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A comment on R Passes SAS, but Python Leaves Them Both Behind. Parent comment

Re:R Passes SAS, but Python Leaves Them Both Behind by fnord123 on Monday March 06, 2017 @07:26AM (#13802228)
Why? The only current benefit of Julia afaict is the tracing jit. If you run the tracing jit on web assembly then it's giving up most of its performance benefits. And Python could be built on web assembly as well.

But who knows. Weird things seem to become popular despite all the negative points.

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Re:R Passes SAS, but Python Leaves Them Both Behind by whyrt12 on Monday March 06, 2017 @10:48AM (#13803409)
It does not have a tracing JIT, and its speed is by far not the only benefit. See link below

It can precompile very fast code before runtime.

Python will require an interpreter and or hefty runtime.

https://discourse.julialang.org/t/julia-motivation-why-weren...

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Re:R Passes SAS, but Python Leaves Them Both Behind by fnord123 on Monday March 06, 2017 @11:36AM (#13803758)
Forgive me, it's not a tracing JIT but just LLVM's JIT.

Precompiling in Julia is extremely not-straight-forward. You would think you just use --compile and it would work; but it doesn't at all.

Also, at ~850kb, Python's runtime is not that hefty. It's intended to be embedded and while it's quite a bit larger than lua's 200kb, but smaller than libjulia's 16mb.

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Re:R Passes SAS, but Python Leaves Them Both Behind by statsmatscats on Monday March 06, 2017 @12:17PM (#13804155)
Right, It can currently precompile to some extent, but full source-to-binary-blob-compilation is on the roadmap. See here: http://juliacomputing.com/blog/2016/02/09/static-julia.html

Julia's runtime includes its compiler and full huge standard lib, but of which are eventually going to be split off, IIUC.

The former because of static compilation potential and the latter into modules that can be included piecemeal.

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