On Thu, Jul 31, 2008 at 5:36 AM, Andrew Dalke <[EMAIL PROTECTED]> wrote: > > The user base for numpy might be .. 10,000 people? 100,000 people? > Let's go with the latter, and assume that with command-line scripts, > CGI scripts, and the other programs that people write in order to > help do research means that numpy is started on average 10 times a day. > > 100,000 people * 10 times / day * 0.1 seconds per startup > = almost 28 people-hours spent each day waiting for numpy to start. > > I'm willing to spend a few days to achieve that. > > > Perhaps there's fewer people than I'm estimating. OTOH, perhaps > there are more imports of numpy per day. An order of magnitude less > time is still a couple of hours each day as the world waits to import > all of the numpy libraries. > > If on average people import numpy 10 times a day and it could be made > 0.1 seconds faster then that's 1 second per person per day. If it > takes on average 5 minutes to learn to import the module directly and > the onus is all on numpy, then after 1 year of use the efficiency has > made up for it, and the benefits continue to grow. >
Just think of the savings that could be achieved if all 2.1 million Walmart employees were outfitted with colostomy bags. 0.5 hours / day for bathroom breaks * 2,100,000 employees * 365 days/year * $7/hour = $2,682,750,000/year Granted, I'm probably not the first to run these numbers. -- Nathan Bell [EMAIL PROTECTED] http://graphics.cs.uiuc.edu/~wnbell/ _______________________________________________ Numpy-discussion mailing list Numpy-discussion@scipy.org http://projects.scipy.org/mailman/listinfo/numpy-discussion
