What mechanisms allow increasing the efficiency of work in asynchronous frameworks?

The following mechanisms are used to improve efficiency in asynchronous frameworks in Python (e.g., asyncio, FastAPI, aiohttp):

• Using non-blocking operations — all input/output (I/O) is performed asynchronously to avoid blocking the event loop.
• Thread or process pools — for executing CPU-bound tasks, ThreadPoolExecutor or ProcessPoolExecutor can be used to avoid blocking the main loop.
• Event loop optimization — minimizing context switches and proper use of await to free the loop.
• Caching and limiting parallelism — using semaphores or limits on the number of concurrent tasks to prevent overload.
• Using specialized libraries — for example, aioredis, asyncpg for asynchronous database operations.

An example of an asynchronous function using await:

import asyncio

async def fetch_data():
    await asyncio.sleep(1)  # simulate asynchronous I/O
    return 'data'

async def main():
    result = await fetch_data()
    print(result)

asyncio.run(main())

This approach allows efficient resource utilization and handling multiple requests simultaneously.