Scientific computing using D

[Ahmat]

On Tuesday, 17 March 2020 at 18:16:17 UTC, bachmeier wrote:
> On Tuesday, 17 March 2020 at 00:48:24 UTC, ahmat wrote:
>> Hi everyone,
>> I use mainly Python for scientific computing and I want to 
>> switch to D but I can't find good libraries as replacement for 
>> pandas, matplotlib, scipy, ...
>> Are there plans to make D better in this area?
>
> Do you mean writing D libraries that do these things? Probably 
> not. That would take a lot of resources and would duplicate 
> work already done.
>
> I've done a fair amount of this type of work myself, and IMO D 
> is great if you don't mind wrapping C libraries like GSL. 
> That's really all Python did in the beginning - it was just a 
> glue language. I don't find it all that time consuming due to 
> D's great interoperability with other languages, and I'm a lot 
> more productive in D than in those other languages. For me, the 
> cost-benefit analysis works out in favor of D.
>
> If you want something polished, something that "just works", 
> you're better off using Julia. If you want to write libraries 
> to make D as convenient to use as Python, it will be welcome. 
> Don't hold your breath waiting for others to deliver something. 
> I'd do it if I had the time...

Python just work and that’s what a beginner need from a language. 
You can just run jupyter notebook, import pandas and load a csv 
dataset to a pandas DataFrame. But if you want to write high 
performance code or use advanced things it’s better to use 
another language like C++ and maybe D.
D is great for wrapping C libraries but many python libraries are 
binding of C++. How is the status of interoperability between D 
and C++ ? I am available to help if someone is interested in 
writing some useful libraries in D.

I think Julia is fast and one doesn’t need numpy and others 
libraries to write high performance. It’s gaining users in 
Academia and research even in deep learning.