Test Guide

Test Guide

Write tests by agreeing on scenarios first, then verifying each one as you implement. The center of gravity is the scenario list and its verification status — not a fixed Red-Green-Refactor cadence (that is one valid way to write the tests; see §3).

1. Propose scenarios first

Before writing code or tests, draft the scenarios and get the user's input:

1. Draft success / exception / edge scenarios from the requirement.
2. Present them to the user for review — they add missing cases and correct expectations.
3. Confirm the merged list. It is the contract for what "done" means.

## Test Target: {Feature}

### Success
1. {primary case} -> {expected}
2. {edge case that should succeed} -> {expected}

### Exception
1. {invalid input} -> raises {ErrorType}
2. {not found} -> raises {ErrorType}
3. {boundary} -> {empty/default behavior}

How to derive scenarios

Walk these axes — every one that applies to the feature becomes one or more scenarios:

Pull exception scenarios straight from the domain rules and the BackendAIError subclasses the code can raise (see manager/errors/AGENTS.md). Every scenario must name a concrete expected outcome or error type — "should fail" is not specific enough to test.

Propose first because the user catches missing cases far faster than reverse-engineering them from code, and the agreed list prevents scope drift.

2. Verify scenarios collaboratively

As you implement, report each scenario's status back to the user and keep it visible:

• Surface gaps (not covered) explicitly — never silently skip a scenario.
• When the user adds a scenario mid-work, append it to the list and the table.
• A scenario is done only when its test exists and passes.

3. Writing tests

One scenario = one test. Arrange (fixtures) → Act (call) → Assert.

class TestFeature:
    @pytest.fixture
    async def scenario_data(
        self, database_engine: ExtendedAsyncSAEngine
    ) -> AsyncGenerator[DataRow, None]:
        # setup with with_tables — see tests/AGENTS.md
        yield data

    async def test_returns_record_when_present(
        self, repository: FeatureRepository, scenario_data: DataRow
    ) -> None:
        result = await repository.method(scenario_data.id)
        assert result.field == expected

• Fixtures: name by scenario (domain_with_record), return complete data, type as AsyncGenerator[T, None].
• Repositories / models: real DB via with_tables; include FK deps, clean up child → parent. See tests/AGENTS.md.
• Services / handlers: unit tests with mocked repositories — isolate business logic.
• Types: annotate everything; test functions return -> None.
• TDD (optional cadence): write the failing test first (confirm it fails for the right reason — ImportError/AttributeError), implement the minimum, then refactor while green.

4. Run and verify

Verify against the tests you added or changed — not a transitive sweep.

# the specific test(s) for the scenarios you implemented
pants test tests/manager/repositories/test_feature.py
pants test tests/.../test_feature.py::TestFeature::test_case

# quality, scoped to your change
pants fmt --changed-since=HEAD~1
pants fix --changed-since=HEAD~1
pants lint --changed-since=HEAD~1
pants check --changed-since=HEAD~1
pants test --changed-since=HEAD~1

• Add a BUILD file with python_tests() to new test directories.
• Fix all lint/type/test errors — never # noqa / # type: ignore / skip. See BUILDING.md.

Cross-References

• tests/AGENTS.md — testing guidelines, with_tables, strategies
• /repository-guide, /service-guide, /api-guide — layer patterns under test
• BUILDING.md — quality enforcement