backend-async-python

Asyncio enables non-blocking I/O by running concurrent tasks on a single event loop. Instead of waiting for I/O operations sequentially, you define async functions and use await to yield control, allowing the event loop to process other tasks while waiting for network or file operations to complete.

Use asyncio.gather() or asyncio.wait() to run coroutines concurrently on the same event loop. gather() waits for all tasks to complete and returns their results; wait() offers finer control over completion conditions like FIRST_COMPLETED or FIRST_EXCEPTION.

Yes. FastAPI runs on asyncio event loops and handles concurrent requests efficiently. Define your route handlers as async functions, use await for I/O-bound operations like database queries or external API calls, and asyncio manages scheduling without blocking.

Wrap coroutines with asyncio.wait_for() to enforce timeouts, and use try-except blocks around await statements to catch exceptions. For robust error handling, use asyncio.gather() with return_exceptions=True to collect results and errors from multiple concurrent tasks.

Async context managers (async with) and async iterators (async for) enable safe resource cleanup and streaming over async operations. They ensure proper connection handling, lock acquisition, and iteration over concurrent streams without blocking or leaking resources.

Yes. Asyncio is designed for scalable concurrent I/O through non-blocking event loops and task scheduling. It excels at handling thousands of concurrent connections and real-time event processing, though CPU-bound tasks require thread pools or multiprocessing.