Is this skill suitable for beginners to asyncio?

Yes, it covers everything from fundamental async/await syntax to complex producer-consumer patterns, making it useful for both learning and professional implementation.

How does it help with API rate limiting?

The skill provides implementation examples for using asyncio.Semaphore to limit the number of concurrent network requests, preventing your application from being throttled.

What is the primary benefit of using this skill?

It provides standardized, battle-tested patterns for Python asyncio, helping you avoid common pitfalls like blocking the event loop or creating unmanaged race conditions.

Can I use this for web development?

Absolutely. It is specifically designed for building modern APIs with frameworks like FastAPI, Sanic, and aiohttp that rely heavily on asynchronous execution.

Does this skill handle error management in concurrent tasks?

Yes, it includes advanced patterns for robust error handling, including managing exceptions within asyncio.gather and implementing safe retry logic.

Async Python Patterns

Name: Async Python Patterns
Author: HermeticOrmus

byHermeticOrmus

Desarrollo de API

Implements high-performance concurrent Python applications using master-level asyncio patterns and non-blocking I/O strategies.

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This skill provides comprehensive architectural guidance and implementation patterns for Python's asynchronous ecosystem. It enables developers to build scalable, high-performance systems by mastering the event loop, coroutines, and advanced concurrency controls like semaphores and producer-consumer queues. Whether you are optimizing I/O-bound web scrapers, building real-time WebSocket servers, or developing high-throughput APIs with FastAPI or aiohttp, this skill ensures best practices for resource management, error handling, and task synchronization within the Claude Code environment.

Características Principales

Design patterns for producer-consumer workflows and background tasks
Safe error and timeout handling for concurrent operations
Advanced asyncio pattern implementation including gather, tasks, and futures
Concurrency control using semaphores and locks for rate limiting
Resource management via async context managers and iterators
0 GitHub stars

Casos de Uso

Developing real-time communication systems and WebSocket servers
Optimizing high-throughput web APIs and microservices with FastAPI or Sanic
Building efficient concurrent web scrapers and data collectors

Acerca de

Características Principales

Design patterns for producer-consumer workflows and background tasks
Safe error and timeout handling for concurrent operations
Advanced asyncio pattern implementation including gather, tasks, and futures
Concurrency control using semaphores and locks for rate limiting
Resource management via async context managers and iterators
0 GitHub stars

Casos de Uso

Developing real-time communication systems and WebSocket servers
Optimizing high-throughput web APIs and microservices with FastAPI or Sanic
Building efficient concurrent web scrapers and data collectors