python-tdd

To write behavior-driven Python tests using TDD, follow the Red-Green-Refactor cycle by writing a failing test first, implementing the minimum code to pass, and then refactoring. This Skill guides you through structuring tests and applying pytest conventions for maintainability.

The best way to isolate code and manage setup in pytest is by using mocking strategies, reusable fakes, and fixtures. This Skill demonstrates effective patterns for these techniques to ensure your tests remain focused and independent of external dependencies.

Monkeypatching in Python unit testing works by dynamically replacing attributes or functions during a test run to control behavior and isolate components. This Skill covers monkeypatching alongside other strategies like parametrization and property-based testing for comprehensive test coverage.

Yes, you can test asynchronous Python code and database operations with pytest. This Skill provides specific guidance on async testing and database testing, including managing temporary files during test execution to ensure clean and reliable test environments.

Common anti-patterns to avoid in test-driven development include poorly structured tests, over-reliance on complex mocks, and ignoring the Red-Green-Refactor cycle. This Skill emphasizes specific anti-patterns to avoid, ensuring your tests remain maintainable and behavior-focused.

You need property-based testing in your TDD workflow when you want to automatically generate test cases based on defined properties to uncover edge cases. This Skill integrates property-based testing alongside parametrization to validate behavior across a wide range of inputs.