python-dev

Implement, refactor, test, and debug Python code with quality checks.

Updated Jul 10, 2023

Search Tags:#testing #development #pydantic #python #mypy #ruff #typing

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npx skills add https://github.com/iamtatsuki05/dotfiles --skill python-dev-iamtatsuki05

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Please help me install this Agent Skill.
Skill: python-dev
Source: https://github.com/iamtatsuki05/dotfiles/tree/main/dotfiles/.agent/skills/python-dev
Command: npx skills add https://github.com/iamtatsuki05/dotfiles --skill python-dev-iamtatsuki05

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

This guide helps Python projects achieve consistent implementation, reliable tests, and robust type safety by outlining standards for tooling, formatting, and model usage.

Core Features & Use Cases

Clear project setup and configuration guidance (pyproject.toml, Ruff, mypy) to enforce consistency.
Coding conventions for Python 3.12+ including Pydantic models and precise type hints.
Comprehensive testing and quality practices (pytest/unittest, fixtures, parameterization, and test organization).
Error handling, packaging guidance, and maintainable design patterns to reduce runtime issues.

Quick Start

Review the project against these standards and start applying them in your next change.

Frequently Asked Questions about python-dev

High-intent search queries and answers about installing and using this skill.

FAQPage Schema

How do I configure pyproject.toml for ruff and mypy to enforce Python type safety?▼

Configure pyproject.toml by defining ruff and mypy settings to enforce formatting and typing discipline. This setup ensures consistent implementation and robust type safety across your Python codebase.

What is the best way to structure pytest fixtures and parameterization for Python testing?▼

Structure pytest testing by organizing fixtures and parameterization logically within your test suite. This approach provides comprehensive quality practices and reliable test coverage for your Python project.

How do I implement Pydantic models with precise type hints in Python 3.12?▼

Implement Pydantic models using Python 3.12 coding conventions and precise type hints. This ensures robust data validation and maintainable design patterns while reducing runtime issues.

Does this Python development guide support both unittest and pytest frameworks?▼

Yes, the Python development guide supports both pytest and unittest frameworks. It provides comprehensive testing and quality practices, including fixtures, parameterization, and test organization for typical Python codebases.

Why use ruff and mypy together for Python codebase quality checks?▼

Use ruff and mypy together to apply automated formatting and static type checking. This combination enforces strict coding conventions, identifies potential errors early, and maintains consistent project quality.

How do I handle runtime errors and packaging guidance in a Python project?▼

Handle runtime errors by applying robust error handling patterns and following packaging guidance. This reduces runtime issues and ensures maintainable design across typical Python codebases.