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

It provides standardized patterns for implementing non-blocking I/O in Python, significantly increasing the throughput of applications that handle many simultaneous connections or network operations.

How does it handle rate limiting?

The skill includes patterns for using semaphores, which allow you to limit the number of concurrent operations to prevent overwhelming external APIs or exhausting system resources.

Does it include error handling for concurrent tasks?

Absolutely. It provides specific patterns for safe operation execution and filtering results when using asyncio.gather to ensure your application remains stable even when individual tasks fail.

Can this skill help with web frameworks like FastAPI?

Yes, it is designed specifically to assist in building async web APIs and performing concurrent network requests using libraries like aiohttp, FastAPI, and Sanic.

Async Python Patterns

Name: Async Python Patterns
Author: donggyun112

bydonggyun112

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API 开发

Implements high-performance Python applications using asyncio, non-blocking I/O, and advanced concurrency patterns.

关于

This skill provides expert guidance for mastering Python's asynchronous ecosystem, enabling developers to build scalable, high-concurrency systems. It covers fundamental asyncio concepts like event loops and coroutines alongside advanced implementation patterns such as producer-consumer queues, rate limiting with semaphores, and robust error handling in concurrent tasks. Whether you are building real-time FastAPI backends, efficient web scrapers with aiohttp, or non-blocking microservices, this skill ensures your implementation follows industry best practices for performance and thread safety.

主要功能

Asynchronous I/O optimization and task scheduling
Concurrent task management using asyncio.gather
Rate limiting and resource management via semaphores
Implementation of async context managers and iterators
Thread-safe synchronization using async locks
3 GitHub stars

使用场景

Optimizing non-blocking database and network communication
Developing efficient web scrapers with concurrent request handling
Building high-performance REST and WebSocket APIs with FastAPI

关于

主要功能

Asynchronous I/O optimization and task scheduling
Concurrent task management using asyncio.gather
Rate limiting and resource management via semaphores
Implementation of async context managers and iterators
Thread-safe synchronization using async locks
3 GitHub stars

使用场景

Optimizing non-blocking database and network communication
Developing efficient web scrapers with concurrent request handling
Building high-performance REST and WebSocket APIs with FastAPI