Contributing to the Jupyter Notebook

If you’re reading this section, you’re probably interested in contributing to Jupyter. Welcome and thanks for your interest in contributing!

Please take a look at the Contributor documentation, familiarize yourself with using the Jupyter Notebook, and introduce yourself on the mailing list and share what area of the project you are interested in working on.

General Guidelines

For general documentation about contributing to Jupyter projects, see the Project Jupyter Contributor Documentation.

Setting Up a Development Environment

Installing Node.js and npm

Building the Notebook from its GitHub source code requires some tools to create and minify JavaScript components and the CSS, specifically Node.js and Node’s package manager, npm. It should be node version ≥ 6.0.

If you use conda, you can get them with:

conda install -c conda-forge nodejs

If you use Homebrew on Mac OS X:

brew install node

Installation on Linux may vary, but be aware that the nodejs or npm packages included in the system package repository may be too old to work properly.

You can also use the installer from the Node.js website.

Installing the Jupyter Notebook

Once you have installed the dependencies mentioned above, use the following steps:

pip install --upgrade setuptools pip
git clone
cd notebook
pip install -e .

If you are using a system-wide Python installation and you only want to install the notebook for you, you can add --user to the install commands.

Once you have done this, you can launch the master branch of Jupyter notebook from any directory in your system with:

jupyter notebook

Rebuilding JavaScript and CSS

There is a build step for the JavaScript and CSS in the notebook. To make sure that you are working with up-to-date code, you will need to run this command whenever there are changes to JavaScript or LESS sources:

npm run build

IMPORTANT: Don’t forget to run npm run build after switching branches. When switching between branches of different versions (e.g. 4.x and master), run pip install -e .. If you have tried the above and still find that the notebook is not reflecting the current source code, try cleaning the repo with git clean -xfd and reinstalling with pip install -e ..

Development Tip

When doing development, you can use this command to automatically rebuild JavaScript and LESS sources as they are modified:

npm run build:watch

Git Hooks

If you want to automatically update dependencies and recompile JavaScript and CSS after checking out a new commit, you can install post-checkout and post-merge hooks which will do it for you:


See git-hooks/ for more details.

Running Tests

Python Tests

Install dependencies:

pip install -e .[test]

To run the Python tests, use:


If you want coverage statistics as well, you can run:

nosetests --with-coverage --cover-package=notebook notebook

JavaScript Tests

To run the JavaScript tests, you will need to have PhantomJS and CasperJS installed:

npm install -g casperjs phantomjs-prebuilt

Then, to run the JavaScript tests:

python -m notebook.jstest [group]

where [group] is an optional argument that is a path relative to notebook/tests/. For example, to run all tests in notebook/tests/notebook:

python -m notebook.jstest notebook

or to run just notebook/tests/notebook/deletecell.js:

python -m notebook.jstest notebook/deletecell.js

Building the Documentation

To build the documentation you’ll need Sphinx, pandoc and a few other packages.

To install (and activate) a conda environment named notebook_docs containing all the necessary packages (except pandoc), use:

conda env create -f docs/environment.yml
source activate notebook_docs  # Linux and OS X
activate notebook_docs         # Windows

If you want to install the necessary packages with pip instead:

pip install -r docs/doc-requirements.txt

Once you have installed the required packages, you can build the docs with:

cd docs
make html

After that, the generated HTML files will be available at build/html/index.html. You may view the docs in your browser.

You can automatically check if all hyperlinks are still valid:

make linkcheck

Windows users can find make.bat in the docs folder.

You should also have a look at the Project Jupyter Documentation Guide.