Can it help improve my code coverage?

Yes, by providing patterns for edge cases, exception handling, and parameterization, it helps you identify and exercise code paths that are often missed by basic tests.

What testing framework does this skill focus on?

This skill primarily focuses on pytest, the industry standard for Python testing, but also covers standard library tools like unittest.mock for isolation.

Does it support Test-Driven Development (TDD)?

Absolutely. It provides the necessary structure and implementation patterns to write tests before feature code, following strict TDD best practices.

Can this skill help with testing asynchronous code?

Yes, it includes specific patterns for testing async/await functions using pytest-asyncio and handling concurrent operations.

How does it handle external dependencies like databases?

It utilizes sophisticated mocking, patching, and the 'monkeypatch' utility to isolate code, alongside fixture patterns for setting up and tearing down temporary test databases.

Python Testing Patterns

Name: Python Testing Patterns
Author: drgaciw

bydrgaciw

Security & Testing

Implements robust Python testing suites using pytest, advanced mocking, and test-driven development best practices.

About

This skill empowers Claude to architect and implement comprehensive testing strategies for Python applications using industry-standard tools and methodologies. It provides expert guidance on leveraging the pytest framework, from structuring unit tests with the Arrange-Act-Assert (AAA) pattern to mastering advanced techniques like fixture scopes, parameterization, and mocking complex external dependencies. Whether you are building an initial test suite, testing asynchronous operations, or implementing Test-Driven Development (TDD), this skill ensures your codebase remains reliable, maintainable, and highly resilient through rigorous automated verification.

Key Features

Comprehensive exception and edge-case handling verification
Sophisticated mocking and patching of external dependencies and APIs
0 GitHub stars
Advanced pytest configuration and fixture lifecycle management
Parameterized testing for efficient multi-scenario verification
Asynchronous testing patterns for concurrent operations

Use Cases

Mocking third-party service responses to ensure stable and isolated CI/CD pipelines
Building a full-stack unit and integration test suite for Python web frameworks
Implementing Test-Driven Development (TDD) for complex business logic layers

About

Key Features

Comprehensive exception and edge-case handling verification
Sophisticated mocking and patching of external dependencies and APIs
0 GitHub stars
Advanced pytest configuration and fixture lifecycle management
Parameterized testing for efficient multi-scenario verification
Asynchronous testing patterns for concurrent operations

Use Cases

Mocking third-party service responses to ensure stable and isolated CI/CD pipelines
Building a full-stack unit and integration test suite for Python web frameworks
Implementing Test-Driven Development (TDD) for complex business logic layers