Using Python for programming algorithms

[sturlamolden]

On May 18, 5:46 am, "inhahe" <inh... at gmail.com> wrote:

> The numbers I heard are that Python is 10-100 times slower than C.

Only true if you use Python as if it was a dialect of Visual Basic. If
you use the right tool, like NumPy, Python can be fast enough. Also
note that Python is not slower than any other language (including C)
if the code is i/o bound. As it turns out, most code is i/o bound,
even many scientific programs.

In scientific research, CPU time is cheap and time spent programming
is expensive. Instead of optimizing code that runs too slowly, it is
often less expensive to use fancier hardware, like parallell
computers. For Python, we e.g. have mpi4py which gives us access to
MPI. It can be a good advice to write scientific software
parallelizable from the start.

I learned Pascal my first year in college. When I started programming
Matlab, I brought with me every habits of a novice Pascal programmer.
Needless to say, my programs ran excruciatingly slow. I learned C just
to write faster "mex" extensions for Matlab. But eventually, my skills
improved and I found that my Matlab programs did not need C anymore.
It took me almost 3 years to unlearn the bad habits I had acquired
while programming Pascal. It is very easy to blame the language, when
in fact it is the programmer who is not using it properly.