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Add bqplot example
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‎docs/bqplot.ipynb‎

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{
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"cells": [
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{
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"cell_type": "markdown",
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"source": [
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"# `bqplot` Interactive Demo\n",
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"\n",
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"Plotting in JupyterLite\n",
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"\n",
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"`bqplot` can be installed in this deployment (it provides the bqplot federated extension), but you will need to make your own deployment to have access to other interactive widgets libraries."
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],
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"metadata": {}
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"source": [
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"import piplite\n",
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"\n",
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"await piplite.install('bqplot')"
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],
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"outputs": [],
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"metadata": {}
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"source": [
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"from bqplot import *\n",
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"\n",
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"import numpy as np\n",
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"import pandas as pd\n",
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"\n",
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"np.random.seed(0)\n",
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"\n",
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"n = 100\n",
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"\n",
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"x = list(range(n))\n",
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"y = np.cumsum(np.random.randn(n)) + 100.\n",
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"\n",
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"sc_x = LinearScale()\n",
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"sc_y = LinearScale()\n",
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"\n",
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"lines = Lines(\n",
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" x=x, y=y,\n",
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" scales={'x': sc_x, 'y': sc_y}\n",
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")\n",
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"ax_x = Axis(scale=sc_x, label='Index')\n",
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"ax_y = Axis(scale=sc_y, orientation='vertical', label='lines')\n",
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"\n",
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"Figure(marks=[lines], axes=[ax_x, ax_y], title='Lines')"
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],
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"outputs": [],
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"metadata": {}
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"source": [
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"lines.colors = ['green']"
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],
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"outputs": [],
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"metadata": {}
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"source": [
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"lines.fill = 'bottom'"
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],
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"outputs": [],
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"metadata": {}
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"source": [
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"lines.marker = 'circle'"
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],
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"outputs": [],
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"metadata": {}
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"source": [
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"n = 100\n",
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"\n",
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"x = list(range(n))\n",
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"y = np.cumsum(np.random.randn(n))\n",
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"\n",
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"sc_x = LinearScale()\n",
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"sc_y = LinearScale()\n",
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"\n",
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"bars = Bars(\n",
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" x=x, y=y,\n",
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" scales={'x': sc_x, 'y': sc_y}\n",
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")\n",
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"ax_x = Axis(scale=sc_x, label='Index')\n",
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"ax_y = Axis(scale=sc_y, orientation='vertical', label='bars')\n",
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"\n",
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"Figure(marks=[bars], axes=[ax_x, ax_y], title='Bars', animation_duration=1000)"
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],
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"outputs": [],
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"metadata": {}
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"source": [
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"bars.y = np.cumsum(np.random.randn(n))"
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],
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"outputs": [],
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"metadata": {}
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},
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{
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"cell_type": "markdown",
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"source": [
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"### Plots which use Nested Buffers"
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],
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"metadata": {}
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"source": [
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"from bqplot import *\n",
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"\n",
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"import numpy as np\n",
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"import pandas as pd\n",
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"\n",
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"np.random.seed(0)\n",
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"y1 = np.cumsum(np.random.randn(150)) + 100.\n",
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"y2 = np.cumsum(np.random.randn(150)) + 100.\n",
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"y3 = np.cumsum(np.random.randn(150)) + 100.\n",
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"y4 = np.cumsum(np.random.randn(150)) + 100.\n",
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"\n",
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"sc_x = LinearScale()\n",
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"sc_y = LinearScale()\n",
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"\n",
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"lines = Lines(x=np.arange(len(y1)), y=[y1, y2, y3, y4],\n",
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" scales={'x': sc_x, 'y': sc_y})\n",
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"ax_x = Axis(scale=sc_x, label='Index')\n",
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"ax_y = Axis(scale=sc_y, orientation='vertical', label='lines')\n",
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"\n",
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"Figure(marks=[lines], axes=[ax_x, ax_y], title='Lines')"
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],
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"outputs": [],
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"metadata": {}
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"source": [],
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"outputs": [],
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"metadata": {}
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}
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],
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"metadata": {
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"orig_nbformat": 4,
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"language_info": {
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"name": "python"
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}
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},
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"nbformat": 4,
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"nbformat_minor": 2
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}

‎docs/index.rst‎

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jupyterlite-sphinx
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==================
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Installation:
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-------------
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Installation
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------------
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You can install ``jupyterlite-sphinx`` with ``pip``:
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# ...
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]
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Replite directive:
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------------------
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Replite directive
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-----------------
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``jupyterlite-sphinx`` provides a ``replite`` directive that allows you to embed a replite console in your docs.
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This directive takes the same options as the ``replite`` package, see https://github.com/jtpio/replite for reference.
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print('Hello, World!')
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Retrolite directive:
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--------------------
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Retrolite directive
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-------------------
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``jupyterlite-sphinx`` provides a ``retrolite`` directive that allows you to embed an entire executable Notebook in your docs.
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It takes the name of the Notebook as argument:
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.. retrolite:: my_notebook.ipynb
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JupyterLab and RetroLab deployed for you:
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-----------------------------------------
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JupyterLab and RetroLab deployed for you
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----------------------------------------
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``jupyterlite-sphinx`` makes a full deployment of JupyterLite for you, you can access the JupyterLab UI and RetroLab UI following the
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``./lite/lab/index.html`` and ``./lite/retro/index.html`` relative URLs:
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`JupyterLab <./lite/lab/index.html>`_
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`Retrolab <./lite/retro/index.html>`_
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Configuration
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-------------
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You can provide custom configuration to your JupyterLite deployment.
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For example, if you want to have bqplot working in this deployment, you need to install the bqplot federated extension
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and you can serve the bqplot wheel to ``piplite``, this is done by telling your ``conf.py`` where to look for the jupyterlite config:
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.. code-block:: python
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jupyterlite_config = "jupyterlite_config.json"
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The ``jupyterlite_config.json`` containing the following:
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.. code-block:: json
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{
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"LiteBuildConfig": {
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"federated_extensions": [
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"https://github.com/conda-forge/releases/releases/download/noarch/bqplot-0.12.33-pyhd8ed1ab_0.tar.bz2/bqplot-0.12.33-pyhd8ed1ab_0.tar.bz2",
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],
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"ignore_sys_prefix": true,
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"piplite_urls": [
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"https://files.pythonhosted.org/packages/py2.py3/b/bqplot/bqplot-0.12.33-py2.py3-none-any.whl",
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]
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}
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}
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Then you should be able to show Notebooks working with bqplot!
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.. code-block:: rst
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.. retrolite:: bqplot.ipynb
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.. retrolite:: bqplot.ipynb

‎docs/jupyterlite_config.json‎

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"https://files.pythonhosted.org/packages/py3/x/xyzservices/xyzservices-2022.2.0-py3-none-any.whl"
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]
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}
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}
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}

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