hissp VS hy

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.

Not exactly the same (doesn't embed into the source like this did), but I believe Hylang[0] is the best Lisp package available for modern Python.

[0] https://github.com/hylang/hy

Isn't that a bit what hy (https://hylang.org/) tries to do ? AIUI it is a lisp interacting directly with the AST of Python, allowing seamless interop: Python modules can be used from hy and vice versa, everything is transparent.

I’ve been keeping loose tabs on this and Hy[1] for a while, but I’ve had some trouble figuring out the major differences between them and the use-cases for either. Would love to see an in-depth comparison in the form of a blog post sometime (though maybe the answer here is to do the research and write one up myself).

1: https://hylang.org

“Python is for scientists. Lisp is for engineers.”

Then what does that make Hy language?

https://hylang.org/

Re Languages with lots of example code and LLM’s

With translators or things like Hy lang, one could get the LLM’s to solve your problem in Python before converting it to another form. Then, you just need a translator. If lacking one, it’s easy to translate by hand.

The practicality of this concept will probably vary by use case. My experiments had GPT doing sketching, implementations, boilerplate, and even porting Python to Rust. A legally-clear LLM trained on multiple languages could probably be fine-tuned to do Python to LISP conversions. If not, Hy might be a stepping stone, too.

You could say so: I've been maintaining the compiler since 2016 ;). Infinitesimal Quest 2 + ε (SQ) exists more to advance Hy than for its own sake.

If you are using Python - you might find Hylang (https://hylang.org) interesting.