python-testing

To write a pytest test, define a function prefixed with `test_` and use standard Python `assert` statements to validate outputs against expected results. Pytest automatically discovers and runs these functions across your test suite.

Pytest fixtures manage test setup and teardown by providing reusable context, objects, or data. You inject fixtures into test functions via arguments, ensuring maintainable and isolated test environments.

Pytest tests asynchronous Python code using specialized plugins and async fixtures. This approach awaits coroutines within test functions to validate non-blocking application logic reliably.

Pytest parametrization allows running the same test logic across multiple datasets. By applying the `@pytest.mark.parametrize` decorator, you generate distinct test cases for varied inputs and expected outputs.

Applying TDD with pytest involves writing failing tests first, implementing minimal code to pass them, and then refactoring. This red-green-refactor cycle ensures high-quality, well-tested Python applications.