python-gitlab 2.9.0

Interact with GitLab API

Python GitLab

python-gitlab is a Python package providing access to the GitLab server API.

It supports the v4 API of GitLab, and provides a CLI tool (gitlab).

Installation

Requirements

python-gitlab depends on:

• python-requests

Install with pip

pip install python-gitlab

Using the python-gitlab docker image

How to build

docker build -t python-gitlab:TAG .

How to use

docker run -it --rm -e GITLAB_PRIVATE_TOKEN=<your token> -v /path/to/python-gitlab.cfg:/python-gitlab.cfg python-gitlab <command> ...

or run it directly from the upstream image:

docker run -it --rm -e GITLAB_PRIVATE_TOKEN=<your token> -v /path/to/python-gitlab.cfg:/python-gitlab.cfg registry.gitlab.com/python-gitlab/python-gitlab:latest <command> ...

To change the GitLab URL, use -e GITLAB_URL=<your url>

Bring your own config file: docker run -it --rm -v /path/to/python-gitlab.cfg:/python-gitlab.cfg -e GITLAB_CFG=/python-gitlab.cfg python-gitlab <command> ...

Bug reports

Please report bugs and feature requests at https://github.com/python-gitlab/python-gitlab/issues.

Gitter Community Chat

There is a gitter community chat available at https://gitter.im/python-gitlab/Lobby

Documentation

The full documentation for CLI and API is available on readthedocs.

Build the docs

You can build the documentation using sphinx:

pip install sphinx
python setup.py build_sphinx

Contributing

You can contribute to the project in multiple ways:

• Write documentation

• Implement features

• Fix bugs

• Add unit and functional tests

• Everything else you can think of

Development workflow

Before contributing, please make sure you have pre-commit installed and configured. This will help automate adhering to code style and commit message guidelines described below:

cd python-gitlab/
pip3 install --user pre-commit
pre-commit install -t pre-commit -t commit-msg --install-hooks

Please provide your patches as GitHub pull requests. Thanks!

Commit message guidelines

We enforce commit messages to be formatted using the conventional-changelog. This leads to more readable messages that are easy to follow when looking through the project history.

Code-Style

We use black as code formatter, so you’ll need to format your changes using the black code formatter. Pre-commit hooks will validate/format your code when committing. You can then stage any changes black added if the commit failed.

To format your code according to our guidelines before committing, run:

cd python-gitlab/
pip3 install --user black
black .

Running unit tests

Before submitting a pull request make sure that the tests and lint checks still succeed with your change. Unit tests and functional tests run in GitHub Actions and passing checks are mandatory to get merge requests accepted.

Please write new unit tests with pytest and using responses. An example can be found in tests/unit/objects/test_runner.py

You need to install tox (pip3 install tox) to run tests and lint checks locally:

# run unit tests using your installed python3, and all lint checks:
tox -s

# run unit tests for all supported python3 versions, and all lint checks:
tox

# run tests in one environment only:
tox -epy38

# build the documentation, the result will be generated in
# build/sphinx/html/
tox -edocs

Running integration tests

Integration tests run against a running gitlab instance, using a docker container. You need to have docker installed on the test machine, and your user must have the correct permissions to talk to the docker daemon.

To run these tests:

# run the CLI tests:
tox -e cli_func_v4

# run the python API tests:
tox -e py_func_v4

When developing tests it can be a little frustrating to wait for GitLab to spin up every run. To prevent the containers from being cleaned up afterwards, pass –keep-containers to pytest, i.e.:

tox -e py_func_v4 -- --keep-containers

If you then wish to test against a clean slate, you may perform a manual clean up of the containers by running:

docker-compose -f tests/functional/fixtures/docker-compose.yml -p pytest-python-gitlab down -v

By default, the tests run against the latest version of the gitlab/gitlab-ce image. You can override both the image and tag by providing either the GITLAB_IMAGE or GITLAB_TAG environment variables.

This way you can run tests against different versions, such as nightly for features in an upcoming release, or an older release (e.g. 12.8.0-ce.0). The tag must match an exact tag on Docker Hub:

# run tests against `nightly` or specific tag
GITLAB_TAG=nightly tox -e py_func_v4
GITLAB_TAG=12.8.0-ce.0 tox -e py_func_v4

# run tests against the latest gitlab EE image
GITLAB_IMAGE=gitlab/gitlab-ee tox -e py_func_v4

A freshly configured gitlab container will be available at http://localhost:8080 (login root / password 5iveL!fe). A configuration for python-gitlab will be written in /tmp/python-gitlab.cfg.

To cleanup the environment delete the container:

docker rm -f gitlab-test
docker rm -f gitlab-runner-test

Releases

A release is automatically published once a month on the 28th if any commits merged to the main branch contain commit message types that signal a semantic version bump (fix, feat, BREAKING CHANGE:).

Additionally, the release workflow can be run manually by maintainers to publish urgent fixes, either on GitHub or using the gh CLI with gh workflow run release.yml.

Note: As a maintainer, this means you should carefully review commit messages used by contributors in their pull requests. If scopes such as fix and feat are applied to trivial commits not relevant to end users, it’s best to squash their pull requests and summarize the addition in a single conventional commit. This avoids triggering incorrect version bumps and releases without functional changes.

The release workflow uses python-semantic-release and does the following:

• Bumps the version in __version__.py and adds an entry in CHANGELOG.md,

• Commits and tags the changes, then pushes to the main branch as the github-actions user,

• Creates a release from the tag and adds the changelog entry to the release notes,

• Uploads the package as assets to the GitHub release,

• Uploads the package to PyPI using PYPI_TOKEN (configured as a secret).