.. _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 <https://apod.nasa.gov/apod/astropix.html>`__" 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 <https://github.com/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 <https://apod.nasa.gov/apod/ap150724.html>`__.
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 <https://docs.conda.io/projects/conda/en/latest/user-guide/install/index.html>`__.
.. _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 <https://github.com/audreyr/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 <https://nodejs.org>`__, the JavaScript runtime you'll use to
compile the web assets (e.g., TypeScript, CSS) for your extension
4. `git <https://git-scm.com>`__, 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 <https://docs.github.com/en/get-started/quickstart/create-a-repo>`__. 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 <https://docs.microsoft.com/en-us/windows/apps/get-started/enable-your-device-for-development>`__
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 <https://developer.chrome.com/devtools#access>`__
- `Opening the Web Console in
Firefox <https://developer.mozilla.org/en-US/docs/Tools/Web_Console/Opening_the_Web_Console>`__
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 <https://github.com/jupyterlab/jupyterlab/blob/3.4.x/README.md#getting-help>`__ 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<void> = {
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 <https://github.com/jupyterlab/jupyterlab_apod/tree/3.0-01-show-a-panel>`__.
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 ``<img>`` 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 <https://developer.mozilla.org/en-US/docs/Web/API/Fetch_API/Using_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 <https://developer.mozilla.org/en-US/docs/Learn/JavaScript/Asynchronous/Promises>`_
Be sure to also refer to the other resources in the
`See Also <https://developer.mozilla.org/en-US/docs/Learn/JavaScript/Asynchronous/Promises#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 <https://apod.nasa.gov/apod/ap140119.html>`__.
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 <https://github.com/jupyterlab/jupyterlab_apod/tree/3.0-02-show-an-image>`__
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 <https://github.com/jupyterlab/jupyterlab_apod/tree/3.0-03-style-and-attribute>`__.
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<void> {
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<void> = {
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 <https://github.com/jupyterlab/jupyterlab_apod/tree/3.0-04-refactor-and-refresh>`__
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<void> = {
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<APODWidget>;
// 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<MainAreaWidget<APODWidget>>({
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 <https://apod.nasa.gov/apod/ap150724.html>`__.
Refer to the `05-restore-panel-state
tag <https://github.com/jupyterlab/jupyterlab_apod/tree/3.0-05-restore-panel-state>`__
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 <https://pypi.org>`_ or
`conda-forge <https://conda-forge.org>`_ 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 <https://www.npmjs.com>`_ 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 <https://github.com/jupyter-server/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 <https://api.nasa.gov/#authentication>`__ 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 <developer_extensions>`.