On Thu, 2008-12-04 at 20:01 +0100, Дамјан Георгиевски wrote:
> > I don't think it matters. Here's a quick comparison between 2.5 and
> > 3.0 on a relatively small 17 meg file:
> >
> > C:\>c:\Python30\python -m timeit -n 1
> > "open('C:\\work\\temp\\bppd_vsub.csv', 'rb').read()"
> > 1 loops, best of 3: 36.8 sec per loop
> >
> > C:\>c:\Python25\python -m timeit -n 1
> > "open('C:\\work\\temp\\bppd_vsub.csv', 'rb').read()"
> > 1 loops, best of 3: 33 msec per loop
> >
> > That's 3 orders of magnitude slower on python3.0!
>
> Isn't this because you have the file cached in memory on the second run?
Even on different files of identical size it's ~3x slower:
$ dd if=/dev/urandom of=file1 bs=1M count=70
70+0 records in
70+0 records out
73400320 bytes (73 MB) copied, 14.8693 s, 4.9 MB/s
$ dd if=/dev/urandom of=file2 bs=1M count=70
70+0 records in
70+0 records out
73400320 bytes (73 MB) copied, 16.1581 s, 4.5 MB/s
$ python2.5 -m timeit -n 1 'open("file1", "rb").read()'
1 loops, best of 3: 5.26 sec per loop
$ python3.0 -m timeit -n 1 'open("file2", "rb").read()'
1 loops, best of 3: 14.8 sec per loop
--
http://mail.python.org/mailman/listinfo/python-list
