Wrap custom iterator result

python/cudf/cudf/pandas/_wrappers/common.py

@@ -52,4 +52,7 @@ def array_interface(self: _FastSlowProxy):
 
 
 def custom_iter(self: _FastSlowProxy):
-    return iter(self._fsproxy_slow)
+    return _maybe_wrap_result(
+        iter(self._fsproxy_slow),
+        None,  # type: ignore
+    )

python/cudf/cudf/pandas/fast_slow_proxy.py

@@ -1099,7 +1099,9 @@ def _maybe_wrap_result(result: Any, func: Callable, /, *args, **kwargs) -> Any:
     """
     Wraps "result" in a fast-slow proxy if is a "proxiable" object.
     """
-    if _is_final_type(result):
+    if isinstance(result, (int, str, float, bool, type(None))):
+        return result
+    elif _is_final_type(result):
         typ = get_final_type_map()[type(result)]
         return typ._fsproxy_wrap(result, func)
     elif _is_intermediate_type(result):

python/cudf/cudf_pandas_tests/test_cudf_pandas.py

@@ -1777,3 +1777,14 @@ def test_cudf_pandas_util_version(attrs):
         assert not hasattr(pd.util, attrs)
     else:
         assert hasattr(pd.util, attrs)
+
+
+def test_iteration_over_dataframe_dtypes_produces_proxy_objects(dataframe):
+    _, xdf = dataframe
+    xdf["b"] = xpd.IntervalIndex.from_arrays(xdf["a"], xdf["b"])
+    xdf["a"] = xpd.Series([1, 1, 1, 2, 3], dtype="category")
+    dtype_series = xdf.dtypes
+    for x in dtype_series:
+        assert is_proxy_object(x)
+    assert isinstance(dtype_series.iloc[0], xpd.CategoricalDtype)
+    assert isinstance(dtype_series.iloc[1], xpd.IntervalDtype)