What problem does it solve?
Writing production-ready Python often becomes inconsistent and error-prone without strong patterns for typing, validation, testing, and project tooling.
Core Features & Use Cases
- Type Hints & Structure: Establish a maintainable project layout and use modern type annotations to reduce runtime surprises.
- Pydantic Validation: Define robust request/response models with constraints to enforce correctness at boundaries.
- Testing & Tooling: Use pytest, ruff, mypy, and pre-commit to catch regressions early and keep code quality high.
- Async & Framework Guidance: Apply patterns for async I/O and common framework setups (FastAPI, Django, Flask) to ship APIs confidently.
Use Case: You’re building a FastAPI endpoint that accepts user input and must guarantee correctness; use this skill to define Pydantic models with constraints, add type-safe handlers, and cover behavior with pytest.
Quick Start
Ask the skill to generate a complete minimal Python project scaffold (pyproject.toml, ruff, mypy, pytest setup, src/ and tests/ structure) plus an example Pydantic model with corresponding pytest tests.
