I am not sure what will happen if I do the programing in
python the find the program doesn't deliver the desired
performance due to lack of a good compiler.
I've rarely found this to be a problem unless you're doing
CPU-intensive work. However, the usual workflow involves:
1) code it in Python
2) if it's slow, profile it and check your algorithm(s), recoding
if you're using some algorithm with a bad big-oh profile
3a) if it's still slow, try using Psyco, Shed-Skin, or their ilk
to compile your code down a bit
3b) if it's still slow, profile again and try using specialized
libraries (numpy/numeric, opengl libraries, cStringIO, etc) for
those bottleneck points
4a) if it's *still* slow, profile it *yet again* and create an
optimized C/C++ module, using that from within your Python
4b) examine your code to see if multiprocessing would help divide
up the CPU intensive tasks
I've never had to go much past step #2. I good choice of
algorithm in Python can beat the pants off a bad choice of
algorithm in C/C++.
However the first rule: profile first!
So I wanted to learn more about the projects that people are
working on using Python to get the feel of the languages
application.
I do a lot of ETL (Extract/Transform/Load) scripts, some web
development, various automation tools, a little game-development
stuff, and a few command-line apps.
-tkc
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