How does this skill handle external dependencies like databases?

It provides strategies for both mocking database responses for unit tests and using fixtures to manage temporary database states for integration testing.

Does it provide guidance on code coverage?

Yes, the skill emphasizes meaningful coverage by identifying untested code paths and providing patterns for testing edge cases and exception handling.

Which Python testing frameworks are supported?

While the skill is optimized for pytest, it also incorporates standard library features like unittest.mock and provides patterns applicable to most modern Python testing environments.

Can this skill help with testing asynchronous functions?

Yes, it includes specific patterns for testing async/await code using pytest-asyncio, including async fixtures and concurrent operation testing.

Python Testing Patterns

Name: Python Testing Patterns
Author: amurata

byamurata

•

Security & Testing

Implements comprehensive Python testing strategies using pytest, mocking, and fixtures to ensure robust and maintainable codebases.

About

The Python Testing Patterns skill equips Claude with the expertise to design and implement high-quality test suites for any Python project. It provides structured guidance on the Arrange-Act-Assert (AAA) pattern, efficient fixture management, and advanced mocking of external dependencies. By leveraging this skill, developers can automate complex testing scenarios, including asynchronous operations, database interactions, and exception handling, ensuring that Python applications are resilient and adhere to Test-Driven Development (TDD) best practices.

Key Features

Specialized support for testing asynchronous code, concurrent operations, and error states
Standardized pytest implementation using the Arrange-Act-Assert (AAA) pattern
Parameterized testing patterns to validate multiple input scenarios with minimal code
Advanced fixture management for reusable setup and teardown logic across test suites
Sophisticated mocking techniques for isolating external APIs and services using unittest.mock
3 GitHub stars

Use Cases

Establishing a Test-Driven Development (TDD) workflow for new Python service modules
Refactoring legacy codebases by implementing missing unit and integration test coverage
Simulating complex third-party API responses and database failures to test application resilience

About

Key Features

Specialized support for testing asynchronous code, concurrent operations, and error states
Standardized pytest implementation using the Arrange-Act-Assert (AAA) pattern
Parameterized testing patterns to validate multiple input scenarios with minimal code
Advanced fixture management for reusable setup and teardown logic across test suites
Sophisticated mocking techniques for isolating external APIs and services using unittest.mock
3 GitHub stars

Use Cases

Establishing a Test-Driven Development (TDD) workflow for new Python service modules
Refactoring legacy codebases by implementing missing unit and integration test coverage
Simulating complex third-party API responses and database failures to test application resilience