On 8/23/21 2:31 PM, Tim Hoffmann via Python-ideas wrote:
> Ethan Furman wrote:
>> It seems to me that the appropriate fix is for numpy to have an "is_empty()"
function
>> that knows how to deal with arrays and array-like structures, not force
every container
>> to grow a new method.
>
> Yes, numpy could and probably should have an "is_empty()" method. However,
defining a
> method downstream breaks duck typing and maybe even more important authors
have to
> mentally switch between the two empty-check variants `if users` and `if
users.is_empty()`
> depending on the context.
The context being whether or not you working with numpy? Is there generic code that works with both numpy arrays and
other non-numpy data? Do we have any non-numpy examples of this problem?
>>> If you want to write a function that accepts array-like `values`, you have
to change
>>> a check `if values` to `if len(values) == 0`. That works for both but is
against the
>>> PEP8 recommendation. This is a shortcoming of the language.
>>
>> Numpy is not Python, but a specialist third-party package that has made
specialist
>> choices about basic operations -- that does not sound like a shortcoming of
the language.
>
> The "specialist choices" ``if len(values) == 0` in Numpy are the best you can
do within
> the capabilities of the Python language if you want the code to function with
lists and
> arrays. For Numpy to do better Python would need to either provide the above
mentioned
> "has element-wise operations" protocol or an is_empty protocol.
>
> I consider emptiness-check a basic concept that should be consistent and easy
to use across containers.
Python has an emptiness-check and numpy chose to repurpose it -- that is not
Python's problem nor a shortcoming in Python.
Suppose we add an `.is_empty()` method, and five years down the road another library repurposes that method, that other
library then becomes popular, and we then have two "emptiness" checks that are no longer consistent -- do we then add a
third?
--
~Ethan~
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