languages = [\\n\",\n \" \\\"Ola Mundo\\\", # Portuguese\\n\",\n \" \\\"Hello World\\\", # English\\n\",\n \" \\\"Hola Mundo\\\", # Spanish\\n\",\n \" \\\"Geiá sou Kósme\\\", # Greek\\n\",\n \" \\\"Kon'nichiwa sekai\\\", # Japanese\\n\",\n \" \\\"Hallo Welt\\\", # German\\n\",\n \" \\\"namaste duniya\\\" #Hindi\\n\",\n \" ]\\n\",\n \" i = random.randint(0, len(hello_world_languages)-1)\\n\",\n \" return {'text': hello_world_languages[i]}\"\n ]\n },\n {\n \"cell_type\": \"markdown\",\n \"metadata\": {\n \"id\": \"g-rkBdq7uXSL\"\n },\n \"source\": [\n \"## Running the javascript function with Python callbacks\"\n ]\n },\n {\n \"cell_type\": \"code\",\n \"execution_count\": null,\n \"metadata\": {\n \"id\": \"HaxtaaB-pj0z\"\n },\n \"outputs\": [],\n \"source\": [\n \"from notebookjs import execute_js\\n\",\n \"execute_js(helloworld_js, \\\"helloworld\\\", callbacks={\\\"get_hello\\\": hello_world_random})\"\n ]\n },\n {\n \"cell_type\": \"code\",\n \"execution_count\": null,\n \"metadata\": {\n \"id\": \"848VKX8jqGbW\"\n },\n \"outputs\": [],\n \"source\": []\n }\n ],\n \"metadata\": {\n \"colab\": {\n \"collapsed_sections\": [],\n \"name\": \"HelloWorld_notebookJS_Colab.ipynb\",\n \"provenance\": []\n },\n \"kernelspec\": {\n \"display_name\": \"Python 3\",\n \"language\": \"python\",\n \"name\": \"python3\"\n },\n \"language_info\": {\n \"codemirror_mode\": {\n \"name\": \"ipython\",\n \"version\": 3\n },\n \"file_extension\": \".py\",\n \"mimetype\": \"text/x-python\",\n \"name\": \"python\",\n \"nbconvert_exporter\": \"python\",\n \"pygments_lexer\": \"ipython3\",\n \"version\": \"3.8.5\"\n }\n },\n \"nbformat\": 4,\n \"nbformat_minor\": 1\n}\n" }, { "path": "Examples/7_D3_scatterplot/D3_Scatter.ipynb", "content": "{\n \"cells\": [\n {\n \"cell_type\": \"markdown\",\n \"metadata\": {},\n \"source\": [\n \"# D3 Scatter Plot\"\n ]\n },\n {\n \"cell_type\": \"markdown\",\n \"metadata\": {},\n \"source\": [\n \"D3 V3 scatter plot. Code adapted from https://www.d3-graph-gallery.com/graph/scatter_animation_start.html\"\n ]\n },\n {\n \"cell_type\": \"markdown\",\n \"metadata\": {},\n \"source\": [\n \"### Loading libraries\"\n ]\n },\n {\n \"cell_type\": \"code\",\n \"execution_count\": null,\n \"metadata\": {},\n \"outputs\": [],\n \"source\": [\n \"with open(\\\"scatterplot_lib.js\\\", \\\"r\\\") as f:\\n\",\n \" scatterplot_lib = f.read()\\n\",\n \" \\n\",\n \"d3_lib_url = \\\"https://d3js.org/d3.v3.min.js\\\"\\n\",\n \"\\n\",\n \"css = \\\"\\\"\\\"\\n\",\n \".axis path,\\n\",\n \".axis line {\\n\",\n \" fill: none;\\n\",\n \" stroke: slategray;\\n\",\n \" shape-rendering: crispEdges;\\n\",\n \"}\\n\",\n \"\\\"\\\"\\\"\"\n ]\n },\n {\n \"cell_type\": \"markdown\",\n \"metadata\": {},\n \"source\": [\n \"### Loading data\"\n ]\n },\n {\n \"cell_type\": \"code\",\n \"execution_count\": null,\n \"metadata\": {},\n \"outputs\": [],\n \"source\": [\n \"import pandas as pd\\n\",\n \"data = pd.read_csv(\\\"Prices.csv\\\").to_dict(orient=\\\"records\\\")\"\n ]\n },\n {\n \"cell_type\": \"markdown\",\n \"metadata\": {},\n \"source\": [\n \"### Plotting Scatter Plot\"\n ]\n },\n {\n \"cell_type\": \"code\",\n \"execution_count\": null,\n \"metadata\": {},\n \"outputs\": [],\n \"source\": [\n \"from notebookjs import execute_js\\n\",\n \"execute_js(library_list=[d3_lib_url, scatterplot_lib], main_function=\\\"scatter\\\", data_dict=data, css_list=css)\"\n ]\n },\n {\n \"cell_type\": \"code\",\n \"execution_count\": null,\n \"metadata\": {},\n \"outputs\": [],\n \"source\": []\n }\n ],\n \"metadata\": {\n \"kernelspec\": {\n \"display_name\": \"Python 3\",\n \"language\": \"python\",\n \"name\": \"python3\"\n },\n \"language_info\": {\n \"codemirror_mode\": {\n \"name\": \"ipython\",\n \"version\": 3\n },\n \"file_extension\": \".py\",\n \"mimetype\": \"text/x-python\",\n \"name\": \"python\",\n \"nbconvert_exporter\": \"python\",\n \"pygments_lexer\": \"ipython3\",\n \"version\": \"3.8.5\"\n }\n },\n \"nbformat\": 4,\n \"nbformat_minor\": 4\n}\n" }, { "path": "Examples/7_D3_scatterplot/Prices.csv", "content": "GrLivArea,SalePrice\n1710,208500\n1262,181500\n1786,223500\n1717,140000\n2198,250000\n1362,143000\n1694,307000\n2090,200000\n1774,129900\n1077,118000\n1040,129500\n2324,345000\n912,144000\n1494,279500\n1253,157000\n854,132000\n1004,149000\n1296,90000\n1114,159000\n1339,139000\n2376,325300\n1108,139400\n1795,230000\n1060,129900\n1060,154000\n1600,256300\n900,134800\n1704,306000\n1600,207500\n520,68500\n1317,40000\n1228,149350\n1234,179900\n1700,165500\n1561,277500\n2452,309000\n1097,145000\n1297,153000\n1057,109000\n1152,82000\n1324,160000\n1328,170000\n884,144000\n938,130250\n1150,141000\n1752,319900\n2149,239686\n1656,249700\n1452,113000\n955,127000\n1470,177000\n1176,114500\n816,110000\n1842,385000\n1360,130000\n1425,180500\n1739,172500\n1720,196500\n2945,438780\n780,124900\n1158,158000\n1111,101000\n1370,202500\n1710,140000\n2034,219500\n2473,317000\n2207,180000\n1479,226000\n747,80000\n2287,225000\n2223,244000\n845,129500\n1718,185000\n1086,144900\n1605,107400\n988,91000\n952,135750\n1285,127000\n1768,136500\n1230,110000\n2142,193500\n1337,153500\n1563,245000\n1065,126500\n1474,168500\n2417,260000\n1560,174000\n1224,164500\n1526,85000\n990,123600\n1040,109900\n1235,98600\n964,163500\n2291,133900\n1786,204750\n1470,185000\n1588,214000\n960,94750\n835,83000\n1225,128950\n1610,205000\n1732,178000\n1535,118964\n1226,198900\n1818,169500\n1992,250000\n1047,100000\n789,115000\n1517,115000\n1844,190000\n1855,136900\n1430,180000\n2696,383970\n2259,217000\n2320,259500\n1458,176000\n1092,139000\n1125,155000\n3222,320000\n1456,163990\n988,180000\n1123,100000\n1080,136000\n1199,153900\n1586,181000\n754,84500\n958,128000\n840,87000\n1348,155000\n1053,150000\n2157,226000\n2054,244000\n1327,150750\n1296,220000\n1721,180000\n1682,174000\n1214,143000\n1959,171000\n1852,230000\n1764,231500\n864,115000\n1734,260000\n1385,166000\n1501,204000\n1728,125000\n1709,130000\n875,105000\n2035,222500\n1080,141000\n1344,115000\n969,122000\n1710,372402\n1993,190000\n1252,235000\n1200,125000\n1096,79000\n1040,109500\n1968,269500\n1947,254900\n2462,320000\n1232,162500\n2668,412500\n1541,220000\n882,103200\n1616,152000\n1355,127500\n1867,190000\n2161,325624\n1720,183500\n1707,228000\n1382,128500\n1656,215000\n1767,239000\n1362,163000\n1651,184000\n2158,243000\n2060,211000\n1920,172500\n2234,501837\n968,100000\n1525,177000\n1802,200100\n1340,120000\n2082,200000\n1252,127000\n3608,475000\n1217,173000\n1656,135000\n1224,153337\n1593,286000\n2727,315000\n1479,184000\n1431,192000\n1709,130000\n864,127000\n1456,148500\n1726,311872\n3112,235000\n2229,104000\n1713,274900\n1121,140000\n1279,171500\n1310,112000\n848,149000\n1284,110000\n1442,180500\n1696,143900\n1100,141000\n2062,277000\n1092,145000\n864,98000\n1212,186000\n1852,252678\n990,156000\n1392,161750\n1236,134450\n1436,210000\n1328,107000\n1954,311500\n1248,167240\n1498,204900\n2267,200000\n1552,179900\n864,97000\n2392,386250\n1302,112000\n2520,290000\n987,106000\n912,125000\n1555,192500\n1194,148000\n2794,403000\n987,94500\n894,128200\n1960,216500\n987,89500\n1414,185500\n1744,194500\n1694,318000\n1487,113000\n1566,262500\n866,110500\n1440,79000\n1217,120000\n2110,205000\n1872,241500\n1928,137000\n1375,140000\n1668,180000\n2144,277000\n1306,76500\n1625,235000\n1640,173000\n1302,158000\n1314