函数内的Python多处理: calling pool.映射

Question

我正在尝试使用 mutltiprocessing 包在一个函数中使用多个 CPU。当我在函数外部运行玩具示例时，它会在四分之一秒内运行，没有任何问题(见下文)。

from multiprocessing import Pool
import time

start = time.clock()

def f(x):
    return x*x

if __name__ == '__main__':
    with Pool(processes=7) as pool:     
        result = pool.map(f, range(1000))



print(time.clock() - start)

但是，当我将相同的代码改编成一个函数时(见下文)，它会打印 True 以指示 __name__ == '__main__'，但随后它会运行永远永远不会返回结果。我在 Windows 7 上运行 Python 3.3。

from multiprocessing import Pool
import time

start = time.clock()

def f(x):
    return x*x

def testfunc(r):
    if __name__ == '__main__':
        print(True)
        with Pool(processes=7) as pool:     
            result = pool.map(f, range(r))

    return result

result = testfunc(1000)
print(time.clock() - start)

Answer 1

您在错误的地方使用了 if __name__ == '__main__'。

from multiprocessing import Pool
import time

start = time.clock()

def f(x):
    return x*x

def testfunc(r):
    print(True)
    with Pool(processes=7) as pool:     
        result = pool.map(f, range(r))
    return result

if __name__ == '__main__':
    result = testfunc(1000)
    print(time.clock() - start)

根据 multiprocessing - Programming guidelines :

Safe importing of main module

Make sure that the main module can be safely imported by a new Python interpreter without causing unintended side effects (such a starting a new process).

... one should protect the “entry point” of the program by using if __name__ == '__main__': as follows: