python-guide

Enforce Python development guardrails, patterns, and best practices for AI-assisted coding.

7|1|Updated Nov 3, 2025
One-click install
npx skills add https://github.com/ar4mirez/samuel --skill python-guide
Or copy as Structured Prompt for Agent
Please help me install this Agent Skill.
Skill: python-guide
Source: https://github.com/ar4mirez/samuel/tree/main/template/.claude/skills/python-guide
Command: npx skills add https://github.com/ar4mirez/samuel --skill python-guide

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill includes references (resource) components.

What problem does it solve?

This Skill provides comprehensive guardrails, best practices, and patterns for Python development, ensuring code quality, maintainability, and adherence to modern standards.

Core Features & Use Cases

  • Type Hinting Enforcement: Ensures all functions and variables are properly type-annotated.
  • Style and Linting: Integrates with Ruff for consistent code formatting and error detection.
  • Testing Standards: Promotes the use of pytest for robust unit and integration testing.
  • Dependency Management: Guides on using pyproject.toml and virtual environments.
  • Error Handling: Establishes clear patterns for exception hierarchies and context management.
  • Use Case: When starting a new Python project, use this Skill to set up a robust project structure, configure linters and type checkers, and establish testing conventions from the outset.

Quick Start

Follow the Python guardrails and best practices outlined in this skill to write clean, maintainable Python code.

Frequently Asked Questions about python-guide

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

FAQPage Schema
What are the best practices for Python type hints and async patterns?

Python best practices for type hints involve annotating all functions and variables, while async patterns require structured error handling and context management to ensure code maintainability.

How do I set up a new Python project with pytest and Ruff linting?

To set up a Python project, configure pyproject.toml for dependency management, establish virtual environments, integrate Ruff for formatting and linting, and configure pytest for robust testing conventions.

Does this Python development guide work with pyproject.toml and requirements.txt?

Yes, this Python development guidance explicitly applies to pyproject.toml and requirements.txt files, offering guardrails for dependency management, virtual environments, and project configuration standards.

Why should I enforce PEP 8 and Ruff standards in Python development?

Enforcing PEP 8 and Ruff standards in Python development ensures consistent code formatting, automated error detection, and overall code quality, which significantly improves long-term project maintainability.

How do I handle exception hierarchies and error handling in Python?

Python error handling should establish clear exception hierarchies and use context management patterns, providing structured guardrails that prevent unhandled exceptions and improve application reliability.

What is the best way to manage Python dependencies using pyproject.toml?

The best way to manage Python dependencies is using pyproject.toml alongside virtual environments, which standardizes project configuration and isolates development environments for consistent builds.