David Grant wrote:

I find myself needing the set operations provided by python 2.4 such as intersection, difference, or even just the advantages of the data strucure itself, like that fact that I can try adding something to it and if it's already there, it won't get added again. Will my decision to use of the python 'set' datastructure come back to haunt me later by being too slow?

If you are adding stuff few items at a time to large sets, it is likely that set() may be better for you O()-wise. However, the only way to know which method will be faster would be to try it yourself with your data.

Is there anything equivalent in scipy or numpy that I can use? I find myself going between numpy arrays and sets a lot because I sometimes need to treat it like an array to use some of the array functions.

Robert Cimrman wrote a number of set operations (union, intersection, difference) for arrays in numpy.lib.arraysetops . There have been some recent discussions on improving them, especially in the face of inf, nan, and other such floating point beasties.

Sorry for cross-posting to scipy and numpy... is that a bad idea?

Yes. Please reserve cross-posting for announcements and other such things that don't require follow-up discussions. Cross-posted discussions can get a bit hairy. For questions like these ("Is there something in numpy or scipy to do foo?"), there is enough cross-readership that it really doesn't matter if you only ask one list. -- Robert Kern "I have come to believe that the whole world is an enigma, a harmless enigma that is made terrible by our own mad attempt to interpret it as though it had an underlying truth." -- Umberto Eco