,145000\n2291,230000\n1728,207500\n1604,220000\n1792,231500\n882,97000\n1382,176000\n2574,276000\n1212,151000\n1316,130000\n764,73000\n1422,175500\n1511,185000\n2192,179500\n778,120500\n1113,148000\n1939,266000\n1363,241500\n2270,290000\n1632,139000\n816,124500\n1548,205000\n1560,201000\n864,141000\n2121,415298\n2022,192000\n1982,228500\n1262,185000\n1314,207500\n1468,244600\n1575,179200\n1250,164700\n1734,159000\n858,88000\n900,122000\n1396,153575\n1919,233230\n1716,135900\n1716,131000\n2263,235000\n1644,167000\n1003,142500\n1558,152000\n1950,239000\n1743,175000\n1152,158500\n1336,157000\n2452,267000\n1541,205000\n894,149900\n3493,295000\n2000,305900\n2243,225000\n1406,89500\n861,82500\n1944,360000\n1501,165600\n972,132000\n1118,119900\n2036,375000\n1641,178000\n1432,188500\n2353,260000\n1959,270000\n2646,260000\n1472,187500\n2596,342643\n2468,354000\n2730,301000\n1163,126175\n2978,242000\n803,87000\n1719,324000\n1383,145250\n2134,214500\n1192,78000\n1728,119000\n1056,139000\n1629,284000\n1358,207000\n1638,192000\n1786,228950\n1922,377426\n1536,214000\n1621,202500\n1215,155000\n1908,202900\n841,82000\n1040,87500\n1684,266000\n1112,85000\n1577,140200\n958,151500\n1478,157500\n1626,154000\n2728,437154\n1869,318061\n1453,190000\n1111,95000\n720,105900\n1595,140000\n1200,177500\n1167,173000\n1142,134000\n1352,130000\n1924,280000\n912,156000\n1505,145000\n1922,198500\n987,118000\n1574,190000\n1344,147000\n1394,159000\n1431,165000\n1268,132000\n1287,162000\n1664,172400\n1588,134432\n752,125000\n1319,123000\n1928,219500\n904,61000\n914,148000\n2466,340000\n1856,394432\n1800,179000\n1691,127000\n1301,187750\n1797,213500\n784,76000\n1953,240000\n1269,192000\n1184,81000\n1125,125000\n1479,191000\n2332,426000\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}, { "path": "Examples/7_D3_scatterplot/scatterplot_lib.js", "content": "function scatter(div_id, data){\n // Code adapted from https://www.d3-graph-gallery.com/graph/scatter_animation_start.html\n // Dataset https://raw.githubusercontent.com/holtzy/data_to_viz/master/Example_dataset/2_TwoNum.csv\n // set the dimensions and margins of the graph\n var margin = {top: 10, right: 30, bottom: 30, left: 60},\n width = 460 - margin.left - margin.right,\n height = 400 - margin.top - margin.bottom;\n // append the svg object to the body of the page\n var svg = d3.select(div_id)\n .append(\"svg\")\n .attr(\"width\", width + margin.left + margin.right)\n .attr(\"height\", height + margin.top + margin.bottom)\n .append(\"g\")\n .attr(\"transform\",\n \"translate(\" + margin.left + \",\" + margin.top + \")\")\n\n // Add X axis\n var x = d3.scale.linear()\n .domain([0, 0])\n .range([ 0, width ]);\n svg.append(\"g\")\n .attr(\"class\", \"myXaxis axis\") // Note that here we give a class to the X axis, to be able to call it later and modify it\n .attr(\"transform\", \"translate(0,\" + height + \")\")\n .call(d3.svg.axis().scale(x))\n .attr(\"opacity\", \"0\")\n\n // Add Y axis\n var y = d3.scale.linear()\n .domain([0, 500000])\n .range([ height, 0]);\n svg.append(\"g\")\n .attr(\"class\", \"axis\")\n .call(d3.svg.axis()\n .orient('left')\n .scale(y));\n\n // Add dots\n svg.append('g')\n .selectAll(\"dot\")\n .data(data)\n .enter()\n .append(\"circle\")\n .attr(\"cx\", function (d) { return x(d.GrLivArea); } )\n .attr(\"cy\", function (d) { return y(d.SalePrice); } )\n .attr(\"r\", 1.5)\n .style(\"fill\", \"#69b3a2\")\n\n // new X axis\n x.domain([0, 4000])\n svg.select(\".myXaxis\")\n .transition()\n .duration(2000)\n .attr(\"opacity\", \"1\")\n .call(d3.svg.axis().scale(x));\n\n svg.selectAll(\"circle\")\n .transition()\n .delay(function(d,i){return(i*3)})\n .duration(2000)\n .attr(\"cx\", function (d) { return x(d.GrLivArea); } )\n .attr(\"cy\", function (d) { return 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f\r\n0000000000 00000 f\r\n0000000000 00000 f\r\n0000000000 00000 f\r\n0000000000 00000 f\r\n0000000000 00000 f\r\n0000000000 00000 f\r\n0000056236 00000 n\r\n0000056432 00000 n\r\n0000057604 00000 n\r\n0000123192 00000 n\r\n0000188780 00000 n\r\n0000000000 00000 f\r\n0000052164 00000 n\r\n0000051977 00000 n\r\n0000218617 00000 n\r\n0000050553 00000 n\r\n0000053480 00000 n\r\n0000053367 00000 n\r\n0000051022 00000 n\r\n0000051416 00000 n\r\n0000051464 00000 n\r\n0000052048 00000 n\r\n0000052079 00000 n\r\n0000052404 00000 n\r\n0000052680 00000 n\r\n0000053515 00000 n\r\n0000218642 00000 n\r\ntrailer\r<<3B62822D93F749AE93EA2DBD804B1028>]>>\rstartxref\r218855\r%%EOF\r" }, { "path": "LICENSE", "content": "MIT License\n\nCopyright (c) 2021 notebookJS Developers\n\nPermission is hereby granted, free of charge, to any person obtaining a copy\nof this software and associated documentation files (the \"Software\"), to deal\nin the Software without restriction, including without limitation the rights\nto use, copy, modify, merge, publish, distribute, sublicense, and/or sell\ncopies of the Software, and to permit persons to whom the Software is\nfurnished to do so, subject to the following conditions:\n\nThe above copyright notice and this permission notice shall be included in all\ncopies or substantial portions of the Software.\n\nTHE SOFTWARE IS PROVIDED \"AS IS\", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR\nIMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,\nFITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE\nAUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER\nLIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,\nOUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE\nSOFTWARE." }, { "path": "MANIFEST.in", "content": "include notebookjs/resources/CommAPI.js\ninclude notebookjs/resources/template.html" }, { "path": "README.md", "content": "# notebookJS: seamless JavaScript integration in Python Notebooks \n\n[![made-with-python](https://img.shields.io/badge/Made%20with-Python-1f425f.svg)](https://www.python.org/)\n[![Open In Collab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/drive/1g8WOn9oZ5G_3-Y8DYmpV1MIj59dnd81u?usp=sharing)\n[![PyPI version](https://badge.fury.io/py/notebookjs.svg)](https://pypi.org/project/notebookjs)\n\n\n\n\n*notebookJS* enables the execution of custom JavaScript code in Python Notebooks (Jupyter Notebook and Google Colab). This Python library can be useful for implementing and reusing interactive Data Visualizations in the Notebook environment.\n\n*notebookJS* takes care of downloading and handling Javascript libraries and CSS stylesheets from the web. Furthermore, it supports bidirectional communication between Python and JavaScript. User interactions in HTML/JavaScript can trigger Python callbacks that process data on demand and send the results back to the front-end code.\n\nImplementation details in [our paper](https://ieeexplore.ieee.org/iel7/5992/9387473/09391750.pdf?casa_token=v05VFeWM3gwAAAAA:ra4uhd2Xpsd6lllS62Woz1IOjaSOZJGGhh4jpF_ZXOlm1Kq4HTBFHJU7Z-Ez6DDQOUE_djlI5Gk).\n\nSee our [blog post](https://jorgehpo.medium.com/introducing-notebookjs-seamless-integration-between-python-and-javascript-in-computational-e654ec3fbd18).