I have my own domain at zhar.net which is where I keep all my stuff including a few python things. In my Game AI area you can find a python A* implementation, a mostly working influence map and my (now deprecated) C implementation of the python heapq module.

I also have a few python scripts in my Shell Scrips area. Including an email spam corpus cleaner (removes duplicates and attachments from my spam corpus) and a re-implementation (based on the original perl version) of the bogominitrain bogofilter spam filter training algorithm.

Just for a touch of original content. Here is a little snippet I came up with that I am fond of... it starts with a description of the problem.

    Given a data struct like this:

    x = {

    I want to end up with this:

    y = [
        { 'lion':'a', 'tiger':'m', 'cheetah':'y', },
        { 'lion':'a', 'tiger':'m', 'cheetah':'z', },
        { 'lion':'a', 'tiger':'o', 'cheetah':'y', },
        { 'lion':'a', 'tiger':'o', 'cheetah':'z', },

        { 'lion':'b', 'tiger':'m', 'cheetah':'y', },
        { 'lion':'b', 'tiger':'m', 'cheetah':'z', },
        { 'lion':'b', 'tiger':'o', 'cheetah':'y', },
        { 'lion':'b', 'tiger':'o', 'cheetah':'z', },
And here is what I came up with. I really like how generators and recursion play well together. Makes for an elegant solution IMO.
    def combinator(items):
        expanded = [[(key,v) for v in values] for key,values in items]
        return (dict(l) for l in _citer(expanded))

    def _citer(lst):
        head,tail = lst[0],lst[1:]
        if not tail:
            for t in head:
                yield [t]
            for t in head:
                for h in _citer(tail):
                    yield [t] + h

    if __name__=="__main__":
        from pprint import pprint
        val = combinator(x.items())