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:
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() 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() 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) 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。