On Fri, Feb 17, 2012 at 8:01 AM, David Cournapeau <[email protected]>wrote:
> Hi Travis, > > On Thu, Feb 16, 2012 at 10:39 PM, Travis Oliphant <[email protected]> > 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 > > * re-factoring of code so that it can compile with a C++ compiler > and be minimally dependent on Python data-structures. > > This is a pretty exciting list of features. What is the rationale for > code being compiled as C++ ? IMO, it will be difficult to do so > without preventing useful C constructs, and without removing some of > the existing features (like our use of C99 complex). The subset that > is both C and C++ compatible is quite constraining. > > I'm in favor of this myself, C++ would allow a lot code cleanup and make it easier to provide an extensible base, I think it would be a natural fit with numpy. Of course, some C++ projects become tangled messes of inheritance, but I'd be very interested in seeing what a good C++ designer like Mark, intimately familiar with the numpy code base, could do. This opportunity might not come by again anytime soon and I think we should grab onto it. The initial step would be a release whose code that would compile in both C/C++, which mostly comes down to removing C++ keywords like 'new'. I did suggest running it by you for build issues, so please raise any you can think of. Note that MatPlotLib is in C++, so I don't think the problems are insurmountable. And choosing a set of compilers to support is something that will need to be done. Chuck
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