On Apr 7, 2020, at 15:31, Christopher Barker <[email protected]> wrote:
>
>> On Tue, Apr 7, 2020 at 11:17 AM Wes Turner <[email protected]> wrote:
>
>> Would you generate a schema from the type annotations so that other
>> languages can use the data?
>
> I haven't done this yet, but it would be pretty cool.
This seems like one of the many things that’s impossible to do for Python
classes with full generality, but pretty easy to do if you only want to support
@dataclass. Either dynamically or statically, in fact. You could even write a
tool that generates dataclasses (statically or dynamically) from a schema, if
you wanted.
> But what is meant by "type annotations"? I'm using them via dataclasses --
> really as a shorthand for assigning a type to every field -- the annotations
> are just a shorthand that auto-generates a schema, essentially.
>
> @dataclass
> class MyClass:
> x: A_Type = A_default
>
> So now I know that this class has a field names x that is the type int. So I
> use that type for validation, and serialization / deserialization.
>
> But if you mean "type annotations" in the sense of the types provided out of
> the box in the typing module and used by MyPy (so I've heard, never did it
> myself) -- no, they are not sufficient -- I need types that support my
> serialization / deserialization system, and my validation system. And I
> suppose we could have a standardized __json__ and __from_json__ protocol that
> I could use, but it seems a special case to me.
A type annotation is just the “: whatever”. It doesn’t matter whether that
whatever is a real dynamic type like int or spam.Eggs or list, or a typing.type
like List[int], it’s still an annotation. And dataclass can handle
either—change that to “x: List[A_Type]” and at runtime, the dataclass will
treat that the same as if you just used list, but mypy can know that it’s only
supposed to have A_Type members in that list. (So if you initialize MyClass([1,
“spam”, open(“eggs.txt”)]) it’ll work at runtime, but mypy will flag it as a
type error.)
An “automated JSON serialization for dataclasses” library could do either. It
could be “dumb” like @dataclass and just treat x as a list of anything
serializable, or it could be “smart” and treat it as a list of A_Type objects
only. Either way seems like it makes sense.
A schema generator for dataclasses, I think you’d want it to use the typing
information. A MyClass property a doesn’t just have an attribute of {“type”:
“array”}; it has a {“type”: “array”, “contains”:
recursively_schematize(A_Type)}._______________________________________________
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