In article <[EMAIL PROTECTED]>,
<[EMAIL PROTECTED]> wrote:
>Bulba wrote:
>>OK, so what projects and why would you consider
>>Python:
>>1. "clearly unsuitable"
>
>Large-scale scientific computing projects, such as numerical weather
>prediction, where performance is critical. Python could be used as the
>"glue" but not the "guts", where Fortran 95 and C++ are more
>appropriate. In my tests, some posted here, there has been a
.
.
.
I feel like growling that it's clearly a mistake for large-scale
scientific computing projects not to leverage dynamic languages,
at least in part. Yes, I've seen projects that would have been
disasters if done entirely in Python. I've also seen many, many
large-scale scientific projects that soaked up far more resources
than they should have because they limited themselves to C++ or
Fortran.
I argue that it's a false opposition to categorize projects in
terms of use of single languages. Many projects are MUCH better
off with a mix of Python and Fortran, say (and probably SQL and
JavaScript and ...), and it's pernicious to accomodate the
managerial conceit that One Language will suffice.
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