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CentOS Python并发处理怎么做

小樊
47
2025-09-26 16:52:08
栏目: 编程语言

在CentOS上使用Python进行并发处理,你可以选择多种方法。以下是一些常用的并发处理库和示例:

  1. 使用threading库:
import threading def worker(num): """线程任务函数""" print(f"Worker: {num}") threads = [] for i in range(5): t = threading.Thread(target=worker, args=(i,)) threads.append(t) t.start() for t in threads: t.join() 
  1. 使用multiprocessing库:
import multiprocessing def worker(num): """进程任务函数""" print(f"Worker: {num}") processes = [] for i in range(5): p = multiprocessing.Process(target=worker, args=(i,)) processes.append(p) p.start() for p in processes: p.join() 
  1. 使用concurrent.futures库:
from concurrent.futures import ThreadPoolExecutor, ProcessPoolExecutor def worker(num): """任务函数""" print(f"Worker: {num}") # 使用线程池 with ThreadPoolExecutor(max_workers=5) as executor: for i in range(5): executor.submit(worker, i) # 使用进程池 with ProcessPoolExecutor(max_workers=5) as executor: for i in range(5): executor.submit(worker, i) 
  1. 使用asyncio库(适用于I/O密集型任务):
import asyncio async def worker(num): """异步任务函数""" print(f"Worker: {num}") await asyncio.sleep(1) async def main(): tasks = [worker(i) for i in range(5)] await asyncio.gather(*tasks) asyncio.run(main()) 

根据你的需求和任务类型,可以选择合适的并发处理方法。对于CPU密集型任务,推荐使用multiprocessing库;对于I/O密集型任务,推荐使用asyncio库。

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