Can this skill help with web scraping?

Yes, it includes specific patterns for concurrent web scraping using libraries like aiohttp to handle multiple requests simultaneously without blocking.

Does it cover error handling in async code?

Absolutely, it provides robust patterns for catching exceptions in concurrent tasks, managing timeouts, and using wait_for safely.

What is the main benefit of using this skill?

It enables Claude to generate expert-level asynchronous Python code that prevents blocking operations and maximizes application throughput for I/O-heavy tasks.

Is it compatible with frameworks like FastAPI?

Yes, these patterns are ideal for building modern asynchronous web APIs using frameworks like FastAPI, Sanic, and aiohttp.

Async Python Patterns

Name: Async Python Patterns
Author: HermeticOrmus

byHermeticOrmus

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Desarrollo de API

Implement high-performance, non-blocking Python applications using asyncio and concurrent programming patterns.

Acerca de

This skill provides comprehensive implementation guidance for Python developers working with asynchronous programming. It covers fundamental and advanced patterns for asyncio, including concurrent task execution with gather(), robust error handling, timeout management, and sophisticated producer-consumer architectures. Whether you are building high-throughput APIs with FastAPI or efficient web scrapers, this skill ensures Claude can generate production-grade, thread-safe, and highly scalable asynchronous code optimized for I/O-bound workloads.

Características Principales

Comprehensive async/await syntax and coroutine lifecycle management
Advanced synchronization primitives including Semaphores and Locks
Implementation of async context managers and asynchronous iterators
Concurrent task coordination using asyncio.gather and Task objects
Real-world patterns for high-performance web scraping and database operations
1 GitHub stars

Casos de Uso

Developing high-concurrency backend services and REST APIs with FastAPI or Sanic
Building efficient data scrapers and real-time WebSocket communication systems
Optimizing I/O-bound workloads to prevent blocking the event loop in microservices

Acerca de

Características Principales

Comprehensive async/await syntax and coroutine lifecycle management
Advanced synchronization primitives including Semaphores and Locks
Implementation of async context managers and asynchronous iterators
Concurrent task coordination using asyncio.gather and Task objects
Real-world patterns for high-performance web scraping and database operations
1 GitHub stars

Casos de Uso

Developing high-concurrency backend services and REST APIs with FastAPI or Sanic
Building efficient data scrapers and real-time WebSocket communication systems
Optimizing I/O-bound workloads to prevent blocking the event loop in microservices