Extensions

Fundamentally, JupyterLab is designed as an extensible environment. JupyterLab extensions can customize or enhance any part of JupyterLab. They can provide new themes, file viewers and editors, or renderers for rich outputs in notebooks. Extensions can add items to the menu or command palette, keyboard shortcuts, or settings in the settings system. Extensions can provide an API for other extensions to use and can depend on other extensions. In fact, the whole of JupyterLab itself is simply a collection of extensions that are no more powerful or privileged than any custom extension.

For information about developing extensions, see the developer documentation.

Installing Extensions

A JupyterLab extension contains JavaScript that is installed into Jupyterlab and run in the browser. An extension contains one or more plugins that extend JupyterLab. There are two types of JupyterLab extensions: a source extension (which requires a rebuild of JupyterLab when installed), and a prebuilt extension (which does not require a rebuild of JupyterLab). Rebuilding JupyterLab requires Node.js to be installed.

JupyterLab extensions can be installed in a number of ways, including:

  • Python pip or conda packages can include either a source extension or a prebuilt extension. These packages may also include a server-side component necessary for the extension to function.

  • The Extension Manager in JupyterLab and the jupyter labextension install command can install source extension packages from npm. Installing a source extension requires Node.js and a JupyterLab rebuild to activate. See Installing Node.js and Managing Extensions with jupyter labextension.

Browsing Extensions on PyPI

The Python Package Index (PyPI) is a repository of software for the Python programming language, and the default source of packages for the pip package manager. While a simple text search will reveal hundreds of packages, a number of trove classifiers are available for packages to self-describe the features and compatibility provided:

Note

These classifiers were accepted in early August 2021, and it will take some time for them to be broadly adopted.

You can help! The proposal of classifiers to a packages’s setup.py, setup.cfg, or pyproject.toml can make a great first open source contribution, as such contributions are:

  • easy for you, often possible directly through a project’s source code website, e.g. GitHub or GitLab,

  • easy for maintainers to review and merge, and

  • can have a positive impact on the discoverability of the package

Installing Node.js

Source extensions require Node.js to rebuild JupyterLab and activate the extension. If you use conda with conda-forge packages, you can get Node.js with:

conda install -c conda-forge nodejs

If you use conda with default Anaconda packages (i.e., you don’t normally use conda-forge), you should install Node.js from the Anaconda default channel with conda install nodejs instead.

You may also be able to get Node.js from your system package manager, or you can download Node.js from the Node.js website and install it directly.

Managing Extensions with jupyter labextension

The jupyter labextension command enables you to install or uninstall source extensions from npm, list all installed extensions, or disable any extension. See the help with jupyter labextension --help.

Installing and Uninstalling Source Extensions

You can install source extensions from npm with:

jupyter labextension install my-extension my-other-extension

Use the my-extension@version syntax to install a specific version of an extension, for example:

jupyter labextension install my-extension@1.2.3

You can also install a source extension that is not uploaded to npm, i.e., my-extension can be a local directory containing the extension, a gzipped tarball, or a URL to a gzipped tarball.

Note

Installing a source extension will require installing Node.js and require a rebuild of JupyterLab.

Uninstall source extensions using the command:

jupyter labextension uninstall my-extension my-other-extension

If you are installing/uninstalling several extensions in several stages, you may want to defer rebuilding JupyterLab by including the flag --no-build in the install/uninstall step. Once you are ready to rebuild, you can run the command:

jupyter lab build

Note

If you are rebuilding JupyterLab on Windows, you may encounter a FileNotFoundError due to the default path length on Windows. Node modules are stored in a deeply nested directory structure, so paths can get quite long. If you have administrative access and are on Windows 8 or 10, you can update the registry setting using these instructions: https://stackoverflow.com/a/37528731.

Listing installed extensions

List all installed extensions, including those installed with pip or conda, with:

jupyter labextension list

Note

jupyter labextension identifies an extension by its JavaScript package name, which may be different from the name of the pip or conda package used to distribute the extension.

