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Strange @typing.no_type_check behavior for class variables #90729
Description
Activity
I was working on improving coverage and test quality of
typing.py, when I saw that@no_type_checkis quite strange.Let's dive into this!
## Everything is correct
We will start with a basic example, that illustrates that everything works fine:
from typing import no_type_check, get_type_hints class A: x: int = 1 class B: y: str = 'a' print(get_type_hints(A)) # ok: {'x': <class 'int'>} print(get_type_hints(B)) # ok: {'y': <class 'str'>}Ok, let's move on.
Adding
@no_type_checkNow, adding
@no_type_checktoBwill make the result ofget_type_hints()call on it - an emptydict:from typing import no_type_check, get_type_hints class A: x: int = 1 @no_type_check class B: y: str = 'a' print(get_type_hints(A)) # ok: {'x': <class 'int'>} print(get_type_hints(B)) # ok: {}This is still ok.
## Broken?
And now we can add some class-level constant to
B, likedelegateto show how it breaksA:from typing import no_type_check, get_type_hints class A: x: int = 1 @no_type_check class B: y: str = 'a' delegate = A # adding this line will make `A` to have `__no_type_check__` as well print(get_type_hints(A)) # {}, wait, what? print(get_type_hints(B)) # {}, okWhy is that important?
It introduces an unfortunate side-effect that can make some totally unrelated (!) class completely ignore
get_type_hints()and break things likepydantic,beartype, `attrs, etc that rely on type hints.By adding a class-level assignment to a class that has
@no_type_checkor otherno_type_check_decorator.Why does this happen?
It happens because
no_type_checkhas this logic:if isinstance(arg, type): arg_attrs = arg.__dict__.copy() for attr, val in arg.__dict__.items(): if val in arg.__bases__ + (arg,): arg_attrs.pop(attr) for obj in arg_attrs.values(): if isinstance(obj, types.FunctionType): obj.__no_type_check__ = True if isinstance(obj, type): no_type_check(obj)Source:
Lines 1952 to 1975 in 8b1b27f
def no_type_check(arg): """Decorator to indicate that annotations are not type hints. The argument must be a class or function; if it is a class, it applies recursively to all methods and classes defined in that class (but not to methods defined in its superclasses or subclasses). This mutates the function(s) or class(es) in place. """ if isinstance(arg, type): arg_attrs = arg.__dict__.copy() for attr, val in arg.__dict__.items(): if val in arg.__bases__ + (arg,): arg_attrs.pop(attr) for obj in arg_attrs.values(): if isinstance(obj, types.FunctionType): obj.__no_type_check__ = True if isinstance(obj, type): no_type_check(obj) try: arg.__no_type_check__ = True except TypeError: # built-in classes pass return arg As you can see above, we traverse all
__dict__values of the givenclassand for some reason recurse into all nested types.I think that the original goal was to handle cases like:
@no_type_check class Outer: class Inner: ...And now it also affects regular assignments.
So, what can we do?
- Nothing, it works correctly (I disagree)
- Do not cover nested classes at all with
@no_type_check, only cover methods - Only cover types that are defined in this class, like my
Innerclass example - Something else?
I think that
(2)is more inline with the currect implementation, so my vote is for it.I would like to implement this when we will have the final agreement :)
- added3.9 (EOL)end of lifeend of life3.10 (EOL)end of lifeend of life3.11only security fixesonly security fixesstdlibStandard Library Python modules in the Lib/ directoryStandard Library Python modules in the Lib/ directorytype-bugAn unexpected behavior, bug, or errorAn unexpected behavior, bug, or error
on Jan 29, 2022 ...Option 3). Deprecate @no_type_check?
Maybe we should gather some stats on how many people are using @no_type_check? My feeling is that it's never achieved widespread adoption, so maybe it's just not that useful a thing to have in the stdlib.
Anyway, the behaviour you've pointed out is nuts, so I agree that something needs to change here!
Let's not jump into deprecating it.
I think (2) makes the most sense. If we can get that working reliably (using __qualname__ I assume), it would be my preference; otherwise we should do (1).
This problem can also affect function objects, right?
class B: meth = some_function.@no_type_check (introduced by PEP-484) is intended for static checkers, to signal to them that they shouldn't check the given function or class.
