python-patterns

Guide Python framework selection and async versus synchronous programming decisions.

Updated Aug 23, 2026

Search Tags:#best practices #project structure #python #frameworks #type hints #async

Ready to run

npx skills add https://github.com/abner-magal/mcp-video-audio --skill python-patterns-abner-magal

💬 Prompt for ChatGPT / Claude Chat▼

Please help me install this Agent Skill.
Skill: python-patterns
Source: https://github.com/abner-magal/mcp-video-audio/tree/main/.opencode/skills/python-patterns
Command: npx skills add https://github.com/abner-magal/mcp-video-audio --skill python-patterns-abner-magal

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

This Skill helps developers make informed decisions about Python frameworks, asynchronous programming, type hinting, and project structure, promoting robust and maintainable code.

Core Features & Use Cases

Framework Selection: Guides choices between FastAPI, Django, and Flask based on project needs.
Async vs. Sync: Clarifies when to use asynchronous programming for I/O-bound tasks versus synchronous for CPU-bound tasks.
Type Hinting: Advises on effective use of type hints for clarity and validation, including Pydantic.
Project Structure: Offers principles for organizing code in small, medium, and large Python projects.
Use Case: A developer is starting a new web service and is unsure whether to use FastAPI for its speed and async capabilities or Django for its batteries-included features. This Skill provides a decision tree and comparison to help them choose the best fit.

Quick Start

Use the python-patterns skill to decide between FastAPI and Django for a new API project.

Frequently Asked Questions about python-patterns

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

FAQPage Schema

How do I choose between FastAPI, Django, and Flask for a new Python project?▼

Choosing between FastAPI, Django, and Flask depends on your project needs. FastAPI offers speed and async capabilities, Django provides batteries-included features, and Flask allows lightweight flexibility for custom project structures.

When should I use async versus sync programming in Python?▼

Use asynchronous programming in Python for I/O-bound tasks to handle concurrent operations efficiently. Use synchronous programming for CPU-bound tasks where processing logic requires blocking execution until completion.

What is the best way to use type hints with Pydantic in Python?▼

The best way to use type hints with Pydantic involves applying them for data validation and clarity. Pydantic enforces type hints at runtime, ensuring robust data parsing and maintainable Python application code.

How do I structure a large Python application for maintainability?▼

Structure a large Python application by following modular organization principles. Separating concerns into distinct directories for routes, models, and services ensures maintainable code across small, medium, and large project scales.

Does FastAPI work well for CPU-bound tasks compared to Django?▼

FastAPI is optimized for asynchronous I/O-bound tasks rather than CPU-bound tasks. For heavy CPU-bound processing, synchronous paradigms or Django's synchronous architecture may be more appropriate to prevent event loop blocking.