>> some more people are looking for a mnemonic-language which should
>> optimized cross-compile to something with multiplatform-capability like
>> Java. Please let me know, if I am entirely wrong.
>
> I'm not really sure what you are asking. Many people find Python to be
> useful and enjoyable for a wide variety of personal and professional
> programming. But if you are happy with Basic and Cobol and they meet
> your needs then there is no need to "waste your time" learning anything
> else, I suppose.
I want to support Kent in this. We're not language bigots. (In fact, I'm
not really much of a Python programmer at the moment. *grin*)
I have no idea what a mnemonic language should be: perhaps you're talking
about domain-specific languages in the sense discussed in:
http://www.ddj.com/184405575
In which case, one argument for learning Python or any other general
purpose language is to know the necessary tools to write the
domain-specific language you want. That is, the point of a general
purpose language is to "bootstrap": to give us enough tools to build our
way up to the domain.
If someone's already done that work, then yes, of course, use the
domain-specific language. If I'm doing some kind of simple text
processing, then Perl's probably a good choice, because that language has
a lot of built-in support for text munging. If I need to do something
with database management, I'd be silly if I didn't take a close look at an
SQL implementation first.
But if I'm writing a simulator for elevator systems, I might be in for
some work. It's unlikely that someone has written a domain-specific
language for ascending platforms, and I'm probably going to have to
bootstrap my way up from a general purpose language (like Python or Perl
or Ruby or Java or Scheme or ...) so that I can eventually talk about the
problem in the natural terms of my domain.
And if a language helps me claw up that much more quickly, then that's a
very good reason for me to learn that new language. That's the claim of
high-level, general purpose languages: we don't learn them just for their
own sake, but because they help us build the tools we need to get to the
real interesting problems.
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