One classic approach to this problem is to use the "decorate, sort, undecorate" idiom, which is especially simple using python's built-in zip
function:
>>> list1 = [3,2,4,1, 1]
>>> list2 = ['three', 'two', 'four', 'one', 'one2']
>>> list1, list2 = zip(*sorted(zip(list1, list2)))
>>> list1
(1, 1, 2, 3, 4)
>>> list2
('one', 'one2', 'two', 'three', 'four')
These of course are no longer lists, but that's easily remedied, if it matters:
>>> list1, list2 = (list(t) for t in zip(*sorted(zip(list1, list2))))
>>> list1
[1, 1, 2, 3, 4]
>>> list2
['one', 'one2', 'two', 'three', 'four']
It's worth noting that the above may sacrifice speed for terseness; the in-place version, which takes up 3 lines, is a tad faster on my machine for small lists:
>>> %timeit zip(*sorted(zip(list1, list2)))
100000 loops, best of 3: 3.3 us per loop
>>> %timeit tups = zip(list1, list2); tups.sort(); zip(*tups)
100000 loops, best of 3: 2.84 us per loop
On the other hand, for larger lists, the one-line version could be faster:
>>> %timeit zip(*sorted(zip(list1, list2)))
100 loops, best of 3: 8.09 ms per loop
>>> %timeit tups = zip(list1, list2); tups.sort(); zip(*tups)
100 loops, best of 3: 8.51 ms per loop
As Quantum7 points out, JSF's suggestion is a bit faster still, but it will probably only ever be a little bit faster, because Python uses the very same DSU idiom internally for all key-based sorts. It's just happening a little closer to the bare metal. (This shows just how well optimized the zip
routines are!)
I think the zip
-based approach is more flexible and is a little more readable, so I prefer it.