A few notes on choosing between Go and D for a quick project

[Chris via Digitalmars-d]

On Friday, 13 March 2015 at 14:34:23 UTC, Russel Winder wrote:
> On Fri, 2015-03-13 at 14:20 +0000, Chris via Digitalmars-d 
> wrote:
> […]
>
>> reluctant to learn something new. Crowd 2. we can win over, 
>> yet we have failed to communicate with them, to reach out to 
>> them. Most people I know have a look at D's homepage and say 
>> "Uh! Hm. Ah, I'll use Python." No, they are not hardcore 
>> programmers, they are engineers and scientists. But they are 
>> _users_, people who need to write software to analyze data, to 
>> create something. We should not ignore them, even if they are 
>> not (initially) interested in templates and metaprogramming. 
>> Neither was I, when I first learned D.
>
> It is not Python or R or Julia the language that people choose, 
> it is
> the superstructure built on top. So for Python, it is Pandas,
> Matplotlib, SciPy, NumPy. And the ability to use ready made C, 
> C++ and
> Fortran libraries.

Exactly, that's part of it. People don't understand that they can 
use all the C libraries with D as well. And if they do, "extern 
(C)" is too "complicated", at least more complicated than "import 
numbergrind". I'm really at loss here, I don't know how to 
communicate these things to people. Colleagues and text books 
that talk about R and Python weigh so much more than "D can 
actually interface to C without any effort".[1]

Also, sometimes I have the impression that people use any excuse 
not to use D.

[1] The problem is that all these nice Python and R 
implementations are practically useless for real world 
applications. Too slow, too cumbersome, too many dependencies. It 
has to be rewritten anyway. (I'd be happy, if they used at least 
C.)