Fix variance inference when using real typeshed stubs

mypy/subtypes.py

@@ -1988,9 +1988,9 @@ def is_more_precise(left: Type, right: Type, *, ignore_promotions: bool = False)
     return is_proper_subtype(left, right, ignore_promotions=ignore_promotions)
 
 
-def all_members(info: TypeInfo) -> set[str]:
+def all_non_object_members(info: TypeInfo) -> set[str]:
     members = set(info.names)
-    for base in info.mro[1:]:
+    for base in info.mro[1:-1]:
         members.update(base.names)
     return members
 
@@ -2012,7 +2012,7 @@ def infer_variance(info: TypeInfo, i: int) -> bool:
         contra = True
         tvar = info.defn.type_vars[i]
         self_type = fill_typevars(info)
-        for member in all_members(info):
+        for member in all_non_object_members(info):
             if member in ("__init__", "__new__"):
                 continue
             node = info[member].node

test-data/unit/pythoneval.test

@@ -2091,3 +2091,24 @@ def f(d: Description) -> None:
     reveal_type(d.name_fn)
 [out]
 _testDataclassStrictOptionalAlwaysSet.py:9: note: Revealed type is "def (Union[builtins.int, None]) -> Union[builtins.str, None]"
+
+[case testPEP695VarianceInference]
+# flags: --python-version=3.12 --enable-incomplete-feature=NewGenericSyntax
+from typing import Callable, Final
+
+class Job[_R_co]:
+    def __init__(self, target: Callable[[], _R_co]) -> None:
+        self.target: Final = target
+
+def func(
+    action: Job[int | None],
+    a1: Job[int | None],
+    a2: Job[int],
+    a3: Job[None],
+) -> None:
+    action = a1
+    action = a2
+    action = a3
+    a2 = action  # Error
+[out]
+_testPEP695VarianceInference.py:17: error: Incompatible types in assignment (expression has type "Job[None]", variable has type "Job[int]")