0158-python-testing-patterns

Structure pytest tests using the Arrange-Act-Assert pattern to keep them readable and focused. This approach separates test setup, execution, and verification into clear sections, ensuring each test checks one behavior and remains isolated from side effects.

Mock external HTTP calls in pytest tests using unittest.mock. By applying Mock, MagicMock, and patch, you can control external dependencies and side effects, ensuring your test suites remain deterministic and fully isolated from network behavior.

Test exceptions in pytest using the pytest.raises context manager alongside match patterns. This failure-path verification technique allows you to assert that specific exceptions are raised and validate their error messages for negative test cases.

Use pytest fixtures to share setup and teardown logic safely across function, module, and session scopes. Fixtures manage test data initialization and cleanup, reducing boilerplate and ensuring isolated, deterministic test behavior.

Cover edge cases in pytest by applying parameterization to your test functions. Parameterization allows you to run the same test logic against multiple input combinations, providing robust scenario coverage without duplicating boilerplate test code.

Yes, this testing strategy targets unit, integration, and functional testing workflows including testing async code. By combining pytest fixtures, marks, and unittest.mock patching, you can build deterministic, isolated test suites for asynchronous Python behavior.