notebook/RELEASE.md
Jeremy Tuloup 23dd0cbb8b
Add workflow to automate releases (#83)
* Add workflow to automate releases

* Tmp: Change to trigger to test the workflow

* Add step to generate the changelog

* Update changelog command

* Tweak changelog

* Pass github token to the docker container

* Get previous tag for changelog

* Fix docker command

* wip workflow

* debug workflow

* Debug tag

* Add defaults for bash

* Add fetch depth to checkout

* Use real tag in GH Action step

* Create draft release for testing

* Tweak CHANGELOG

* More tweaks

* Update release instructions

* Tweak changelog

* Ensure build and release share common test jobs

* Upload artifacts to PyPI

* Prepare dist/

* Copy the wheel

* Update workflow to trigger on tags

* Test on TestPyPI

* Test API token

* Add TODO

* skip existing

* Switch to tags
2021-01-21 23:14:54 +01:00

2.6 KiB

Releasing JupyterLab Classic

Automated releases

Releases are automated using GitHub Actions. They are triggered when a new tag is pushed to the remote.

To cut a new release, run the following:

# checkout the main branch
git checkout main

# for a patch release
jlpm release:patch

# for a minor version bump
jlpm release:bump minor

# for a major version bump
jlpm release:bump major

# push to the main branch
git push origin main --tags

We follow a similar bump strategy as in JupyterLab: https://github.com/jupyterlab/jupyterlab/blob/master/RELEASE.md#bump-version

The release workflow also creates a GitHub release with the new changes generated with github-changelog-generator.

If you would still like to do the release manually instead, read below.

Making a nanual new release of JupyterLab Classic

This process is still a bit manual and consists in running a couple of commands.

Getting a clean environment

Creating a new environment can help avoid pushing local changes and any extra tag.

mamba create -q -y -n jupyterlab-classic-release -c conda-forge twine nodejs jupyter-packaging jupyterlab -y
conda activate jupyterlab-classic-release

Alternatively, the local repository can be cleaned with:

git clean -fdx

Releasing on PyPI

Make sure the dist/ folder is empty.

  1. Update jupyterlab_classic/_version.py with the new version number
  2. Commit the changes
  • git add jupyterlab_classic/_version.py
  • git commit -m "Release x.y.z"
  1. Bump the frontend packages:
  • jlpm
  • jlpm run lerna version x.y.z --no-push --amend --force-publish
  1. Run: python setup.py sdist bdist_wheel
  2. Double check the size of the bundles in the dist/ folder
  3. Test the release by installing the wheel or sdist: `python -m pip install ./dist/jupyterlab_classic-x.y.z-py3-none-any.whl
  4. export TWINE_USERNAME=mypypi_username
  5. twine upload dist/*

Releasing on conda-forge

The simplest is to wait for the bot to automatically open the PR.

Alternatively, to do the update manually:

  1. Open a new PR on https://github.com/conda-forge/jupyterlab-classic-feedstock to update the version and the sha256 hash
  2. Wait for the tests
  3. Merge the PR

The new version will be available on conda-forge soon after.

Publish the packages to npm

  1. Publish the packages: jlpm run lerna publish from-package

Committing and tagging

Push the release commit to the main branch:

git push origin main

Then create a new release from the GitHub interface.