答案取决于版本和情况。
JF Sebastian首先描述了最近版本的Python（从3.3开始）的最一般的答案。
1它使用
Pool.starmap方法，该方法接受一个参数元组序列。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：
import multiprocessingfrom itertools import productdef 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，则还需要编写一个包装器以变为Pool上下文管理器。（感谢muon指出这一点。）
import multiprocessingfrom itertools import productfrom contextlib import contextmanagerdef merge_names(a, b): return '{} & {}'.format(a, b)def merge_names_unpack(args): return merge_names(*args)@contextmanagerdef 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。
import multiprocessingfrom functools import partialfrom contextlib import contextmanager@contextmanagerdef 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', ...
