[Numpy-discussion] Proposed Roadmap Overview
Sat Feb 18 10:32:07 CST 2012
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.
(on a mobile)
On Feb 18, 2012, at 3:46 AM, Ralf Gommers <email@example.com> wrote:
> On Thu, Feb 16, 2012 at 11:39 PM, Travis Oliphant <firstname.lastname@example.org> 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?
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