dsdale24 at gmail
Sep 13, 2009, 9:27 AM
Post #6 of 7
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Hi Paul,
On Sun, Sep 13, 2009 at 10:54 AM, Paul Moore <p.f.moore [at] gmail> wrote:
> 2009/9/13 Darren Dale <dsdale24 [at] gmail>:
>>> If Phillip doesn't respond here, you may want to ask him directly.
>>> My impression is that it is deferred because nobody is pursuing it
>>> actively (including Phillip Eby). It's common for a PEP to be in that
>>> state for several years, "deferred" then is an indication that readers
>>> shouldn't expect a resolution in short term.
>>
>> That is why I asked, I wondered if it is being actively considered and
>> pursued, or if it had been deferred or worse abandoned.
>>
>>> That said: my personal feeling is that this PEP is way too large, and
>>> should be broken into seperate pieces of functionality that can be
>>> considered independently. There is a lot of stuff in it that isn't
>>> strictly necessary to provide the feature listed in the rationale.
>>
>> It would be nice to have a suitable foundation upon which more
>> elaborate third party dispatchers could build. The potential generic
>> functions have in a project like numpy are pretty exciting.
>
> You may also be interested in http://bugs.python.org/issue5135 which
> is a (much) simpler attempt to introduce generic functions into the
> standard library.
Thanks for the pointer. I actually read through the discussion there
yesterday. I don't think simplegeneric would be especially useful to
numpy. For example, multiplying a numpy.array([1,2,3]) with a
quantities.Quantity([1,2,3], 'm/s') should produce a new Quantity
regardless of the order in which they are provided to
numpy.multiply(). Numpy can handle this particular example now, but
the mechanisms are a bit convoluted.
> Generally, these things get stalled because the core developers don't
> have sufficient interest in the topic to do anything directly, and the
> arguments in favour aren't compelling enough to make a difference.
> Maybe the benefits numpy would get would help the case.
I am a relatively new contributor to the numpy project, contributing
bug fixes and features (most of which have been related to -- or could
benefit from -- generic functions) to better support subclasses like
Quantity. Numpy has different kinds of arrays (ndarrays, array
scalars, masked arrays, matrices) and supports many different data
types (int8, float32, complex64, etc). The ability to dispatch based
on the object type (or combinations thereof), or on combinations of
data types, or perhaps on the units of quantities, seem like good
examples where predicative dispatch would be useful.
I am primarily trying to get up to speed to help with the effort to
transition numpy to python-3. Perhaps generic functions could help
make the numpy source code more accessible and maintainable, so that
maybe someday there would even be interest in including numpy or some
subset thereof in the standard library. Anyway, it is helpful to me to
see where generic functions stand and how they might develop in the
standard library as we work on numpy support for python 3.
Regards,
Darren
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