我创建了这个示例程序来概括我面临的问题
import multiprocessing
from multiprocessing import Manager
def f (_print):
print _print
manager = multiprocessing.Manager()
dict = manager.dict()
dict['process_obj'] = multiprocessing.current_process()
print dict
if __name__ == '__main__':
process = multiprocessing.Process(target=f, args= ('hello function', ))
process.start()
process.join()
那么如何在多处理Manager.dict()中存储一个进程对象?
答案 0 :(得分:1)
我假设您正在谈论收到此错误:
hello function
Process Process-1:
Traceback (most recent call last):
File "/usr/local/lib/python2.7/multiprocessing/process.py", line 258, in _bootstrap
self.run()
File "/usr/local/lib/python2.7/multiprocessing/process.py", line 114, in run
self._target(*self._args, **self._kwargs)
File "mp2.py", line 8, in f
dict['process_obj'] = multiprocessing.current_process()
File "<string>", line 2, in __setitem__
File "/usr/local/lib/python2.7/multiprocessing/managers.py", line 758, in _callmethod
conn.send((self._id, methodname, args, kwds))
PicklingError: Can't pickle <type 'instancemethod'>: attribute lookup __builtin__.instancemethod failed
(在问题中包含“我得到的东西”和“我希望得到的东西”通常是一个好主意。)
这里的根本问题是multiprocessing.current_process()
返回一个实例方法。实例方法没有正确地进行pickle,multiprocessing
必须保存(pickle)和加载(unpickle)共享数据项,以便将它们的值从一个进程传递到另一个进程。例如,请参阅Can't pickle <type 'instancemethod'> when using python's multiprocessing Pool.map()和Overcoming Python's limitations regarding instance methods。特别注意第二个答案之一:最好找出一些发送/共享的状态,而不是整个实例。例如,如果进程的ident
足够,则可以执行以下操作:
dict['process_obj'] = multiprocessing.current_process().ident
工作正常。