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.)
