.. _extension_tutorial: Extension Tutorial ================== JupyterLab extensions add features to the user experience. This page describes how to create one type of extension, an *application plugin*, that: - Adds a "Random `Astronomy Picture `__" command to the *command palette* sidebar - Fetches the image and metadata when activated - Shows the image and metadata in a tab panel By working through this tutorial, you'll learn: - How to set up an extension development environment from scratch on a Linux or OSX machine. (You'll need to modify the commands slightly if you are on Windows.) - How to start an extension project from `jupyterlab/extension-cookiecutter-ts `__ - How to iteratively code, build, and load your extension in JupyterLab - How to version control your work with git - How to release your extension for others to enjoy .. figure:: images/extension_tutorial_complete.png :align: center :class: jp-screenshot :alt: The completed extension, showing the Astronomy Picture of the Day for 24 Jul 2015. The completed extension, showing the `Astronomy Picture of the Day for 24 Jul 2015 `__. Sound like fun? Excellent. Here we go! Set up a development environment -------------------------------- Install conda using miniconda ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ Start by installing miniconda, following `Conda's installation documentation `__. .. _install-nodejs-jupyterlab-etc-in-a-conda-environment: Install NodeJS, JupyterLab, etc. in a conda environment ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ Next create a conda environment that includes: 1. the latest release of JupyterLab 2. `cookiecutter `__, the tool you'll use to bootstrap your extension project structure (this is a Python tool which we'll install using conda below). 3. `NodeJS `__, the JavaScript runtime you'll use to compile the web assets (e.g., TypeScript, CSS) for your extension 4. `git `__, a version control system you'll use to take snapshots of your work as you progress through this tutorial It's a best practice to leave the root conda environment (i.e., the environment created by the miniconda installer) untouched and install your project-specific dependencies in a named conda environment. Run this command to create a new environment named ``jupyterlab-ext``. .. code:: bash conda create -n jupyterlab-ext --override-channels --strict-channel-priority -c conda-forge -c nodefaults jupyterlab=3 cookiecutter nodejs jupyter-packaging git Now activate the new environment so that all further commands you run work out of that environment. .. code:: bash conda activate jupyterlab-ext Note: You'll need to run the command above in each new terminal you open before you can work with the tools you installed in the ``jupyterlab-ext`` environment. Create a repository ------------------- Create a new repository for your extension (see, for example, the `GitHub instructions `__. This is an optional step, but highly recommended if you want to share your extension. Create an extension project --------------------------- Initialize the project from a cookiecutter ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ Next use cookiecutter to create a new project for your extension. This will create a new folder for your extension in your current directory. .. code:: bash cookiecutter https://github.com/jupyterlab/extension-cookiecutter-ts When prompted, enter values like the following for all of the cookiecutter prompts (``apod`` stands for Astronomy Picture of the Day, the NASA service we are using to fetch pictures). :: Select kind: 1 - frontend 2 - server 3 - theme Choose from 1, 2, 3 [1]: 1 author_name []: Your Name author_email []: your@name.org labextension_name [myextension]: jupyterlab_apod python_name [myextension]: jupyterlab_apod project_short_description [A JupyterLab extension.]: Show a random NASA Astronomy Picture of the Day in a JupyterLab panel has_settings [n]: n has_binder [n]: y repository [https://github.com/github_username/myextension]: https://github.com/github_username/jupyterlab_apod Note: if not using a repository, leave the repository field blank. You can come back and edit the repository field in the ``package.json`` file later. Change to the directory the cookiecutter created and list the files. .. code:: bash cd jupyterlab_apod ls You should see a list like the following. :: binder CHANGELOG.md install.json jupyterlab_apod LICENSE MANIFEST.in package.json pyproject.toml README.md RELEASE.md setup.py src style tsconfig.json Commit what you have to git ^^^^^^^^^^^^^^^^^^^^^^^^^^^ Run the following commands in your ``jupyterlab_apod`` folder to initialize it as a git repository and commit the current code. .. code:: bash git init