Can I use this for testing asynchronous Python code?

Absolutely. The skill includes specific patterns for testing async functions and concurrent operations using pytest-asyncio.

Does this skill support pytest-specific features?

Yes, it covers core pytest features including fixtures, parameterization, and markers for specialized testing needs.

Can it help me handle environment variables during tests?

Yes, it includes patterns for using monkeypatch to safely set, delete, or modify environment variables and object attributes during test execution.

How does it help with mocking external services?

It provides detailed patterns for using unittest.mock to simulate API responses and database interactions, ensuring tests remain isolated from external dependencies.

Is this skill compatible with Test-Driven Development (TDD)?

Yes, it promotes the AAA (Arrange, Act, Assert) pattern and isolation practices which are fundamental to a successful TDD workflow.

Python Testing Patterns

Name: Python Testing Patterns
Author: HermeticOrmus

byHermeticOrmus

Security & Testing

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

About

Python Testing Patterns provides a structured framework for building high-quality, reliable Python applications through rigorous testing methodologies. It equips Claude with the expertise to implement the AAA (Arrange, Act, Assert) pattern, design reusable fixtures, and mock complex dependencies, ensuring codebases remain maintainable and bug-free. Whether you are setting up a new test suite, migrating to pytest, or implementing specialized asynchronous testing, this skill streamlines the process of achieving high-quality code coverage and stability.

Key Features

Asynchronous testing patterns for concurrent operations and modern APIs
Comprehensive pytest implementation including fixtures and parameterization
Environment and attribute manipulation using monkeypatch
Standardized test structure following the Arrange, Act, Assert pattern
0 GitHub stars
Advanced mocking techniques using unittest.mock and patch decorators

Use Cases

Building a complete, automated test suite for a new Python backend service
Refactoring legacy codebases by implementing unit and integration tests
Mocking external API dependencies to ensure stable and isolated CI/CD pipelines

About

Key Features

Asynchronous testing patterns for concurrent operations and modern APIs
Comprehensive pytest implementation including fixtures and parameterization
Environment and attribute manipulation using monkeypatch
Standardized test structure following the Arrange, Act, Assert pattern
0 GitHub stars
Advanced mocking techniques using unittest.mock and patch decorators

Use Cases

Building a complete, automated test suite for a new Python backend service
Refactoring legacy codebases by implementing unit and integration tests
Mocking external API dependencies to ensure stable and isolated CI/CD pipelines