多处理池内进程超时

发布于 2024-08-11 21:56:53 字数 453 浏览 8 评论 0原文

当我使用以下代码时，池结果总是返回超时，我在做的事情在逻辑上是否不正确？

from multiprocessing import Pool, Process, cpu_count

def add(num):
  return num+1

def add_wrap(num):
  new_num = ppool.apply_async(add, [num])
  print new_num.get(timeout=3)

ppool = Pool(processes=cpu_count() )

test = Process(target=add_wrap, args=(5,)).start()

我知道这个错误，并且认为它会在 python 2.6 中得到修复。 4？

原文

When ever I use the following code the pool result always returns a timeout, is there something logically incorrect I am doing?

from multiprocessing import Pool, Process, cpu_count

def add(num):
  return num+1

def add_wrap(num):
  new_num = ppool.apply_async(add, [num])
  print new_num.get(timeout=3)

ppool = Pool(processes=cpu_count() )

test = Process(target=add_wrap, args=(5,)).start()

I'm aware of this bug, and would have thought that it would have been fixed in python 2.6.4?

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一影成城 2024-08-18 21:56:53

您不能在进程之间传递 Pool 对象。

如果您尝试此代码，Python 将引发异常：“NotImplementedError：池对象无法在进程之间传递或腌制”。

from multiprocessing import Queue, Pool

q = Queue()
ppool = Pool(processes=2)                                                       
q.put([ppool])
ppool = q.get()

因此，如果您希望代码正常工作，只需在 add_wrap 方法中创建 Pool 对象即可。

from multiprocessing import Pool, Process, cpu_count

def add(num):
  return num+1

def add_wrap(num):
  ppool = Pool(processes=cpu_count() )
  new_num = ppool.apply_async(add, [num])
  print new_num.get(timeout=3)

test = Process(target=add_wrap, args=(5,)).start()

You can't pass Pool objects between processes.

If you try this code, Python will raise a exception : 'NotImplementedError: pool objects cannot be passed between processes or pickled'.

from multiprocessing import Queue, Pool

q = Queue()
ppool = Pool(processes=2)                                                       
q.put([ppool])
ppool = q.get()

So if you want your code to work, just create your Pool object in the add_wrap method.

from multiprocessing import Pool, Process, cpu_count

def add(num):
  return num+1

def add_wrap(num):
  ppool = Pool(processes=cpu_count() )
  new_num = ppool.apply_async(add, [num])
  print new_num.get(timeout=3)

test = Process(target=add_wrap, args=(5,)).start()

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