git add . git commit -m 'Seed apod project from cookiecutter' Note: This step is not technically necessary, but it is good practice to track changes in version control system in case you need to rollback to an earlier version or want to collaborate with others. You can compare your work throughout this tutorial with the commits in a reference version of ``jupyterlab_apod`` on GitHub at https://github.com/jupyterlab/jupyterlab_apod. Build and install the extension for development ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ Your new extension project has enough code in it to see it working in your JupyterLab. Run the following commands to install the initial project dependencies and install the extension into the JupyterLab environment. .. code:: bash pip install -ve . The above command copies the frontend part of the extension into JupyterLab. We can run this ``pip install`` command again every time we make a change to copy the change into JupyterLab. Even better, we can use the ``develop`` command to create a symbolic link from JupyterLab to our source directory. This means our changes are automatically available in JupyterLab: .. code:: bash jupyter labextension develop --overwrite . .. note:: On Windows, symbolic links can be activated on Windows 10 for Python version 3.8 or higher by activating the 'Developer Mode'. That may not be allowed by your administrators. See `Activate Developer Mode on Windows `__ for instructions. See the initial extension in action ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ After the install completes, open a second terminal. Run these commands to activate the ``jupyterlab-ext`` environment and start JupyterLab in your default web browser. .. code:: bash conda activate jupyterlab-ext jupyter lab In that browser window, open the JavaScript console by following the instructions for your browser: - `Accessing the DevTools in Google Chrome `__ - `Opening the Web Console in Firefox `__ After you reload the page with the console open, you should see a message that says ``JupyterLab extension jupyterlab_apod is activated!`` in the console. If you do, congratulations, you're ready to start modifying the extension! If not, go back make sure you didn't miss a step, and `reach out `__ if you're stuck. Note: Leave the terminal running the ``jupyter lab`` command open and running JupyterLab to see the effects of changes below. Add an Astronomy Picture of the Day widget ------------------------------------------ Show an empty panel ^^^^^^^^^^^^^^^^^^^ The *command palette* is the primary view of all commands available to you in JupyterLab. For your first addition, you're going to add a *Random Astronomy Picture* command to the palette and get it to show an *Astronomy Picture* tab panel when invoked. Fire up your favorite text editor and open the ``src/index.ts`` file in your extension project. Change the import at the top of the file to get a reference to the command palette interface and the `JupyterFrontEnd` instance. .. code:: typescript import { JupyterFrontEnd, JupyterFrontEndPlugin } from '@jupyterlab/application'; import { ICommandPalette } from '@jupyterlab/apputils'; Locate the ``extension`` object of type ``JupyterFrontEndPlugin``. Change the definition so that it reads like so: .. code:: typescript /** * Initialization data for the jupyterlab_apod extension. */ const extension: JupyterFrontEndPlugin = { id: 'jupyterlab-apod', autoStart: true, requires: [ICommandPalette], activate: (app: JupyterFrontEnd, palette: ICommandPalette) => { console.log('JupyterLab extension jupyterlab_apod is activated!'); console.log('ICommandPalette:', palette); } }; The ``requires`` attribute states that your plugin needs an object that implements the ``ICommandPalette`` interface when it starts. JupyterLab will pass an instance of ``ICommandPalette`` as the second parameter of ``activate`` in order to satisfy this requirement. Defining ``palette: ICommandPalette`` makes this instance available to your code in that function. The second ``console.log`` line exists only so that you can immediately check that your changes work. Now you will need to install these dependencies. Run the following commands in the repository root folder to install the dependencies and save them to your `package.json`: .. code:: bash jlpm add @jupyterlab/apputils jlpm add @jupyterlab/application Finally, run the following to rebuild your extension. .. code:: bash jlpm run build .. note:: This tutorial uses ``jlpm`` to install Javascript packages and run build commands, which is JupyterLab's bundled version of ``yarn``. If you prefer, you can use another Javascript package manager like ``npm`` or ``yarn`` itself. After the