\n\n[![ScatterPlot](https://user-images.githubusercontent.com/14821895/114492279-478ae380-9be6-11eb-8750-30ec3a206816.gif)](https://github.com/jorgehpo/notebookJS/tree/main/Examples/7_D3_scatterplot)\n\n\n## Install\n\nTo install, run:\n`pip install notebookjs`\n\nOr clone this repository and run:\n`python setup.py install`\n\n## API\n\n### execute_js\nThis method executes a javascript function and sets up the infrastructure for bidirectional communication between Python and Javascript using callbacks. \n\n```python\nexecute_js(\n library_list,\n main_function,\n data_dict={},\n callbacks={},\n css_list=[],\n)\n```\n\n**Parameters**\n\n- library_list : list of str. \n List of strings containing either 1) URL to a javascript library, 2) javascript code, 3) javascript [bundle](https://github.com/jorgehpo/notebookJS/tree/main/Examples/5_Webpack_BaseballAnnotator_Bidirectional) (Plain JS only - No support for ES6 Modules)\n- main_function : str. \n Name of the main function to be called. The function will be called with two parameters: \n , for example \"#my_div\", and .\n- data_dict : dict. \n Dictionary containing the data to be passed to \n- callbacks : dict. \n Dictionary of the form { : }. The javascript library can\n use callbacks to talk to python.\n- css_list : list of str. \n List of strings containing either 1) URL to a CSS stylesheet or 2) CSS styles\n\n**Main Function**\n\n*main_function* is the javascript function that will be run when execute_js is called. It has the following signature:\n```Javascript\nfunction main_function(div_id, data_dict)\n```\n\n**Example of Main Function**\n\nAs a simple example, we can use D3 to add a circular div to the output cell:\n\n```Javascript\nfunction draw_circle(div_id, data){\n // Function that draws a circle of color inside the div using D3\n d3.select(div_id)\n .append(\"div\")\n .style(\"width\", \"50px\")\n .style(\"height\", \"50px\")\n .style(\"background-color\", data.color)\n .style(\"border-radius\", \"50px\")\n}\n```\n\n**Callbacks**\n\n*callbacks* contains a dictionary that maps an identifier string to a Python function. Data is passed to/from callbacks using json/dicts.\n\nFor example, the following callback computes the number to the power of 2.\n\n``` Python\ndef compute_power_2(data){\n n = data.n\n n2 = n**2\n return {\"power2\": n2}\n}\n\ncallbacks = {\n \"compute_power_2\": compute_power_2\n}\n\nexecute_js(..., callbacks=callbacks)\n```\n\nIn Javascript, we can call this callback with the class *CommAPI*. *CommAPI* is automatically injected in the Javascript by *notebookJS*.\n\n``` Javascript\nlet comm = new CommAPI(\"compute_power_2\", (ret)=>{alert(\"The returned value is \" + ret.power2)})\n\ncomm.call({n: 3}) \n// An alert will be shown with the message: \"The returned value is 9\"\n```\n\nJupyter Notebook and Google Colab have different APIs for sending data to/from Javascript/Python. *CommAPI* abstracts the different APIs in a single convenient class.\n\n**Warning**: Callbacks between Python and JS are only available in Jupyter and Colab notebooks. Jupyter Lab is not supported currently.\n\n### save_html\nThis method creates a standalone HTML bundle (containing all data, JS and CSS resources) and saves it to disk. It accepts all parameters of execute_js, with the addition of *html_dest*, the path to the output file. For example, *html_dest=\"./output.html\"*\n\n```python\nsave_html(,\n html_dest,\n library_list,\n main_function,\n data_dict={},\n callbacks=None,\n css_list=[],\n)\n```\n\n**Warning:** callbacks do not work in standalone HTML files. This parameter only exists to make *execute_js* and *save_html* interoperable.\n\n## Examples\n\n### Hello World - Python Callbacks\n\nIn this example, we show how to display \"hello world\" in multiple languages using Javascript and Python. The Javascript is responsible for updating the front end and requesting a new message from Python. Python returns a random message every time the callback is invoked.