[Numpy-discussion] Good use of __dunder__ methods in numpy

[Chris Barker]

On Thu, Mar 5, 2020 at 2:15 PM Gregory Lee <grlee77 at gmail.com> wrote:

> If i can get a link to a file that shows how dunder methods help with
>> having cool coding APIs that would be great!
>>
>>
> You may want to take a look at PEP 465 as an example, then. If I recall
> correctly, the __matmul__ method described in it was added to the standard
> library largely with NumPy in mind.
> https://www.python.org/dev/peps/pep-0465/
>

and so were "rich comparisons", and in-place operators (at least in part).

numpy is VERY, VERY, heavily built on the concept of overloading operators,
i.e. using dunders or magic methods.

I'm going to venture a guess that numpy arrays custom define every single
standard dunder -- and certainly most of them.

-CHB





> On Thu, Mar 5, 2020 at 10:32 PM Sebastian Berg <sebastian at sipsolutions.net>
>> wrote:
>>
>>> Hi,
>>>
>>> On Thu, 2020-03-05 at 11:14 +0400, Abdur-Rahmaan Janhangeer wrote:
>>> > Greetings list,
>>> >
>>> > I have a talk about dunder methods in Python
>>> >
>>> > (
>>> >
>>> https://conference.mscc.mu/speaker/67604187-57c3-4be6-987c-ea4bef388ad3
>>> > )
>>> >
>>> > and it would be nice to include Numpy in the mix. Can someone point
>>> > me to one or two use cases / file link where dunder methods help
>>> > numpy?
>>> >
>>>
>>> I am not sure in what sense you are looking for. NumPy has its own set
>>> of dunder methods (some of which should not be used super much
>>> probably), like `__array__`, `__array_interface__`, `__array_ufunc__`,
>>> `__array_function__`, `__array_finalize__`, ...
>>> So we are using `__array_*__` for numpy related dunders.
>>>
>>> Of course we use most Python defined dunders, but I am not sure that
>>> you are looking for that?
>>>
>>> Best,
>>>
>>> Sebastian
>>>
>>>
>>> > Thanks
>>> >
>>> > fun info: i am a tiny numpy contributor with a one line merge.
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