What the future of this?
Graph[NodeType]
However, I knew that they may ultimately want
Graph[NodeType, EdgeTypedDict, NodeTypedDict]
but no one is going to want to replace their calls with
Graph[str, dict[str, Any], dict[str, Any]]
That's what too noisy.
This proposal would allow you to have default parameters. But what's the future looking like now? Do we expect to have a type constructor?
class Graph:
def T(node_type, edge_type_dict=..., node_type_dict=...) -> a type annotation
And then
g: Graph.T(whatever) = Graph(....)
Does that work?
On Friday, July 10, 2020 at 4:20:58 AM UTC-4, Stefano Borini wrote:
I am one of the authors of the PEP. My problem was to deal with
natural notation in quantum chemistry mostly. It had no technical
purpose, but I still think it would open some interesting options.
The PEP was rejected mostly because of lack of interest.
On Mon, 4 May 2020 at 00:07, Andras Tantos <and...@tantosonline.com> wrote:
>
> Hello!
>
> I'm not sure I'm addressing the right audience here, so please direct me to the appropriate channel if that's the case...
>
> My name is Andras Tantos and I'm working on a Python library desscribing HW designs. I came across this problem of __getitem__ and co. not supporting kwargs. Apparently this extension was proposed and rejected as PEP 472.
>
> Apart from my use-case, which is arguably a corner-case and not worth modifying the language for, I believe there are two important use-cases that are worth considering with the latest improvements in the language:
>
> 1. With the recent type-hint support, the feature could be made way more descriptive if this PEP got implemented.
>
> For example, instead of doing the following:
>
> def func(in: Dict[str, int])
>
> one could write:
>
> def func(in: Dict[key=str, value=int])
>
> 2. It would also make 'generic classes' much cleaner to implement, similar to the way type-hints look. Consider the following code:
>
> class _Generic(object):
> Specializations = []
> @classmethod
> def __getitem__(cls, *args):
> name = f"Generic_{len(cls.Specializations)}"
> Specialized = type(name, (cls,), {"specials": tuple(args)})
> cls.Specializations.append(Specialized)
> return Specialized
> def __init__(self, value = None):
> self.value = value
> def __str__(self):
> if hasattr(self, "specials"):
> return(f"[{type(self)} - " + ",".join(str(special) for special in self.specials) + f"] - {self.value}")
> else:
> return(f"[{type(self)} - GENERIC" + f"] - {self.value}")
> Generic = _Generic()
> #g = Generic() - fails because of no specialization is given
> s1 = Generic[12]()
> s2 = Generic[42]("Hi!")
> print(s1)
> print(s2)
>
> Running this simple example results in:
>
> python3 -i python_test.py
> [<class '__main__.Generic_0'> - 12] - None
> [<class '__main__.Generic_1'> - 42] - Hi!
>
> You can see how the specialized parameters got passed as well as the ones to '__init__'. Obviously, in real code the idea would be to filter generic parameters and set up 'Specialized' with the right set of methods and arguments.
>
> Now, without kwargs support for __getitem__, it's impossible to pass named arguments to the specialization list, which greatly limits the usability of this notation.
>
> I don't know how convincing these arguments and use-cases are for you, but could you advise me about how to start the 'ball rolling' to drum-up support for re-activating this PEP?
>
> Thanks again,
> Andras Tantos
>
>
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--
Kind regards,
Stefano Borini
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