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Found 130 Skills
Implement comprehensive testing strategies with pytest, fixtures, mocking, and test-driven development. Use when writing Python tests, setting up test suites, or implementing testing best practices.
Python testing strategies using pytest, TDD methodology, fixtures, mocking, parametrization, and coverage requirements.
Run pytest tests with coverage, discover lines missing coverage, and increase coverage to 100%.
Write comprehensive unit tests with high coverage using testing frameworks like Jest, pytest, JUnit, or RSpec. Use when writing tests for functions, classes, components, or establishing testing standards.
Auto-activate for polyfactory, ModelFactory, DataclassFactory, MsgspecFactory, AttrsFactory, Use, register_fixture, pytest plugin, __random_seed__, or coverage(). Not for production seeding.
Creates test infrastructure with Vitest, xUnit, and pytest
Create factory fixture patterns for customizable test setup with variations. Use when building reusable test fixtures with multiple configurations, creating parameterizable mocks, or implementing test data builders. Works with pytest fixtures, mock objects, and test utilities. Enables DRY test setup while maintaining flexibility for edge cases.
Django testing strategies with pytest-django, TDD methodology, factory_boy, mocking, coverage, and testing Django REST Framework APIs.
Run Python quality checks with ruff, pytest, mypy, and bandit in deterministic order. Use WHEN user requests "quality gate", "lint", "verify code quality", "check python", or "pre-commit check". Use for pre-merge validation, CI/CD gating, or comprehensive code quality reports. Do NOT use for single-tool runs (run tool directly), debugging runtime bugs (use systematic-debugging), refactoring (use systematic-refactoring), or architecture review.
Modern Python development with uv, ruff, mypy, and pytest. Use when: - Writing or reviewing Python code - Setting up Python projects or pyproject.toml - Choosing dependency management (uv, poetry, pip) - Configuring linting, formatting, or type checking - Organizing Python packages Keywords: Python, pyproject.toml, uv, ruff, mypy, pytest, type hints, virtual environment, lockfile, package structure
Comprehensive pytest testing skill for Python projects. Write efficient, maintainable tests with fixtures, parametrization, markers, mocking, and assertions. Use when: (1) Writing new tests for Python code, (2) Setting up pytest in a project, (3) Creating fixtures for test dependencies, (4) Parametrizing tests for multiple inputs, (5) Mocking/patching with monkeypatch, (6) Debugging test failures, (7) Organizing test suites with markers, (8) Any Python testing task.
Use when building Python 3.11+ applications requiring type safety, async programming, or production-grade patterns. Invoke for type hints, pytest, async/await, dataclasses, mypy configuration.