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有皱纹的地方只表示微笑曾在那儿呆过。-------马克.吐温
在Unix/Linux下，multiprocessing模块封装了fork（）调用，是我们不需要关注fork（）的细节。由于windows没有fork调用，因此，multiprocessing需要“模拟”出fork的效果，父进程所有Python对象都必须通过pickle序列号再传到子进程中去。所以，如果multiprocessing在Windows下调用失败了，要先考虑是不是pickle失败了。
Python3中模拟分布式调用时，如果是在Unix/Linux下，测试程序可以正常运行，但如果实在Windows下，将会报错：
代码如下：
import random,time,queue
from multiprocessing.managers import BaseManagertask_queue = queue.Queue()
result_queue = queue.Queue()class QueueManager(BaseManager):passQueueManager.register('get_task_queue',callable=lambda:task_queue)
QueueManager.register('get_result_queue',callable=lambda:result_queue)manager=QueueManager(address=('',5000),authkey=b'abc')
manager.start()task = manager.get_task_queue()
result = manager.get_result_queue()for i in range(10):n = random.randint(0,10000)print('Put task %d' % n)task.put(n)print('Try get results..')
for i in range(10):r = result.get(timeout=10)print('Result:%s' % r)manager.shutdown()
print('master exit.')
"E:\python\python project\myfirst\venv\Scripts\python.exe" "E:/python/python project/myfirst/vari/distibuted_master.py"
Traceback (most recent call last):File "E:/python/python project/myfirst/vari/distibuted_master.py", line 20, in <module>manager.start()File "D:\program files\Python3.6\Lib\multiprocessing\managers.py", line 513, in startself._process.start()File "D:\program files\Python3.6\Lib\multiprocessing\process.py", line 105, in startself._popen = self._Popen(self)File "D:\program files\Python3.6\Lib\multiprocessing\context.py", line 322, in _Popenreturn Popen(process_obj)File "D:\program files\Python3.6\Lib\multiprocessing\popen_spawn_win32.py", line 65, in __init__reduction.dump(process_obj, to_child)File "D:\program files\Python3.6\Lib\multiprocessing\reduction.py", line 60, in dumpForkingPickler(file, protocol).dump(obj)
_pickle.PicklingError: Can't pickle <function <lambda> at 0x00000000003D2EA0>: attribute lookup <lambda> on __main__ failedProcess finished with exit code 1
import queue
import random
from multiprocessing.managers import BaseManagertask_queue = queue.Queue()
result_queue = queue.Queue()def return_task_queue():global task_queuereturn task_queuedef return_result_queue():global result_queuereturn result_queueclass QueueManager(BaseManager):passif __name__=='__main__':QueueManager.register('get_task_queue', callable=return_task_queue)QueueManager.register('get_result_queue', callable=return_result_queue)manager = QueueManager(address=('127.0.0.1', 5000), authkey=b'abc')manager.start()task = manager.get_task_queue()result = manager.get_result_queue()for i in range(10):n = random.randint(0, 10000)print('Put task %d' % n)task.put(n)print('Try get results..')for i in range(10):r = result.get(timeout=10)print('Result:%s' % r)manager.shutdown()print('master exit.')
"E:\python\python project\myfirst\venv\Scripts\python.exe" "E:/python/python project/myfirst/vari/distibuted_master.py"
Put task 4752
Put task 5446
Put task 9628
Put task 8701
Put task 225
Put task 3059
Put task 5046
Put task 5630
Put task 9980
Put task 7492
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