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

[bachmeier via Digitalmars-d]

On Saturday, 14 March 2015 at 09:00:11 UTC, Russel Winder wrote:

>
> If D is to compete in the financial computing arena where 
> Python and R
> currently rule, there needs to be all the libraries for doing 
> time
> series analysis, and rendering them graphically. There also 
> needs to be
> a workflow that fits the users of the domain. The market leader 
> is
> currently Jupyter (*) in the finance places I have connection 
> with.

D can gain popularity by doing what Rcpp has done, by making it 
easy to embed C++ code inside R. Rcpp is currently the most 
common dependency among all R packages. I have done the same with 
D though it's not yet in a form that others can really use it 
(https://bitbucket.org/bachmeil/dmdinline).

The best thing to happen to D was the ability to create shared 
libraries on Linux. You can add D to your existing codebase 
incrementally. That is, in my opinion, D's "killer application". 
And D has an advantage over C++. R users will write C++ because 
they have to, whereas D is a language they'll use because they 
want to.