Does this skill support modern Python versions?

Yes, it is optimized for modern Python (3.11+) and includes patterns like pipe union types and advanced type hinting protocols.

Is it useful for web frameworks like FastAPI or Django?

Yes, the skill includes patterns relevant to major frameworks, specifically focusing on async context managers, request validation, and clean architectural layers.

How does it handle data models and validation?

It suggests using Dataclasses for simple data containers and Pydantic for robust models requiring validation, coercion, and complex serialization.

Can it help me configure my linter and formatter?

Absolutely, it provides configuration templates for industry-standard tools like Ruff, Black, and Mypy within the pyproject.toml file.

Python Best Practices

Name: Python Best Practices
Author: eous

byeous

개발자 도구

Implements industry-standard Python patterns, type hinting, and structural conventions for clean and maintainable code.

소개

The Python Best Practices skill equips Claude with the specialized knowledge required to write and review Python code according to modern professional standards. It covers a comprehensive range of topics including PEP 8 naming conventions, formatting with tools like Ruff and Black, advanced type hinting for better static analysis, and asynchronous programming patterns with asyncio. By integrating this skill, developers can ensure their projects utilize robust error handling, efficient data modeling with Pydantic or Dataclasses, and standardized project structures that facilitate easier collaboration and long-term maintenance.

주요 기능

Provides modern type hinting patterns for improved static analysis and IDE support.
Standardizes project structures and dependency management using pyproject.toml.
Guides the implementation of robust error handling and domain-specific exceptions.
0 GitHub stars
Enforces PEP 8 naming conventions and formatting standards across codebases.
Streamlines testing workflows with pytest fixtures and asynchronous testing patterns.

사용 사례

Scaffolding new Python projects with standardized directory structures and configuration files.
Reviewing pull requests to identify and fix common Python anti-patterns and performance bottlenecks.
Refactoring legacy Python code to meet modern typing and formatting standards.

소개

주요 기능

Provides modern type hinting patterns for improved static analysis and IDE support.
Standardizes project structures and dependency management using pyproject.toml.
Guides the implementation of robust error handling and domain-specific exceptions.
0 GitHub stars
Enforces PEP 8 naming conventions and formatting standards across codebases.
Streamlines testing workflows with pytest fixtures and asynchronous testing patterns.

사용 사례

Scaffolding new Python projects with standardized directory structures and configuration files.
Reviewing pull requests to identify and fix common Python anti-patterns and performance bottlenecks.
Refactoring legacy Python code to meet modern typing and formatting standards.