python-testing

Fakes are in-memory simulators that validate business behavior without coupling to implementation, while mocks verify interaction at external boundaries. This skill guides you to prefer fakes for stable unit tests and use mocks only for integration points.

To write unit tests with fakes, replace real I/O dependencies with in-memory simulators that replicate behavior. This skill applies fixture patterns and test-doubles guidance to build maintainable fake-driven tests that survive refactoring.

Yes, pytest fixtures support unit, integration, and end-to-end tests. This skill applies a five-layer testing strategy with fixture patterns to ensure business logic is validated via in-memory simulators across all test layers.

Use mocks only for integration points or external boundaries where interaction verification is required. Fakes should be preferred for business logic validation to ensure test stability and maintainable behavior verification across refactors.

Following a structured five-layer testing strategy with proper fixture patterns and test-doubles guidance helps avoid anti-patterns. This skill ensures maintainable, observable behavior by preferring fakes over mocks for business logic validation.

Fake-driven testing applies to unit, integration, and end-to-end tests where business logic should be validated via in-memory simulators rather than real I/O. This satisfies the five-layer testing strategy for maintainable behavior verification.