extension build finishes, return to the browser tab that opened when you started JupyterLab. Refresh it and look in the console. You should see the same activation message as before, plus the new message about the ICommandPalette instance you just added. If you don't, check the output of the build command for errors and correct your code. :: JupyterLab extension jupyterlab_apod is activated! ICommandPalette: Palette {_palette: CommandPalette} Note that we had to run ``jlpm run build`` in order for the bundle to update. This command does two things: compiles the TypeScript files in `src/` into JavaScript files in ``lib/`` (``jlpm run build``), then bundles the JavaScript files in ``lib/`` into a JupyterLab extension in ``jupyterlab_apod/static`` (``jlpm run build:extension``). If you wish to avoid running ``jlpm run build`` after each change, you can open a third terminal, activate the ``jupyterlab-ext`` environment, and run the ``jlpm run watch`` command from your extension directory, which will automatically compile the TypeScript files as they are changed and saved. Now return to your editor. Modify the imports at the top of the file to add a few more imports: .. code:: typescript import { ICommandPalette, MainAreaWidget } from '@jupyterlab/apputils'; import { Widget } from '@lumino/widgets'; Install this new dependency as well: .. code:: bash jlpm add @lumino/widgets Then modify the ``activate`` function again so that it has the following code: .. code-block:: typescript activate: (app: JupyterFrontEnd, palette: ICommandPalette) => { console.log('JupyterLab extension jupyterlab_apod is activated!'); // Create a blank content widget inside of a MainAreaWidget const content = new Widget(); const widget = new MainAreaWidget({ content }); widget.id = 'apod-jupyterlab'; widget.title.label = 'Astronomy Picture'; widget.title.closable = true; // Add an application command const command: string = 'apod:open'; app.commands.addCommand(command, { label: 'Random Astronomy Picture', execute: () => { if (!widget.isAttached) { // Attach the widget to the main work area if it's not there app.shell.add(widget, 'main'); } // Activate the widget app.shell.activateById(widget.id); } }); // Add the command to the palette. palette.addItem({ command, category: 'Tutorial' }); } The first new block of code creates a ``MainAreaWidget`` instance with an empty content ``Widget`` as its child. It also assigns the main area widget a unique ID, gives it a label that will appear as its tab title, and makes the tab closable by the user. The second block of code adds a new command with id ``apod:open`` and label *Random Astronomy Picture* to JupyterLab. When the command executes, it attaches the widget to the main display area if it is not already present and then makes it the active tab. The last new line of code uses the command id to add the command to the command palette in a section called *Tutorial*. Build your extension again using ``jlpm run build`` (unless you are using ``jlpm run watch`` already) and refresh the browser tab. Open the command palette by clicking on *Commands* from the View menu or using the keyboard shortcut ``Command/Ctrl Shift C`` and type *Astronomy* in the search box. Your *Random Astronomy Picture* command should appear. Click it or select it with the keyboard and press *Enter*. You should see a new, blank panel appear with the tab title *Astronomy Picture*. Click the *x* on the tab to close it and activate the command again. The tab should reappear. Finally, click one of the launcher tabs so that the *Astronomy Picture* panel is still open but no longer active. Now run the *Random Astronomy Picture* command one more time. The single *Astronomy Picture* tab should come to the foreground. .. figure:: images/extension_tutorial_empty.png :align: center :class: jp-screenshot :alt: The in-progress extension, showing a blank panel. The in-progress extension, showing a blank panel. If your widget is not behaving, compare your code with the reference project state at the `01-show-a-panel tag `__. Once you've got everything working properly, git commit your changes and carry on. .. code-block:: bash git add package.json src/index.ts git commit -m 'Show Astronomy Picture command in palette' Show a picture in the panel ^^^^^^^^^^^^^^^^^^^^^^^^^^^ You now have an empty panel. It's time to add a picture to it. Go back to your code editor. Add the following code below the lines that create a ``MainAreaWidget`` instance and above the lines that define the command. .. code-block:: typescript // Add an image element to the content let img = document.createElement('img'); content.node.appendChild(img); // Get a random date string in YYYY-MM-DD format