Python 多处理：对特定对象的方法应用 pool.map

Question

以下并行函数执行完美：来自多处理导入池来自随机导入 randrange

def triple(number):
    return number * 3

if __name__ == '__main__':
    numbers = [5, 10, 20]
    pool = Pool(processes=3)
    print(pool.map(triple, numbers))

但是我如何通过始终在对象列表上调用相同的方法来获得相同的结果，即当函数是某些 class 个对象上的方法时：

from multiprocessing import Pool
from random import randrange


class RandomNumber():
    def __init__(self):
        self.no = randrange(100)

    def triple(self, *args, **kwargs):
        print(triple(self.no))
        return triple(self.no)


if __name__ == '__main__':
    # but how can I always call the same method on an object
    numbers = [RandomNumber() for m in range(0, 3)]
    # e.g. here on every random number within the list
    # call numbers[0].triple(), numbers[1].triple() ...
    # paralelly?

问题是我绑定到特定对象，不能只使用函数..

提前致谢！

Answer 1

你可以用函数扭曲这个方法：

def triple_warpper(random_number: RandomNumber):
    return random_number.triple()

if __name__ == '__main__':
    numbers = [RandomNumber() for m in range(0, 3)]
    pool = Pool(processes=3)
    print(pool.map(triple_warpper, numbers))

Answer 2

这里有一个使用__call__方法的方法：

class RandomNumber:

    def __call__(self, *args, **kwargs):
        r = randrange(100)
        return r

if __name__ == '__main__':

    r = RandomNumber()
    numbers = [x for x in range(0, 10)]
    pool = Pool(processes=3)
    print(pool.map(r, numbers))

Python 多处理：对特定对象的方法应用 pool.map

Python multiprocessing: apply pool.map on methods of specific objects

python

python-multiprocessing