REF: avoid _internal_get_values in json (#32754)

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

@@ -222,13 +222,19 @@ static PyObject *get_values(PyObject *obj) {
 
     PRINTMARK();
 
-    if (PyObject_HasAttrString(obj, "_internal_get_values")) {
+    if (PyObject_TypeCheck(obj, cls_index) || PyObject_TypeCheck(obj, cls_series)) {
+        // The special cases to worry about are dt64tz and category[dt64tz].
+        //  In both cases we want the UTC-localized datetime64 ndarray,
+        //  without going through and object array of Timestamps.
         PRINTMARK();
-        values = PyObject_CallMethod(obj, "_internal_get_values", NULL);
+        values = PyObject_GetAttrString(obj, "values");
 
         if (values == NULL) {
             // Clear so we can subsequently try another method
             PyErr_Clear();
+        } else if (PyObject_HasAttrString(values, "__array__")) {
+            // We may have gotten a Categorical or Sparse array so call np.array
+            values = PyObject_CallMethod(values, "__array__", NULL);
         } else if (!PyArray_CheckExact(values)) {
             // Didn't get a numpy array, so keep trying
             PRINTMARK();

pandas/core/generic.py

@@ -5382,26 +5382,6 @@ def _values(self) -> np.ndarray:
         """internal implementation"""
         return self.values
 
-    def _internal_get_values(self) -> np.ndarray:
-        """
-        Return an ndarray after converting sparse values to dense.
-
-        This is the same as ``.values`` for non-sparse data. For sparse
-        data contained in a `SparseArray`, the data are first
-        converted to a dense representation.
-
-        Returns
-        -------
-        numpy.ndarray
-            Numpy representation of DataFrame.
-
-        See Also
-        --------
-        values : Numpy representation of DataFrame.
-        SparseArray : Container for sparse data.
-        """
-        return self.values
-
     @property
     def dtypes(self):
         """

pandas/core/indexes/base.py

@@ -3872,50 +3872,6 @@ def _values(self) -> Union[ExtensionArray, np.ndarray]:
         """
         return self._data
 
-    def _internal_get_values(self) -> np.ndarray:
-        """
-        Return `Index` data as an `numpy.ndarray`.
-
-        Returns
-        -------
-        numpy.ndarray
-            A one-dimensional numpy array of the `Index` values.
-
-        See Also
-        --------
-        Index.values : The attribute that _internal_get_values wraps.
-
-        Examples
-        --------
-        Getting the `Index` values of a `DataFrame`:
-
-        >>> df = pd.DataFrame([[1, 2, 3], [4, 5, 6], [7, 8, 9]],
-        ...                    index=['a', 'b', 'c'], columns=['A', 'B', 'C'])
-        >>> df
-           A  B  C
-        a  1  2  3
-        b  4  5  6
-        c  7  8  9
-        >>> df.index._internal_get_values()
-        array(['a', 'b', 'c'], dtype=object)
-
-        Standalone `Index` values:
-
-        >>> idx = pd.Index(['1', '2', '3'])
-        >>> idx._internal_get_values()
-        array(['1', '2', '3'], dtype=object)
-
-        `MultiIndex` arrays also have only one dimension:
-
-        >>> midx = pd.MultiIndex.from_arrays([[1, 2, 3], ['a', 'b', 'c']],
-        ...                                  names=('number', 'letter'))
-        >>> midx._internal_get_values()
-        array([(1, 'a'), (2, 'b'), (3, 'c')], dtype=object)
-        >>> midx._internal_get_values().ndim
-        1
-        """
-        return self.values
-
     def _get_engine_target(self) -> np.ndarray:
         """
         Get the ndarray that we can pass to the IndexEngine constructor.

pandas/core/internals/blocks.py

@@ -237,9 +237,6 @@ def get_block_values_for_json(self) -> np.ndarray:
         # TODO(2DEA): reshape will be unnecessary with 2D EAs
         return np.asarray(self.values).reshape(self.shape)
 
-    def to_dense(self):
-        return self.values.view()
-
     @property
     def fill_value(self):
         return np.nan
@@ -1820,9 +1817,6 @@ def get_values(self, dtype=None):
     def array_values(self) -> ExtensionArray:
         return self.values
 
-    def to_dense(self):
-        return np.asarray(self.values)
-
     def to_native_types(self, slicer=None, na_rep="nan", quoting=None, **kwargs):
         """override to use ExtensionArray astype for the conversion"""
         values = self.values
@@ -2378,12 +2372,6 @@ def get_values(self, dtype=None):
             values = values.reshape(1, -1)
         return values
 
-    def to_dense(self):
-        # we request M8[ns] dtype here, even though it discards tzinfo,
-        # as lots of code (e.g. anything using values_from_object)
-        # expects that behavior.
-        return np.asarray(self.values, dtype=_NS_DTYPE)
-
     def _slice(self, slicer):
         """ return a slice of my values """
         if isinstance(slicer, tuple):
@@ -2911,12 +2899,6 @@ def __init__(self, values, placement, ndim=None):
     def _holder(self):
         return Categorical
 
-    def to_dense(self):
-        # Categorical.get_values returns a DatetimeIndex for datetime
-        # categories, so we can't simply use `np.asarray(self.values)` like
-        # other types.
-        return self.values._internal_get_values()
-
     def to_native_types(self, slicer=None, na_rep="", quoting=None, **kwargs):
         """ convert to our native types format, slicing if desired """
         values = self.values

pandas/core/series.py

@@ -574,18 +574,6 @@ def _values(self):
     def array(self) -> ExtensionArray:
         return self._data._block.array_values()
 
-    def _internal_get_values(self):
-        """
-        Same as values (but handles sparseness conversions); is a view.
-
-        Returns
-        -------
-        numpy.ndarray
-            Data of the Series.
-        """
-        blk = self._data._block
-        return np.array(blk.to_dense(), copy=False)
-
     # ops
     def ravel(self, order="C"):
         """