domain:python

Standardize Python project conventions for typing, testing, and tooling.

Updated Jul 27, 2025
One-click install
npx skills add https://github.com/TheCactusBlue/nixfiles --skill domain-python
Or copy as Structured Prompt for Agent
Please help me install this Agent Skill.
Skill: domain:python
Source: https://github.com/TheCactusBlue/nixfiles/tree/main/.claude/skills/domain%3Apython
Command: npx skills add https://github.com/TheCactusBlue/nixfiles --skill domain-python

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

Python projects often drift in conventions, leading to inconsistent type hints, testing, error handling, and dependency choices. This Skill codifies project conventions to improve maintainability and reliability across teams.

Core Features & Use Cases

  • Type hints on all function signatures and class attributes
  • Standardized testing practices (pytest) with clear fixtures and parametrization
  • Consistent error handling with defined exception hierarchies
  • Specified dependencies and project metadata to streamline setup (pyproject.toml, linting/typing tools)
  • Use Case: Start a new Python project with these conventions to ensure clean APIs, robust tests, and predictable tooling.

Quick Start

Apply the Python conventions to a project by enabling type hints, configuring pytest-based tests, and adding the recommended tools (ruff, mypy) in pyproject.toml.

Frequently Asked Questions about domain:python

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

FAQPage Schema
How do I enforce Python coding conventions for type hints and testing?

Standardize Python coding conventions by enforcing type hints on all function signatures, configuring pytest with clear fixtures, and defining consistent error handling to improve project maintainability.

What's the best way to set up a new Python project with standardized dependencies and tooling?

Set up a new Python project using standardized conventions by configuring pyproject.toml with recommended linting and typing tools like ruff and mypy to ensure clean APIs and predictable tooling.

How do you handle error handling and exception hierarchies in Python projects?

Handle Python errors consistently by codifying defined exception hierarchies within project conventions, ensuring predictable error handling and improving reliability across the team.

Do I need pytest and mypy to maintain reliable Python code?

Standardized testing with pytest and typing tools like mypy are recommended to enforce coding conventions, ensure robust tests, and maintain reliability across Python projects.

Can I use ruff and pyproject.toml to manage Python project metadata and linting?

Yes, you can streamline Python project setup by specifying dependencies and project metadata in pyproject.toml, utilizing ruff for linting to maintain coding standards and clean APIs.