Does this skill support pytest fixtures?

Yes, it includes detailed patterns for setup and teardown using both function-scoped and session-scoped pytest fixtures for efficient resource management.

How does it handle external API dependencies?

The skill utilizes the unittest.mock library to provide clean patterns for patching requests, mocking response objects, and verifying API call arguments.

Is it compatible with Test-Driven Development (TDD)?

Yes, the skill is specifically designed to support TDD workflows by providing quick-start templates, assertion patterns, and red-green-refactor guidance.

Does it include coverage for exception handling?

Yes, it provides patterns for using pytest.raises to verify that your code correctly handles errors and raises exceptions with the expected messages.

Can I use this for testing asynchronous code?

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

Python Testing Patterns

Name: Python Testing Patterns
Author: Krosebrook

byKrosebrook

•

Security & Testing

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

This skill provides a standardized framework for building robust Python test suites, covering unit, integration, and functional testing. It streamlines the implementation of complex testing patterns such as dependency mocking with unittest.mock, sophisticated fixture management for setup/teardown, and asynchronous test execution. Whether you are debugging failing tests, improving code coverage, or setting up CI/CD test infrastructure, this skill ensures your Python projects maintain high reliability through the Arrange-Act-Assert (AAA) pattern and industry-standard validation techniques.

Key Features

01Dedicated support for testing asynchronous code and concurrent operations

02Comprehensive mocking patterns for isolating external APIs and services

03Parameterized testing templates for broad input validation and edge cases

041 GitHub stars

05Advanced pytest fixture configurations for efficient resource management

06Standardized patterns for environment variable manipulation and exception testing

Use Cases

01Building a unit test suite for a new Python backend service

02Setting up automated integration tests within a CI/CD pipeline

03Mocking external REST API dependencies to isolate internal business logic

What are Skills?·How to Install

Install with 🐟 Skill.Fish

npx skillfish add krosebrook/source-of-truth-monorepo python-testing-patterns

For use in Claude.ai and ChatGPT

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