What is invariant-based testing?

Instead of writing tests that just confirm a bug existed, it focuses on verifying the core rules and behaviors that should always be true in your application.

How does this skill help with bug fixing?

It implements a strict TDD workflow: finding existing tests, improving them until they fail to expose the bug, fixing the code, and then verifying all tests pass.

Why does it recommend patch.object over standard patch?

Using patch.object is more robust as it requires a direct reference to the class or object being mocked, reducing errors related to string-based path resolution.

Does this skill support async testing?

Yes, it includes patterns for using AsyncMock and testing asynchronous code paths commonly found in modern Python applications.

Python Testing Standards

Name: Python Testing Standards
Author: gigaverse-app

bygigaverse-app

安全与测试

Implements industry-leading Python testing patterns and TDD workflows using pytest and advanced mocking strategies.

关于

The Python Testing Standards skill equips Claude with a specialized framework for writing robust, maintainable tests. It emphasizes invariant-based testing—verifying what should always be true rather than simply proving a bug existed—and enforces strict Test-Driven Development (TDD) workflows. By utilizing modern patterns like Pydantic for test data, patch.object for mocking, and the extraction of pure functions for maximum testability, this skill ensures your Python codebase maintains high coverage and architectural integrity.

主要功能

Includes comprehensive checklists for imports, coverage, and fixture usage
Standardizes mocking patterns using patch.object and AsyncMock for dependencies
Utilizes Pydantic models for structured, consistent test data generation
Enforces TDD workflows to ensure bugs are reproduced before being fixed
0 GitHub stars
Promotes invariant-based testing to verify core system logic and edge cases

使用场景

Fixing complex bugs by first improving test coverage to expose failures
Establishing standardized E2E and integration testing patterns for microservices
Refactoring legacy code into testable pure functions and infrastructure code

关于

主要功能

Includes comprehensive checklists for imports, coverage, and fixture usage
Standardizes mocking patterns using patch.object and AsyncMock for dependencies
Utilizes Pydantic models for structured, consistent test data generation
Enforces TDD workflows to ensure bugs are reproduced before being fixed
0 GitHub stars
Promotes invariant-based testing to verify core system logic and edge cases

使用场景

Fixing complex bugs by first improving test coverage to expose failures
Establishing standardized E2E and integration testing patterns for microservices
Refactoring legacy code into testable pure functions and infrastructure code