I have now:
list1 = [1, 2, 3]
list2 = [4, 5, 6]
I wish to have:
[1, 2, 3]
+ + +
The others gave examples how to do this in pure python. If you want to do this with arrays with 100.000 elements, you should use numpy:
In [1]: import numpy as np
In [2]: vector1 = np.array([1, 2, 3])
In [3]: vector2 = np.array([4, 5, 6])
Doing the element-wise addition is now as trivial as
In [4]: sum_vector = vector1 + vector2
In [5]: print sum_vector
[5 7 9]
just like in Matlab.
Timing to compare with Ashwini's fastest version:
In [16]: from operator import add
In [17]: n = 10**5
In [18]: vector2 = np.tile([4,5,6], n)
In [19]: vector1 = np.tile([1,2,3], n)
In [20]: list1 = [1,2,3]*n
In [21]: list2 = [4,5,6]*n
In [22]: timeit map(add, list1, list2)
10 loops, best of 3: 26.9 ms per loop
In [23]: timeit vector1 + vector2
1000 loops, best of 3: 1.06 ms per loop
So this is a factor 25 faster! But use what suits your situation. For a simple program, you probably don't want to install numpy, so use standard python (and I find Henry's version the most Pythonic one). If you are into serious number crunching, let numpy
do the heavy lifting. For the speed freaks: it seems that the numpy solution is faster starting around n = 8
.