python-engineering

Define Python engineering best practices for structuring, testing, typing, and tooling projects.

5|1|Updated Jul 30, 2010

Search Tags:#testing #pytest #python #engineering #ruff #guidelines #typing

Ready to run

npx skills add https://github.com/gonzaloserrano/dotfiles --skill python-engineering-gonzaloserrano

💬 Prompt for ChatGPT / Claude Chat▼

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

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

Python projects often suffer from inconsistent structure, ambiguous guidelines, and weak testing and typing practices that slow development and reduce reliability.

Core Features & Use Cases

Standard project blueprint: src/ layout, clear packaging, and aligned testing structure.
Quality guarantees: enforced style, typing discipline, and tests with pytest, mypy, and ruff.
Real-world use: teams building libraries, CLIs, and apps can adopt these guidelines to accelerate onboarding and maintainable code.
Example: structure a new CLI tool with packaging, type hints, docs, and CI checks.

Quick Start

Instruct the AI to outline a Python project skeleton following the guidelines for a new library named "mylib".

Frequently Asked Questions about python-engineering

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

FAQPage Schema

What is the best way to structure a production-ready Python project?▼

A standard Python project structure uses a src/ layout with clear packaging aligned alongside a dedicated testing directory to accelerate onboarding and maintainability. This enforces a standard project layout and explicit dependencies for robust engineering.

How do I set up testing and typing for a Python library?▼

Set up testing and typing by integrating pytest for thorough test coverage and mypy for typing discipline to ensure robust code quality. This combination satisfies requirements for code quality checks and reliable library development.

Does ruff work with mypy and pytest for Python code quality checks?▼

Ruff works with mypy and pytest to enforce style, typing discipline, and comprehensive tests in Python projects. Together, these tools provide quality guarantees for production-ready code across libraries, CLIs, and applications.

How do I create a Python CLI tool skeleton with packaging and documentation?▼

Create a Python CLI tool skeleton by applying standard engineering guidelines to establish packaging, type hints, docs, and CI checks. This provides a structured project layout with explicit dependencies and enforced code quality.

Why do I need explicit dependencies for a Python engineering project?▼

Explicit dependencies are required for Python engineering projects to satisfy standard layout guidelines and ensure reliable, production-ready code execution. They prevent environment conflicts and maintain clear packaging structure for libraries and applications.

Can I use these Python engineering guidelines for AI agent development?▼

These Python engineering guidelines apply directly to AI agent development by providing the structure, testing, typing, and tooling needed for production-ready code. They detail how to satisfy requirements for standard layouts and quality checks in agent projects.