concurrent.futures模块

1.concurrent.futures模块介绍

2.ThreadPoolExecutor线程池使用

3.ProcessPoolExecutor进程池使用

4.其他方法使用

1.concurrent.futures模块介绍

 # 介绍
     concurrent.futures模块提供了高度封装的异步调用接口
     ThreadPoolExecutor：线程池，提供异步调用
     ProcessPoolExecutor: 进程池，提供异步调用

 # 基本方法
 # submit(fn, *args, **kwargs)  异步提交任务

 # map(func, *iterables, timeout=None, chunksize=1)  取代for循环submit的操作

 # shutdown(wait=True) 相当于进程池的pool.close()+pool.join()操作
     wait=True，等待池内所有任务执行完毕回收完资源后才继续
     wait=False，立即返回，并不会等待池内的任务执行完毕
     但不管wait参数为何值，整个程序都会等到所有任务执行完毕
     submit和map必须在shutdown之前

 # result(timeout=None) 取得结果

 # add_done_callback(fn) 回调函数

2.ThreadPoolExecutor线程池使用

 from concurrent.futures import ThreadPoolExecutor
 import time
 import random

 def task(n):
     print(n)
     time.sleep(random.randint(1, 3))
     return n ** 2

 if __name__ == '__main__':
     executor = ThreadPoolExecutor(max_workers=5)       # 最多5个线程
     futures = []
     for i in range(11):
         future = executor.submit(task, i)
         futures.append(future)
     executor.shutdown(True)
     print('+++>')
     for future in futures:
         print(future.result())

3.ProcessPoolExecutor进程池使用

 from concurrent.futures import ProcessPoolExecutor
 import os
 import time
 import random

 def task(n):
     print('%s is runing' % os.getpid())
     time.sleep(random.randint(1, 3))
     return n ** 2

 if __name__ == '__main__':
     executor = ProcessPoolExecutor(max_workers=3)       # 最多3个进程
     futures = []
     for i in range(11):
         future = executor.submit(task, i)
         futures.append(future)
     executor.shutdown(True)
     print('+++>')
     for future in futures:
         print(future.result())

4.其他方法使用

 # map方法使用
 import time
 from concurrent.futures import ThreadPoolExecutor

 def func(n):
     time.sleep(2)
     print(n)
     return n * n

 def call_back(m):
     print('结果是 %s' % m.result())

 tpool = ThreadPoolExecutor(max_workers=5)
 tpool.map(func, range(20))  # 注意map方法拿不到返回值

 # 回调函数
 import time
 from concurrent.futures import ThreadPoolExecutor

 def func(n):
     time.sleep(2)
     print(n)
     return n * n

 # 回调函数
 def call_back(m):
     print('结果是 %s' % m.result())

 tpool = ThreadPoolExecutor(max_workers=5)
 for i in range(20):
     tpool.submit(func, i).add_done_callback(call_back)