python multiprocessing pool.map用于多个参数 [英] Python multiprocessing pool.map for multiple arguments

问题描述

在Python多处理库中，是否存在pool.map的变体，它支持多个参数?

In the Python multiprocessing library, is there a variant of pool.map which support multiple arguments?

text = "test"
def harvester(text, case):
    X = case[0]
    text+ str(X)

if __name__ == '__main__':
    pool = multiprocessing.Pool(processes=6)
    case = RAW_DATASET
    pool.map(harvester(text,case),case, 1)
    pool.close()
    pool.join()

推荐答案

答案取决于版本和情况. J.F首先在下面描述了最近版本的Python(从3.3版开始)的最通用答案. Sebastian . ¹ 它使用 Pool.starmap 方法，该方法接受一系列参数元组.然后，它会自动将每个元组的参数解包，并将其传递给给定的函数:

The answer to this is version- and situation-dependent. The most general answer for recent versions of Python (since 3.3) was first described below by J.F. Sebastian.¹ It uses the Pool.starmap method, which accepts a sequence of argument tuples. It then automatically unpacks the arguments from each tuple and passes them to the given function:

import multiprocessing
from itertools import product

def merge_names(a, b):
    return '{} & {}'.format(a, b)

if __name__ == '__main__':
    names = ['Brown', 'Wilson', 'Bartlett', 'Rivera', 'Molloy', 'Opie']
    with multiprocessing.Pool(processes=3) as pool:
        results = pool.starmap(merge_names, product(names, repeat=2))
    print(results)

# Output: ['Brown & Brown', 'Brown & Wilson', 'Brown & Bartlett', ...

对于早期版本的Python，您需要编写一个辅助函数来显式解压缩参数.如果要使用with，还需要编写一个包装程序以将Pool转换为上下文管理器. (感谢μon来指向这个.)

For earlier versions of Python, you'll need to write a helper function to unpack the arguments explicitly. If you want to use with, you'll also need to write a wrapper to turn Pool into a context manager. (Thanks to muon for pointing this out.)

import multiprocessing
from itertools import product
from contextlib import contextmanager

def merge_names(a, b):
    return '{} & {}'.format(a, b)

def merge_names_unpack(args):
    return merge_names(*args)

@contextmanager
def poolcontext(*args, **kwargs):
    pool = multiprocessing.Pool(*args, **kwargs)
    yield pool
    pool.terminate()

if __name__ == '__main__':
    names = ['Brown', 'Wilson', 'Bartlett', 'Rivera', 'Molloy', 'Opie']
    with poolcontext(processes=3) as pool:
        results = pool.map(merge_names_unpack, product(names, repeat=2))
    print(results)

# Output: ['Brown & Brown', 'Brown & Wilson', 'Brown & Bartlett', ...

在更简单的情况下，使用固定的第二个参数，您也可以使用partial，但仅在Python 2.7+中使用.

In simpler cases, with a fixed second argument, you can also use partial, but only in Python 2.7+.

import multiprocessing
from functools import partial
from contextlib import contextmanager

@contextmanager
def poolcontext(*args, **kwargs):
    pool = multiprocessing.Pool(*args, **kwargs)
    yield pool
    pool.terminate()

def merge_names(a, b):
    return '{} & {}'.format(a, b)

if __name__ == '__main__':
    names = ['Brown', 'Wilson', 'Bartlett', 'Rivera', 'Molloy', 'Opie']
    with poolcontext(processes=3) as pool:
        results = pool.map(partial(merge_names, b='Sons'), names)
    print(results)

# Output: ['Brown & Sons', 'Wilson & Sons', 'Bartlett & Sons', ...

^{1.这在很大程度上是受他的回答启发的，而他的回答可能应该被接受.但是，由于这个问题排在第一位，因此最好是对将来的读者进行改进.}

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