function randomDate() { const start = new Date(2010, 1, 1); const end = new Date(); const randomDate = new Date(start.getTime() + Math.random()*(end.getTime() - start.getTime())); return randomDate.toISOString().slice(0, 10); } // Fetch info about a random picture const response = await fetch(`https://api.nasa.gov/planetary/apod?api_key=DEMO_KEY&date=${randomDate()}`); const data = await response.json() as APODResponse; if (data.media_type === 'image') { // Populate the image img.src = data.url; img.title = data.title; } else { console.log('Random APOD was not a picture.'); } The first two lines create a new HTML ```` element and add it to the widget DOM node. The next lines define a function get a random date in the form ``YYYY-MM-DD`` format, and then the function is used to make a request using the HTML `fetch `__ API that returns information about the Astronomy Picture of the Day for that date. Finally, we set the image source and title attributes based on the response. Now define the ``APODResponse`` type that was introduced in the code above. Put this definition just under the imports at the top of the file. .. code-block:: typescript interface APODResponse { copyright: string; date: string; explanation: string; media_type: 'video' | 'image'; title: string; url: string; }; And update the ``activate`` method to be ``async`` since we are now using ``await`` in the method body. .. code-block:: typescript activate: async (app: JupyterFrontEnd, palette: ICommandPalette) => .. note:: If you are new to JavaScript / TypeScript and want to learn more about ``async``, ``await``, and ``Promises``, you can check out the following `tutorial on MDN `_ Be sure to also refer to the other resources in the `See Also `_ section for more materials. Rebuild your extension if necessary (``jlpm run build``), refresh your browser tab, and run the *Random Astronomy Picture* command again. You should now see a picture in the panel when it opens (if that random date had a picture and not a video). .. figure:: images/extension_tutorial_single.png :align: center :class: jp-screenshot The in-progress extension, showing the `Astronomy Picture of the Day for 19 Jan 2014 `__. Note that the image is not centered in the panel nor does the panel scroll if the image is larger than the panel area. Also note that the image does not update no matter how many times you close and reopen the panel. You'll address both of these problems in the upcoming sections. If you don't see a image at all, compare your code with the `02-show-an-image tag `__ in the reference project. When it's working, make another git commit. .. code:: bash git add src/index.ts git commit -m 'Show a picture in the panel' Improve the widget behavior --------------------------- Center the image, add attribution, and error messaging ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ Open ``style/base.css`` in our extension project directory for editing. Add the following lines to it. .. code-block:: css .my-apodWidget { display: flex; flex-direction: column; align-items: center; overflow: auto; } This CSS stacks content vertically within the widget panel and lets the panel scroll when the content overflows. This CSS file is included on the page automatically by JupyterLab because the ``package.json`` file has a ``style`` field pointing to it. In general, you should import all of your styles into a single CSS file, such as this ``index.css`` file, and put the path to that CSS file in the ``package.json`` file ``style`` field. Return to the ``index.ts`` file. Modify the ``activate`` function to apply the CSS classes, the copyright information, and error handling for the API response. The beginning of the function should read like the following: .. code-block:: typescript :emphasize-lines: 6,16-17,28-50 activate: async (app: JupyterFrontEnd, palette: ICommandPalette) => { console.log('JupyterLab extension jupyterlab_apod is activated!'); // Create a blank content widget inside of a MainAreaWidget const content = new Widget(); content.addClass('my-apodWidget'); // new line const widget = new MainAreaWidget({content}); widget.id = 'apod-jupyterlab'; widget.title.label = 'Astronomy Picture'; widget.title.closable = true; // Add an image element to the content let img = document.createElement('img'); content.node.appendChild(img); let summary = document.createElement('p'); content.node.appendChild(summary); // Get a random date string in YYYY-MM-DD format function randomDate() { const start = new Date(2010, 1, 1); const end = new Date(); const randomDate = new Date(start.getTime() + Math.random()*(end.getTime() - start.getTime())); return randomDate.toISOString().slice(0, 10); } // Fetch info about