Anyone have thoughts on nim vs rust for data centric (Scala like) applications
But the Rust community is so much bigger, pretty much every question I had was answered after a quick Google search.
Nim does have a syntax I prefer more, but overall I find I’m quite a bit more productive with Rust.
That said, nothing beats “already been answered” and the Rust community is much bigger.
Do you use Scala as a better Java? If so, Nim may be what you want.
Do you use Scala for its incredible type system? Rust may be what you want.
Do you use Scala for its functional tendencies? Rust may be what you want.
As an aside, I've found that once you get over the Rust learning curve, writing 'correct' programs is easier in Rust than any other language I've used. And for data centric applications, being 'correct' is extra important.
Some of the rust problems mentioned (like clone for arrays) have been fixed. Others, like static generics, have not been (AFAIK).
(a) you need performance for applications outside of numpy / pandas & you want to avoid writing a C extension to do so (nim is also actually a good choice for python extensions via nimpy - if you are still using python as the main language of your project/system)
(a2) you want good concurrency (some would say python's async/await is good - but it feels too little too late to me) & you at least want the option of parallelism (like this article takes advantage of)
(b) you want / need the powerful macro system for dsls / custom (compile-type-checkable) language extensions.
There is a good future for nim in scientific computing (frankly, there is a good present) - but for it to be better, people need to be willing to forgo some of the ecosystem (when possible) and to help build that future.
https://narimiran.github.io/2018/05/10/python-numpy-nim.html
I think if this were on the order of minutes/hours you would see numpy outperform.