BUG: raise on RangeIndex.array

pandas/_testing/__init__.py

@@ -100,6 +100,7 @@
 )
 from pandas.core.arrays import (
     DatetimeArray,
+    PandasArray,
     PeriodArray,
     TimedeltaArray,
     period_array,
@@ -204,7 +205,11 @@ def box_expected(expected, box_cls, transpose=True):
     subclass of box_cls
     """
     if box_cls is pd.array:
-        expected = pd.array(expected)
+        if isinstance(expected, RangeIndex):
+            # pd.array would return an IntegerArray
+            expected = PandasArray(np.asarray(expected._values))
+        else:
+            expected = pd.array(expected)
     elif box_cls is Index:
         expected = Index(expected)
     elif box_cls is Series:

pandas/core/construction.py

@@ -58,6 +58,7 @@
     ABCExtensionArray,
     ABCIndex,
     ABCPandasArray,
+    ABCRangeIndex,
     ABCSeries,
 )
 from pandas.core.dtypes.missing import isna
@@ -367,7 +368,9 @@ def array(
     return PandasArray._from_sequence(data, dtype=dtype, copy=copy)
 
 
-def extract_array(obj: object, extract_numpy: bool = False) -> Any | ArrayLike:
+def extract_array(
+    obj: object, extract_numpy: bool = False, extract_range: bool = False
+) -> Any | ArrayLike:
     """
     Extract the ndarray or ExtensionArray from a Series or Index.
 
@@ -382,6 +385,10 @@ def extract_array(obj: object, extract_numpy: bool = False) -> Any | ArrayLike:
     extract_numpy : bool, default False
         Whether to extract the ndarray from a PandasArray
 
+    extract_range : bool, default False
+        If we have a RangeIndex, return range._values if True
+        (which is a materialized integer ndarray), otherwise return unchanged.
+
     Returns
     -------
     arr : object
@@ -410,6 +417,11 @@ def extract_array(obj: object, extract_numpy: bool = False) -> Any | ArrayLike:
     array([1, 2, 3])
     """
     if isinstance(obj, (ABCIndex, ABCSeries)):
+        if isinstance(obj, ABCRangeIndex):
+            if extract_range:
+                return obj._values
+            return obj
+
         obj = obj.array
 
     if extract_numpy and isinstance(obj, ABCPandasArray):

pandas/core/indexes/range.py

@@ -528,12 +528,17 @@ def argsort(self, *args, **kwargs) -> np.ndarray:
         --------
         numpy.ndarray.argsort
         """
+        ascending = kwargs.pop("ascending", True)  # EA compat
         nv.validate_argsort(args, kwargs)
 
         if self._range.step > 0:
-            return np.arange(len(self))
+            result = np.arange(len(self))
         else:
-            return np.arange(len(self) - 1, -1, -1)
+            result = np.arange(len(self) - 1, -1, -1)
+
+        if not ascending:
+            result = result[::-1]
+        return result
 
     def factorize(
         self, sort: bool = False, na_sentinel: int | None = -1
@@ -920,7 +925,8 @@ def _arith_method(self, other, op):
         if op in [operator.mul, ops.rmul, operator.truediv, ops.rtruediv]:
             step = op
 
-        other = extract_array(other, extract_numpy=True)
+        # TODO: if other is a RangeIndex we may have more efficient options
+        other = extract_array(other, extract_numpy=True, extract_range=True)
         attrs = self._get_attributes_dict()
 
         left, right = self, other

pandas/core/reshape/merge.py

@@ -2080,8 +2080,9 @@ def _factorize_keys(
     (array([0, 1, 2]), array([0, 1]), 3)
     """
     # Some pre-processing for non-ndarray lk / rk
-    lk = extract_array(lk, extract_numpy=True)
-    rk = extract_array(rk, extract_numpy=True)
+    lk = extract_array(lk, extract_numpy=True, extract_range=True)
+    rk = extract_array(rk, extract_numpy=True, extract_range=True)
+    # TODO: if either is a RangeIndex, we can likely factorize more efficiently?
 
