Testing

• We use pytest for testing. Please try to ensure that all functions are tested, including both unit and integration tests. We aim for 100% coverage where possible.

• We use codecov as the coverage reporting tool. This is free for open-source projects and integrates with GitHub actions.

Local testing with pytest and coverage

pytest

We recommend to start unit testing locally through your project’s terminal with the activated environment. You can also use VS Code or PyCharm for unit testing. To run pytest from the repository directory

pytest

Sometimes, you may need to run a single test or specific modules. You can do so using the following examples. Make sure to check the paths, filenames, and test names.

pytest tests/atlasapi/test_cli.py
pytest tests/atlasapi/test_cli.py::test_config_cli

Continuous integration

A GitHub actions workflow (.github/workflows/test_and_deploy.yml) has been set up to run (on each commit/PR):

• Linting checks (pre-commit).

• Testing (only if linting checks pass)

• Release to PyPI (only if a git tag is present and if tests pass). Requires TWINE_API_KEY from PyPI to be set in repository secrets.

• Sometimes additional, cross-repository, tests are run such as testing brainmapper with a development version of cellfinder

Many of these workflows use actions from neuroinformatics-unit/actions. Feel free to raise a PR to that repository!

Test data

Data used by the tests should be kept on GIN and fetched using pooch. Test data should not live on GitHub. To avoid local tests running checks on user data interfering with separate user data on the same machine, tests should mock test-user data by mocking Path.home() - an example of how to achieve this can be viewed in brainrender-napari.