python如何同時運作兩個函數_Python：如何并行運作python函數？

如果您是Windows使用者并使用python 3，那麼這篇文章将幫助您在python中進行并行程式設計。當您運作通常的多處理庫的池程式設計時，您将收到有關程式中主函數的錯誤。這是因為windows沒有fork（）功能。以下文章正在解決上述問題。

由于我使用的是python 3，我将程式改為：from types import FunctionTypeimport marshaldef _applicable(*args, **kwargs):

name = kwargs['__pw_name']

code = marshal.loads(kwargs['__pw_code'])

gbls = globals() #gbls = marshal.loads(kwargs['__pw_gbls'])

defs = marshal.loads(kwargs['__pw_defs'])

clsr = marshal.loads(kwargs['__pw_clsr'])

fdct = marshal.loads(kwargs['__pw_fdct'])

func = FunctionType(code, gbls, name, defs, clsr)

func.fdct = fdct del kwargs['__pw_name']

del kwargs['__pw_code']

del kwargs['__pw_defs']

del kwargs['__pw_clsr']

del kwargs['__pw_fdct']

return func(*args, **kwargs)def make_applicable(f, *args, **kwargs):

if not isinstance(f, FunctionType): raise ValueError('argument must be a function')

kwargs['__pw_name'] = f.__name__ # edited

kwargs['__pw_code'] = marshal.dumps(f.__code__) # edited

kwargs['__pw_defs'] = marshal.dumps(f.__defaults__) # edited

kwargs['__pw_clsr'] = marshal.dumps(f.__closure__) # edited

kwargs['__pw_fdct'] = marshal.dumps(f.__dict__) # edited

return _applicable, args, kwargsdef _mappable(x):

x,name,code,defs,clsr,fdct = x

code = marshal.loads(code)

gbls = globals() #gbls = marshal.loads(gbls)

defs = marshal.loads(defs)

clsr = marshal.loads(clsr)

fdct = marshal.loads(fdct)

func = FunctionType(code, gbls, name, defs, clsr)

func.fdct = fdct return func(x)def make_mappable(f, iterable):

if not isinstance(f, FunctionType): raise ValueError('argument must be a function')

name = f.__name__ # edited

code = marshal.dumps(f.__code__) # edited

defs = marshal.dumps(f.__defaults__) # edited

clsr = marshal.dumps(f.__closure__) # edited

fdct = marshal.dumps(f.__dict__) # edited

return _mappable, ((i,name,code,defs,clsr,fdct) for i in iterable)

在這個函數之後，上面的問題代碼也改變了一點：from multiprocessing import Poolfrom poolable import make_applicable, make_mappabledef cube(x):

return x**3if __name__ == "__main__":

pool = Pool(processes=2)

results = [pool.apply_async(*make_applicable(cube,x)) for x in range(1,7)]

print([result.get(timeout=10) for result in results])

我得到的輸出為：[1, 8, 27, 64, 125, 216]

我認為這篇文章可能對某些Windows使用者有用。