Make sure multiple_outputs is inferred correctly even when using TypedDict

airflow/decorators/base.py

@@ -27,7 +27,6 @@
     Callable,
     ClassVar,
     Collection,
-    Dict,
     Generic,
     Iterator,
     Mapping,
@@ -351,7 +350,7 @@ def fake():
         except TypeError:  # Can't evaluate return type.
             return False
         ttype = getattr(return_type, "__origin__", return_type)
-        return ttype is dict or ttype is Dict
+        return issubclass(ttype, Mapping)
 
     def __attrs_post_init__(self):
         if "self" in self.function_signature.parameters:

docs/apache-airflow/tutorial/taskflow.rst

@@ -428,8 +428,8 @@ Tasks can also infer multiple outputs by using dict Python typing.
    def identity_dict(x: int, y: int) -> dict[str, int]:
        return {"x": x, "y": y}
 
-By using the typing ``Dict`` for the function return type, the ``multiple_outputs`` parameter
-is automatically set to true.
+By using the typing ``dict``, or any other class that conforms to the ``typing.Mapping`` protocol,
+for the function return type, the ``multiple_outputs`` parameter is automatically set to true.
 
 Note, If you manually set the ``multiple_outputs`` parameter the inference is disabled and
 the parameter value is used.

tests/decorators/test_python.py

@@ -97,6 +97,19 @@ def identity_dict_with_decorator_call(x: int, y: int) -> resolve(annotation):
 
         assert identity_dict_with_decorator_call(5, 5).operator.multiple_outputs is True
 
+    @pytest.mark.skipif(sys.version_info < (3, 8), reason="PEP 589 is implemented in Python 3.8")
+    def test_infer_multiple_outputs_typed_dict(self):
+        from typing import TypedDict
+
+        class TypeDictClass(TypedDict):
+            pass
+
+        @task_decorator
+        def t1() -> TypeDictClass:
+            return {}
+
+        assert t1().operator.multiple_outputs is True
+
     def test_infer_multiple_outputs_forward_annotation(self):
         if TYPE_CHECKING: