Can I use this skill for mocking external dependencies?

Yes, it includes comprehensive instructions for using the monkeypatch fixture to mock functions, environment variables, and dictionary values.

Does it support testing for multiple input scenarios?

Absolutely. The skill covers basic and advanced parametrization, allowing you to run the same test logic against multiple data sets and expected results.

Can I configure pytest settings through this skill?

Yes, it provides configuration templates for pyproject.toml and pytest.ini to manage test paths, markers, and filter warnings.

What kind of assertions are covered?

The skill covers basic equality, floating-point approximations, exception matching, and capturing stdout/stderr output for verification.

How does this skill help with test organization?

It provides standardized patterns for test discovery, custom markers, and a recommended directory layout including the use of conftest.py for shared fixtures.

Pytest Python Testing

Name: Pytest Python Testing
Author: alijilani-dev

byalijilani-dev

安全与测试

Facilitates the creation, organization, and execution of comprehensive Python test suites using the pytest framework.

关于

This skill empowers developers to implement robust Python testing strategies within Claude Code by providing expert guidance on the pytest ecosystem. It covers everything from basic test discovery and assertions to advanced concepts like fixture lifecycle management, complex parametrization, and sophisticated mocking with monkeypatch. Whether you are architecting a new test suite, debugging intermittent failures, or optimizing performance with markers, this skill ensures your Python projects maintain high code quality through maintainable and efficient testing patterns.

主要功能

0 GitHub stars
Advanced fixture management with custom scopes and teardowns
Standardized project structure and configuration templates
Automated test discovery and execution command patterns
Data-driven testing through parametrization and combinations
Dependency and environment mocking using monkeypatch

使用场景

Setting up a new Python project with optimized pytest configuration and folder structure
Refactoring redundant test code into reusable factory fixtures and shared conftest.py files
Implementing comprehensive error handling and boundary testing using exception assertions

关于

主要功能

0 GitHub stars
Advanced fixture management with custom scopes and teardowns
Standardized project structure and configuration templates
Automated test discovery and execution command patterns
Data-driven testing through parametrization and combinations
Dependency and environment mocking using monkeypatch

使用场景

Setting up a new Python project with optimized pytest configuration and folder structure
Refactoring redundant test code into reusable factory fixtures and shared conftest.py files
Implementing comprehensive error handling and boundary testing using exception assertions