What is the main benefit of the Async Python Patterns skill?

It helps Claude generate optimized, non-blocking Python code using asyncio, which is essential for high-concurrency applications like web servers, real-time systems, and scrapers.

Does this skill cover error handling in asynchronous code?

Absolutely. It provides standardized patterns for safely handling exceptions within concurrent tasks and implementing robust timeout logic using asyncio.wait_for.

Does this skill help with web scraping performance?

Yes, it includes specific patterns for concurrent web scraping using aiohttp and implements semaphore-based rate limiting to prevent being blocked by target servers.

Is this skill compatible with modern web frameworks?

Yes, the patterns provided follow industry standards used in modern Python frameworks like FastAPI, Sanic, and Tortoise ORM, focusing on async/await best practices.

Async Python Patterns

Name: Async Python Patterns
Author: HermeticOrmus

byHermeticOrmus

API 开发

Implements high-performance asynchronous Python patterns using asyncio to build non-blocking, concurrent applications and APIs.

关于

This skill provides comprehensive guidance for mastering Python's asynchronous programming model, enabling developers to build scalable systems that handle high I/O workloads efficiently. It covers fundamental and advanced patterns including coroutines, task management, concurrent execution with gather(), error handling, and synchronization primitives like semaphores and locks. Whether you are building real-time APIs with FastAPI or high-speed web scrapers, this skill ensures best practices for non-blocking operations, resource management, and producer-consumer architectures.

主要功能

Implementation of async context managers and iterators for resource safety
Mastery of async/await syntax and coroutine lifecycle management
Advanced synchronization using locks, semaphores, and event loops
Robust error handling and timeout management for async operations
0 GitHub stars
Concurrent execution patterns using asyncio.gather and Task objects

使用场景

Building high-concurrency web APIs with FastAPI, aiohttp, or Sanic
Implementing background task processing and producer-consumer queues
Developing efficient web scrapers and data collectors using concurrent requests

关于

主要功能

Implementation of async context managers and iterators for resource safety
Mastery of async/await syntax and coroutine lifecycle management
Advanced synchronization using locks, semaphores, and event loops
Robust error handling and timeout management for async operations
0 GitHub stars
Concurrent execution patterns using asyncio.gather and Task objects

使用场景

Building high-concurrency web APIs with FastAPI, aiohttp, or Sanic
Implementing background task processing and producer-consumer queues
Developing efficient web scrapers and data collectors using concurrent requests