Jupyter Scala VS hissp

Checkout almond

What about https://github.com/alexarchambault/plotly-scala and https://almond.sh/

I use Almond in JupyterLab, which has pretty solid code completion. In IntelliJ, you can create a scratch sc file and run lines of it in the Scala REPL. That's really convenient for code completion and I normally will use that when I'm testing something from a specific project.

The UI part. There's only the scala REPL. I think the closest is a scala kernel for Jupyter notebooks, check this out: https://almond.sh/

We have used https://almond.sh/ to create a Spark SQL interpreter using Jupyter Notebooks - plus a whole lot more which you can see here: https://arc.tripl.ai/tutorial

After seeing many companies writing ETL using code we decided it was too hard to manage at scale so provided this abstraction layer - which is heavily centered around expressing business logic in SQL - to standardise development (JupyterLab) and allow rapid deployments.

Hissp is a Python library that can compile a whole program into one Python expression.

If you want Python to be as customizable as Lissp, check out Hissp (and Hebigo).

Hissp is really cool for metaprogramming Python. There's also macropy, but it's harder to use.

I prefer https://github.com/gilch/hissp, where Hy has to use shims to pretend statements are expressions, Hissp just targets the expression subset in the first place. (though as you mentioned, hy has a lot of literature and support around it, where as you're going to have to find your own way around hissp)

No shortage of options, e.g. Dg, Mochi, Coconut, and Hebigo (based on Hissp[1]).

[1]: https://github.com/gilch/hissp

If you want Lisp metaprogramming plus Python ecosystem, check out Hissp

Hissp is really interesting. Read through the docs and you'll understand Python more deeply. It works well with Toolz and Pyrsistent.