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.
Table of contents
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
orconda
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.
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 adisabledExtensions
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/pageconfig.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 fromallowed_extensions_uris
: A list of comma-separated URIs to fetch an allowlist file fromlistings_refresh_seconds
: The interval delay in seconds to refresh the listslistings_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"
}
]
}