it is intentional. scala maintainers want to keep the language evolving faster than python/java. if you look at scala3/dotty, it actually is a very different language than scala2

Scala’s type system doesn’t map perfectly to that of the JVM, so they had to bend the latter to implement scala. That’s similar to how C++ compilers bend the rules to confirm with C linkers (https://en.wikipedia.org/wiki/Name_mangling#C++), but much more complex because of the richer type system of the JVM.

Scala developers aren’t willing to freeze that mapping, partly because they found out better ways to do such mappings, and partly because they keep changing the language, changing what was the best way to do that mapping.

I think it’s easier for interpreted languages to keep their internals compatible. They are willing to give up some speed for convenience, so even if they think “I wish we had done that differently”, the pressure to change it isn’t that high.

They also keep more metadata around. In some cases, that enables them to discover “this is using the old way to do Foo”, and fix that up to use the new way.

but scala's cousin kotlin doesn't seem to suffer from this a lot... kotlin library-packages don't have kotlin-version to their download link... maybe I'm missing something?

Python 3.9 was released on October 5, 2020, but TensorFlow still doesn't support it. But that's an aberration and most of the time and for most packages minor Python releases doesn't break them.