[Numpy-discussion] numpy's future (1.1 and beyond): which direction(s) ?

[David Cournapeau]

Hi,

	numpy 1.0.5 is on the way, and I was wondering about numpy's future. I
myself have some ideas about what could be done; has there been any
discussion behind what is on 1.1 trac's roadmap ? Some of the things I
would like to see myself:
	- a framework for plug-in architecture, that is the ability for numpy
to load/unload some libraries at runtime, plus a common api to access
the functions. Example: instead of calling directly atlas/etc..., it
would load the dll at runtime, so that other libraries can be loaded
instead (numpy itself could load different runtimes depending on the
CPU, for example: SSE vs SSE2 vs SSE3, multi-thread vs non
multi-thread). That would require the ability to build loadable
libraries (numscons, or a new numpy.distutils command).
	- a pure C core library for some common operations. For example, I
myself would really like to be able to use the fft in some C extensions.
Numpy has a fft, but I cannot access it from C (well, I could access the
python fft from C, but that would be... awkward); same for blas/lapack.
I really like the idea of a numpy "split" into a core C library reusable
by many C extensions, and python wrappers (in C, cython, ctypes,
whatever). That would be a huge work, of course, but hopefully can be
done gradually and smoothly. Only having fft + some basic blas/lapack
(dot, inv, det, etc...) and some basic functions (beta, gamma, digamma)
would be great, for example.
	- a highly optimized core library for memory copy, simple addition,
etc... basically, everything which can see huge improvements when using
MMX/SSE and co. This is somewhat linked to point 1. This would also
require more sophisticated memory allocator (aligned, etc...).

What do people think about this ? Is that a direction numpy developers
are interested in ?

cheers,

David