Re: 10 problems with Elisp, part 10

["Dr. Arne Babenhauserheide" <arne_bab@web.de>]

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Christopher Dimech <dimech@gmx.com> writes:

> It is practically impossible to teach good programming to students that
> have had a prior exposure to Python, as potential programmers they are
> mentally mutilated beyond hope of regeneration.

Having learned Scheme after learning Python, I strongly disagree — both
to your point and to your ugly portrayal of people.

You point: Python helps to understand Scheme because it provides
fundamentals to structure reasoning. To separate concerns. To test with
low overhead. To access data in common formats. To do the task you care
about instead of adhering to ceremony. Going from Python to Scheme isn’t
hard. suggest reading "The Adventures of a Pythonista in Schemeland":
http://www.phyast.pitt.edu/~micheles/scheme/

Your portrayal: this dehumanizing language has no place in a discussion.
Badmouthing people does a disservice to any point you want to make.

> In the good old days physicists repeated each other's experiments, just
> to be sure. Today they stick to Python, so that they can share each
> other's programs, bugs included.

Replace "Python" with whatever programming language they use.

If you think, Physicists do not share C++ code, or matlab code, or (yes)
Fortran-code, where did you get this notion? Did you work with them?
(I did)

Did you read code of large weather models?

Meteorologists who prove the deviations of a model down to phase shifts
before they write the first line of code (do you do that before you
write a program?) are still happy to share code. They know what they get
and what they share.
Theoretical meteorology (at least in a faculty that works with that) is
an eye-opener for how primitive software development of typical business
software often is (this is not derogatory: business software has other
main challenges, like staying maintainable in the face of constantly
changing requirements).

Physicists who write a Python tool and then add a Cython part compiled
to C to get native performance and who test this in detail against
different existing tools using multitudes of parameters and datasets
will still happily share code.

Physicists who write a Python model that binds complex atmospheric
transport Fortran code know what they do: they keep the
non-performance-critical parts in Python, because that enables them to
spend more time on the actually critical parts.

Don’t go badmouthing other people.

The disdain spread among software developers against Fortran caused me
to lose a lot of time during my PhD until I finally understood how
misguided it is.

Please don’t repeat that mistake with Python.

Best wishes,
Arne
-- 
Unpolitisch sein
heißt politisch sein,
ohne es zu merken.
draketo.de

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