General Jupyter contributor guidelines#

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 Server, and introduce yourself on the mailing list and share what area of the project you are interested in working on.

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

Setting Up a Development Environment#

Installing the Jupyter Server#

The development version of the server requires node and pip.

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

pip install --upgrade pip
git clone
cd jupyter_server
pip install -e ".[test]"

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

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

jupyter server

Code Styling and Quality Checks#

jupyter_server has adopted automatic code formatting so you shouldn’t need to worry too much about your code style. As long as your code is valid, the pre-commit hook should take care of how it should look. pre-commit and its associated hooks will automatically be installed when you run pip install -e ".[test]"

To install pre-commit hook manually, run the following:

pre-commit install

You can invoke the pre-commit hook by hand at any time with:

pre-commit run

which should run any autoformatting on your code and tell you about any errors it couldn’t fix automatically. You may also install black integration into your text editor to format code automatically.

If you have already committed files before setting up the pre-commit hook with pre-commit install, you can fix everything up using pre-commit run --all-files. You need to make the fixing commit yourself after that.

Some of the hooks only run on CI by default, but you can invoke them by running with the --hook-stage manual argument.

There are three hatch scripts that can be run locally as well: hatch run lint:build will enforce styling. hatch run typing:test will run the type checker.

Troubleshooting the Installation#

If you do not see that your Jupyter Server is not running on dev mode, it’s possible that you are running other instances of Jupyter Server. You can try the following steps:

  1. Uninstall all instances of the jupyter_server package. These include any installations you made using pip or conda

  2. Run python -m pip install -e . in the jupyter_server repository to install the jupyter_server from there

  3. Run npm run build to make sure the Javascript and CSS are updated and compiled

  4. Launch with python -m jupyter_server --port 8989, and check that the browser is pointing to localhost:8989 (rather than the default 8888). You don’t necessarily have to launch with port 8989, as long as you use a port that is neither the default nor in use, then it should be fine.

  5. Verify the installation with the steps in the previous section.

Running Tests#

Install dependencies:

pip install -e .[test]
pip install -e examples/simple  # to test the examples

To run the Python tests, use:

pytest examples/simple  # to test the examples

You can also run the tests using hatch without installing test dependencies in your local environment:

pip install hatch
hatch run test:test

The command takes any argument that you can give to pytest, e.g.:

hatch run test:test -k name_of_method_to_test

You can also drop into a shell in the test environment by running:

hatch -e test shell

Building the Docs#

Install the docs requirements using pip:

pip install .[doc]

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

cd docs
make html

You can also run the tests using hatch without installing test dependencies in your local environment.

pip install hatch hatch run docs:build

You can also drop into a shell in the docs environment by running:

hatch -e docs shell

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

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

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