Julia doesn't have broad adoption because it's too specific, and C++/Rust are more cumbersome, also Python for data science and ML was popular before Rust or Julia even existed. Python's biggest advantage is that it's good enough for general usage while also being convenient for data science.

Julia has more adoption than many wannabe languages.

https://info.juliahub.com/case-studies

Sure, but not more adoption than Python. All the examples look math-focused; would you write a web backend or a batch script in Julia?

No, that wasn't why it was designed for in first place anyway.

Likewise I wouldn't use Python for anything besides teaching programming, or scripting OS tasks and native libraries.

Well that's the problem. Part of why Python is nice for ML stuff is because it was adopted for several other purposes too. I've never used Julia but have used niche things like Erlang, and there's always more friction that way.

Tcl