On Wednesday, 14 October 2015 at 18:17:29 UTC, Russel Winder
wrote:
The thing about Python is NumPy, SciPy, Pandas, Matplotlib,
IPython, Jupyter, GNU Radio. The data science, bioinformatics,
quant, signal provessing, etc. people do not give a sh!t which
language they used, what they want is to get their results as
fast as possible. Most of them do not write programs that are
to last, they are effectively throw away programs. This leads
them to Python (or R) and they are not really interested in
learning anything else.
Scary, but I agree with you again. In science this is exactly
what usually happens. Throw away programs, a list here, a loop
there, clumsy, inefficient code. And that's fine, in a way that's
what scripting is for. The problems start to kick in when the
same guys get the idea to go public and write a program that
everyone can use. Then you have a mess of slow code
(undocumented) in a slow language. This is why I always say "Use
C, C++ or D from the very beginning" or at least document your
code in a way that it can easily be rewritten in D or C. But
well, you know, results, papers, conferences ... This is why many
innovations live in an eternal Matlab or Python limbo.