I don't think PEP-484 specifies its runtime effect -- arguably get_type_hints() could just ignore it. Or raise an exception when called on such a class. We could even argue that @no_type_check shouldn't have a runtime effect.
But before we change anything we should be guided by:
- What is documented?
- What does it do now?
- How is that used by runtime type inspectors?
- What would be most useful to runtime type inspectors?
## 1. What is documented?
The docs makes this even more weird!
@typing.no_type_check
Decorator to indicate that annotations are not type hints.
This works as class or function decorator. With a class, it applies recursively to all methods defined in that class (but not to methods defined in its superclasses or subclasses).
This mutates the function(s) in place.https://docs.python.org/3/library/typing.html#typing.no_type_check
Docs do not mention modifing nested classes at all! So, it looks like the
(1)solution.## 2. What does it do now?
It modifies nested types, even ones used in assignments.
## 3. How is that used by runtime type inspectors?
I've made a little research:
-
Hypothesis (I help with maintaining its typing API) does not support
@no_type_checkat all: Improve error message whenst.builds()is missing required uninferrable arguments HypothesisWorks/hypothesis#3225 -
Pydantic, looks like
@no_type_checkdoes not change anything at all.
from pydantic import BaseModel from typing import no_type_check @no_type_check # the same with and without this decorator class MyModel(BaseModel): a: int print(MyModel(a=1)) # ok print(MyModel(a='1a')) # ok # pydantic.error_wrappers.ValidationError: 1 validation error for MyModel # a: value is not a valid integer (type=type_error.integer)So, it always tries to coerce types. Docs: https://pydantic-docs.helpmanual.io/usage/types/
They also use it inside their own code-base: https://github.com/samuelcolvin/pydantic/search?q=no_type_check Probably for
mypyto be happy.dataclassesandattrs- nothing changes. Both do not use neither@no_type_checknorget_type_hintsinside.
Attrs: https://github.com/python-attrs/attrs/search?q=get_type_hints
- Beartype: https://github.com/beartype/beartype
We've verified that @beartype reduces to the identity decorator when decorating unannotated callables. That's but the tip of the iceberg, though. @beartype unconditionally reduces to a noop when:
The decorated callable is itself decorated by the PEP-484-compliant @typing.no_type_check decorator.So, as far as I understand, they only have
@no_type_checksupport for callables. Related test: https://github.com/beartype/beartype/blob/50b213f315ecf97ea6a42674defe474b8f5d7203/beartype_test/a00_unit/a00_util/func/pep/test_utilpep484func.pySo, to conclude, some project might still rely on current behavior that nested types are also implicitly marked as
@no_type_check, but I cannot find any solid proof for it.The noticable thing is that this never came up before in ~6 years while this logic exists: https://github.com/python/cpython/blame/8fb36494501aad5b0c1d34311c9743c60bb9926c/Lib/typing.py#L1969-L1970
It helps to prove my point: probably, no one uses it.
## 3. How is that used by runtime type inspectors?
## 4. What would be most useful to runtime type inspectors?With all the information I gathered, I've changed my opinion :)
Now I think that we should drop the part with modifing nested types at all ((1)solution). Only a type with@no_type_checkshould be modified.This is what docs say. This will also solve the original problem.
Even if someone relies on current behavior: the fix is not hard, just add@no_type_checkto nested types as well.So, do others have any objections / comments / feedback? :)
-
I agree with Jelle, let's go with (2). It feels strange to have a decorator modify types that it doesn't own.
I fully withdraw my suggestion of deprecating the decorator; it's evidently used more than I realised. I don't have any strong opinion on whether (1) or (2) would be a better solution.
Ken Jin, Jelle, can you please share your ideas why
(2)is better than(1)?-
Less change in behavior
-
From the purpose of the decorator, it makes sense for it to apply to nested classes as well as methods, even if the docs don't say so explicitly.
-
I agree that Jelle's proposal (Nikita's #2) looks best *if* we can implement it.
How do we ensure that
class A: ... @no_type_check class B: AA = A class C: ... ...
suppresses annotations in B and C but not in A?
I think we could do it by looking at __qualname__.
Okay, somebody can submit a PR!
Thanks for the fix Nikita!
typing.no_type_checkto skip foreign objects #31042Note: these values reflect the state of the issue at the time it was migrated and might not reflect the current state.
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