suitability of python
Dave Angel
d at davea.name
Thu Nov 24 08:08:39 EST 2011
On 11/24/2011 07:31 AM, Rudra Banerjee wrote:
> Dear friends,
> I am a newbie in python and basically i use python for postprocessing
> like plotting, data manipulation etc.
> Based on ease of programming on python I am wondering if I can consider
> it for the main development as well. My jobs (written on fortran) runs
> for weeks and quite CPU intensive. How python works on these type of
> heavy computation?
> Any comment or reference is welcome.
>
If I take your description at face value, then I'd say that stock
CPython would be slower than Fortran. If the CPU-intensive parts had to
be rewritten in CPython, they'd be slower than the Fortran they replace,
by somewhere between 10:1 and 500:1. Further, if you've already got
those Fortran algorithms written and debugged, why rewrite them? And
finally, even for new code, you might be getting ideas for your
algorithms from journals and other resources, where the examples may
well be done in Fortran, so productivity might be best in Fortran as well.
HOWEVER, you don't have to use stock CPython, alone. It could be that
some of your Fortran algorithms are written in shared libraries, and
that you could get your CPython code to call them to do the "heavy
lifting." Or it could be that numpy, sage, or other 3rd party libraries
might be usable for your particular problems, and that speed is then
comparable to Fortran. Or it could be that one of the alternative
Python implementations might be fast enough.
Or it could even be that you're mistaken that the present code is even
CPU intensive.
Or it could be that by the time you recode the problem in Python, you
discover a more efficient algorithm, and that way gain back all the
speed you theoretically lost.
There are tools to measure things, though I'm not the one to recommend
specifics. And those probably depend on your platform as well.
The last Fortran that I wrote was over 40 years ago. I'm afraid when I
need speed, I usually use C++. But if I were starting a personal
math-intensive project now, I'd try to prototype it in Python, and only
move portions of it to Fortran or other compiled language. Only the
portions that measurably took too long. And those portions might be
rewritten in Cython, C++, or Fortran, depending on what kind of work
they actually did.
Another alternative that might make sense is to use Python as a "macro
language" to Fortran, where you call out to Python to automate some
tasks within the main program. I have no experience with doing that,
but I assume it'd be something like how MSWord can call out to VBA
routines. And it'd make the most sense when the main app is already
written, and the macro stuff is an afterthought.
I think the real point is that it doesn't have to be "all or nothing."
I suspect that the pieces you're already doing in Python are calling out
to pre-existing libraries as well. So your plotting code does some
massaging, and then calls into some plotting library, or even execs a
plotting executable.
--
DaveA
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