Enabling and Disabling Extensions

Disabling an extension prevents the all plugins in the extension from running in JupyterLab (though the code is still loaded). You can disable specific JupyterLab extensions (including core extensions) without rebuilding JupyterLab with:

jupyter labextension disable my-extension

You can enable a disabled extension with:

jupyter labextension enable my-extension

Installed extensions are enabled by default unless there is configuration explicitly disabling them. Extensions can be disabled or enabled using the command line. Extensions or individual plugins within an extension can be disabled by another extension.

The priority order for determining whether an extension is enabled or disabled is as follows:

  • Presence of <jupyter_config_path>/labconfig/page_config.json file(s) with a disabledExtensions key that is a object with package names as keys and boolean values.

  • (deprecated) Presence of disabledExtensions key in <lab_app_dir>/settings/page_config.json. This value is a list of extensions to disable, but is deprecated in favor of the layered configuration approach in the labconfig location(s).

  • Presence of disabledExtensions key in another JupyterLab extension’s metadata that disables a given extension. The key is ignored if that extension itself is disabled.

When using the command line, you can target the --level of the config: user, system, or sys-prefix (default).

An example <jupyter_config_path>/labconfig/page_config.json could look as follows:

{
   "disabledExtensions": {
         "@jupyterlab/notebook-extension": true
   }
}

See documentation on LabConfig directories for more information.

Managing Extensions Using the Extension Manager

You can use the Extension Manager in JupyterLab to manage extensions that are distributed as single JavaScript packages on npm.

The Extension Manager is in the left sidebar.

Figure: The default view has three components: a search bar, an “Installed” section, and a “Discover” section.

Disclaimer

Danger

Installing an extension allows it to execute arbitrary code on the server, kernel, and the browser. Therefore, we ask you to explicitly acknowledge this.

By default, the disclaimer is not acknowledged.

Figure: User has not acknowledged the disclaimer

As the disclaimer is not acknowledged, you can search for an extension, but can not install it (no install button is available).

Figure: With Disclaimer unchecked, you can not install an extension

To install an extension, you first have to explicitly acknowledge the disclaimer. Once done, this will remain across sessions and the user does not have to check it again.

Figure: Disclaimer checked

For ease of use, you can hide the disclaimer so it takes less space on your screen.

Figure: Disclaimer is hidden

Finding Extensions

You can use the extension manager to find extensions for JupyterLab. To discovery freely among the currently available extensions, expand the “Discovery” section. This triggers a search for all JupyterLab extensions on the NPM registry, and the results are listed according to the registry’s sort order. An exception to this sort order is that extensions released by the Jupyter organization are always placed first. These extensions are distinguished by a small Jupyter icon next to their name.

Alternatively, you can limit your discovery by using the search bar. This performs a free-text search of JupyterLab extensions on the NPM registry.

Installing an Extension

Once you have found a source extension that you think is interesting, install it by clicking the “Install” button of the extension list entry.

Danger

Installing an extension allows it to execute arbitrary code on the server, kernel, and in the client’s browser. You should therefore avoid installing extensions you do not trust, and watch out for any extensions trying to masquerade as a trusted extension.

A short while after starting the install of an extension, a drop-down should appear under the search bar indicating that the extension has been downloaded, but that a rebuild is needed to complete the installation.

If you want to install/uninstall other extensions as well, you can ignore the rebuild notice until you have made all the changes you want. Once satisfied, click the ‘Rebuild’ button to start a rebuild in the background. Once the rebuild completes, a dialog will pop up, indicating that a reload of the page is needed in order to load the latest build into the browser.

If you ignore the rebuild notice by mistake, simply refresh your browser window to trigger a new rebuild check.

Managing Installed Extensions

When there are some installed extensions, they will be shown in the “Installed” section. These can then be uninstalled (if they are source extensions) or disabled. Disabling an extension will prevent it from being activated, but without rebuilding the application.

Companion packages

During installation of an extension, JupyterLab will inspect the package metadata for any instructions on companion packages. Companion packages can be:

  • Notebook server extensions (or any other packages that need to be installed on the Notebook server).

