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Re:The Accelerating Adoption of Julia by marmaduke on Tuesday October 20, 2020 @03:32PM (#24841461)
The subset of Python compatible with Julia's whole performance story (mostly, structs are the missing piece), yes sure.
Re:The Accelerating Adoption of Julia by DNF2 on Tuesday October 20, 2020 @04:18PM (#24841947)
You mean the type system and multiple dispatch? I guess those are fairly minor points, yes.
Re:The Accelerating Adoption of Julia by DNF2 on Tuesday October 20, 2020 @04:39PM (#24842127)
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?

Re:The Accelerating Adoption of Julia by amkkma on Tuesday October 20, 2020 @06:50PM (#24843096)
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