Does this skill support testing for async Python code?

Yes, it includes specialized patterns and markers for testing asynchronous functions using the pytest-asyncio framework.

How does this help with the AAA testing pattern?

It provides structural templates for the Arrange-Act-Assert pattern, ensuring your tests are readable, organized, and follow industry best practices.

Which Python testing framework is the primary focus?

The skill is centered around pytest, the most widely used testing framework in the Python ecosystem, including its fixtures and plugin system.

Can I use this skill to mock external API dependencies?

Absolutely. The skill provides detailed implementation patterns for using unittest.mock to simulate external services and HTTP responses.

Python Testing Patterns

Name: Python Testing Patterns
Author: carloscroc

bycarloscroc

安全与测试

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

关于

Python Testing Patterns is a specialized Claude Code skill designed to streamline the creation of robust, maintainable test suites. It provides domain-specific guidance on implementing the AAA (Arrange, Act, Assert) pattern, managing complex fixtures, and mocking external dependencies. Whether you are building unit tests for local functions, integration tests for REST APIs, or handling asynchronous operations, this skill ensures your Python code meets high quality and reliability standards through industry-standard practices and efficient test infrastructure setup.

主要功能

Comprehensive mocking techniques using unittest.mock and patch
Asynchronous code testing patterns using pytest-asyncio
0 GitHub stars
Parameterized testing for data-driven validation across multiple scenarios
Environment isolation and attribute manipulation with monkeypatch
Advanced pytest fixture management for setup and teardown

使用场景

Refactoring legacy codebases with a focus on Test-Driven Development (TDD)
Setting up professional test infrastructure and coverage reporting for CI/CD pipelines
Automating unit and integration test generation for complex Python projects

关于

主要功能

Comprehensive mocking techniques using unittest.mock and patch
Asynchronous code testing patterns using pytest-asyncio
0 GitHub stars
Parameterized testing for data-driven validation across multiple scenarios
Environment isolation and attribute manipulation with monkeypatch
Advanced pytest fixture management for setup and teardown

使用场景

Refactoring legacy codebases with a focus on Test-Driven Development (TDD)
Setting up professional test infrastructure and coverage reporting for CI/CD pipelines
Automating unit and integration test generation for complex Python projects