线程池的概念：

　　使用concurrent模块进行并发编程的

先上简单的代码

import timefrom concurrent.futures import ThreadPoolExecutorfrom threading import current_threaddef func(i):    print('thread',i,current_thread())  # 线程ID    time.sleep(1)    print('thread %s end'%i)tp = ThreadPoolExecutor(5) # 开了5个线程for i in range(20):    tp.submit(func,i)tp.shutdown()print('主线程')

返回值

import timefrom concurrent.futures import ThreadPoolExecutorfrom threading import current_threaddef func(i):    print('thread',i,current_thread())  # 线程ID    time.sleep(1)    print('thread %s end'%i)    return i*'*'tp = ThreadPoolExecutor(5) # 实例化线程池，开了5个线程ret_l = []for i in range(20):    ret = tp.submit(func,i)    ret_l.append(ret)for ret in ret_l:    print(ret.result())print('主线程')

回调函数

import osimport timefrom concurrent.futures import ProcessPoolExecutorfrom threading import current_thread as cthread# 线程池的回调函数 子线程完成的def func(i):    print('thread',i,os.getpid())    time.sleep(1)    print('thread %s end'%i)    return i*'*'def call_back(arg):    print('call back:',os.getpid())    print('ret:',arg.result())if __name__ == '__main__':    tp = ProcessPoolExecutor(5)    ret_l = []    for i in range(20):        tp.submit(func,i).add_done_callback(call_back)    print('主线程',os.getpid())

# 回调函数     # 在线程池中 由子线程完成的     # 在进程池中 由主线程完成的 # 线程池     # 实例化线程池 ThreadPoolExecutor   5*cpu_count     # 异步提交任务  submit/map     # 阻塞直到任务完成 shutdown     # 获取子线程的返回值 result     # 回调函数          add_down_callback