On 2/14/10 8:06 PM, Nathaniel Smith wrote:
> On Sun, Feb 14, 2010 at 12:14 AM, Laurent Gautier<lgaut...@gmail.com>  wrote:
>>> Can you elaborate on what cool new features we'll see as a result of
>>> this?
>>
>> By exporting the buffer protocol, all Python tools that make use of (so
>> obviously numpy among them) will be able to access efficiently the data in R
>> vectors/arrays.
>>
>> In other terms, that means that C-level code can be implemented to do
>> perform operation on either array.array, numpy.ndarray,
>> rpy2.rinterface.SexpVector (and by inheritance rpy2.robjects.IntVector,
>> rpy2.robjects.FloatVector, ...). For example, python-opencl is able to
>> create memory buffers on the (graphical) device from numpy arrays, or from
>> any other object implementing the buffer protocol.
>>
>> This means being able to inter-exchange array, numpy, rpy2, or anything else
>> implementing the buffer protocol without having formal dependencies between
>> packages.
> [...]
>> Also, the memory views (new in Python 3) provide an API to create
>> vector/arrays that are "views" on an underlying larger object without
>> copying them.
>
> Ah, okay, so the practical advantage is that there are non-numpy
> consumers of the buffer interface starting to pop up, so the advantage
> is that rpy2 will interoperate with them too, without having to create
> a numpy array in between? That makes sense, and is good to know;
> thanks.

Yes... or in a sense that's the numpy interface that is being moved to 
core Python, becoming the 'linga franca' for numerical structures.

I read some more and the new buffers may still have limited 
capabilities; memoryviews (Python 3, backported to Python 2.7) is touted 
as THE thing.


> -- Nathaniel


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