Python sort() method on list vs builtin sorted() function

Your error in measurement is as follows: after your first call of test_list1.sort(), that list object IS sorted — and Python’s sort, aka timsort, is wickedly fast on already sorted lists!!! That’s the most frequent error in using timeit — inadvertently getting side effects and not accounting for them.

Here’s a good set of measurements, using timeit from the command line as it’s best used:

$ python -mtimeit -s'import random; x=range(1000); random.shuffle(x)' '
y=list(x); y.sort()'
1000 loops, best of 3: 452 usec per loop
$ python -mtimeit -s'import random; x=range(1000); random.shuffle(x)' '
x.sort()'
10000 loops, best of 3: 37.4 usec per loop
$ python -mtimeit -s'import random; x=range(1000); random.shuffle(x)' '
sorted(x)'
1000 loops, best of 3: 462 usec per loop

As you see, y.sort() and sorted(x) are neck and neck, but x.sort() thanks to the side effects gains over an order of magnitude’s advantage — just because of your measurement error, though: this tells you nothing about sort vs sorted per se! -)