Yes.  Basically, one NEP per feature.  Some of them might be merged.  The NEP will be an outline and overview and then fleshed out as the code is developed in a branch.   Some of the NEPs will be more detailed than others a first of course.

I just wanted to provide a preview about the kind of things I see needed in the code.   The details will emerge in the coming weeks and months.

Thanks,

Travis  

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Travis Oliphant
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On Feb 18, 2012, at 3:46 AM, Ralf Gommers <ralf.gommers@googlemail.com> wrote:



On Thu, Feb 16, 2012 at 11:39 PM, Travis Oliphant <travis@continuum.io> wrote:
Mark Wiebe and I have been discussing off and on (as well as talking with Charles) a good way forward to balance two competing desires:

       * addition of new features that are needed in NumPy
       * improving the code-base generally and moving towards a more maintainable NumPy

I know there are load voices for just focusing on the second of these and avoiding the first until we have finished that.  I recognize the need to improve the code base, but I will also be pushing for improvements to the feature-set and user experience in the process.

As a result, I am proposing a rough outline for releases over the next year:

       * NumPy 1.7 to come out as soon as the serious bugs can be eliminated.  Bryan, Francesc, Mark, and I are able to help triage some of those.

       * NumPy 1.8 to come out in July which will have as many ABI-compatible feature enhancements as we can add while improving test coverage and code cleanup.   I will post to this list more details of what we plan to address with it later.    Included for possible inclusion are:
       * resolving the NA/missing-data issues
       * finishing group-by
       * incorporating the start of label arrays
       * incorporating a meta-object
       * a few new dtypes (variable-length string, varialbe-length unicode and an enum type)
       * adding ufunc support for flexible dtypes and possibly structured arrays
       * allowing generalized ufuncs to work on more kinds of arrays besides just contiguous
       * improving the ability for NumPy to receive JIT-generated function pointers for ufuncs and other calculation opportunities
       * adding "filters" to Input and Output
       * simple computed fields for dtypes
       * accepting a Data-Type specification as a class or JSON file
       * work towards improving the dtype-addition mechanism

For some of these things it's not entirely (or at all, what's a meta-object?) clear to me what they mean or how they would work. How do you plan to go about working on these features? One NEP per feature?

Ralf
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