* For a full comparison of features D vs Nim see [0], or a more succint selection of items by Nim's creator [1]; these also contains some remarks about metaprogramming and C/C++ interoperability.
* syntax-wise you could also argue that is a step forward: it embraces Python syntax and it would be easy to read and understand for all Python devs.
* Nim does have a "faster NumPy" by the same author of the article: [2]
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.
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.
* syntax-wise you could also argue that is a step forward: it embraces Python syntax and it would be easy to read and understand for all Python devs.
* Nim does have a "faster NumPy" by the same author of the article: [2]
[0]: https://github.com/timotheecour/D_vs_nim [1]: https://forum.nim-lang.org/t/1779#11098 [2]: https://mratsim.github.io/Arraymancer/index.html