[a + b for a, b in zip(list1, list2)]

如果您需要处理不同大小的列表，不用担心!很棒的itertools模块已经介绍过了:

>>> from itertools import zip_longest
>>> list1 = [1,2,1]
>>> list2 = [2,1,2,3]
>>> [sum(x) for x in zip_longest(list1, list2, fillvalue=0)]
[3, 3, 3, 3]
>>>

在Python 2中，zip_longest被称为izip_longest。

参见相关回答，并对另一个问题进行评论。

在我看来，使用numpy更简单:

import numpy as np
list1=[1,2,3]
list2=[4,5,6]
np.add(list1,list2)

结果:

有关详细参数信息，请查看这里:numpy.add

也许“最python化的方式”应该包括处理list1和list2大小不同的情况。运用其中的一些方法，你会不动声色地得到答案。numpy方法会让您知道，很可能使用ValueError。

例子:

import numpy as np
>>> list1 = [ 1, 2 ]
>>> list2 = [ 1, 2, 3]
>>> list3 = [ 1 ]
>>> [a + b for a, b in zip(list1, list2)]
[2, 4]
>>> [a + b for a, b in zip(list1, list3)]
[2]
>>> a = np.array (list1)
>>> b = np.array (list2)
>>> a+b
Traceback (most recent call last):
  File "<stdin>", line 1, in <module>
ValueError: operands could not be broadcast together with shapes (2) (3)

如果这是你问题中的函数你想要什么结果?

这将适用于2个或更多的列表;遍历列表的列表，但使用numpy加法处理每个列表的元素

import numpy as np
list1=[1, 2, 3]
list2=[4, 5, 6]

lists = [list1, list2]
list_sum = np.zeros(len(list1))
for i in lists:
   list_sum += i
list_sum = list_sum.tolist()    

[5.0, 7.0, 9.0]

使用map和operator.add:

>>> from operator import add
>>> list( map(add, list1, list2) )
[5, 7, 9]

或者压缩一个列表理解:

>>> [sum(x) for x in zip(list1, list2)]
[5, 7, 9]

时间比较:

>>> list2 = [4, 5, 6]*10**5
>>> list1 = [1, 2, 3]*10**5
>>> %timeit from operator import add;map(add, list1, list2)
10 loops, best of 3: 44.6 ms per loop
>>> %timeit from itertools import izip; [a + b for a, b in izip(list1, list2)]
10 loops, best of 3: 71 ms per loop
>>> %timeit [a + b for a, b in zip(list1, list2)]
10 loops, best of 3: 112 ms per loop
>>> %timeit from itertools import izip;[sum(x) for x in izip(list1, list2)]
1 loops, best of 3: 139 ms per loop
>>> %timeit [sum(x) for x in zip(list1, list2)]
1 loops, best of 3: 177 ms per loop