Can I use this for mocking external API calls?

Absolutely; the skill provides detailed patterns for using unittest.mock and patching the requests library to simulate external service responses safely.

What is the AAA pattern mentioned in the skill?

The AAA (Arrange-Act-Assert) pattern is a standard for organizing tests: Arrange sets up the data, Act executes the code, and Assert verifies the results.

Which testing framework does this skill focus on?

This skill focuses primarily on pytest, the industry-standard testing framework for Python, due to its powerful fixture system and scalability.

Does it support testing asynchronous code?

Yes, it includes specific patterns and decorators like @pytest.mark.asyncio for testing async functions and concurrent operations.

Does this skill help with database testing?

Yes, it includes patterns for setting up database fixtures with proper setup and teardown (cleanup) logic to ensure test isolation.

Python Testing Patterns

Name: Python Testing Patterns
Author: pur3v4d3r

bypur3v4d3r

•

Security & Testing

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

About

The Python Testing Patterns skill provides Claude with expert-level guidance for creating robust, maintainable test suites within Python environments. It covers essential and advanced patterns including complex fixture management, sophisticated mocking with unittest.mock, and parameterized testing for edge-case validation. By utilizing standardized architectures like the Arrange-Act-Assert (AAA) pattern and providing specialized support for asynchronous code and environment monkeypatching, this skill ensures high code quality and reliable CI/CD outcomes for any Python project.

Key Features

Parameterized testing configurations for efficient multi-input validation
Automated pytest structure implementation using the AAA pattern
Advanced fixture management for complex setup and teardown logic
Comprehensive mocking and patching of external APIs and dependencies
Specialized patterns for testing async/await code and environment variables
1 GitHub stars

Use Cases

Debugging and fixing complex integration test failures within CI/CD pipelines
Implementing Test-Driven Development (TDD) workflows for new feature development
Migrating legacy Python codebases to standardized pytest-based suites

About

Key Features

Parameterized testing configurations for efficient multi-input validation
Automated pytest structure implementation using the AAA pattern
Advanced fixture management for complex setup and teardown logic
Comprehensive mocking and patching of external APIs and dependencies
Specialized patterns for testing async/await code and environment variables
1 GitHub stars

Use Cases

Debugging and fixing complex integration test failures within CI/CD pipelines
Implementing Test-Driven Development (TDD) workflows for new feature development
Migrating legacy Python codebases to standardized pytest-based suites