22 ms·

A subset of Python for one, and debugging stays awkward with gdb. Makes me think of this little pun: https://github.com/FluxML/Flux.jl/blob/master/src/utils.jl

• marmaduke 6y ago
  The subset of Python compatible with Julia's whole performance story (mostly, structs are the missing piece), yes sure.
  • DNF2 6y ago
    You mean the type system and multiple dispatch? I guess those are fairly minor points, yes.
    • DNF2 6y ago
      One performance feature I find really nice in Julia, is that you can write your own function (cost function, function to integrate, whatever) that you can pass into a solver/integrator/etc. Then it will be inlined and compiled into that external library. Does this work with numba? Are your jit-compiled functions compiled into external modules?
  • amkkma 6y ago
    Even if structs worked, they wouldn't be part of a good type system, don't work with abstract interfaces/inheritance,traits, multiple dispatch, fast union types, zero allocation immutables or any myriad of other things