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python-tests

Skill73 starsChanged 56 days agoApache-2.0View on GitHub

Python tests for NeMo Fabric; use this when writing tests

3 other projects use a version of this.

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The file

We split this skill into the rules it gives an agent

11 rules. 0 are common, 4 are distinctive, and 7 are very specific to this project.

  • 0

    Common

    Most of the 3 edited versions we read keep these.

  • 4

    Distinctive

    This author's own choices. Worth a look.

  • 7

    Very specific

    Tied to their project's names, files or tools. Probably skip.

  • Common
  • Distinctive
  • Very specific
  1. Very specific:

    Do not add @pytest.mark.asyncio to any test.

    line 12
  2. Very specific:

    Do not add a -> None return type annotation to test functions.

    line 13
  3. Very specific:

    When mocking a class, do not define a new class.

    line 14
  4. Distinctive:

    Prefer pytest fixtures over helper methods.

    line 16
  5. Very specific:

    Do not repeat fixtures, if a fixture is needed in multiple test files, place it in a conftest.py file.

    line 17
  6. Distinctive:

    When creating a fixture follow this pattern:

    line 18
  7. Distinctive:

    Only specify the scope argument when the value is something other than "function".

    line 24
  8. Very specific:

    Prefer pytest.mark.parametrize over creating individual tests for different input types.

    line 25
  9. Very specific:

    If a fixture is needed for a test, but either does not return a value or the value is not used in the test, use the …

    line 27
  10. Distinctive:

    Avoid defensive programming in tests.

    line 29
  11. Very specific:

    Test helper code under tests/_utils/.

    line 52

“Common” is measured: kept by at least 6 in 10 of the 3 edited versions of this file we could read. “Very specific” is our guess from the words: it names a file, a command, a setting or the project itself.

Keep what fits and drop the rest. Your version, ready for your agents.
Files
SKILL.md

Python Test Style

  • Pytest is used to run tests.
  • Do not add @pytest.mark.asyncio to any test. Async tests are automatically detected and run by the async runner; the decorator is unnecessary clutter.
  • Do not add a -> None return type annotation to test functions. This is not a common convention in pytest and adds unnecessary verbosity.
  • When mocking a class, do not define a new class. Use unittest.mock.MagicMock or unittest.mock.AsyncMock, with the spec constructor argument when necessary.
  • The name of the mocked class should be prefixed with mock, not fake.
  • Prefer pytest fixtures over helper methods.
  • Do not repeat fixtures, if a fixture is needed in multiple test files, place it in a conftest.py file.
  • When creating a fixture follow this pattern:
    @pytest.fixture(name="<fixture_name>"[, scope="<scope>"])
    def <fixture_name>_fixture() -> <return_type>:
        ...
    Only specify the scope argument when the value is something other than "function".
  • Prefer pytest.mark.parametrize over creating individual tests for different input types.
  • If a fixture is needed for a test, but either does not return a value or the value is not used in the test, use the @pytest.mark.usefixtures decorator.
  • tests/conftest.py contains a restore_environ_fixture fixture that restores the environment variables to their original state after each test, it is defined with autouse=True so it is automatically applied to all tests. If you need to modify the environment variables in a test, do so using os.environ and the fixture will restore them after the test completes. There is no need to use monkeypatch.setenv to modify environment variables in tests.
  • Avoid defensive programming in tests. If a test fails, it should fail loudly and clearly, rather than silently passing due to defensive checks. For example
    data = results["data"]
    is preferred over
    data = results.get("data")
    Simply allow the resulting KeyError to be raised if the "data" key is not present in the results dictionary, as this will provide a clear indication of what went wrong in the test.

Common Commands

# Focused test loop
uv run pytest -k "<pattern>"

# Run all tests
uv run pytest

Do Not Write Tests For

  • Documentation.
  • Test helper code under tests/_utils/.
  • Package metadata or wheel installation behavior.

References

  • pyproject.toml
  • tests/conftest.py

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