我认为以下内容会更好：

def multi_run_wrapper(args):
   return add(*args)

def add(x,y):
    return x+y

if __name__ == "__main__":
    from multiprocessing import Pool
    pool = Pool(4)
    results = pool.map(multi_run_wrapper,[(1,2),(2,3),(3,4)])
    print results

输出

[3, 5, 7]

Python 2的更好解决方案：

from multiprocessing import Pool
def func((i, (a, b))):
    print i, a, b
    return a + b
pool = Pool(3)
pool.map(func, [(0,(1,2)), (1,(2,3)), (2,(3, 4))])

输出

2 3 4

1 2 3

0 1 2

out[]:

[3, 5, 7]

在J.F.Sebastian的回答中了解了itertools之后，我决定更进一步，编写一个关注并行化的parmap包，在Python 2.7和Python 3.2（以及更高版本）中提供可以接受任意数量位置参数的map和starmap函数。

安装

pip install parmap

如何并行化：

import parmap
# If you want to do:
y = [myfunction(x, argument1, argument2) for x in mylist]
# In parallel:
y = parmap.map(myfunction, mylist, argument1, argument2)

# If you want to do:
z = [myfunction(x, y, argument1, argument2) for (x,y) in mylist]
# In parallel:
z = parmap.starmap(myfunction, mylist, argument1, argument2)

# If you want to do:
listx = [1, 2, 3, 4, 5, 6]
listy = [2, 3, 4, 5, 6, 7]
param = 3.14
param2 = 42
listz = []
for (x, y) in zip(listx, listy):
        listz.append(myfunction(x, y, param1, param2))
# In parallel:
listz = parmap.starmap(myfunction, zip(listx, listy), param1, param2)

我已经将parmap上传到PyPI和GitHub存储库。

例如，问题的答案如下：

import parmap

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

if __name__ == "__main__":
    case = RAW_DATASET  # assuming this is an iterable
    parmap.map(harvester, case, "test", chunksize=1)

pool.map是否有支持多个参数的变体？

Python 3.3包含pool.starmap（）方法：

#!/usr/bin/env python3
from functools import partial
from itertools import repeat
from multiprocessing import Pool, freeze_support

def func(a, b):
    return a + b

def main():
    a_args = [1,2,3]
    second_arg = 1
    with Pool() as pool:
        L = pool.starmap(func, [(1, 1), (2, 1), (3, 1)])
        M = pool.starmap(func, zip(a_args, repeat(second_arg)))
        N = pool.map(partial(func, b=second_arg), a_args)
        assert L == M == N

if __name__=="__main__":
    freeze_support()
    main()

对于旧版本：

#!/usr/bin/env python2
import itertools
from multiprocessing import Pool, freeze_support

def func(a, b):
    print a, b

def func_star(a_b):
    """Convert `f([1,2])` to `f(1,2)` call."""
    return func(*a_b)

def main():
    pool = Pool()
    a_args = [1,2,3]
    second_arg = 1
    pool.map(func_star, itertools.izip(a_args, itertools.repeat(second_arg)))

if __name__=="__main__":
    freeze_support()
    main()

输出

1 1
2 1
3 1

注意这里是如何使用itertools.izip（）和itertools.crepeat（）的。

由于@unsubu提到的错误，您不能在Python 2.6上使用functools.partial（）或类似功能，因此应该显式定义简单包装函数func_tar（）。另请参阅uptimebox建议的解决方法。

对于Python 2，可以使用此技巧

def fun(a, b):
    return a + b

pool = multiprocessing.Pool(processes=6)
b = 233
pool.map(lambda x:fun(x, b), range(1000))

另一种方法是将列表列表传递给单参数例程：

import os
from multiprocessing import Pool

def task(args):
    print "PID =", os.getpid(), ", arg1 =", args[0], ", arg2 =", args[1]

pool = Pool()

pool.map(task, [
        [1,2],
        [3,4],
        [5,6],
        [7,8]
    ])

然后可以用自己喜欢的方法构造一个参数列表。