Week 19 - Testing, Property-Based Testing, Mutation Testing, Fakes vs. Mocks¶

19.1 Conceptual Core¶

The test pyramid still applies: many fast unit tests, some integration, few end-to-end. In Python, the unit tier is so cheap there's almost never an excuse for skipping it.
Prefer fakes to mocks. A fake is a working implementation with simpler internals (in-memory repo, fake clock). A mock is a script of expected calls. Mocks couple tests to implementation; fakes don't.

pytest: fixtures, conftest.py, parametrize, marks, pytest.raises, pytest.warns, tmp_path, caplog, capsys. Plugin ecosystem: pytest-asyncio, pytest-cov, pytest-xdist (parallel), pytest-benchmark, pytest-mock, pytest-randomly.
hypothesis: property-based testing. Strategies, @given, @settings, assume, stateful tests with RuleBasedStateMachine. The single biggest force-multiplier in this curriculum.
mutmut / cosmic-ray: mutation testing. Verifies that your tests fail when production code is broken - surfaces vacuous tests.
unittest.mock: when you must. Prefer monkeypatch fixture and respx/vcr.py for HTTP.
Test doubles taxonomy: dummy, stub, spy, mock, fake. Know the difference.

Add hypothesis property tests to your week-3 word counter. Watch them find a UTF-8 boundary bug or an empty-input issue.
Add a stateful hypothesis test against your tiny ORM from week 5.
Run mutmut. Identify untested branches.
Replace any Mock you used with a fake implementing a Protocol.

Enable ruff PT (pytest style). Refactor assert x == 1; assert y == 2 patterns; prefer one assertion per test.

CI gate: coverage ≥ 90%, mutmut killed-mutant ratio ≥ 80%, hypothesis profile --ci.