Numpy and Common Lisp?

[Robert Goldman]

Hi, Daniel --

I was looking for a system that I could use to do some numerical computations I now do in Python in CL instead.  That involves a relatively large function library (or perhaps more accurately, the developers of numpy have a better idea what functions are likely to be needed than do I), and the ability to do vectorized operations.

I asked for a CFFI binding because I found a number of stabs at something similar in CL, but none looked promising for use in the short term.

I'm not sure what you mean by "a custom kernel," I'm afraid.

Schedule was "as soon as possible," in the sense of "if it's there I will start using it right away."

I guess the trait valuation is that I would like something that I could use instead of numpy, so quite portable (although if it only worked in SBCL, that would be fine), implementation effort: essentially none (I want to use a capable linear algebra library, not write one).

Best,
R


On 11 Apr 2023, at 23:18, Daniel Herring wrote:

> Hi Robert,
>
> The answer to your original question appears to be no, so the conversation turned to brainstorming solutions.  However your question did not provide a clear scope and purpose or measure of fitness for such a development.
>
> Answers to the following questions may help focus this conversation.
>
> Why did you ask for the CFFI binding?
>
> Do you want access to a bigger function library, better numeric performance, or something else?
>
> Why would you prefer CFFI bindings to numpy over CFFI bindings to a custom kernel?
>
> What schedule are you hoping for?
>
> How would you value traits such as portability, performance, implementation effort, user effort, and schedule?
>
> -- Daniel