It is great that you are looking into this !! We are currently running on a fork of numpy because we really need these performance improvements .

I noticed that, as suggested, you took from the pull request I posted a while ago for the
PyObject_GetAttrString
PyObject_GetBuffer

issues.

( https://github.com/raulcota/numpy )

A couple of comments on that,

- Seems like you did not grab the latest revisions of that code that I posted that fixes the style of the comments and 'attempts' to fix an issue reported about Python 3 . I say 'attempts' because I thought it was fixed but I someone mentioned this was not correct.

- There was also some feedback from Nathaniel about not liking the macros and siding for inline functions. I have not gotten around to it, but it would be nice if you jump on that boat.

On the has lookup table, haven't looked at the implementation but the speed up is remarkable.

Cheers !

Raul

On 30/04/2013 8:26 PM, Arink Verma wrote:

Hi all!
I have written my application[1] for Performance parity between numpy arrays and Python scalars[2]. It would be a great help if you view it. Does it look achievable and deliverable according to the project.

[1] http://www.google-melange.com/gsoc/proposal/review/google/gsoc2013/arinkverma/40001#

[2] http://projects.scipy.org/scipy/wiki/SummerofCodeIdeas

--
Arink
Computer Science and Engineering
Indian Institute of Technology Ropar
www.arinkverma.in
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