On 2012-09-10, Dan Goodman <dg.gm...@thesamovar.net> wrote: > On 10/09/2012 18:07, Dan Goodman wrote: >> On 04/09/2012 03:54, Roy Smith wrote: >>> Let's assume you're testing two strings for equality. You've already >>> done the obvious quick tests (i.e they're the same length), and you're >>> down to the O(n) part of comparing every character. >>> >>> I'm wondering if it might be faster to start at the ends of the strings >>> instead of at the beginning? If the strings are indeed equal, it's the >>> same amount of work starting from either end. But, if it turns out that >>> for real-life situations, the ends of strings have more entropy than the >>> beginnings, the odds are you'll discover that they're unequal quicker by >>> starting at the end. >> >> From the rest of the thread, it looks like in most situations it won't >> make much difference as typically very few characters need to be >> compared if they are unequal. >> >> However, if you were in a situation with many strings which were almost >> equal, the most general way to improve the situation might be store a >> hash of the string along with the string, i.e. store (hash(x), x) and >> then compare equality of this tuple. Almost all of the time, if the >> strings are unequal the hash will be unequal. Or, as someone else >> suggested, use interned versions of the strings. This is basically the >> same solution but even better. In this case, your startup costs will be >> higher (creating the strings) but your comparisons will always be instant. > > Just had another thought about this. Although it's unlikely to be > necessary in practice since (a) it's rarely necessary at all, and (b) > when it is, hashing and optionally interning seems like the better > approach, I had another idea that would be more general. Rather than > starting from the beginning or the end, why not do something like: check > the first and last character, then the len/2 character, then the len/4, > then 3*len/4, then len/8, 3*len/8, etc. You'd need to be a bit clever > about making sure you hit every character but I'm sure someone's already > got an efficient algorithm for this. You could probably even make this > cache efficient by working on cache line length blocks. Almost certainly > entirely unnecessary, but I like the original question and it's a nice > theoretical problem.
It's not totally theoretical in the sense that the reasoning applies to all sequence comparisons. If you needed to compare lists of objects where the comparison of each pair of elements was an expensive operation then you would want to think carefully about what order you used. Also in general you can't hash/intern all sequences. If I was going to change the order of comparisons for all strings then I would use a random order. This is essentially how dict gets away with claiming to have O(1) lookup. There are sequences of inputs that can cause every possible hash collision to occur but because the hash function acts as a kind of randomisation filter the pathological sequences are very unlikely to occur unless someone is going out of their way. The clever way that Python 3.3 prevents someone from even doing this on purpose is just to introduce additional per-process randomisation. The difference between dict lookup and string comparison is that string comparison always compares the characters in the same order and it corresponds to the natural ordering of the data. This means that some pefectly natural use cases like comparing file-paths can have close to worst case behaviour. If string/sequence comparison occurs in a random order then there can be no use case where the likely strings would induce close to worst case behaviour unless you really are just comparing lots of almost identical sequences. Oscar -- http://mail.python.org/mailman/listinfo/python-list