  • Kernel packages. An example of companion packages for the kernel are Jupyter Widget packages, like the ipywidgets Python package for the @jupyter-widgets/jupyterlab-manager package.

If JupyterLab finds instructions for companion packages, it will present a dialog to notify you about these. These are informational only, and it will be up to you to take these into account or not.

Listings

When searching source extensions in the Extension Manager, JupyterLab displays the complete search result and the user is free to install any source extension. This is the Default mode.

To bring more security, you or your administrator can enable blocklists or allowlists mode. JupyterLab will check the extensions against the defined listings.

Warning

Only one mode at a time is allowed. If you or your server administrator configures both block and allow listings, the JupyterLab server will not start.

Figure: Simultaneous block and allow listings

The following details the behavior for the Blocklist mode and the Allowlist mode. The details to enable configure the listings can be read Listing Configuration.

Default mode

In the default mode, no listing is enabled and the search behavior is unchanged and is the one described previously.

Blocklist mode

Extensions can be freely downloaded without going through a vetting process. However, users can add malicious extensions to a blocklist. The extension manager will show all extensions except for those that have been explicitly added to the blocklist. Therefore, the extension manager does not allow you to install blocklisted extensions.

If you, or your administrator, has enabled the blocklist mode, JupyterLab will use the blocklist and remove all blocklisted extensions from your search result.

If you have installed an extension before it has been blocklisted, the extension entry in the installed list will be highlighted in red. It is recommended that you uninstall it. You can move your mouse on the question mark icon to read the instructions.

Figure: Blocklisted installed extension which should be removed

Allowlist mode

An allowlist maintains a set of approved extensions that users can freely search and install. Extensions need to go through some sort of vetting process before they are added to the allowlist. When using an allowlist, the extension manager will only show extensions that have been explicitly added to the allowlist.

If you, or your administrator, has enabled the allowlist mode JupyterLab will use the allowlist and only show extensions present in the allowlist. The other extensions will not be show in the search result.

If you have installed an allowlisted extension and at some point in time that extension is removed from the allowlist, the extension entry in the installed list will be highlighted in red. It is recommended that you uninstall it. You can move your mouse on the question mark icon to read the instructions.

Figure: The second of the installed extensions was removed from the allowlist and should be removed

Listing Configuration

You or your administrator can use the following traits to define the listings loading.

  • blocked_extensions_uris: A list of comma-separated URIs to fetch a blocklist file from

  • allowed_extensions_uris: A list of comma-separated URIs to fetch an allowlist file from

  • listings_refresh_seconds: The interval delay in seconds to refresh the lists

  • listings_request_options: The optional kwargs to use for the listings HTTP requests

For example, to set blocked extensions, launch the server with --LabServerApp.blocked_extensions_uris=http://example.com/blocklist.json where http://example.com/blocklist.json is a JSON file as described below.

The details for the listings_request_options are listed on this page (for example, you could pass {'timeout': 10} to change the HTTP request timeout value).

The listings are json files hosted on the URIs you have given.

For each entry, you have to define the name of the extension as published in the NPM registry. The name attribute supports regular expressions.

Optionally, you can also add some more fields for your records (type, reason, creation_date, last_update_date). These optional fields are not used in the user interface.

This is an example of a blocklist file.

{
  "blocked_extensions": [
    {
      "name": "@jupyterlab-examples/launcher",
      "type": "jupyterlab",
      "reason": "@jupyterlab-examples/launcher is blocklisted for test purpose - Do NOT take this for granted!!!",
      "creation_date": "2020-03-11T03:28:56.782Z",
      "last_update_date":  "2020-03-11T03:28:56.782Z"
    }
  ]
}

In the following allowed extensions @jupyterlab/* will allow all jupyterlab organization extensions.

{
  "allowed_extensions": [
    {
      "name": "@jupyterlab/*",
      "type": "jupyterlab",
      "reason": "All @jupyterlab org extensions are allowed, of course…",
      "creation_date": "2020-03-11T03:28:56.782Z",
      "last_update_date":  "2020-03-11T03:28:56.782Z"
    }
  ]
}