a random picture const response = await fetch(`https://api.nasa.gov/planetary/apod?api_key=DEMO_KEY&date=${randomDate()}`); if (!response.ok) { const data = await response.json(); if (data.error) { summary.innerText = data.error.message; } else { summary.innerText = response.statusText; } } else { const data = await response.json() as APODResponse; if (data.media_type === 'image') { // Populate the image img.src = data.url; img.title = data.title; summary.innerText = data.title; if (data.copyright) { summary.innerText += ` (Copyright ${data.copyright})`; } } else { summary.innerText = 'Random APOD fetched was not an image.'; } } // Keep all the remaining command lines the same // as before from here down ... Build your extension if necessary (``jlpm run build``) and refresh your JupyterLab browser tab. Invoke the *Random Astronomy Picture* command and confirm the image is centered with the copyright information below it. Resize the browser window or the panel so that the image is larger than the available area. Make sure you can scroll the panel over the entire area of the image. If anything is not working correctly, compare your code with the reference project `03-style-and-attribute tag `__. When everything is working as expected, make another commit. .. code:: bash git add style/index.css src/index.ts git commit -m 'Add styling, attribution, error handling' Show a new image on demand ^^^^^^^^^^^^^^^^^^^^^^^^^^ The ``activate`` function has grown quite long, and there's still more functionality to add. Let's refactor the code into two separate parts: 1. An ``APODWidget`` that encapsulates the Astronomy Picture panel elements, configuration, and soon-to-be-added update behavior 2. An ``activate`` function that adds the widget instance to the UI and decide when the picture should refresh Start by refactoring the widget code into the new ``APODWidget`` class. Add the following additional import to the top of the file. .. code-block:: typescript import { Message } from '@lumino/messaging'; Install this dependency: .. code:: bash jlpm add @lumino/messaging Then add the class just below the definition of ``APODResponse`` in the ``index.ts`` file. .. code-block:: typescript class APODWidget extends Widget { /** * Construct a new APOD widget. */ constructor() { super(); this.addClass('my-apodWidget'); // Add an image element to the panel this.img = document.createElement('img'); this.node.appendChild(this.img); // Add a summary element to the panel this.summary = document.createElement('p'); this.node.appendChild(this.summary); } /** * The image element associated with the widget. */ readonly img: HTMLImageElement; /** * The summary text element associated with the widget. */ readonly summary: HTMLParagraphElement; /** * Handle update requests for the widget. */ async onUpdateRequest(msg: Message): Promise { const response = await fetch(`https://api.nasa.gov/planetary/apod?api_key=DEMO_KEY&date=${this.randomDate()}`); if (!response.ok) { const data = await response.json(); if (data.error) { this.summary.innerText = data.error.message; } else { this.summary.innerText = response.statusText; } return; } const data = await response.json() as APODResponse; if (data.media_type === 'image') { // Populate the image this.img.src = data.url; this.img.title = data.title; this.summary.innerText = data.title; if (data.copyright) { this.summary.innerText += ` (Copyright ${data.copyright})`; } } else { this.summary.innerText = 'Random APOD fetched was not an image.'; } } /** * Get a random date string in YYYY-MM-DD format. */ randomDate(): string { const start = new Date(2010, 1, 1); const end = new Date(); const randomDate = new Date(start.getTime() + Math.random()*(end.getTime() - start.getTime())); return randomDate.toISOString().slice(0, 10); } } You've written all of the code before. All you've done is restructure it to use instance variables and move the image request to its own function. Next move the remaining logic in ``activate`` to a new, top-level function just below the ``APODWidget`` class definition. Modify the code to create a widget when one does not exist in the main JupyterLab area or to refresh the image in the existing widget when the command runs again. The code for the ``activate`` function should read as follows after these changes: .. code-block:: typescript /** * Activate the APOD widget extension. */ function activate(app: JupyterFrontEnd, palette: ICommandPalette) { console.log('JupyterLab extension jupyterlab_apod is activated!'); // Create a single widget const content = new APODWidget(); const widget = new MainAreaWidget({content}); widget.id = 'apod-jupyterlab'; widget.title.label = 'Astronomy Picture'; widget.title.closable = true; // Add an application command const command: string = 'apod:open'; app.commands.addCommand(command, { label: 'Random Astronomy Picture', execute: () => { if (!widget.isAttached) { // Attach the widget to the main work area if it's not there app.shell.add(widget, 'main'); } // Refresh the picture in the widget content.update(); // Activate the widget app.shell.activateById(widget.id); } }); // Add the command to the palette. palette.addItem({ command, category: 'Tutorial' }); } Remove the ``activate`` function definition from the ``JupyterFrontEndPlugin`` object and refer instead to the top-level function like this: .. code-block:: typescript const extension: JupyterFrontEndPlugin = { id: 'jupyterlab_apod', autoStart: true, requires: [ICommandPalette], activate: activate }; Make sure you retain the ``export default extension;`` line in the file. Now build the extension again and refresh the JupyterLab browser tab. Run the *Random Astronomy Picture* command more than once without closing the panel. The picture should update each time you execute the command. Close the panel, run the command, and it should both reappear and show a new image. If anything is not working correctly, compare your code with the `04-refactor-and-refresh tag `__ to debug. Once it is working properly, commit it. .. code:: bash git add package.json src/index.ts git commit -m 'Refactor, refresh image' Restore panel state when the browser refreshes ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ You may notice that every time you refresh your browser tab, the Astronomy Picture panel disappears, even if it was open before you refreshed. Other open panels, like notebooks, terminals, and text editors, all reappear and return to where you left them in the panel layout. You can make your extension behave this way too. Update the imports at the top of your ``index.ts`` file so that the entire list of import statements looks like the following: .. code-block:: typescript :emphasize-lines: 2,10 import { ILayoutRestorer, JupyterFrontEnd, JupyterFrontEndPlugin } from '@jupyterlab/application'; import { ICommandPalette, MainAreaWidget, WidgetTracker } from '@jupyterlab/apputils'; import { Message } from '@lumino/messaging'; import { Widget } from '@lumino/widgets'; Then add the ``ILayoutRestorer`` interface to the ``JupyterFrontEndPlugin`` definition. This addition passes the global ``LayoutRestorer`` as the third parameter of the ``activate`` function. .. code-block:: typescript :emphasize-lines: 4 const extension: JupyterFrontEndPlugin = { id: 'jupyterlab_apod', autoStart: true, requires: [ICommandPalette, ILayoutRestorer], activate: activate }; Finally, rewrite the ``activate`` function so that it: 1. Declares a widget variable, but does not create an instance immediately. 2. Constructs a ``WidgetTracker`` and tells the ``ILayoutRestorer`` to use it to save/restore panel state. 3. Creates, tracks, shows, and refreshes the widget panel appropriately. .. code-block:: typescript function activate(app: JupyterFrontEnd, palette: ICommandPalette, restorer: ILayoutRestorer) { console.log('JupyterLab extension jupyterlab_apod is activated!'); // Declare a widget variable let widget: MainAreaWidget; // Add an application command const command: string = 'apod:open'; app.commands.addCommand(command, { label: 'Random Astronomy Picture', execute: () => { if (!widget || widget.isDisposed) { // Create a new widget if one does not exist // or if the previous one was disposed after closing the panel const content = new APODWidget(); widget = new MainAreaWidget({content}); widget.id = 'apod-jupyterlab'; widget.title.label = 'Astronomy Picture'; widget.title.closable = true; } if (!tracker.has(widget)) { // Track the state of the widget for later restoration tracker.add(widget); } if (!widget.isAttached) { // Attach the widget to the main work area if it's not there app.shell.add(widget, 'main'); } widget.content.update(); // Activate the widget app.shell.activateById(widget.id); } }); // Add the command to the palette. palette.addItem({ command, category: 'Tutorial' }); // Track and restore the widget state let tracker = new WidgetTracker>({ namespace: 'apod' }); restorer.restore(tracker, { command, name: () => 'apod' }); } Rebuild your extension one last time and refresh your browser tab. Execute the *Random Astronomy Picture* command and validate that the panel appears with an image in it. Refresh the browser tab again. You should see an Astronomy Picture panel reappear immediately without running the command. Close the panel and refresh the browser tab. You should then not see an Astronomy Picture tab after the refresh. .. figure:: images/extension_tutorial_complete.png :align: center :class: jp-screenshot :alt: The completed extension, showing the Astronomy Picture of the Day for 24 Jul 2015. The completed extension, showing the `Astronomy Picture of the Day for 24 Jul 2015 `__. Refer to the `05-restore-panel-state tag `__ if your extension is not working correctly. Make a commit when the state of your extension persists properly. .. code:: bash git add src/index.ts git commit -m 'Restore panel state' Congratulations! You've implemented all of the behaviors laid out at the start of this tutorial. .. _packaging your extension: Packaging your extension ------------------------ JupyterLab extensions for JupyterLab 3.0 can be distributed as Python packages. The cookiecutter template we used contains all of the Python packaging instructions in the ``pyproject.toml`` file to wrap your extension in a Python package. Before generating a package, we first need to install ``build``. .. code:: bash pip install build To create a Python source package (``.tar.gz``) in the ``dist/`` directory, do: .. code:: bash python -m build -s To create a Python wheel package (``.whl``) in the ``dist/`` directory, do: .. code:: bash python -m build Both of these commands will build the JavaScript into a bundle in the ``jupyterlab_apod/labextension/static`` directory, which is then distributed with the Python package. This bundle will include any necessary JavaScript dependencies as well. You may want to check in the ``jupyterlab_apod/labextension/static`` directory to retain a record of what JavaScript is distributed in your package, or you may want to keep this "build artifact" out of your source repository history. You can now try installing your extension as a user would. Open a new terminal and run the following commands to create a new environment and install your extension. .. code:: bash conda create -n jupyterlab-apod jupyterlab conda activate jupyterlab-apod pip install jupyterlab_apod/dist/jupyterlab_apod-0.1.0-py3-none-any.whl jupyter lab You should see a fresh JupyterLab browser tab appear. When it does, execute the *Random Astronomy Picture* command to check that your extension works. .. _extension_tutorial_publish: Publishing your extension ------------------------- You can publish your Python package to the `PyPI `_ or `conda-forge `_ repositories so users can easily install the extension using ``pip`` or ``conda``. You may want to also publish your extension as a JavaScript package to the `npm `_ package repository for several reasons: 1. Distributing an extension as an npm package allows users to compile the extension into JupyterLab explicitly (similar to how was done in JupyterLab versions 1 and 2), which leads to a more optimal JupyterLab package. 2. As we saw above, JupyterLab enables extensions to use services provided by other extensions. For example, our extension above uses the ``ICommandPalette`` and ``ILayoutRestorer`` services provided by core extensions in JupyterLab. We were able to tell JupyterLab we required these services by importing their tokens from the ``@jupyterlab/apputils`` and ``@jupyterlab/application`` npm packages and listing them in our plugin definition. If you want to provide a service to the JupyterLab system for other extensions to use, you will need to publish your JavaScript package to npm so other extensions can depend on it and import and require your token. Automated Releases ^^^^^^^^^^^^^^^^^^ If you used the cookiecutter to bootstrap your extension, the repository should already be compatible with the `Jupyter Releaser `_. The Jupyter Releaser provides a set of GitHub Actions Workflows to: - Generate a new entry in the Changelog - Draft a new release - Publish the release to ``PyPI`` and ``npm`` For more information on how to run the release workflows, check out the documentation: https://github.com/jupyter-server/jupyter_releaser Learn more ---------- You've completed the tutorial. Nicely done! If you want to keep learning, here are some suggestions about what to try next: - Add the image description that comes in the API response to the panel. - Assign a default hotkey to the *Random Astronomy Picture* command. - Make the image a link to the picture on the NASA website (URLs are of the form ``https://apod.nasa.gov/apod/apYYMMDD.html``). - Make the image title and description update after the image loads so that the picture and description are always synced. - Give users the ability to pin pictures in separate, permanent panels. - Add a setting for the user to put in their `API key `__ so they can make many more requests per hour than the demo key allows. - Push your extension git repository to GitHub. - Learn how to write :ref:`other kinds of extensions `.