QOTW?

[Ganesan R]

>>>>> "Samuel" == Samuel Walters <swalters_usenet at yahoo.com> writes:

> I/O is one of our strengths, because we understand that most programs are
> not algorithmically bound, but rather I/O bound.  I/O is a big
> bottle-neck, so we should be damn good at it.  The fastest assembly
> program won't do much good if it's always waiting on the disk-drive.

Actually, Python is much slower than Perl for I/O. See the thread titled
"Python IO Performance?" in groups.google.com for a thread started by me on
this topic. I am a full time C programmer but do write occasional
Python/Perl for professional/personal use.

To answer the original question about how much percentage of time I spend
optimizing my Python programs - probably never. However I did switch back to
using Perl for my most of my text processing needs. For one program that was
intended to lookup patterns in a gzipped word list, performance of the
original python version was horribly slow. Instead of rewriting it in Perl,
I simply opened a pipe to zgrep and did post processing in python. This
turned out to be much faster - I don't remember how much faster, but I
remember waiting for the output from the pure python version while the
python+zgrep hybrid results were almost instantaneous.

Ganesan

--
Ganesan R