Speed with Python

[Ken Seehof]

In situations where I want speed, I prototype in python, then write extensions.
This is a convenient approach since the test suite you write for the prototype
can be used on the extension unchanged.

I do all GUI work in python (wxPython) and I have not noticed a difference in
speed as compared to C++, probably because most time is spent in library calls
anyway.  I suspect you will have similar results with database work, though I
haven't done high volume database work in python myself.  The benchmarks that
show 10-20 fold differences are doing number crunching or equivalent low-level
processing.  In real world situations, where your inner loop is calling into
libraries, the difference is negligable in my experience.

Jeff Massung wrote:

> Many threads with this kind of name have popped up, comparing the speed of
> Python to C, Java, etc. and trying to determine how fast some of the
> algorithms in Python are.
>
> My question however, is how many of you who are Python gurus/junkies (no
> offence, I myself am a C and Forth junkie) :) use Python for speed intensive
> processing (not graphics, but databases and such)? Does efficiency of
> developement outweight the eventual speed of use?
>
> Cheers,
> Jeff

--
Ken Seehof
kens at sightreader.com
starship.python.net/crew/seehof
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