JavaCall.jl

> I don't really see how new languages that are not compatible can be competitive. 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).

Even though there parent misspoke here, there's https://github.com/aviks/JavaCall.jl for interfacing with the JVM, though of course that's more the reverse.

Static compilation is not too far away: https://github.com/JuliaLang/julia/pull/8656 https://github.com/JuliaLang/julia/pull/8745 Being tied to LLVM is real, but we do have JavaCall.jl to call Java code. https://github.com/aviks/JavaCall.jl

Sorry for self-reply, but ran out of edit time: a very valid concern about Julia is the lack of packages because it is new - a catch-22 situation that all new languages. This has been recognized by developers and Julia has now got some great inter-language interop packages and functionality, allowing it to harness a world of packages in other languages. * Very efficient interaction with C and Fortran libraries is a core Julia feature, with the ability to pass arrays and structs directly between C and Julia. Calling C: http://docs.julialang.org/en/latest/manual/calling-c-and-for... * Python libraries can be used through PyCall.jl, which is used most famously to call matplotlib (PyPlot.jl) but also other libraries like pandas (Pandas.jl). PyCall.jl: https://github.com/stevengj/PyCall.jl PyPlot.jl: https://github.com/stevengj/PyPlot.jl Panda