tastyminerals

You should also try D to see that seamless C interop has always been there for many years.

It may outclass it in performance. However, all my life I've been waiting for something that runs over 10h on a single charge. I am naturally surprised that this is not something that ppl truly appreciate in a laptop. Hell, I even bought a cheap Atom laptop once just to have more battery time. So as of now, there's literally no decent competitor to M1 laptops. One must be living under a rock to buy anything but Apple and this is coming from someone who doesn't have Apple products and always hated their walled off ecosystem. I am reconsidering my life choices :)

What?! There are static languages that compile faster: Nim, D... Honestly, I used ggplotD library and it takes roughly two seconds to compile and miliseconds to show the plot.

Julia is fast but not faster and very memory hungry. If you care about squeezing every bit of performance you generally go to C++. If you too lazy for C++ you go D. Hence to me, Julia is an odd tool. Interesting but more as a language with some cool scientific libs that Python might not yet have.

Noice! Reading through the release notes leaves a feeling of D being a mature language long enough.

If you're looking for magnitutes faster scripting alternative to Python like once me, take a peek!

Rust is not a very good example here considering the amount of time the op might have spent waiting for the compiler and steep learning curve of the language...

Why don't you try D if type-and-compile is what you enjoy?

not on mobile but as a service -- Abbyy is the market leader in OCR from documents.

Julia looks more like Python than a fp language tbo and that was why I staed away. The most elegant fp code I've seen was written in Scala.

I read through Arraymancer readme and the rationale and got very mixed feelings about the project and its purpose. It's everything and nothing at the same time. NumPy like syntax and functionality, sklearn algorithms and look, deep learning too, here is and example and some screens which we borrowed from Scipy. Seriously? Sorry if that might be too judgemental but it sounds and looks amateurish. And I thought of benchmarking it against D mir... Also, the name... And this is what I feel about Nim in general, rushed and undercooked.

Thanks. So here are the points for D according to the table. Very few breaking changes because language is pretty mature. Not sure if Nim is as stable but just this one fact is enough for me personally.

D has slices, ranges and lazy evaluation which is a joy when you do data number crunching. Nim does not have them.

Also no mention of dpp in a table is surprising tbo.

D PRs take time mostly because they go through a rigorous community review. And by that I mean your PR does need to hit the quality bar. Which is only good and does not make a language a sandbox of community features like C++. See the PR for macros in D and why it didn't happen. Another reason is the lack of people of course.

Also, all good points. Appreciate that.

Thank you for the detailed answer. It clears things up.

Ok. But going back to the issue. I live in Munich and know at least two big companies who use D in production and organize meetups. I have yet to see a single company that uses Nim.

It was a developed by too few ppl from the start and by the time it became usable it was way too late