[Python-ideas] [RFC] draft PEP: Dedicated infix operators for matrix multiplication and matrix power

[Steven D'Aprano]

On Sun, Mar 23, 2014 at 11:40:10AM +0100, Sturla Molden wrote:
> On 15/03/14 01:09, Antoine Pitrou wrote:
> 
> >Really? That should be up to the third-party library implementing the @
> >operator for its types, not to the language itself: Python _suggests_
> >an use case for @, it doesn't mandate it (especially as there's no
> >appropriate data type in the stdlib).
> 
> array.array is an appropriate type for supporting @ for matrix 
> multiplication.

No it isn't. The PEP even discusses it:


    [quote]
    array objects cannot represent multidimensional data at all, 
    which makes ``__matmul__`` much less useful.  Second, 
    providing a quality implementation of matrix multiplication 
    is highly non-trivial.  Naive nested loop implementations 
    are very slow and providing one in CPython would just create
    a trap for users.  But the alternative -- providing a modern,
    competitive matrix multiply -- would require that CPython link
    to a BLAS library, which brings a set of new complications.  
    In particular, several popular BLAS libraries (including the
    one that ships by default on OS X) currently break the use of 
    ``multiprocessing`` [#blas-fork]_.  And finally, we'd have to
    add quite a bit beyond ``__matmul__`` before ``memoryview``
    or  ``array.array`` would be useful for numeric work -- like
    elementwise versions of the other arithmetic operators, just
    to start.
    [end quote]


I don't think we should be looking for additional use-cases for @. 
Either the PEP stands on its own, and @ is approved for matrix 
multiplication (and possibly @@ for exponentiation), or it isn't. If the 
PEP is accepted -- and I think it should be -- then people will invent 
new uses for @. Or they won't. Either way, it doesn't matter.


-- 
Steven