async-python-patternslisted

# 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. ## Core concepts (summary) - **Event loop**: Single-threaded cooperative scheduler that runs coroutines and handles I/O without blocking. - **Coroutines**: `async def` functions that can be paused at `await` points and resumed by the event loop. - **Tasks**: Scheduled coroutines running concurrently on the loop (created via `asyncio.create_task`). - **Futures**: Low-level objects representing eventual results of async operations. - **Async context managers**: Objects supporting `async with` for safe resource setup/teardown. - **Async iterators**: Objects supporting `async for` to consume data from async sources (e.g., generators with `