Skip to main content

JupyterLab computational environment

Project description

Installation | Documentation | Contributing | License | Team | Getting help |

JupyterLab

PyPI version Downloads Build Status Build Status Documentation Status Crowdin GitHub Discourse Gitter Gitpod

Binder

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.

Notes are archived on GitHub Jupyter Frontends team compass.

Project details


Release history Release notifications | RSS feed

Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Source Distribution

jupyterlab-4.2.6.tar.gz (21.5 MB view details)

Uploaded Source

Built Distribution

jupyterlab-4.2.6-py3-none-any.whl (11.6 MB view details)

Uploaded Python 3

File details

Details for the file jupyterlab-4.2.6.tar.gz.

File metadata

  • Download URL: jupyterlab-4.2.6.tar.gz
  • Upload date:
  • Size: 21.5 MB
  • Tags: Source
  • Uploaded using Trusted Publishing? Yes
  • Uploaded via: twine/5.1.1 CPython/3.11.10

File hashes

Hashes for jupyterlab-4.2.6.tar.gz
Algorithm Hash digest
SHA256 625f3ac19da91f9706baf66df25723b2f1307c1159fc7293035b066786d62a4a
MD5 b3b6ff42b26eeccb8f8f098a3bbdab17
BLAKE2b-256 5d45bcbad1b69a21ae2a6cfb0cdc2bce8853741179d609d578e30e64aaed3792

See more details on using hashes here.

File details

Details for the file jupyterlab-4.2.6-py3-none-any.whl.

File metadata

  • Download URL: jupyterlab-4.2.6-py3-none-any.whl
  • Upload date:
  • Size: 11.6 MB
  • Tags: Python 3
  • Uploaded using Trusted Publishing? Yes
  • Uploaded via: twine/5.1.1 CPython/3.11.10

File hashes

Hashes for jupyterlab-4.2.6-py3-none-any.whl
Algorithm Hash digest
SHA256 78dd42cae5b460f377624b03966a8730e3b0692102ddf5933a2a3730c1bc0a20
MD5 402bbc146b311366d21673f570144212
BLAKE2b-256 f004853abc46fef36afd4e5f9a4fd1fbc1b477f910a29bb71711b6653098b703

See more details on using hashes here.

Supported by

AWS AWS Cloud computing and Security Sponsor Datadog Datadog Monitoring Fastly Fastly CDN Google Google Download Analytics Microsoft Microsoft PSF Sponsor Pingdom Pingdom Monitoring Sentry Sentry Error logging StatusPage StatusPage Status page