0158-python-testing-patterns

What problem does it solve?

This Skill solves the challenge of building trustworthy automated tests by showing practical pytest patterns for isolating behavior, managing test data, and validating both success and failure cases.

Core Features & Use Cases

• Comprehensive pytest test structure: Use the Arrange-Act-Assert (AAA) pattern to keep tests readable and focused.
• Reliable test setup with fixtures: Share setup/teardown logic safely via function, module, and session-scoped fixtures.
• Robust scenario coverage: Apply parameterization to cover edge cases without duplicating boilerplate tests.
• External dependency control: Mock HTTP calls and other side effects using unittest.mock (Mock, patch, MagicMock).
• Failure-path verification: Test exceptions, error messages, and negative cases using pytest.raises and match patterns.
• Test design best practices: Ensure each test checks one behavior, remains isolated, and follows clear naming conventions.

Quick Start

Use the skill to design pytest tests for a Python module by mocking network calls and writing focused AAA-style unit tests that verify both expected outputs and raised exceptions.