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 test data, execute the code under test, then verify the results. Run tests with the pytest command.

Use unittest.mock's patch function to replace requests.get or requests.post with a Mock object whose return_value simulates the HTTP response. Configure mock_response.json.return_value with your expected data and assert the mock was called with the correct URL.

Pytest fixtures are declared with the @pytest.fixture decorator and injected into tests as parameters, supporting scopes like function, module, and session. They use yield to separate setup from teardown, offering more flexibility than xUnit-style setUp/tearDown methods.

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

Install pytest-cov and run pytest with the --cov flag targeting your package, such as pytest --cov=myapp tests/. Add --cov-report=term-missing to see uncovered lines and --cov-fail-under=80 to enforce a minimum coverage threshold.

This indicates shared state between tests, violating test isolation. Use fixtures with function scope to reset state, monkeypatch to safely modify environment variables, and tmp_path for file operations so each test cleans up after itself.