How does it handle complex test setups?

The skill utilizes pytest fixtures with various scopes (function, module, session) to manage complex setup and teardown logic efficiently, ensuring test isolation.

What testing framework does this skill focus on?

This skill primarily focuses on pytest, the industry-standard testing framework for Python, utilizing its advanced features like fixtures, marks, and parameterization.

Does it support testing for modern async Python code?

Yes, it includes specialized patterns for testing asynchronous functions and concurrent operations using the pytest-asyncio plugin and async fixtures.

Can I use this skill to mock external API dependencies?

Absolutely. It provides detailed implementation patterns for using unittest.mock to patch requests, database connections, and other external services.

Python Testing Patterns

Name: Python Testing Patterns
Author: kivilaid

bykivilaid

•

보안 및 테스팅

Implements comprehensive Python testing strategies using pytest, fixtures, mocking, and test-driven development best practices.

소개

Python Testing Patterns provides Claude with specialized guidance for creating robust, maintainable, and high-coverage test suites for Python applications. It focuses on the modern pytest ecosystem, covering everything from the Arrange-Act-Assert (AAA) pattern and complex fixtures to advanced mocking of external dependencies and testing asynchronous code. This skill is essential for developers looking to implement professional-grade testing workflows, ensure API reliability, and maintain code quality through automated test-driven development.

주요 기능

Robust exception testing and environment variable manipulation with monkeypatch
Parameterized testing for efficient data-driven test cases
Specialized patterns for testing asynchronous functions and concurrent operations
Advanced pytest implementation including session and module scoped fixtures
Comprehensive mocking and patching strategies using unittest.mock
6 GitHub stars

사용 사례

Implementing Test-Driven Development (TDD) to ensure feature correctness and reliability
Refactoring legacy Python code by establishing a baseline of automated tests
Building a comprehensive unit and integration test suite for a new Python service

소개

주요 기능

Robust exception testing and environment variable manipulation with monkeypatch
Parameterized testing for efficient data-driven test cases
Specialized patterns for testing asynchronous functions and concurrent operations
Advanced pytest implementation including session and module scoped fixtures
Comprehensive mocking and patching strategies using unittest.mock
6 GitHub stars

사용 사례

Implementing Test-Driven Development (TDD) to ensure feature correctness and reliability
Refactoring legacy Python code by establishing a baseline of automated tests
Building a comprehensive unit and integration test suite for a new Python service