线程池

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大数据

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from concurrent.futures import ThreadPoolExecutor, ProcessPoolExecutor  # 线程池，进程池
import threading, time

def test(arg):
    #print(arg, threading.current_thread().name)
    print('thread_name={thread_name},arg={arg}'.format(thread_name=threading.current_thread().name,arg=arg) )
    time.sleep(2)

if __name__ == "__main__":
    thread_pool = ThreadPoolExecutor(5)  # 定义5个线程执行此任务

    for i in range(20):
        thread_pool.submit(test, i)

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