\n\n![Hello World Output Gif](https://user-images.githubusercontent.com/14821895/114482788-2d94d500-9bd5-11eb-9ec3-7ee5c5d62a86.gif)\n\n**Javascript to update the div with a hello world message**\n```Python\nhelloworld_js = \"\"\"\nfunction helloworld(div_id, data){\n comm = new CommAPI(\"get_hello\", (ret) => {\n document.querySelector(div_id).textContent = ret.text;\n });\n setInterval(() => {comm.call({})}, 1000);\n comm.call({});\n}\n\"\"\"\n```\n\n**Defining the Python Callback**\n```Python\nimport random\ndef hello_world_random(data):\n hello_world_languages = [\n \"Ola Mundo\", # Portuguese\n \"Hello World\", # English\n \"Hola Mundo\", # Spanish\n \"Geiá sou Kósme\", # Greek\n \"Kon'nichiwa sekai\", # Japanese\n \"Hallo Welt\", # German\n \"Namaste duniya\", # Hindi\n \"Ni hao, shijiè\" # Chinese\n ]\n i = random.randint(0, len(hello_world_languages)-1)\n return {'text': hello_world_languages[i]}\n```\n\n**Invoking the function helloworld in notebook**\n```Python\nfrom notebookjs import execute_js\nexecute_js(helloworld_js, \"helloworld\", callbacks={\"get_hello\": hello_world_random})\n```\n\nSee this [colab notebook](https://colab.research.google.com/drive/1g8WOn9oZ5G_3-Y8DYmpV1MIj59dnd81u?usp=sharing) for a live demo.\n\n### Radial Bar Chart - Running D3 code in the Notebook\n\nPlotting a Radial Bar Chart with data loaded from Python. Adapted from this [bl.ock](https://bl.ocks.org/AntonOrlov/6b42d8676943cc933f48a43a7c7e5b6c). See [Examples/3_RadialBarChart](https://github.com/jorgehpo/notebookJS/blob/main/Examples/3_RadialBarChart/).\n\n```Python\n# Loading libraries\nd3_lib_url = \"https://d3js.org/d3.v3.min.js\"\n\nwith open(\"radial_bar.css\", \"r\") as f:\n radial_bar_css = f.read()\n \nwith open (\"radial_bar_lib.js\", \"r\") as f:\n radial_bar_lib = f.read()\n\n# Loading data\nimport pandas as pd\nenergy = pd.read_csv(\"energy.csv\")\n\n# Plotting the Radial Bar Chart\nfrom notebookjs import execute_js\nexecute_js(library_list=[d3_lib_url, radial_bar_lib], main_function=\"radial_bar\", \n data_dict=energy.to_dict(orient=\"records\"), css_list=[radial_bar_css])\n```\n\n![Radial Bar Chart](https://user-images.githubusercontent.com/14821895/114483438-536ea980-9bd6-11eb-8502-77f7a8864322.gif)\n\n### More examples\n\nPlease see the [Examples/](https://github.com/jorgehpo/notebookJS/blob/main/Examples/) folder for more examples.\n\n## Reference\n\nIf you use *notebookJS*, please reference our related work:\n\n\"*Interactive Data Visualization in Jupyter Notebooks*. JP Ono, J Freire, CT Silva - Computing in Science & Engineering, 2021\"\n\nBibtex:\n```\n@article{ono2021interactive,\n title={Interactive Data Visualization in Jupyter Notebooks},\n author={Ono, Jorge Piazentin and Freire, Juliana and Silva, Claudio T},\n journal={Computing in Science \\& Engineering},\n volume={23},\n number={2},\n pages={99--106},\n year={2021},\n publisher={IEEE}\n}\n```\n" }, { "path": "notebookjs/__init__.py", "content": "from ._display import execute_js, save_html" }, { "path": "notebookjs/_comm.py", "content": "from IPython.core.display import display, HTML, Javascript\nfrom IPython import get_ipython\n\n\ndef setup_comm_colab(api_call_id, callback):\n \"\"\"Function that connects javascript call with a Colab Notebook\"\"\"\n from google.colab import output\n from IPython import display\n def _recv(msg):\n return display.JSON(callback(msg)) # Use display.JSON to transfer an object\n output.register_callback(api_call_id, _recv)\n\ndef setup_comm_jupyter(api_call_id, callback): \n \"\"\"Function that connects javascript call with a Jupyter Notebook\"\"\"\n