Is it compatible with standard pytest plugins?

Yes, the patterns are designed to work seamlessly with the standard pytest ecosystem and common extensions like pytest-cov and pytest-mock.

Does this skill support both unit and integration tests?

Yes, it provides standardized patterns for unit tests (isolated logic), integration tests (component interaction), and functional end-to-end tests.

Can I use this for testing asynchronous Python code?

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

How does it handle external API dependencies?

It utilizes unittest.mock and monkeypatch patterns to isolate your code from external services, allowing you to simulate various API responses and error states.

Does it help with code coverage?

While it doesn't generate the coverage reports itself, it provides the structural best practices needed to write tests that exercise more code paths and improve overall coverage.

Python Testing Patterns

Name: Python Testing Patterns
Author: agi-house-india

byagi-house-india

보안 및 테스팅

Implements comprehensive Python testing strategies using pytest, fixtures, and advanced mocking patterns to ensure code reliability.

소개

Python Testing Patterns equips Claude with specialized knowledge to build robust, maintainable test suites for any Python project. It covers a full spectrum of testing methodologies, from the fundamental AAA (Arrange, Act, Assert) pattern and unit testing to advanced concepts like asynchronous test execution, database isolation, and complex dependency mocking. By following these established patterns, developers can implement Test-Driven Development (TDD) more effectively and ensure their applications remain stable through high-quality integration and functional testing.

주요 기능

AAA (Arrange-Act-Assert) pattern enforcement for clean test structure
Asynchronous testing patterns for concurrent operations
Robust exception handling and boundary case validation
0 GitHub stars
Advanced mocking and monkeypatching for external dependencies
Comprehensive pytest optimization with fixtures and parameterization

사용 사례

Generating unit tests for complex business logic and edge cases
Implementing Test-Driven Development (TDD) workflows in Python projects
Setting up scalable test infrastructure for REST APIs and microservices

소개

주요 기능

AAA (Arrange-Act-Assert) pattern enforcement for clean test structure
Asynchronous testing patterns for concurrent operations
Robust exception handling and boundary case validation
0 GitHub stars
Advanced mocking and monkeypatching for external dependencies
Comprehensive pytest optimization with fixtures and parameterization

사용 사례

Generating unit tests for complex business logic and edge cases
Implementing Test-Driven Development (TDD) workflows in Python projects
Setting up scalable test infrastructure for REST APIs and microservices