JupyterLab

An extensible environment for interactive and reproducible computing, based on the Jupyter Notebook and Architecture.

JupyterLab is the next-generation user interface for Project Jupyter offering all the familiar building blocks of the classic Jupyter Notebook (notebook, terminal, text editor, file browser, rich outputs, etc.) in a flexible and powerful user interface.

JupyterLab can be extended using npm packages that use our public APIs. The prebuilt extensions can be distributed via PyPI, conda, and other package managers. The source extensions can be installed directly from npm (search for jupyterlab-extension) but require an additional build step. You can also find JupyterLab extensions exploring GitHub topic jupyterlab-extension. To learn more about extensions, see the user documentation.

Read the current JupyterLab documentation on ReadTheDocs.

[!IMPORTANT] JupyterLab 3 reached its end of maintenance date on May 15, 2024. Fixes for critical issues will still be backported until December 31, 2024. If you are still running JupyterLab 3, we strongly encourage you to upgrade to JupyterLab 4 as soon as possible. For more information, see JupyterLab 3 end of maintenance on the Jupyter Blog.

Getting started

Installation

If you use conda, mamba, or pip, you can install JupyterLab with one of the following commands.

If you use conda:

conda install -c conda-forge jupyterlab

If you use mamba:

mamba install -c conda-forge jupyterlab

If you use pip:
```
pip install jupyterlab
```
If installing using pip install --user, you must add the user-level bin directory to your PATH environment variable in order to launch jupyter lab. If you are using a Unix derivative (e.g., FreeBSD, GNU/Linux, macOS), you can do this by running export PATH="$HOME/.local/bin:$PATH". If you are using a macOS version that comes with Python 2, run pip3 instead of pip.

For more detailed instructions, consult the installation guide. Project installation instructions from the git sources are available in the contributor documentation.

Installing with Previous Versions of Jupyter Notebook

When using a version of Jupyter Notebook earlier than 5.3, the following command must be run after installing JupyterLab to enable the JupyterLab server extension:

jupyter serverextension enable --py jupyterlab --sys-prefix

Running

Start up JupyterLab using:

jupyter lab

JupyterLab will open automatically in the browser. See the documentation for additional details.

If you encounter an error like "Command 'jupyter' not found", please make sure PATH environment variable is set correctly. Alternatively, you can start up JupyterLab using ~/.local/bin/jupyter lab without changing the PATH environment variable.

Prerequisites and Supported Browsers

The latest versions of the following browsers are currently known to work:

Firefox
Chrome
Safari

See our documentation for additional details.

Getting help

We encourage you to ask questions on the Discourse forum. A question answered there can become a useful resource for others.

Bug report

To report a bug please read the guidelines and then open a Github issue. To keep resolved issues self-contained, the lock bot will lock closed issues as resolved after a period of inactivity. If a related discussion is still needed after an issue is locked, please open a new issue and reference the old issue.

Feature request

We also welcome suggestions for new features as they help make the project more useful for everyone. To request a feature please use the feature request template.

Development

Extending JupyterLab

To start developing an extension for JupyterLab, see the developer documentation and the API docs.

Contributing

To contribute code or documentation to JupyterLab itself, please read the contributor documentation.

JupyterLab follows the Jupyter Community Guides.

License

JupyterLab uses a shared copyright model that enables all contributors to maintain the copyright on their contributions. All code is licensed under the terms of the revised BSD license.

Team

JupyterLab is part of Project Jupyter and is developed by an open community. The maintenance team is assisted by a much larger group of contributors to JupyterLab and Project Jupyter as a whole.

JupyterLab's current maintainers are listed in alphabetical order, with affiliation, and main areas of contribution:

Mehmet Bektas, Netflix (general development, extensions).
Alex Bozarth, IBM (general development, extensions).
Eric Charles, Datalayer, (general development, extensions).
Frédéric Collonval, WebScIT (general development, extensions).
Martha Cryan, Mito (general development, extensions).
Afshin Darian, QuantStack (co-creator, application/high-level architecture, prolific contributions throughout the code base).
Vidar T. Fauske, JPMorgan Chase (general development, extensions).
Brian Granger, AWS (co-creator, strategy, vision, management, UI/UX design, architecture).
Jason Grout, Databricks (co-creator, vision, general development).
Michał Krassowski, Quansight (general development, extensions).
Max Klein, JPMorgan Chase (UI Package, build system, general development, extensions).
Gonzalo Peña-Castellanos, QuanSight (general development, i18n, extensions).
Fernando Perez, UC Berkeley (co-creator, vision).
Isabela Presedo-Floyd, QuanSight Labs (design/UX).
Steven Silvester, MongoDB (co-creator, release management, packaging, prolific contributions throughout the code base).
Jeremy Tuloup, QuantStack (general development, extensions).

Maintainer emeritus:

Chris Colbert, Project Jupyter (co-creator, application/low-level architecture, technical leadership, vision, PhosphorJS)
Jessica Forde, Project Jupyter (demo, documentation)
Tim George, Cal Poly (UI/UX design, strategy, management, user needs analysis).
Cameron Oelsen, Cal Poly (UI/UX design).
Ian Rose, Quansight/City of LA (general core development, extensions).
Andrew Schlaepfer, Bloomberg (general development, extensions).
Saul Shanabrook, Quansight (general development, extensions)

This list is provided to give the reader context on who we are and how our team functions. To be listed, please submit a pull request with your information.

Weekly Dev Meeting

We have videoconference meetings every week where we discuss what we have been working on and get feedback from one another.

Anyone is welcome to attend, if they would like to discuss a topic or just listen in.

When: Wednesdays 9:00 AM Pacific Time (USA)
Where: jovyan Zoom
What: Meeting notes

Notes are archived on GitHub Jupyter Frontends team compass.

Release files for jupyterlab 4.2.5

For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.

Source distribution (sdist)

Source distribution for jupyterlab 4.2.5
File	Size	Uploaded
jupyterlab-4.2.5.tar.gz	21.5 MB	Aug 26, 2024	Details

Built distribution (wheel)

Table of built distributions (wheels) for jupyterlab 4.2.5
File	Interpreter	ABI	Platform	Reset
jupyterlab-4.2.5-py3-none-any.whl 11.6 MB Aug 26, 2024	Python 3	none	any	Details

Total release size: 33.2 MB

Release files / jupyterlab-4.2.5.tar.gz

Download URL	jupyterlab-4.2.5.tar.gz
Size	21.5 MB
Tags	Source
SHA-256 checksum How to use checksums	`ae7f3a1b8cb88b4f55009ce79fa7c06f99d70cd63601ee4aa91815d054f46f75`
BLAKE2b-256 checksum How to use checksums	`4a78ba006df6edaa561fe40be26c35e9da3f9316f071167cd7cc1a1a25bd2664`
Upload date	Aug 26, 2024
Uploaded using Trusted Publishing? What is trusted publishing?	Yes
Uploaded via	`twine/5.1.1 CPython/3.11.9`

Release files / jupyterlab-4.2.5-py3-none-any.whl

Download URL	jupyterlab-4.2.5-py3-none-any.whl
Size	11.6 MB
Tags	Python 3
SHA-256 checksum How to use checksums	`73b6e0775d41a9fee7ee756c80f58a6bed4040869ccc21411dc559818874d321`
BLAKE2b-256 checksum How to use checksums	`fd3f24a0f0ce60959cfd9756a3291cd3a5581e51cbd6f7b4aa121f5bba5320e3`
Upload date	Aug 26, 2024
Uploaded using Trusted Publishing? What is trusted publishing?	Yes
Uploaded via	`twine/5.1.1 CPython/3.11.9`