Testing

We use pytest for testing. Please try to ensure that all functions are tested, including both unit and integration tests.

Long running tests

Some tests may take a long time, e.g. those requiring TensorFlow if you don’t have a GPU. These tests should be marked with @pytest.mark.slow, e.g.:

import pytest
@pytest.mark.slow
def test_something_slow() -> None:
    slow_result = run_slow_processes()
    assert slow_result == expected_slow_thing, "some useful error message"

During development, these “slow” tests can be skipped by running pytest -m "not slow".

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.

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.