Does it support testing for asynchronous Python code?

Yes, it includes specialized patterns for using pytest-asyncio to handle concurrent operations and verify async function behavior.

Can I use this for mocking external database connections?

Absolutely. The skill features patterns for using unittest.mock and monkeypatch to isolate your code from databases, file systems, and third-party APIs.

Does it help with measuring test coverage?

While it focuses on implementation patterns, it provides the structural foundation necessary to achieve high, meaningful code coverage across unit and integration tests.

How does this skill improve my pytest workflow?

It provides standardized templates for fixtures, parameterization, and test organization, reducing boilerplate and ensuring your test suite remains maintainable as it grows.

Python Testing Patterns

Name: Python Testing Patterns
Author: HermeticOrmus

byHermeticOrmus

安全与测试

Implements comprehensive Python testing strategies using pytest, fixtures, and mocking to ensure code reliability.

关于

Python Testing Patterns is a specialized Claude Code skill designed to streamline the creation of robust, production-grade test suites. It provides expert guidance on implementing the Arrange-Act-Assert (AAA) pattern, managing complex test data through reusable pytest fixtures, and isolating external dependencies with sophisticated mocking techniques. Whether you are practicing Test-Driven Development (TDD), validating asynchronous operations, or setting up continuous testing for CI/CD pipelines, this skill provides the architectural blueprints needed to maintain high code quality and test coverage in Python projects.

主要功能

Asynchronous and concurrent code testing implementation
Parameterized testing for efficient data-driven validation
Sophisticated mocking and patching of external APIs and services
Comprehensive exception and error handling verification
Advanced pytest fixture management for modular setup and teardown
0 GitHub stars

使用场景

Simulating external service failures using monkeypatch and mocks
Implementing Test-Driven Development (TDD) for new feature modules
Building unit and integration test suites for complex Python APIs

关于

主要功能

Asynchronous and concurrent code testing implementation
Parameterized testing for efficient data-driven validation
Sophisticated mocking and patching of external APIs and services
Comprehensive exception and error handling verification
Advanced pytest fixture management for modular setup and teardown
0 GitHub stars

使用场景

Simulating external service failures using monkeypatch and mocks
Implementing Test-Driven Development (TDD) for new feature modules
Building unit and integration test suites for complex Python APIs