Question

For example:

a = [1,2,3]
x = [2*i for i in a]
y = [3*i for i in a]

Would it be more efficient to combine the list comprehensions into one (if possible) if the size of a is large? If so, how do you do this?

Something like,

x,y = [2*i, 3*i for i in a]

which doesn’t work. If using list comprehension is not more computationally efficient than using a normal for loop, let me know too. Thanks.

Answer 1

When in doubt about efficiency use the timeit module, it’s always easy to use:

import timeit

def f1(aRange):
    x = [2*i for i in aRange]
    y = [3*i for i in aRange]
    return x,y

def f2(aRange):
    x, y = zip(*[(2*i, 3*i) for i in aRange])
    return x,y

def f3(aRange):
    x, y = zip(*((2*i, 3*i) for i in aRange))
    return x,y

def f4(aRange):
    x = []
    y = []
    for i in aRange:
        x.append(i*2)
        y.append(i*3)
    return x,y

print "f1: %f" %timeit.Timer("f1(range(100))", "from __main__ import f1").timeit(100000)
print "f2: %f" %timeit.Timer("f2(range(100))", "from __main__ import f2").timeit(100000)
print "f3: %f" %timeit.Timer("f3(range(100))", "from __main__ import f3").timeit(100000)
print "f4: %f" %timeit.Timer("f4(range(100))", "from __main__ import f4").timeit(100000)

The results seem to be consistent in pointing to the first option as the quickest.

f1: 2.127573
f2: 3.551838
f3: 3.859768
f4: 4.282406