I was working on improving coverage and test quality of typing.py, when I saw that @no_type_check is 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_check
Now, adding @no_type_check to B will make the result of get_type_hints() call on it - an empty dict:
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, like delegate to show how it breaks A:
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)) # {}, ok
Why is that important?
It introduces an unfortunate side-effect that can make some totally unrelated (!) class completely ignore get_type_hints() and break things like pydantic, beartype, `attrs, etc that rely on type hints.
By adding a class-level assignment to a class that has @no_type_check or other no_type_check_decorator.
Why does this happen?
It happens because no_type_check has 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)
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!
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?
@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.
Pydantic, looks like @no_type_check does 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)
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, 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.
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_check should 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_check to nested types as well.
So, do others have any objections / comments / feedback? :)
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.
Activity
sobolevn commented on Jan 29, 2022
I was working on improving coverage and test quality of typing.py, when I saw that @no_type_check is 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_check
Now, adding @no_type_check to B will make the result of get_type_hints() call on it - an empty dict:
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, like delegate to show how it breaks A:
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 like pydantic, beartype, `attrs, etc that rely on type hints.
By adding a class-level assignment to a class that has @no_type_check or other no_type_check_decorator.
Why does this happen?
It happens because no_type_check has 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:
cpython/Lib/typing.py
Lines 1952 to 1975 in 8b1b27f
As you can see above, we traverse all __dict__ values of the given class and 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?
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 :)
AlexWaygood commented 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!
JelleZijlstra commented on Jan 29, 2022
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.
gvanrossum commented on Jan 29, 2022
@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:
sobolevn commented on Jan 30, 2022
## 1. What is documented?
The docs makes this even more weird!
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_check at all: Improve error message when st.builds() is missing required uninferrable arguments HypothesisWorks/hypothesis#3225
Pydantic, looks like @no_type_check does 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 mypy to be happy.
Attrs: https://github.com/python-attrs/attrs/search?q=get_type_hints
So, as far as I understand, they only have @no_type_check support for callables. Related test: https://github.com/beartype/beartype/blob/50b213f315ecf97ea6a42674defe474b8f5d7203/beartype_test/a00_unit/a00_util/func/pep/test_utilpep484func.py
So, 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_check should 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_check to nested types as well.
So, do others have any objections / comments / feedback? :)
Fidget-Spinner commented on Jan 30, 2022
I agree with Jelle, let's go with (2). It feels strange to have a decorator modify types that it doesn't own.
AlexWaygood commented on Jan 30, 2022
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.
sobolevn commented on Jan 30, 2022
Ken Jin, Jelle, can you please share your ideas why (2) is better than (1)?
JelleZijlstra commented on Jan 30, 2022
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.
gvanrossum commented on Jan 30, 2022
I agree that Jelle's proposal (Nikita's #2) looks best *if* we can implement it.
How do we ensure that
suppresses annotations in B and C but not in A?
JelleZijlstra commented on Jan 30, 2022
I think we could do it by looking at __qualname__.
gvanrossum commented on Jan 30, 2022
Okay, somebody can submit a PR!
JelleZijlstra commented on Feb 19, 2022
New changeset 395029b by Nikita Sobolev in branch 'main':
bpo-46571: improve typing.no_type_check to skip foreign objects (GH-31042)
395029b
JelleZijlstra commented on Feb 19, 2022
Thanks for the fix Nikita!