How does this skill help with framework selection?

It provides a specific decision tree based on project requirements—such as API-first needs, full-stack requirements, or background worker complexity—to recommend FastAPI, Django, or Flask.

Can it help organize a messy Python project?

Absolutely. It defines clear structural principles for small scripts, medium APIs, and large-scale applications using either layered or feature-based organization.

How does it handle the async vs sync debate?

It provides a 'Golden Rule' for choosing execution models: async for I/O-bound operations like database calls and sync for CPU-bound or legacy operations.

Does it support the latest Python features?

Yes, it is optimized for 2025 standards, covering modern type hinting, Django 5.0+ async capabilities, and Pydantic v2 integration.

Does it include testing best practices?

Yes, it outlines strategies for unit and integration testing using pytest, including specific patterns for testing asynchronous endpoints.

Python Development Patterns

Name: Python Development Patterns
Author: lev-os

bylev-os

•

API開発

Guides architectural decision-making and best practices for modern Python development, from framework selection to async patterns.

This skill acts as a senior architectural advisor for Python projects, helping developers navigate the complex ecosystem of 2025. It provides structured decision trees for choosing between FastAPI, Django, and Flask, while offering deep technical guidance on when to implement asynchronous programming versus synchronous execution. By focusing on the 'why' behind patterns like Pydantic validation, modular project structures, and background task management, it ensures that Claude produces code that is not only functional but also maintainable, scalable, and type-safe.

主な機能

01Best practices for background tasks, error handling, and testing

02Modular project structure templates for varying application scales

031 GitHub stars

04Implementation strategies for Type Hints and Pydantic v2 validation

05Async vs. Sync architectural decision trees and library matching

06Context-aware framework selection (FastAPI, Django, Flask)

ユースケース

01Implementing robust data validation and type safety across complex API endpoints

02Architecting a new Python web service with the optimal framework and folder structure

03Transitioning synchronous I/O operations to high-performance async patterns

What are Skills?·How to Install

Install with 🐟 Skill.Fish

npx skillfish add lev-os/agents python-patterns

For use in Claude.ai and ChatGPT