[Python-Dev] Postponed annotations break inspection of dataclasses (original) (raw)

David Hagen david at drhagen.com
Sat Sep 22 08🔞40 EDT 2018

The new postponed annotations have an unexpected interaction with dataclasses. Namely, you cannot get the type hints of any of the data classes methods.

For example, I have some code that inspects the type parameters of a class's __init__ method. (The real use case is to provide a default serializer for the class, but that is not important here.)

from dataclasses import dataclass
from typing import get_type_hints

class Foo:
    pass

@dataclass
class Bar:
    foo: Foo

print(get_type_hints(Bar.__init__))

In Python 3.6 and 3.7, this does what is expected; it prints {'foo': <class '__main__.Foo'>, 'return': <class 'NoneType'>}.

However, if in Python 3.7, I add from __future__ import annotations, then this fails with an error:

NameError: name 'Foo' is not defined

I know why this is happening. The __init__ method is defined in the dataclasses module which does not have the Foo object in its environment, and the Foo annotation is being passed to dataclass and attached to __init__ as the string "Foo" rather than as the original object Foo, but get_type_hints for the new annotations only does a name lookup in the module where __init__ is defined not where the annotation is defined.

I know that the use of lambdas to implement PEP 563 was rejected for performance reasons. I could be wrong, but I think this was motivated by variable annotations because the lambda would have to be constructed each time the function body ran. I was wondering if I could motivate storing the annotations as lambdas in class bodies and function signatures, in which the environment is already being captured and is code that usually only runs once. -------------- next part -------------- An HTML attachment was scrubbed... URL: <http://mail.python.org/pipermail/python-dev/attachments/20180922/4bfe10ca/attachment-0001.html>

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