nimib VS karax

Jupyter notebook is indeed very important. It mainly provides data scientists with two things: a literate programming environment (mixing text, code and outputs) and a way to hold state of data in memory (so that you can perform computation interactively).

As a different take to literate programming we have created a library and an ecosystem around it: https://github.com/pietroppeter/nimib

For holding state a Nim repl (which is on the roadmap as secondary priority after completing incremental compilation) is definitely an option.

Another option could be to create a library framework for caching (or be able to serialize and deserialize quickly) large data and objects. One way to see it, could be to build something similar to streamlit cache (streamlit indeed provides great interactivity)

As a reminder, at Nim Conf back in October 2022 Andreas presented Nim 2.0 in this video https://www.youtube.com/watch?v=aDi50K_Id_k&list=PLxLdEZg8DR...

Hearing again I cannot chuckle when Araq says: Nim v1 is good at everything, Nim v2 is supposed to be better at everything.

Back then it was supposed to come out in 2022 and indeed a RC1 came out in Dec. In the blogpost for RC1 you find the desciption of all new features: https://nim-lang.org/blog/2022/12/21/version-20-rc.html

This longer time is because extra care is being taken into having a smooth transitions (for example important libraries have been tested to work on nim v2, e.g. we made sure nimib was working with v2 in early Feb: https://github.com/pietroppeter/nimib/releases/tag/v0.3.6)

https://github.com/pietroppeter/nimib

Based on that and using a book theme, scinim getting started documentation is being built, e.g.:

The frontend uses Karax, which is my favorite frontend/SPA library. It is an absolute joy to use, even if it's a bit rough around the edges.

https://github.com/karaxnim/karax

I have used Nim for personal projects for 6 years now and it continues to surprise me on how well versed it is for many problem domains. I am fond of it's SPA framework, karax https://github.com/karaxnim/karax for which I wrote a translation utility https://github.com/nim-lang-cn/html2karax Latest Nimv2 release candidate has improved in the ergonomics and syntax that affect compilation to js, so I was able to cleanup my webapp's code to be less verbose. On GPU programming there has been a few projects that touch GPU programming, most notably https://github.com/treeform/shady

And it's present not only in Python but in other languages as well. Check for example https://github.com/karaxnim/karax - I don't know why people would want to hide all of their HTML in Python/whatever language. Then limit their ability to script and style it in one way or another.

> the real killer feature to me is the javascript target

Agree, this is amazing because you can share code and data structures between front and backend (for example: https://github.com/karaxnim/karax).

Also, it's really nice having high level stuff like metaprogramming and static typing spanning both targets. Things like reading a spec file and generating statically checked APIs for server/client is straightforward, which opens up a lot of possibilities.

E.g. Nim focuses on enabling what it calls "single page web apps": https://github.com/karaxnim/karax.

Karax [1] being Nim's SPA framework that also supports server side rendering.

[1]: https://github.com/karaxnim/karax

I recommend you to take a look at Karax. It's a front-end framework for Nim that can compile to regular JavaScript. If you want to know how to use it with a webserver, Joker is a good example. With the Joker config, all of the compiled .js files land in /public/views, where you can take a look at them. But keep in mind that the JS that Nim produces is often rather cumbersome and hundreds of lines long, even if it's just a simple program.