Find non-common elements in lists

Old question, but looks like python has a built-in function to provide exactly what you're looking for: .difference().

EXAMPLE

list_one = [1,2,3,4]
list_two = [2,3,5]

one_not_two = set(list_one).difference(list_two)
# set([1, 4])

two_not_one = set(list_two).difference(list_one)
# set([5])

This could also be written as:

one_not_two = set(list_one) - set(list_two)

Timing

I ran some timing tests on both and it appears that .difference() has a slight edge, to the tune of 10 - 15% but each method took about an eighth of a second to filter 1M items (random integers between 500 and 100,000), so unless you're very time sensitive, it's probably immaterial.

Other Notes

It appears the OP is looking for a solution that provides two separate lists (or sets) - one where the first contains items not in the second, and vice versa. Most of the previous answers return a single list or set that include all of the items.

There is also the question as to whether items that may be duplicated in the first list should be counted multiple times, or just once.

If the OP wants to maintain duplicates, a list comprehension could be used, for example:

one_not_two = [ x for x in list_one if x not in list_two ]
two_not_one = [ x for x in list_two if x not in list_one ]

...which is roughly the same solution as posed in the original question, only a little cleaner. This method would maintain duplicates from the original list but is considerably (like multiple orders of magnitude) slower for larger data sets.

Use the symmetric difference operator for sets (aka the XOR operator):

>>> set([1,2,3]) ^ set([3,4,5])
set([1, 2, 4, 5])