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.
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What the file says
# 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) |
…
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Source
GitHub
rudycity/superagent · 64 stars · license MIT · pushed 2026-11-06 · branch main
API
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