Eric V. Smith wrote:
> On 10/17/2019 2:36 PM, Steve Jorgensen wrote:
> > Andrew Barnert wrote:
> > [snip]
> > But meanwhile, you still haven’t given any
> > reason why Record would be useful. What
> > exactly is it supposed to mean? When would you want to check it? What would
> > you do with
> > an
> > object only if you know it’s a Record?
> > This isn’t like checking for a POD type in C++ or a struct type in Swift,
> > because none
> > of the important things that tells you even make sense in Python.
> > The reason I am interested in having it is to disambiguate collections that
> > are
> > primarily to be treated as collections of values from those that are
> > primarily to be
> > accessed as attributes with values. As an example, when converting to JSON,
> > it would make
> > more sense to represent a regular tuple as a JSON array, but it would make
> > more sense to
> > represent a namedtuple as a JSON object.
> > This seems specific to your application. I don't think the language can
> disambiguate this for you. I think the best you can do is use the known
> way of looking for namedtuples and dataclasses. Although I think that in
> dataclasses case, is_dataclass is an anti-pattern and I should not have
> added it.
> For your use case, what's the difference between these two classes:
> @dataclass
> class A:
> x: int
> y: float
> class B:
> def __init__(self, x, y):
> self.x = x
> self.y = y
> Do you really want code that treats these differently, just because one
> used some shortcut to write the __init__ function?
> Eric
My thinking is that checking for type of `Struct` (or `Record` or whatever name
it has) is most useful in cases when the object is also identifiable as a
collection and is to disambiguate those that are primarily collections from
those that are not.
A miscellaneous class like…
def __init__(self, x, y):
self.x = x
self.y = y
…would not be a collection, so there would be no need to disambiguate it.
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