     if is_datetime64tz_dtype(lk.dtype) and is_datetime64tz_dtype(rk.dtype):
         # Extract the ndarray (UTC-localized) values

pandas/core/series.py

@@ -5078,7 +5078,7 @@ def _cmp_method(self, other, op):
             raise ValueError("Can only compare identically-labeled Series objects")
 
         lvalues = self._values
-        rvalues = extract_array(other, extract_numpy=True)
+        rvalues = extract_array(other, extract_numpy=True, extract_range=True)
 
         with np.errstate(all="ignore"):
             res_values = ops.comparison_op(lvalues, rvalues, op)
@@ -5090,7 +5090,7 @@ def _logical_method(self, other, op):
         self, other = ops.align_method_SERIES(self, other, align_asobject=True)
 
         lvalues = self._values
-        rvalues = extract_array(other, extract_numpy=True)
+        rvalues = extract_array(other, extract_numpy=True, extract_range=True)
 
         res_values = ops.logical_op(lvalues, rvalues, op)
         return self._construct_result(res_values, name=res_name)
@@ -5100,7 +5100,8 @@ def _arith_method(self, other, op):
         self, other = ops.align_method_SERIES(self, other)
 
         lvalues = self._values
-        rvalues = extract_array(other, extract_numpy=True)
+        rvalues = extract_array(other, extract_numpy=True, extract_range=True)
+
         with np.errstate(all="ignore"):
             result = ops.arithmetic_op(lvalues, rvalues, op)
 

pandas/core/sorting.py

@@ -25,7 +25,10 @@
     ensure_platform_int,
     is_extension_array_dtype,
 )
-from pandas.core.dtypes.generic import ABCMultiIndex
+from pandas.core.dtypes.generic import (
+    ABCMultiIndex,
+    ABCRangeIndex,
+)
 from pandas.core.dtypes.missing import isna
 
 from pandas.core.construction import extract_array
@@ -362,9 +365,12 @@ def nargsort(
             mask=mask,
         )
 
-    items = extract_array(items)
+    if isinstance(items, ABCRangeIndex):
+        return items.argsort(ascending=ascending)  # TODO: test coverage with key?
+    elif not isinstance(items, ABCMultiIndex):
+        items = extract_array(items)
     if mask is None:
-        mask = np.asarray(isna(items))
+        mask = np.asarray(isna(items))  # TODO: does this exclude MultiIndex too?
 
     if is_extension_array_dtype(items):
         return items.argsort(ascending=ascending, kind=kind, na_position=na_position)

pandas/tests/arithmetic/test_numeric.py

@@ -311,6 +311,7 @@ def test_add_sub_datetimelike_invalid(self, numeric_idx, other, box_with_array):
                 "Concatenation operation is not implemented for NumPy arrays",
                 # pd.array vs np.datetime64 case
                 r"operand type\(s\) all returned NotImplemented from __array_ufunc__",
+                "can only perform ops with numeric values",
             ]
         )
         with pytest.raises(TypeError, match=msg):

pandas/tests/construction/test_extract_array.py

@@ -0,0 +1,18 @@
+from pandas import Index
+import pandas._testing as tm
+from pandas.core.construction import extract_array
+
+
+def test_extract_array_rangeindex():
+    ri = Index(range(5))
+
+    expected = ri._values
+    res = extract_array(ri, extract_numpy=True, extract_range=True)
+    tm.assert_numpy_array_equal(res, expected)
+    res = extract_array(ri, extract_numpy=False, extract_range=True)
+    tm.assert_numpy_array_equal(res, expected)
+
+    res = extract_array(ri, extract_numpy=True, extract_range=False)
+    tm.assert_index_equal(res, ri)
+    res = extract_array(ri, extract_numpy=False, extract_range=False)
+    tm.assert_index_equal(res, ri)