OT: why do people use python when it is slow?

[Chris via Digitalmars-d-learn]

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.