How does it handle shared test resources?

It utilizes conftest.py patterns to manage shared fixtures, session-wide configurations, and custom markers across your entire test suite.

Does this skill support pytest-mock?

Yes, the skill includes patterns for using both the standard unittest.mock library and the pytest-mock plugin for cleaner and more readable test code.

Does it help with generating coverage reports?

Yes, it includes commands and pyproject.toml configurations for generating terminal, missing-line, and HTML coverage reports using pytest-cov.

Can I use this for testing async Python code?

Absolutely. It provides specific guidance and decorators for testing asynchronous functions and fixtures using pytest-asyncio.

Python Testing with pytest

Name: Python Testing with pytest
Author: laurigates

bylaurigates

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Security & Testing

Simplifies Python test suite creation and maintenance using pytest, mocking, and comprehensive coverage analysis.

About

This skill provides Claude with specialized knowledge for implementing robust Python testing strategies. It covers the full testing lifecycle, from writing unit tests with pytest fixtures and parametrization to advanced mocking techniques and asynchronous test handling. Designed for developers practicing Test-Driven Development (TDD) or aiming for high code coverage, this skill ensures your Python projects are reliable, maintainable, and adhere to industry-standard testing patterns and directory structures.

Key Features

Parametrized testing for efficient edge-case validation
3 GitHub stars
Advanced mocking and patching patterns for external dependencies
Asynchronous testing support for modern Python applications
Comprehensive pytest command reference and configuration
Code coverage analysis and HTML reporting integration

Use Cases

Designing complex integration tests using shared fixtures in conftest.py
Implementing Test-Driven Development (TDD) workflows in new Python projects
Improving code coverage and reliability in legacy Python codebases

About

Key Features

Parametrized testing for efficient edge-case validation
3 GitHub stars
Advanced mocking and patching patterns for external dependencies
Asynchronous testing support for modern Python applications
Comprehensive pytest command reference and configuration
Code coverage analysis and HTML reporting integration

Use Cases

Designing complex integration tests using shared fixtures in conftest.py
Implementing Test-Driven Development (TDD) workflows in new Python projects
Improving code coverage and reliability in legacy Python codebases