> but when a and b have many elements. such as: > >>>>a=range(100000) >>>>b=range(50000) >>>>for x in b: > > ... a.remove(x) > ... > it will very slowly.
Well, your problem is rather ambiguous. In your examples, you're removing contiguous ranges. Thus, you should be able to do something like >>> a = range(100000) >>> del a[:50000] which may have a considerable speedup. However, if B contains a disjoint sets of entries, the simple solution will require A*B checks, making it dependant on the size of A and B (as you've discovered). Assuming the "del" method is considerably faster, you might be able to do some sort of optimization of the disjoint set, using the above-mentioned method. Break B into contiguous pieces, and then pass those as slices to delete. Or if B is a pattern of some sort, you could do >>> a = range(100000) >>> del a[::2] #delete even numbers >>> a = range(100000) >>> del a[1::2] #delete odd numbers >>> a = range(100000) >>> del a[2::5] # delete every 5th element beginning with the 3rd Another attempt might be to try >>> a = [x for x in a if x not in b] However, this is still doing A*B checks, and will likely degrade with as their sizes increase. Just a few ideas. -tkc -- http://mail.python.org/mailman/listinfo/python-list
