Documentation

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.

Use this skill when

●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

Do not use this skill when

●The workload is CPU-bound with minimal I/O.

●A simple synchronous script is sufficient.

●The runtime environment cannot support asyncio/event loop usage.

Instructions

●Clarify workload characteristics (I/O vs CPU), targets, and runtime constraints.

●Pick concurrency patterns (tasks, gather, queues, pools) with cancellation rules.

●Add timeouts, backpressure, and structured error handling.

●Include testing and debugging guidance for async code paths.

●If detailed examples are required, open resources/implementation-playbook.md.

Refer to resources/implementation-playbook.md for detailed patterns and examples.

Resources

●resources/implementation-playbook.md for detailed patterns and examples.

async-python-patterns

Documentation