https://depth-first.com/articles/2020/09/21/interactive-rust...
https://github.com/google/evcxr
The other option is to use the playground, https://play.rust-lang.org/?version=stable&mode=debug&editio...
> but then they're going to hit the large legacy of existing code and wonder why you taught them something that not related to what they're going to use.
OTOH other languages should be easier to learn by reference to a comparatively elegant language like Rust. Python, Fortran, C++ etc. have almost nothing in common but Rust could arguably be a good introductory baseline that shares features with all of these.
Maybe evcxr would give you a head start, it's a Rust-based Jupyter Kernel. Jupyter has a fairly mature ecosystem with widgets and it's easy to come up with renderers for different MIME types, so you might be able to lift some ideas or connect with other people working on similar tasks.
And the compiler messages (once you get the hang of it; and the investment in learning the syntax is so trivially worth it in the long run) are so much richer and more helpful than other languages. So it really does "feel" like a REPL or most of the way there as a REPL (and I have one of the few wikis at our work advocating for Common Lisp that I wrote a year ago, and still actively follow Clojure groups, etc.).
It's just Rust starts and runs so fast (and Cargo makes it easy and clear like Go); so that being able to re-run periodically really fast is like a REPL. Yeah there's no retained state or ability to keep a REPL running for days, etc. (though Tmux.. and nix as a repl.... more on that later), but it's reached a point where compilation is an OOM faster than before, so the loop of: read, eval, print now can include the compiler.
And you get this amazing boost where if you're operating e.g. on large data (if you're a senior engineer, like Dan Luu blogs https://danluu.com/, you're often scanning codebases or log files or other metadata to answer questions); so being able to tweak and re-run even without caching at OOM faster speeds than other languages is wonderful.
I can create complex refactoring scripts in Rust on GBs of data and constantly re-run them until it's just right.
To my knowledge you can learn the ins and outs of CL or Rust; both fairly specific-knowledge-heavy languages at first (Rust with some syntax, CL with its non-uniformity of functions). It just seems like Rust is the future. It sort of "merges" dynamic languages with REPLs and *nix (with tmux) as the REPL. Pretty exciting.
And if someone wrote a CL-like REPL with something like SLIME/SLY for debugging for Rust it'd be kind of game over. And I could see that coming in the next few years (https://github.com/google/evcxr seems cool, but perhaps the dependency on Jupyter complicates it a bit).
I hope all the work being done on improving incremental compilation[a] and developing interactive Rust REPLs like evcxr[b] makes using Rust for AI a practical reality.
[a] https://doc.rust-lang.org/edition-guide/rust-2018/the-compil...
https://github.com/jupyter/jupyter/wiki/Jupyter-kernels will give you a more detailed list