async-python-patterns

Documentation & Productivité

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.

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.

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