On 2014-05-22 12:47, Adam Funk wrote: > I'm using Python 3.3 and the sqlite3 module in the standard library. > I'm processing a lot of strings from input files (among other > things, values of headers in e-mail & news messages) and suppressing > duplicates using a table of seen strings in the database. > > It seems to me --- from past experience with other things, where > testing integers for equality is faster than testing strings, as > well as from reading the SQLite3 documentation about INTEGER > PRIMARY KEY --- that the SELECT tests should be faster if I am > looking up an INTEGER PRIMARY KEY value rather than TEXT PRIMARY > KEY. Is that right?
If sqlite can handle the absurd length of a Python long, you *can* do it as ints: >>> from hashlib import sha1 >>> s = "Hello world" >>> h = sha1(s) >>> h.hexdigest() '7b502c3a1f48c8609ae212cdfb639dee39673f5e' >>> int(h.hexdigest(), 16) 703993777145756967576188115661016000849227759454L That's a pretty honkin' huge int for a DB key, but you can use it. And it's pretty capped on length regardless of the underlying string's length. > If so, what sort of hashing function should I use? The "maxint" for > SQLite3 is a lot smaller than the size of even MD5 hashes. The only > thing I've thought of so far is to use MD5 or SHA-something modulo > the maxint value. (Security isn't an issue --- i.e., I'm not > worried about someone trying to create a hash collision.) You could truncate that to something like >>> int(h.hexdigest()[-8:], 16) which should give you something that would result in a 32-bit number that should fit in sqlite's int. -tkc -- https://mail.python.org/mailman/listinfo/python-list