BUG: copy np.ndarray inputs to Index constructor by default (pandas-dev#63370)

Author: mroeschke

pandas/core/indexes/base.py

@@ -341,8 +341,13 @@ class Index(IndexOpsMixin, PandasObject):
         Data type for the output Index. If not specified, this will be
         inferred from `data`.
         See the :ref:`user guide <basics.dtypes>` for more usages.
-    copy : bool, default False
-        Copy input data.
+    copy : bool, default None
+        Whether to copy input data, only relevant for array, Series, and Index
+        inputs (for other input, e.g. a list, a new array is created anyway).
+        Defaults to True for array input and False for Index/Series.
+        Set to False to avoid copying array input at your own risk (if you
+        know the input data won't be modified elsewhere).
+        Set to True to force copying Series/Index input up front.
     name : object
         Name to be stored in the index.
     tupleize_cols : bool (default: True)
@@ -482,7 +487,7 @@ def __new__(
         cls,
         data=None,
         dtype=None,
-        copy: bool = False,
+        copy: bool | None = None,
         name=None,
         tupleize_cols: bool = True,
     ) -> Self:
@@ -499,9 +504,16 @@ def __new__(
         if not copy and isinstance(data, (ABCSeries, Index)):
             refs = data._references
 
+        if isinstance(data, (ExtensionArray, np.ndarray)):
+            # GH 63306
+            if copy is not False:
+                if dtype is None or astype_is_view(data.dtype, dtype):
+                    data = data.copy()
+                    copy = False
+
         # range
         if isinstance(data, (range, RangeIndex)):
-            result = RangeIndex(start=data, copy=copy, name=name)
+            result = RangeIndex(start=data, copy=bool(copy), name=name)
             if dtype is not None:
                 return result.astype(dtype, copy=False)
             # error: Incompatible return value type (got "MultiIndex",
@@ -569,7 +581,7 @@ def __new__(
                 data = com.asarray_tuplesafe(data, dtype=_dtype_obj)
 
         try:
-            arr = sanitize_array(data, None, dtype=dtype, copy=copy)
+            arr = sanitize_array(data, None, dtype=dtype, copy=bool(copy))
         except ValueError as err:
             if "index must be specified when data is not list-like" in str(err):
                 raise cls._raise_scalar_data_error(data) from err

pandas/tests/copy_view/index/test_index.py

@@ -5,6 +5,7 @@
     DataFrame,
     Index,
     Series,
+    array,
 )
 import pandas._testing as tm
 from pandas.tests.copy_view.util import get_array
@@ -150,3 +151,27 @@ def test_index_values():
     idx = Index([1, 2, 3])
     result = idx.values
     assert result.flags.writeable is False
+
+
+def test_constructor_copy_input_ndarray_default():
+    arr = np.array([0, 1])
+    idx = Index(arr)
+    assert not np.shares_memory(arr, get_array(idx))
+
+
+def test_constructor_copy_input_ea_default():
+    arr = array([0, 1], dtype="Int64")
+    idx = Index(arr)
+    assert not tm.shares_memory(arr, idx.array)
+
+
+def test_series_from_temporary_index_readonly_data():
+    # GH 63370
+    arr = np.array([0, 1], dtype=np.dtype(np.int8))
+    arr.flags.writeable = False
+    ser = Series(Index(arr))
+    assert not np.shares_memory(arr, get_array(ser))
+    assert ser._mgr._has_no_reference(0)
+    ser[[False, True]] = np.array([0, 2], dtype=np.dtype(np.int8))
+    expected = Series([0, 2], dtype=np.dtype(np.int8))
+    tm.assert_series_equal(ser, expected)