vscode-nim VS Arraymancer

You may fare better hooking VSCode to nimlangserver:

https://github.com/saem/vscode-nim#nim-lanugage-server-integ...

nimlangserver is an implementation of Language Server Protocol with the goal to make nim IDE experience more mature. The main difference between nimlangserver and the existing nimlsp is that nimlangserver runs nimsuggest in a separate process and that nimlangserver is using a newly introduced version of nimsuggest v3(see bellow). nimlangserver is currently integrated in VScode via vscode-nim and in Emacs via lsp-mode but adding integraion with other editors should be trivial.

admittedly the editor support is far away from perfect, but that particular issue just sounds like https://github.com/saem/vscode-nim/issues/80

To all those wondering about IDE support , the actively maintained VSCode extension is :

https://github.com/saem/vscode-nim

The default extension suggested by VSCode which have over 43k downloads in un-maintained for Eons and it won't work.

Here is the link : https://marketplace.visualstudio.com/items?itemName=nimsaem....

@dom96 can you pin this somewhere on the forum or website ?

UPDATE: improved highlighting rules you would get this code highligting more details https://github.com/saem/vscode-nim/issues/49

It is a small DSL written using macros at https://github.com/mratsim/Arraymancer/blob/master/src/array....

Nim has pretty great meta-programming capabilities and arraymancer employs some cool features like emitting cuda-kernels on the fly using standard templates depending on backend !

Nim has also a powerful deep learning library called Arraymancer. It's selling point is that you don't have to rewrite your code from research to production. It's used in various machine learning projects, but one recent one that caught my eye was https://github.com/amkrajewski/nimCSO "Composition Space Optimization"

https://github.com/mratsim/Arraymancer

- https://github.com/mratsim/Arraymancer/blob/master/src/array...

It's worth noting that nim async/await transformation is fully implemented as a library in macros.

https://github.com/mratsim/Arraymancer 11. « Premature optimisation is the root of all evil », Donald Knuth, The art of computer Programming It would be quite useful that someone writes one with examples for all these recommendations and more ...

In particular for deep learning as bobsyourunkl already mentioned there is arraymancer on the one hand and also flambeau on the other. The latter is a Nim wrapper around libtorch (i.e. the PyTorch C++ backend). It is missing things (to be wrapped by adding a few lines) and has some rough edges, but if one needs to get stuff done, it's possible.

how are u compiling (optimization, custom compilation flags etc.?) In my case https://github.com/mratsim/Arraymancer big project compile under your 4.2s so or you have like 10k+ lines of codes with macros or you just pass some debug flags to compiler :D

We have both raw wrappers for BLAS:

https://github.com/andreaferretti/nimblas

as well as LAPACK:

https://github.com/andreaferretti/nimlapack

For an example, consider calling the least squares routine `dgelsd` in arraymancer:

https://github.com/mratsim/Arraymancer/blob/master/src/array...

wrapped up in a nicer user facing API.

Feel free to hop onto matrix, if you have more questions!