The best chance Julia has isn’t attracting average devs alone, but the library developers. Writing new python libraries for research purposes often requires writing C/C++ code. There’s already a number of Julia libraries focusing on interesting research topics in scientific, mathematics, and AI. Those lead to better and more useful libraries over time which can interact over time. Plus Julia Computing seems to be going towards building a successful commercial side of Julia. Personally I don’t find the software poverty thing much of an issue, outside a few core areas (database drivers, basic http, c interop, networking, text editors).
What exactly would you like Julia to be compatible with?
Python? https://github.com/JuliaPy/PyCall.jl
JS? https://github.com/SimonDanisch/JSCall.jl
C++? https://github.com/JuliaInterop/Cxx.jl
Java? https://github.com/JuliaInterop/JavaCall.jl
R? https://github.com/JuliaInterop/RCall.jl
Not all of these are fully polished, but they're all being worked on (plus there are a bunch of others that aren't being actively worked on that I haven't put here).
C/Fortran anything else that compiles to C-API supporting shared libraries is supported in built by `ccall`
JuliaLang is amazing at of FFI
...if you do anything towards ML or datascience, typescript and kotlin are the poor relatives. For most tasks 90% of the ecosystem is useless to you and you can spend more time wrangling the dependencies of a nasty nodejs package than quickly coding smth from scratch.
That "richness" is also... "garbage".