python-testing-patterns

Write test functions prefixed with test_ and use plain assert statements to verify behavior. Follow the Arrange-Act-Assert pattern: set up data, execute the code under test, then verify results. Run tests with the pytest command.

Use unittest.mock's patch to replace requests.get or requests.post with a Mock object whose return_value simulates the HTTP response. Configure json.return_value for the payload and verify calls with assert_called_once_with.

Pytest fixtures are functions decorated with @pytest.fixture that provide setup and teardown for tests, such as database connections. Use scope parameters like session or module to control how often expensive resources are created.

Yes, pytest supports parameterized tests via @pytest.mark.parametrize, which runs one test function against many input and expected-output pairs. Use pytest.param with id to label individual cases clearly.

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 in CI.

This indicates shared state between tests, violating test isolation. Use fixtures with proper teardown, avoid module-level mutable state, and ensure each test cleans up resources it creates.