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A comment on Why I Still Use Python for High Performance Scientific Computing. Parent comment

Re:Why I Still Use Python for High Performance Scientific Co... by anon4 on Wednesday December 02, 2015 @05:15AM (#10662054)
Let me just add Numba to the list. It compiles numpy-using code to native via llvm and can remove temporary arrays in the process.

I tried a very simple toy program the other day and while I had to write some things slightly un-pythonically (it can't deal with syntax like a[:] = b+c yet), it performed practically as good as hand-written C code.

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Re:Why I Still Use Python for High Performance Scientific Co... by pbowyer on Wednesday December 02, 2015 @05:36AM (#10662143)
If your code falls within the subset it supports :) I've not yet got it to run our code in nopython mode - I think the latest problem is a function expecting a function as an argument, but the error messages aren't helpful or enlightening, even with DEBUG turned on.
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Re:Why I Still Use Python for High Performance Scientific Co... by Nrpf on Wednesday December 02, 2015 @02:19PM (#10665157)
The dev team is pretty responsive and prioritize adding features based on bug reports like this. Can you open an issue?

https://github.com/numba/numba

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