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. ## 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 ## 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:** ```python async def my_coroutine(): result = await some_async_operation() return result ``` ### 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 da