jupyterlab

JupyterLab

An extensible computational environment for Jupyter.

JupyterLab is a very early developer preview, and is not suitable for general usage yet. Features and implementation are subject to change.

With JupyterLab, you can create a computational environment for Jupyter that meets your workflow needs. Here's a quick preview of JupyterLab:

Getting started

Prerequisite

Jupyter notebook version 4.2 or later. To check the notebook version:

jupyter notebook --version

User installation

From the command line:

pip install jupyterlab
jupyter serverextension enable --py jupyterlab

Start up JupyterLab:

jupyter lab

JupyterLab will open automatically in your browser. You may also access JupyterLab by entering the notebook server's URL (http://localhost:8888) in the browser.

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Documentation

• API Docs
• Architecture tutorial

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Contributing to JupyterLab

Setting up a development system

Prerequisites

• Jupyter notebook version 4.2 or later
• NodeJS (preferably version 5 or later) and npm

Installation

Fork the JupyterLab repo using the GitHub UI. Clone the repo and build using these commands:

git clone https://github.com/<your-github-username>/jupyterlab.git
cd jupyterlab
npm install
pip install -e . # will take a long time to build everything
jupyter serverextension enable --py jupyterlab

Run JupyterLab

Start JupyterLab:

jupyter lab

Alternatively, you can run JupyterLab in debug mode:

jupyter lab --debug

Run the tests

npm test

Build and run the stand-alone examples

To install and build the examples in the examples directory:

npm run build:examples

To run a specific example, change to the example's directory (i.e. examples/filebrowser) and enter:

python main.py

Build API Docs

To build the API docs:

npm run docs

Navigate to docs/index.html.

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High level Architecture

The JupyterLab application is made up of two major parts:

• an npm package
• a Jupyter server extension (Python package)

Each part is named jupyterlab. The developer tutorial documentation provides additional architecture information.

The NPM Package

The npm package source files are in the src/ subdirectory.

Prerequisites

• node (preferably version 5 or later)
• Jupyter notebook server version 4.2 or later (to run examples)

npm install --save jupyterlab

Build the NPM Package from Source

git clone https://github.com/jupyter/jupyterlab.git
cd jupyterlab
npm install
npm run build:all

Rebuild

npm run clean
npm run build:all

The Jupyter Server Extension

The Jupyter server extension source files are in the jupyterlab/ subdirectory. To use this extension, make sure the Jupyter notebook server version 4.2 or later is installed.

Build the JupyterLab server extension

When you make a change to JupyterLab npm package source files, run:

npm run build:serverextension

to build the changes and then refresh your browser to see the changes.

To have the system build after each source file change, run:

npm run watch:serverextension

and refresh the browser.

Bundle for the Browser

Follow the package install instructions first.

Any bundler that understands how to require() files with .js and .css extensions can be used with this package.

Note: This npm module is fully compatible with Node/Babel/ES6/ES5. Simply omit the type declarations when using a language other than TypeScript.

Supported Runtimes

The runtime versions which are currently known to work:

• IE 11+
• Firefox 32+
• Chrome 38+

Earlier browser versions may also work, but come with no guarantees.

Note: "requirejs" must be included in a global context (usually as a <script> tag) for Comm targets.

Publishing packages for a JupyterLab release

We publish an npm package, a Python source package, and a Python universal binary wheel. We also publish a conda package on conda-forge (see below). See the Python docs on package uploading for twine setup instructions and for why twine is the recommended method.

npm version patch
git push origin master --tags
npm publish
rm -rf dist
python setup.py sdist
python setup.py bdist_wheel --universal
twine upload dist/*
md5 dist/*.tar.gz  # get the md5 hash for conda-forge install

Publish on conda-forge

• Fork https://github.com/conda-forge/jupyterlab-feedstock
• Create a PR with the version bump
• Update recipe/meta.yaml with the new version and md5