Matthew Brett wrote:
>
> I'm +3 for the plugin idea - it would have huge benefits for
> installation and automatic optimization. What needs to be done? Who
> could do it?
The main issues are portability, and reliability I think. All OS
supported by numpy have more or less a dynamic library loading support
(that's how python itself works, after all, unless you compile
everything statically), but the devil is in the details. In particular:
- I am not sure whether plugin unloading is supported by all OS (Mac
os X posix api does not enable unloading, for example, you have to use a
specific API which I do not know anything about). Maybe we do not need
it, I don't know; unloading sounds really difficult to support reliably
anyway (how to make sure numpy won't use the functions of the plugins ?)
- build issues: it is really the same thing than ctypes at the build
level, I think
- an api so that it can be used throughout numpy. there should be a
clear interface for the plugins, which does not sound trivial either.
That's the most difficult part in my mind (well, maybe not difficult,
but time-consuming at least).
That's one of the reason why I was thinking about a gradual move of most
"core functionalities of the core" toward a separate C library, with a
simple and crystal clear interface, without any reference to any python
API, just plain C with plain pointers. We could then force this core,
"pure" C library to be used only through dereferencing of an additional
pointer, thus enabling dynamic change of the actual functions (at least
when numpy is started).
I have to say I really like the idea of more explicit separation between
the actual computation code and the python wrapping; it can only help if
we decide to write some of the wrappers in Cython/ctypes/whatever
instead of pure C as today. It has many advantages in terms of
reliability, maintainability and performance (testing performance would
be much easier I think, since it could be done in pure C).
cheers,
David
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