def _comm_api(comm, open_msg): \n @comm.on_msg\n def _recv(msg):\n ret = callback(msg['content']['data'])\n comm.send(ret)\n get_ipython().kernel.comm_manager.register_target(api_call_id, _comm_api)\n\ndef setup_comm_api(api_call_id, callback):\n \"\"\"Function that abstracts notebook connection (Jupyter or Colab) to javascript\"\"\"\n try:\n jupyter_setup = True\n setup_comm_jupyter(api_call_id, callback)\n except Exception:\n jupyter_setup = False\n try:\n colab_setup = True\n setup_comm_colab(api_call_id, callback)\n except Exception:\n colab_setup = False\n if not jupyter_setup and not colab_setup:\n print(\"Error: Cannot find Jupyter/Colab namespace for Python\")" }, { "path": "notebookjs/_display.py", "content": "from IPython.core.display import display, HTML, Javascript\nfrom string import Template, ascii_uppercase\nimport pkg_resources\nimport random\nimport re\nimport json\nfrom ._comm import setup_comm_api\n\ndef id_generator(size=15):\n \"\"\"Helper function to generate random div ids.\"\"\"\n chars = list(ascii_uppercase)\n return ''.join(random.choice(chars) for i in range(size))\n\ndef make_html(library_list, main_function, parameter_dict, css_list):\n \"\"\"Makes the HTML that will be added to the Notebook\"\"\"\n # Loading Python CommAPI\n comm_api_path = pkg_resources.resource_filename(__name__, \"resources/CommAPI.js\")\n with open(comm_api_path, \"r\") as f:\n comm_api_js = f.read()\n\n # Making sure library_list and css_list are lists.\n if type(library_list) is not list: \n library_list = [library_list]\n if type(css_list) is not list:\n css_list = [css_list]\n \n # Downloading web resources\n for idx in range(len(library_list)):\n if check_url(library_list[idx]):\n library_list[idx] = download_url(library_list[idx])\n for idx in range(len(css_list)):\n if check_url(css_list[idx]):\n css_list[idx] = download_url(css_list[idx])\n\n # Adding CommAPI to library_list \n library_list.insert(0, comm_api_js)\n\n # Generating HTML\n div_id = id_generator()\n library_bundle = '\\n\\n'.join(library_list)\n css_bundle = '\\n'.join(css_list)\n template_path = pkg_resources.resource_filename(__name__, \"resources/template.html\")\n with open(template_path, \"r\") as f:\n html_all_template = f.read()\n html_all_template = Template(html_all_template)\n\n return html_all_template.substitute(div_id=div_id, \n library_bundle=library_bundle, \n main_function=main_function, \n parameter_dict=json.dumps(parameter_dict),\n css_bundle=css_bundle)\n\n# Regex expression to test if a string is a URL\nregex_url = re.compile(\n r'^(?:http|ftp)s?://' # http:// or https://\n r'(?:(?:[A-Z0-9](?:[A-Z0-9-]{0,61}[A-Z0-9])?\\.)+(?:[A-Z]{2,6}\\.?|[A-Z0-9-]{2,}\\.?)|' #domain...\n r'localhost|' #localhost...\n r'\\d{1,3}\\.\\d{1,3}\\.\\d{1,3}\\.\\d{1,3})' # ...or ip\n r'(?::\\d+)?' # optional port\n r'(?:/?|[/?]\\S+)$', re.IGNORECASE)\n\ndef check_url(string):\n \"\"\"Checks if the string argument is a URL\"\"\"\n return re.match(regex_url, string) is not None\n\ndef download_url(url):\n \"\"\"Downloads a URL file as a browser.\"\"\"\n import requests\n headers = {'User-Agent': 'Mozilla/5.0 (X11; Ubuntu; Linux x86_64; rv:78.0) Gecko/20100101 Firefox/78.0'}\n r = requests.get(url, headers=headers, stream=False)\n return r.content.decode(\"utf-8\") \n\n\n\ndef save_html(html_dest, library_list, main_function, data_dict = {}, callbacks = None, css_list=[]):\n \"\"\"Saves the bundled code (output of execute_js) to an HTML file\n\n Parameters\n ----------\n html_dest : str\n Path to the output HTML dest file. Example: \"./output.html\"\n library_list : list of str\n List of strings containing either 1) URL to a javascript library, 2) javascript code\n main_function : str\n Name of the main function to be called. The function will be called with two parameters: \n , for example \"#my_div\", and .