mirror of
https://github.com/tiennm99/serena.git
synced 2026-06-18 03:31:48 +00:00
Michael Panchenko
129 lines
3.4 KiB
Plaintext
129 lines
3.4 KiB
Plaintext
{
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"cells": [
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"# The role of notebooks\n",
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"\n",
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"Notebooks are great for illustrations and examples that at the same time serve as integration tests.\n",
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"In this library template, notebooks will be executed with pytest (thus on every\n",
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"commit in your CI/CD pipeline). The results of the executions will be saved to the docs directory and converted to\n",
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"static websites through nbconvert. The static websites are then added to the documentation under the\n",
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"_Guides and Tutorials_ section. These websites will be deployed to Github pages on push to develop."
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]
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},
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"## Before running the notebook\n",
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"\n",
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"Install the library and its dependencies with, if you haven't done so already\n",
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"```\n",
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"poetry install\n",
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"```\n",
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"from the root directory. You can also execute this command directly in the notebook but will need to reload the\n",
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"kernel afterwards"
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]
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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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"metadata": {
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"pycharm": {
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"name": "#%%\n"
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}
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},
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"outputs": [],
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"source": [
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"# Here an illustration of your library\n",
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"from serena.sample_package.sample_module import hello_stranger\n",
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"\n",
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"hello_stranger()"
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]
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},
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{
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"cell_type": "markdown",
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"metadata": {
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"pycharm": {
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"name": "#%% md\n"
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}
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},
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"source": [
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"## Interactive Documentation\n",
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"\n",
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"Note that since notebooks are rendered to html+javascript, you can embed interactive components like maps, videos and\n",
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"widgets into your documentation, as long as the interaction does not require re-execution of cells.\n",
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"Below an example of an interactive map created with plotly {cite}`PlotlyMaps`."
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]
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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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"metadata": {
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"pycharm": {
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"name": "#%%\n"
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}
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},
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"outputs": [],
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"source": [
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"# slightly adjusted example from https://plotly.com/python/mapbox-layers/\n",
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"import pandas as pd\n",
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"import plotly.express as px\n",
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"\n",
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"us_cities = pd.read_csv(\n",
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" \"https://raw.githubusercontent.com/plotly/datasets/master/us-cities-top-1k.csv\",\n",
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")\n",
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"\n",
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"fig = px.scatter_mapbox(\n",
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" us_cities,\n",
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" lat=\"lat\",\n",
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" lon=\"lon\",\n",
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" hover_name=\"City\",\n",
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" hover_data=[\"State\", \"Population\"],\n",
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" color_discrete_sequence=[\"fuchsia\"],\n",
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" zoom=3,\n",
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" height=300,\n",
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")\n",
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"\n",
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"fig.update_layout(mapbox_style=\"open-street-map\", margin={\"r\": 0, \"t\": 0, \"l\": 0, \"b\": 0})\n",
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"fig.show()"
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]
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},
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{
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"cell_type": "markdown",
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"source": [
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"```{bibliography}\n",
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":style: unsrtalpha\n",
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":filter: docname in docnames\n",
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"```"
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],
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"metadata": {
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"collapsed": false
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}
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}
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],
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"metadata": {
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"kernelspec": {
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"display_name": "Python 3",
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"language": "python",
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"name": "python3"
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},
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"language_info": {
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"codemirror_mode": {
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"name": "ipython",
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"version": 2
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},
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"file_extension": ".py",
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"mimetype": "text/x-python",
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"name": "python",
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"nbconvert_exporter": "python",
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"pygments_lexer": "ipython2",
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"version": "2.7.6"
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}
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},
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"nbformat": 4,
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"nbformat_minor": 0
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}
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