如果从函数内部执行,则具有“apply\u async”的多处理池不会执行任何操作

为了检索计算结果,请对代码进行以下更改。

import multiprocessing

def test():

    def do():
        print("Foobar", flush=True)

    with multiprocessing.Pool(1) as pool:
        for i in range(5):
            result = pool.apply_async(do)

            result.get()

        pool.close()
        pool.join()

test()

你会明白为什么“什么都没发生”。

Traceback (most recent call last):
  File "/tmp/test.py", line 17, in <module>
    test()
  File "/tmp/test.py", line 12, in test
    result.get()
  File "/usr/lib/python3.5/multiprocessing/pool.py", line 608, in get
    raise self._value
  File "/usr/lib/python3.5/multiprocessing/pool.py", line 385, in _handle_tasks
    put(task)
  File "/usr/lib/python3.5/multiprocessing/connection.py", line 206, in send
    self._send_bytes(ForkingPickler.dumps(obj))
  File "/usr/lib/python3.5/multiprocessing/reduction.py", line 50, in dumps
    cls(buf, protocol).dump(obj)
AttributeError: Can't pickle local object 'test.<locals>.do'    

python multiprocessing.Pool 依赖于 pickle 将要发送到其他进程的数据序列化的协议。这个 泡菜 协议只能序列化顶级函数,不能序列化嵌套函数。

查看哪些可以腌制,哪些不能检查 documentation 。