DataFrame.dtypes.to_json OverflowError: Maximum recursion level reached

doc/source/whatsnew/v3.0.0.rst

@@ -749,6 +749,7 @@ I/O
 - Bug in :meth:`read_stata` where the missing code for double was not recognised for format versions 105 and prior (:issue:`58149`)
 - Bug in :meth:`set_option` where setting the pandas option ``display.html.use_mathjax`` to ``False`` has no effect (:issue:`59884`)
 - Bug in :meth:`to_excel` where :class:`MultiIndex` columns would be merged to a single row when ``merge_cells=False`` is passed (:issue:`60274`)
+- Bug in :meth:`to_json` raising ``OverflowError`` when convert DataFrame.dtypes Series to JSON (:issue:`61170`)
 
 Period
 ^^^^^^

pandas/_libs/src/vendored/ujson/python/objToJSON.c

@@ -62,6 +62,7 @@ int object_is_series_type(PyObject *obj);
 int object_is_index_type(PyObject *obj);
 int object_is_nat_type(PyObject *obj);
 int object_is_na_type(PyObject *obj);
+int object_is_ndtypes_type(PyObject *obj);
 
 typedef struct __NpyArrContext {
   PyObject *array;
@@ -396,6 +397,25 @@ static const char *PyDecimalToUTF8Callback(JSOBJ _obj, JSONTypeContext *tc,
   return outValue;
 }
 
+static const char *PyNpyDtypesToUTF8Callback(JSOBJ _obj, JSONTypeContext *tc,
+                                             size_t *len) {
+  PyObject *obj = (PyObject *)_obj;
+  PyObject *str = PyObject_Str(obj);
+
+  if (str == NULL) {
+    ((JSONObjectEncoder *)tc->encoder)->errorMsg = "";
+    return NULL;
+  }
+
+  GET_TC(tc)->newObj = str;
+
+  Py_ssize_t s_len;
+  char *outValue = (char *)PyUnicode_AsUTF8AndSize(str, &s_len);
+  *len = s_len;
+
+  return outValue;
+}
+
 //=============================================================================
 // Numpy array iteration functions
 //=============================================================================
@@ -1583,6 +1603,10 @@ static void Object_beginTypeContext(JSOBJ _obj, JSONTypeContext *tc) {
   } else if (object_is_na_type(obj)) {
     tc->type = JT_NULL;
     return;
+  } else if (object_is_ndtypes_type(obj)) {
+    tc->type = JT_UTF8;
+    pc->PyTypeToUTF8 = PyNpyDtypesToUTF8Callback;
+    return;
   }
 
 ISITERABLE:

pandas/_libs/src/vendored/ujson/python/ujson.c

@@ -211,6 +211,16 @@ int object_is_na_type(PyObject *obj) {
   }
   return result;
 }
+
+int object_is_ndtypes_type(PyObject *obj) {
+  PyObject *ndtype = (PyObject *)&PyArrayDescr_Type;
+  int result = PyObject_IsInstance(obj, ndtype);
+  if (result == -1) {
+    PyErr_Clear();
+    return 0;
+  }
+  return result;
+}
 #else
 /* Used in objToJSON.c */
 int object_is_decimal_type(PyObject *obj) {

pandas/tests/io/json/test_pandas.py

@@ -2311,3 +2311,21 @@ def test_large_number():
     )
     expected = Series([9999999999999999])
     tm.assert_series_equal(result, expected)
+
+
+@pytest.mark.parametrize(
+    "df",
+    [
+        DataFrame({"A": [1, 2, 3], "B": [4, 5, 6]}),
+        DataFrame({"X": [1.1, 2.2], "Y": ["a", "b"]}),
+    ],
+)
+def test_dtypes_to_json_consistency(df: DataFrame):
+    # GH 61170
+    expected = df.dtypes.apply(str).to_json()
+    result = df.dtypes.to_json()
+    result = json.loads(result)
+    for k in result:
+        if "name" in result[k]:
+            result[k] = result[k]["name"]
+    assert result == json.loads(expected)