Enforce pytest best practices for Django tests with fixtures and mocking.
npx skills add https://github.com/felipe3dfx/dotfiles --skill pytest-felipe3dfx
Please help me install this Agent Skill. Skill: pytest Source: https://github.com/felipe3dfx/dotfiles/tree/main/skills/pytest Command: npx skills add https://github.com/felipe3dfx/dotfiles --skill pytest-felipe3dfx
This Skill provides best practices and patterns for writing robust, maintainable, and efficient Python tests using pytest, reducing common pitfalls and improving code quality.
pytest-mock's mocker fixture over unittest.mock and prioritize HTTP-layer mocking.Use the pytest skill to write a new test for a Django view that requires authentication.
High-intent search queries and answers about installing and using this skill.
Writing pytest tests for Django views relies on standalone functions, Factory Boy for data generation, and fixture composition to handle authentication reliably while avoiding class-based test structures.
Mocking external services in Python tests is best handled at the HTTP layer using the `pytest-mock` mocker fixture, which ensures test reliability and maintainability over direct `unittest.mock` usage.
pytest works seamlessly with Factory Boy for test data generation by enforcing specific factory patterns and fixture composition, ensuring complex data setups remain maintainable and standardized across your test suite.
Standalone functions in pytest are enforced because they avoid common testing anti-patterns found in class-based tests, reducing module-level docstrings and ensuring a standardized, maintainable test structure across your project.
Using `pytest-mock`'s `mocker` fixture is prioritized over `unittest.mock` for Django testing because it enforces correct mocking strategies and HTTP-layer mocking, preventing external service anti-patterns and improving test reliability.
Fixture composition is needed for Python testing when handling complex setups in Django projects, allowing you to combine factories and mocking patterns effectively to ensure test data generation remains robust and maintainable.
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