[Numpy-discussion] Proposed Roadmap Overview
Sat Feb 18 23:19:30 CST 2012
On Sat, Feb 18, 2012 at 8:38 PM, Travis Oliphant <email@example.com> wrote:
> We will need to see examples of what Mark is talking about and clarify some
> of the compiler issues. Certainly there is some risk that once code is
> written that it will be tempting to just use it. Other approaches are
> certainly worth exploring in the mean-time, but C++ has some strong
> arguments for it.
The worry as I understand it is that a C++ rewrite might make the
numpy core effectively a read-only project for anyone but Mark. Do
you have any feeling for whether that is likely?
> I thought so, but I can't find it either. We should ask Jason McCampbell of
> Enthought where the code is located. Here are the distributed eggs:
Should I email him? Happy to do that.
> From my perspective having a standalone core NumPy is still a goal. The
> primary advantages of having a NumPy library (call it NumLib for the sake of
> argument) are
> 1) Ability for projects like PyPy, IronPython, and Jython to use it more
> 2) Ability for Ruby, Perl, Node.JS, and other new languages to use the code
> for their technical computing projects.
> 3) increasing the number of users who can help make it more solid
> 4) being able to build the user-base (and corresponding performance with
> eye-balls from Intel, NVidia, AMD, Microsoft, Google, etc. looking at the
> The disadvantages I can think of:
> 1) More users also means we might risk "lowest-commond-denominator" problems
> --- i.e. trying to be too much to too many may make it not useful for
> anyone. Also, more users means more people with opinions that might be
> difficult to re-concile.
> 2) The work of doing the re-write is not small: probably at least 6
> 3) Not being able to rely on Python objects (dictionaries, lists, and tuples
> are currently used in the code-base quite a bit --- though the re-factor did
> show some examples of how to remove this usage).
> 4) Handling of "Object" arrays requires some re-design.
How would numpylib compare to libraries like eigen? How likely do you
think it would be that unrelated projects would use numpylib rather
than eigen or other numerical libraries? Do you think the choice of
C++ rather than C will influence whether other projects will take it
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