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Lihaoyi mostly authors scala libraries. I switched from python to scala and found many of the things that I love about scala ported to python with this library.

Case classes (pretty .toString, structural equality, .copy, and destructuring), Scala 3-esque enums, f-string interpolations before python added them, pattern matching, and _ based lambdas are the highlights for me.

The page has links to a dozen different examples, with code snippets and discussion of the motivations and potential use cases for each

Totally off topic, but I was wondering if you have looked at Coconut, a kind of ML Lite that compiles to Python? And if so, what do you think?

http://coconut-lang.org/

Are you still mainly programming in Scala? Do you see yourself programming in your current language in 5 years?

This project is great

Would love to see a new release on PyPI that works with Python > 3.4

;)

(last release seems to be "1.1b2" in 2018...)

Tail call optimization is appealing. Sometimes recursion is the cleanest implementation, but call depth is not known up front.

I’m having a hard time understanding what advantages @case has over data classes.

The main reason @case is an example macro is that data classes did not exist when this project was conceived