Agent skill · software engineering · wshobson
async-python-patterns
Master Python asyncio, concurrent programming, and async/await patterns for high-performance applications. Use when building async APIs, concurrent systems, or I/O-bound applications requiring non-blocking operations.
Why this skill is useful
Provides specific patterns and examples for implementing asynchronous programming in Python that the AI wouldn't reliably generate on its own.
What it needs
About 4k tokens when loaded. Last updated 2026-08-05. 38,570 stars on the source repository.
What this skill does
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.tothread() Simple scripts, few connections Sync (simpler, easier to debug) Web APIs with high concurrency Async frameworks (FastAPI, aiohttp) Key Rule: Stay fully sync or fully async within a call path. Mixing creates hidden blocking and complexity. Core Concepts 1. Event Loop The event loop is the heart of asyncio, managing and scheduling asynchronous tasks. Key characteristics: Single-threaded cooperative multitasking Schedules coroutines for execution Handles I/O operations without blocking Manages callbacks and futures 2. Coroutines Functions defined with async def that can be paused and resumed. Syntax: 3. Tasks Scheduled coroutines that run concurrently on the event loop. 4. Futures Low-level objects representing eventual results of async operations. 5. Async Context Managers Resources that support async with for proper cleanup. 6. Async Iterators Objects that support async for for iterating over async data sources. …
How to use it
Reference it in AdaL, Claude Code, Cursor or any coding agent — nothing to install:
@skills wshobson/async-python-patterns