\n data_dict : dict\n Dictionary containing the data to be passed to \n callbacks : dict\n Dictionary of the form { : }. The javascript library can\n use callbacks to talk to python.\n css_list : list of str\n List of strings containing either 1) URL to a CSS stylesheet or 2) CSS styles\n \"\"\"\n if callbacks is not None:\n print (\"Warning: Python callbacks do not work in standalone HTML file.\")\n print (\"Saving file...\")\n\n html_all = make_html(library_list, main_function, data_dict, css_list)\n with open(html_dest, \"w\") as f:\n f.write(html_all)\n\ndef execute_js(library_list, main_function, data_dict = {}, callbacks = {}, css_list=[]):\n \"\"\"Executes a javascript function that can add content to an output div\n\n Parameters\n ----------\n library_list : list of str\n List of strings containing either 1) URL to a javascript library, 2) javascript code\n main_function : str\n Name of the main function to be called. The function will be called with two parameters: \n , for example \"#my_div\", and .\n data_dict : dict\n Dictionary containing the data to be passed to \n callbacks : dict\n Dictionary of the form { : }. The javascript library can\n use callbacks to talk to python.\n css_list : list of str\n List of strings containing either 1) URL to a CSS stylesheet or 2) CSS styles\n \"\"\"\n html_all = make_html(library_list, main_function, data_dict, css_list)\n for callback_id in callbacks.keys():\n setup_comm_api(callback_id, callbacks[callback_id])\n display(HTML(html_all))\n" }, { "path": "notebookjs/resources/CommAPI.js", "content": "const COMM_TYPES = {\n JUPYTER: 'JUPYTER',\n COLAB: 'COLAB'\n};\n\nclass CommAPI{\n constructor(api_call_id, callback) {\n this.callback = callback;\n this.mode = null;\n if (window.Jupyter !== undefined) {\n this.mode = COMM_TYPES.JUPYTER;\n this.comm = window.Jupyter.notebook.kernel.comm_manager.new_comm(api_call_id, {});\n this.comm.on_msg(msg => {\n const data = msg.content.data;\n callback(data);\n });\n } else if (window.google !== undefined) {\n this.mode = COMM_TYPES.COLAB;\n this.comm = async function(msg){\n const result = await google.colab.kernel.invokeFunction(\n api_call_id,\n [msg], // The argument\n {}); // kwargs\n callback(result.data['application/json']);\n };\n } else {\n console.error(new Error(\"Cannot find Jupyter/Colab namespace from javascript\"));\n }\n }\n\n call(msg) {\n if (this.comm){\n if (this.mode === COMM_TYPES.JUPYTER){\n this.comm.send(msg);\n } else if (this.mode === COMM_TYPES.COLAB){\n this.comm(msg);\n }\n }\n }\n}" }, { "path": "notebookjs/resources/template.html", "content": "\n\n\n\n\n
\n
\n \n\n" }, { "path": "setup.py", "content": "from setuptools import setup, find_packages\n\nwith open(\"README.md\", \"r\") as fh:\n long_description = fh.read()\n\nsetup(\n name=\"notebookjs\",\n version=\"0.1.4\",\n author=\"Jorge Piazentin Ono, Juliana Freire, Claudio Silva\",\n author_email=\"jorgehpo@nyu.edu\",\n description=\"notebookJS library - Seamless JavaScript integration in Python Notebooks\",\n long_description=long_description,\n long_description_content_type=\"text/markdown\",\n url=\"https://github.com/jorgehpo/notebookJS\",\n packages=find_packages(exclude=['resources']),\n include_package_data=True,\n license=\"MIT\",\n classifiers=[\n \"Programming Language :: Python :: 3\",\n \"License :: OSI Approved :: MIT License\",\n \"Operating System :: OS Independent\",\n ],\n python_requires='>=3.6',\n install_requires=[\n \"notebook\"\n ]\n)\n" } ]