What methods in Python are used to implement parallel operations when processing requests?

In Python, several approaches are often used to implement parallel operations when processing requests:

1. Multithreading — suitable for tasks with a large number of I/O operations, as Python is limited by the GIL (Global Interpreter Lock) and cannot efficiently utilize multiple cores for CPU-intensive tasks.

import threading

def handle_request(request):
    # handle request
    pass

thread = threading.Thread(target=handle_request, args=(request,))
thread.start()

2. Multiprocessing — allows running multiple processes, bypassing the GIL limitation, effective for CPU-intensive tasks.

from multiprocessing import Pool

def process_request(request):
    # handle request
    return result

with Pool(4) as p:
    results = p.map(process_request, requests)

3. Asynchronous programming (asyncio) — enables processing many requests without creating new threads or processes, effective for a large number of I/O operations.

import asyncio

async def handle_request(request):
    # asynchronous handling
    pass

async def main():
    tasks = [handle_request(req) for req in requests]
    await asyncio.gather(*tasks)

asyncio.run(main())

The choice of method depends on the nature of the task and performance requirements.