BUG: to_dict not converting masked dtype to native python types

doc/source/whatsnew/v2.0.0.rst

@@ -913,6 +913,7 @@ I/O
 - Bug in displaying ``string`` dtypes not showing storage option (:issue:`50099`)
 - Bug in :meth:`DataFrame.to_string` with ``header=False`` that printed the index name on the same line as the first row of the data (:issue:`49230`)
 - Bug in :meth:`DataFrame.to_string` ignoring float formatter for extension arrays (:issue:`39336`)
+- Bug in :meth:`DataFrame.to_dict` not converting elements to native Python types for masked arrays (:issue:`34665`)
 - Fixed memory leak which stemmed from the initialization of the internal JSON module (:issue:`49222`)
 - Fixed issue where :func:`json_normalize` would incorrectly remove leading characters from column names that matched the ``sep`` argument (:issue:`49861`)
 - Bug in :meth:`DataFrame.to_json` where it would segfault when failing to encode a string (:issue:`50307`)

pandas/core/arrays/masked.py

@@ -250,15 +250,15 @@ def __setitem__(self, key, value) -> None:
     def __iter__(self) -> Iterator:
         if self.ndim == 1:
             if not self._hasna:
-                for val in self._data:
-                    yield val
+                for i, val in enumerate(self._data):
+                    yield self._data.item(i)
             else:
                 na_value = self.dtype.na_value
-                for isna_, val in zip(self._mask, self._data):
+                for i, (isna_, val) in enumerate(zip(self._mask, self._data)):
                     if isna_:
                         yield na_value
                     else:
-                        yield val
+                        yield self._data.item(i)
         else:
             for i in range(len(self)):
                 yield self[i]

pandas/tests/frame/methods/test_to_dict.py

@@ -9,6 +9,7 @@
 import pytz
 
 from pandas import (
+    NA,
     DataFrame,
     Index,
     MultiIndex,
@@ -458,3 +459,13 @@ def test_to_dict_index_false(self, orient, expected):
         df = DataFrame({"col1": [1, 2], "col2": [3, 4]}, index=["row1", "row2"])
         result = df.to_dict(orient=orient, index=False)
         tm.assert_dict_equal(result, expected)
+
+    def test_to_dict_masked_native_python(self):
+        # GH#34665
+        df = DataFrame({"a": Series([1, 2], dtype="Int64"), "B": 1})
+        result = df.to_dict(orient="records")
+        assert type(result[0]["a"]) is int
+
+        df = DataFrame({"a": Series([1, NA], dtype="Int64"), "B": 1})
+        result = df.to_dict(orient="records")
+        assert type(result[0]["a"]) is int