If you want to test a feature that has been integrated in main but not delivered yet to pip or conda, use
HATCH_BUILD_HOOKS_ENABLE=true pip install git+https://github.com/mwouts/jupytext.git
The above requires node. You can install it with e.g.
conda install 'nodejs>=20' -c conda-forge
Alternatively you can build only Jupytext core (e.g. skip the JupyterLab extension). To do so, remove HATCH_BUILD_HOOKS_ENABLE=true in the above.
Finally, if you want to test a development branch, use
HATCH_BUILD_HOOKS_ENABLE=true pip install git+https://github.com/mwouts/jupytext.git@branch
where branch is the name of the branch you want to test.
Most of Jupytext's code is written in Python. To develop the Python part of Jupytext, you should clone Jupytext, then create a dedicated Python env:
conda env create --file environment.yml # or conda env update --file ...
conda activate jupytext-dev
Install the jupytext package in development mode with
HATCH_BUILD_HOOKS_ENABLE=true pip install -e '.[dev]'
We use the pre-commit package to run pre-commit scripts like black and ruff on the code.
Install it with
pre-commit install
Tests are executed with pytest. You can run them in parallel with for instance
pytest -n 5
Some tests require a Jupyter kernel pointing to the current environment:
python -m ipykernel install --name jupytext-dev --user
Our extension for JupyterLab adds a series of Jupytext commands to JupyterLab. The code is in packages/labextension. See the README.md there for instructions on how to develop that extension.
Install the documentation tools with
conda env create --file docs/environment.yml
conda activate jupytext-docs
cd docs
and build the HTML documentation locally with
rm -rf _build
make html