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 https://github.com/jupyter/notebook
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:
git-hooks/install-hooks.sh
See git-hooks/README.md
for more details.
Running Tests¶
Python Tests¶
Install dependencies:
pip install -e .[test]
To run the Python tests, use:
nosetests
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.