write-tests

To write Python unit tests using pytest, you define test functions in files following pytest naming conventions, using assertions to verify functional correctness. Test structure should cover functions, edge cases, and potential errors.

To mock external dependencies in pytest, you replace real dependencies with mock objects during test execution. This isolates the code being tested, ensuring functional correctness without relying on external services or state.

Using fixtures and parameterization in Python testing allows you to reuse setup code and run the same test across multiple inputs. Fixtures provide a baseline for tests, while parameterization maps inputs to expected outcomes.

Yes, pytest works well for testing new Python library features. It provides the necessary structure to write tests covering functionality, edge cases, and error handling, ensuring robust code quality during development.

The best way to handle errors in pytest test cases is to use assertions to explicitly verify expected exceptions. Structuring tests to catch and assert specific errors ensures your code maintains functional correctness under adverse conditions.