Scientific computing and parallel computing C++23/C++26

[sfp]

On Tuesday, 18 January 2022 at 22:00:42 UTC, bachmeier wrote:
> On Tuesday, 18 January 2022 at 21:22:11 UTC, H. S. Teoh wrote:
>> [...]
>
> The next release of my embedr library (which I've been able to 
> do now that my work life is finally returning to normal) will 
> make it trivial to call D functions from R. What I mean by that 
> is that you write a file of D functions and by the magic of 
> metaprogramming, you don't need to write any boilerplate at all.
>
> Example:
>
> ```
> import mir.random;
> import mir.random.variable;
>
> RVector rngexample(int n) {
> 	auto gen = Random(unpredictableSeed);
> 	auto rv = uniformVar(-10, 10); // [-10, 10]
> 	auto result = RVector(n);
> 	foreach(ii; 0..n) {
> 		result[ii] = rv(gen);
> 	}
> 	return result;
> }
> mixin(createRFunction!rngexample);
> ```
>
> The only way you can do better is if someone else writes the 
> program for you. But then it doesn't make much difference which 
> language is used.

This is all news to me. It's a shame these libraries and their 
capabilities aren't advertised my prominently.

How hard would it be to automatically wrap a D library and expose 
it to Python, MATLAB, and Julia simultaneously? Say the library 
even has a simple C-style API, or a very simple 
single-inheritance OO hierarchy with no templates.