Async Python Patterns

The async-python-patterns skill provides comprehensive guidance for implementing asynchronous Python applications using asyncio and async/await patterns for high-performance, non-blocking systems. It serves developers building async web APIs, concurrent systems, and I/O-bound applications who need to understand when and how to use asyncio versus synchronous or multiprocessing approaches. The skill solves the problem of designing and implementing efficient concurrent Python applications by teaching core async concepts, decision frameworks for choosing async over alternatives, and practical code patterns for common use cases.

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last updated: Aug 21, 2026

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Install

$ npx -y skills add wshobson/agents --skill async-python-patterns --agent claude-code

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Async Python Patterns

Comprehensive guidance for implementing asynchronous Python applications using asyncio, concurrent programming patterns, and async/await for building high-performance, non-blocking systems.

When to Use This Skill

Building async web APIs (FastAPI, aiohttp, Sanic)
Implementing concurrent I/O operations (database, file, network)
Creating web scrapers with concurrent requests
Developing real-time applications (WebSocket servers, chat systems)
Processing multiple independent tasks simultaneously
Building microservices with async communication
Optimizing I/O-bound workloads
Implementing async background tasks and queues

Sync vs Async Decision Guide

Before adopting async, consider whether it's the right choice for your use case.

Use Case	Recommended Approach
Many concurrent network/DB calls	`asyncio`
CPU-bound computation	`multiprocessing` or thread pool
Mixed I/O + CPU	Offload CPU work with `asyncio.to_thread()`
Simple scripts, few connections	Sync (simpler, easier to debug)
Web APIs with high concurrency	Async frameworks (FastAPI, aiohttp)