Internationalization and Localization

This section describes the various elements at play to create localized strings for JupyterLab.

Four elements are used to handle the internationalization of JupyterLab:

  • language-packs repository: It contains the source strings, their translations, the language packs and the GitHub workflows to update and publish the translations.

  • Crowdin project: Crowdin is the cloud-based solution that streamlines localization management for JupyterLab. This is the place where contributors can translate JupyterLab strings.

  • jupyterlab-translate repository: Python library defining helpers to deal with internationalization (e.g. extracting the strings).

  • Cookiecutter template repository: It defines the Python package template of a language pack.

The language-packs repository is the main entry point. It interacts with Crowdin to publish newer source strings and get the latest translation. It also creates and updates the language packs. And finally it publishes them. All those actions are carried out using helpers defined in jupyterlab-translate and the cookiecutter template.

Workflows

The workflows at play will be described next, in the order they are usually called.

Note

Automatic tasks are carried out through the jupyterlab-bot. To do that, that bot has access to the GitHub repository, the Crowdin project and all language packs projects on PyPI.

Source strings generation

Source strings are extracted for JupyterLab and a list of extensions at a given version defined in repository-map.yaml file in language-packs repository. The workflow to trigger an update is as follow:

  1. Edit repository-map.yaml by adding new repositories and/or updating the target version.

  2. Push the change in a pull request.

  3. Once the pull request is merged, the workflow Update source strings will automatically be triggered.

  4. That workflow will open a new pull request that will update the source strings and optionally the Crowdin configuration.

  5. Once that pull request is merged, Crowdin will upload the new source strings automatically.

Note

Crowdin is uploading automatically its source strings using GitHub Integration set up with the Crowdin account of jupyterlab-bot.

The script used for this workflow is 02_update_catalogs.py.

Translation update

The new and/or updated translation are automatically pushed to the language-packs repository. The workflow is as follow:

  1. A contributor updates the translation on JupyterLab Crowdin project

  2. A new commit with those changes is pushed to the language-packs repository on a branch named l10n_master.

  3. If there is no pull request associated with that branch, a new pull request will be opened.

  4. A maintainer needs to merge that pull request.

Note

Crowdin is automatically uploading the translation using GitHub Integration set up with the Crowdin account of jupyterlab-bot. Hence the commits and pull request is attributed to the bot.

If the branch is deleted, it will be re-created.

Warning

To avoid merge conflicts on those translation update pull requests, they should be merged before any repository-map.yaml pull requests as those will update the source strings. If not, the pull requests updating the source strings need to be closed in order for the Crowdin integration to re-open the PR.

Language packs update

Before a release of updated language packs with new translations from Crowdin the language packs need to be prepared by updating the version strings of all packages. This is done by manually triggering the Prepare language packs for release workflow.

There is one optional setting:

  • The new version in form X.Y.postZ - if not provided, the post number will be bumped.

../_images/prep_language_packs.png

The workflow is:

  1. Trigger the manual Prepare language packs for release workflow

  2. That workflow will open a new pull request with the changes to the language packs

  3. The validation workflow Check language packs version should pass on that pull request

  4. A maintainer needs to merge the pull request

Note

The version policy for the language packs is to follow major and minor version numbers of JupyterLab and bumping the post number for any intermediate updates. The version of all language packs is identical to ease maintenance.

The script used for this workflow is 03_prepare_release.py.

Language packs publication

Each time a .bumpversion.cfg in any language packs is modified the Create Release and publish packages will be automatically triggered. Its steps are:

  1. Check that all language packs have identical versions

  2. Start a matrix of job (one for each language pack)

    1. Build the source and wheel artifacts

    2. Create a GitHub release with tag <locale>@v<version>

    3. Publish the artifacts to PyPI

Note

Publication is done using jupyterlab-bot credentials on all PyPI projects.

Conda recipe should be updated by the auto-tick bot of conda-forge.

Adding a new language pack

This requires the following manual actions to be executed (in that order):

  1. Add the language on Crowdin

  2. Execute the Language packs update workflow

  3. Manually upload the package on PyPI

  4. Update the owner on PyPI to add jupyterlab-bot as maintainer

  5. Acknowledge the grant for the bot

  6. Update the github action list

  7. Update the conda-forge variant list