How Can I Increase the Speed of a Large Number of Date Conversions

[vdicarlo]

I am a programming amateur and a Python newbie who needs to convert
about 100,000,000 strings of the form "1999-12-30" into ordinal dates
for sorting, comparison, and calculations. Though my script does a ton
of heavy calculational lifting (for which numpy and psyco are a
blessing) besides converting dates, it still seems to like to linger
in the datetime and time libraries.  (Maybe there's a hot module in
there with a cute little function and an impressive set of
attributes.)

Anyway, others in this group have said that the date and time
libraries are a little on the slow side but, even if that's true, I'm
thinking that the best code I could come up with to do the conversion
looks so clunky that I'm probably running around the block three times
just to go next door. Maybe someone can suggest a faster, and perhaps
simpler, way.

Here's my code, in which I've used a sample date string instead of its
variable name for the sake of clarity. Please don't laugh loud enough
for me to hear you in Davis, California.

dateTuple = time.strptime("2005-12-19", '%Y-%m-%d')
            dateTuple = dateTuple[:3]
            date = datetime.date(dateTuple[0], dateTuple[1],
dateTuple[2])
            ratingDateOrd = date.toordinal()

P.S. Why is an amateur newbie trying to convert 100,000,000 date
strings into ordinal dates? To win try to win a million dollars, of
course! In case you haven't seen it, the contest is at www.netflixprize.com.
There are currently only about 23,648 contestants on 19,164 teams from
151 different countries competing, so I figure my chances are pretty
good. ;-)