python-testing-patterns

Write test functions prefixed with test_ and use plain assert statements to verify behavior, following the Arrange-Act-Assert pattern. Run tests with the pytest command, which auto-discovers files matching test_*.py.

Use unittest.mock's patch to replace requests.get or requests.post with a Mock object whose return_value simulates the HTTP response. Then assert the mock was called with expected arguments using assert_called_once_with.

Fixture scopes control how often setup runs: function scope creates a fresh instance per test, module scope once per file, and session scope once per test run. Use broader scopes for expensive resources like database connections.

Yes, pytest supports async tests through the pytest-asyncio plugin using the @pytest.mark.asyncio decorator on async test functions. Async fixtures can also be defined with yield for setup and teardown of async resources.

Install pytest-cov and run pytest with --cov=yourpackage to measure coverage. Add --cov-report=term-missing to see uncovered lines and --cov-fail-under=80 to enforce a minimum coverage threshold.

Use property-based testing with hypothesis when you want to verify invariants across many generated inputs, such as reversing a string twice returning the original. It complements example-based tests by exploring edge cases you did not anticipate.