# Making a JupyterLab release This document guides a contributor through creating a release of JupyterLab. ## Check installed tools Review ``CONTRIBUTING.md``. Make sure all the tools needed to generate the built JavaScript files are properly installed. ## Creating a full release We publish the npm packages, a Python source package, and a Python universal binary wheel. We also publish a conda package on conda-forge (see below). See the Python docs on [package uploading](https://packaging.python.org/guides/tool-recommendations/) for twine setup instructions and for why twine is the recommended method. ### Publish the npm packages The command below ensures the latest dependencies and built files, then prompts you to select package versions. When one package has an effective major release, the packages that depend on it should also get a major release, to prevent consumers that are using the `^` semver requirement from getting a conflict. ```bash jlpm run publish ``` ### Publish the Python package - Update `jupyterlab/_version.py` with an `rc` version - Prep the static assets for release: ```bash jlpm run build:update ``` - Commit and tag and push the tag - Create the Python release artifacts: ```bash rm -rf dist python setup.py sdist python setup.py bdist_wheel --universal twine upload dist/* ``` - Test the `rc` in a clean environment - Make sure the CI builds pass - The build will fail if we publish a new package because by default it is private. Use `npm access public @jupyterlab/` to make it public. - The build will fail if we forget to include `style/` in the `files:` of a package (it will fail on the `jupyter lab build` command because webpack cannot find the referenced styles to import. - Update the other repos listed below - Update the extension examples listed below - Update the xkcd tutorial - Update `jupyterlab/_version.py` with a final version - Make another Python release - Create a branch for the release and push to GitHub - Merge the PRs on the other repos and set the default branch of the xckd repo - Publish to conda-forge (see below) - Update `jupyterlab/_version.py` with a `dev` version - Run `jlpm integrity` to update the `dev_mode` version - Commit and push the version update to master - Release the other repos as appropriate - Update version for binder (see below) ### Other repos to update - https://github.com/jupyterlab/extension-cookiecutter-js - https://github.com/jupyterlab/extension-cookiecutter-ts - https://github.com/jupyterlab/mimerender-cookiecutter - https://github.com/jupyterlab/mimerender-cookiecutter-ts - https://github.com/jupyterlab/jupyter-renderers - https://github.com/jupyterhub/jupyterlab-hub ### Extension examples to update - https://github.com/jupyterlab/jupyterlab/blob/master/docs/source/developer/notebook.rst#adding-a-button-to-the-toolbar ### Updating the xkcd tutorial - Create a new empty branch in the xkcd repo. ```bash git checkout --orphan name-of-branch git rm -rf . git clean -dfx cookiecutter path-to-local-extension-cookiecutter-ts # Fill in the values from the previous branch package.json initial commit cp -r jupyterlab_xkcd/ . rm -rf jupyterlab_xkcd ``` - Create a new PR in JupyterLab. - Run through the tutorial in the PR, making commits and updating the tutorial as appropriate. - Replace the tag references in the tutorial with the new branch number, e.g. replace `0.28-` with `0.29-`. - Prefix the new tags with the branch name, e.g. `0.28-01-show-a-panel` - For the publish section of the readme, use the `README` file from the previous branch, as well as the `package.json` fields up to `license`. - Push the branch and set it as the default branch for the tutorial repo. - Submit the PR to JupyterLab If you make a mistake and need to start over, clear the tags using the following pattern: ```bash git tag | grep 0.xx | xargs git tag -d ``` ### Publishing to conda-forge - Get the sha256 hash for conda-forge release: ```bash shasum -a 256 dist/*.tar.gz ``` - Fork https://github.com/conda-forge/jupyterlab-feedstock - Create a PR with the version bump - Update `recipe/meta.yaml` with the new version and md5 and reset the build number to 0. ## Making a patch release of a JavaScript package - Backport the change to the previous release branch - Make a new PR against the previous branch - Run the following script, where the package is in `/packages/package-folder-name`: ```bash jlpm run patch:release package-folder-name ``` - Push the resulting commit and tag. - Create a new Python release on the previous branch - Cherry pick the patch commit to the master branch - Update the dev version of the master branch in `_version.py` - Update the `package.json` file in `dev_mode` with the new JupyterLab version in the `jupyterlab` metadata section. ## Update version for binder Each time we release JupyterLab, we should update the version of JupyterLab used in binder and repo2docker. Here is an example PR that updates the relevant files: https://github.com/jupyter/repo2docker/pull/169/files This needs to be done in both the conda and pip buildpacks in both the frozen and non-frozen version of the files.