TYP: overload maybe_downcast_numeric and maybe_downcast_to_dtype

pandas/core/dtypes/cast.py

@@ -246,6 +246,16 @@ def _disallow_mismatched_datetimelike(value, dtype: DtypeObj):
         raise TypeError(f"Cannot cast {repr(value)} to {dtype}")
 
 
+@overload
+def maybe_downcast_to_dtype(result: np.ndarray, dtype: str | np.dtype) -> np.ndarray:
+    ...
+
+
+@overload
+def maybe_downcast_to_dtype(result: ExtensionArray, dtype: str | np.dtype) -> ArrayLike:
+    ...
+
+
 def maybe_downcast_to_dtype(result: ArrayLike, dtype: str | np.dtype) -> ArrayLike:
     """
     try to cast to the specified dtype (e.g. convert back to bool/int
@@ -301,6 +311,20 @@ def maybe_downcast_to_dtype(result: ArrayLike, dtype: str | np.dtype) -> ArrayLi
     return result
 
 
+@overload
+def maybe_downcast_numeric(
+    result: np.ndarray, dtype: np.dtype, do_round: bool = False
+) -> np.ndarray:
+    ...
+
+
+@overload
+def maybe_downcast_numeric(
+    result: ExtensionArray, dtype: DtypeObj, do_round: bool = False
+) -> ArrayLike:
+    ...
+
+
 def maybe_downcast_numeric(
     result: ArrayLike, dtype: DtypeObj, do_round: bool = False
 ) -> ArrayLike:

pandas/core/groupby/ops.py

@@ -637,9 +637,7 @@ def _call_cython_op(
         else:
             op_result = result
 
-        # error: Incompatible return value type (got "Union[ExtensionArray, ndarray]",
-        # expected "ndarray")
-        return op_result  # type: ignore[return-value]
+        return op_result
 
     @final
     def cython_operation(

pandas/core/indexes/interval.py

@@ -1141,11 +1141,7 @@ def interval_range(
         if all(is_integer(x) for x in com.not_none(start, end, freq)):
             # np.linspace always produces float output
 
-            # error: Incompatible types in assignment (expression has type
-            # "Union[ExtensionArray, ndarray]", variable has type "ndarray")
-            breaks = maybe_downcast_numeric(  # type: ignore[assignment]
-                breaks, np.dtype("int64")
-            )
+            breaks = maybe_downcast_numeric(breaks, np.dtype("int64"))
     else:
         # delegate to the appropriate range function
         if isinstance(endpoint, Timestamp):