I love using attrs, like the idea of bringing something similar to the standard library, but strongly disagree with the dataclasses API. It treats untyped Python as a second class citizen.
This is what I'd prefer
from dataclasses import dataclass, field
@dataclass
class MyClass:
x = field()
but it produces an error because fields need to be declared with a type annotation. This is the GvR recommended way to get around it:
@dataclass
class MyClass:
x: object
You could use the typing.Any type instead of object, but then you need to import a whole typing library to use untyped dataclasses. I highly prefer the former code block.
This is what I'd prefer
but it produces an error because fields need to be declared with a type annotation. This is the GvR recommended way to get around it: You could use the typing.Any type instead of object, but then you need to import a whole typing library to use untyped dataclasses. I highly prefer the former code block.There's a big thread discussing the issue on python-dev somewhere. Also some discussion in https://github.com/ericvsmith/dataclasses/issues/2#issuecomm...
Anyway, it's not a huge issue—attrs is great and there's no reason not to use it instead for untyped Python.