API: Copy inputs in Index subclass constructors by default (GH#63388) (#63398)

Author: zacharym-collins

doc/source/whatsnew/v3.0.0.rst

@@ -820,6 +820,7 @@ Other API changes
   :meth:`~DataFrame.ffill`, :meth:`~DataFrame.bfill`, :meth:`~DataFrame.interpolate`,
   :meth:`~DataFrame.where`, :meth:`~DataFrame.mask`, :meth:`~DataFrame.clip`) now return
   the modified DataFrame or Series (``self``) instead of ``None`` when ``inplace=True`` (:issue:`63207`)
+- All Index constructors now copy ``numpy.ndarray`` and ``ExtensionArray`` inputs by default when ``copy=None``, consistent with :class:`Series` behavior (:issue:`63388`)
 
 .. ---------------------------------------------------------------------------
 .. _whatsnew_300.deprecations:

pandas/core/indexes/base.py

@@ -505,12 +505,8 @@ 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
+        # GH 63306, GH 63388
+        data, copy = cls._maybe_copy_array_input(data, copy, dtype)
 
         # range
         if isinstance(data, (range, RangeIndex)):
@@ -5197,6 +5193,21 @@ def _raise_scalar_data_error(cls, data):
             "was passed"
         )
 
+    @classmethod
+    def _maybe_copy_array_input(
+        cls, data, copy: bool | None, dtype
+    ) -> tuple[Any, bool]:
+        """
+        Ensure that the input data is copied if necessary.
+        GH#63388
+        """
+        if isinstance(data, (ExtensionArray, np.ndarray)):
+            if copy is not False:
+                if dtype is None or astype_is_view(data.dtype, pandas_dtype(dtype)):
+                    data = data.copy()
+                    copy = False
+        return data, bool(copy)
+
     def _validate_fill_value(self, value):
         """
         Check if the value can be inserted into our array without casting,

pandas/core/indexes/datetimes.py

@@ -181,8 +181,13 @@ class DatetimeIndex(DatetimeTimedeltaMixin):
         If True parse dates in `data` with the year first order.
     dtype : numpy.dtype or DatetimeTZDtype or str, default None
         Note that the only NumPy dtype allowed is `datetime64[ns]`.
-    copy : bool, default False
-        Make a copy of input ndarray.
+    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 up front.
     name : label, default None
         Name to be stored in the index.
 
@@ -669,7 +674,7 @@ def __new__(
         dayfirst: bool = False,
         yearfirst: bool = False,
         dtype: Dtype | None = None,
-        copy: bool = False,
+        copy: bool | None = None,
         name: Hashable | None = None,
     ) -> Self:
         if is_scalar(data):
@@ -679,6 +684,9 @@ def __new__(
 
         name = maybe_extract_name(name, data, cls)
 
+        # GH#63388
+        data, copy = cls._maybe_copy_array_input(data, copy, dtype)
+
         if (
             isinstance(data, DatetimeArray)
             and freq is lib.no_default

pandas/core/indexes/interval.py

@@ -169,8 +169,13 @@ class IntervalIndex(ExtensionIndex):
         neither.
     dtype : dtype or None, default None
         If None, dtype will be inferred.
-    copy : bool, default False
-        Copy the 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, optional
          Name to be stored in the index.
     verify_integrity : bool, default True
@@ -252,12 +257,15 @@ def __new__(
         data,
         closed: IntervalClosedType | None = None,
         dtype: Dtype | None = None,
-        copy: bool = False,
+        copy: bool | None = None,
         name: Hashable | None = None,
         verify_integrity: bool = True,
     ) -> Self:
         name = maybe_extract_name(name, data, cls)
 
+        # GH#63388
+        data, copy = cls._maybe_copy_array_input(data, copy, dtype)
+
         with rewrite_exception("IntervalArray", cls.__name__):
             array = IntervalArray(
                 data,

pandas/core/indexes/period.py

@@ -101,8 +101,13 @@ class PeriodIndex(DatetimeIndexOpsMixin):
         One of pandas period strings or corresponding objects.
     dtype : str or PeriodDtype, default None
         A dtype from which to extract a freq.
-    copy : bool
-        Make a copy of input ndarray.
+    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 : str, default None
         Name of the resulting PeriodIndex.
 
@@ -220,7 +225,7 @@ def __new__(
         data=None,
         freq=None,
         dtype: Dtype | None = None,
-        copy: bool = False,
+        copy: bool | None = None,
         name: Hashable | None = None,
     ) -> Self:
         refs = None
@@ -231,6 +236,9 @@ def __new__(
 
         freq = validate_dtype_freq(dtype, freq)
 
+        # GH#63388
+        data, copy = cls._maybe_copy_array_input(data, copy, dtype)
+
         # PeriodIndex allow PeriodIndex(period_index, freq=different)
         # Let's not encourage that kind of behavior in PeriodArray.
 

pandas/core/indexes/timedeltas.py

@@ -81,8 +81,13 @@ class TimedeltaIndex(DatetimeTimedeltaMixin):
     dtype : numpy.dtype or str, default None
         Valid ``numpy`` dtypes are ``timedelta64[ns]``, ``timedelta64[us]``,
         ``timedelta64[ms]``, and ``timedelta64[s]``.
-    copy : bool
-        Make a copy of input array.
+    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.
 
@@ -158,11 +163,14 @@ def __new__(
         data=None,
         freq=lib.no_default,
         dtype=None,
-        copy: bool = False,
+        copy: bool | None = None,
         name=None,
     ):
         name = maybe_extract_name(name, data, cls)
 
+        # GH#63388
+        data, copy = cls._maybe_copy_array_input(data, copy, dtype)
+
         if is_scalar(data):
             cls._raise_scalar_data_error(data)
 

pandas/tests/arrays/test_datetimelike.py

@@ -707,7 +707,7 @@ def test_array_object_dtype(self, arr1d):
     def test_array_tz(self, arr1d):
         # GH#23524
         arr = arr1d
-        dti = self.index_cls(arr1d)
+        dti = self.index_cls(arr1d, copy=False)
         copy_false = None if np_version_gt2 else False
 
         expected = dti.asi8.view("M8[ns]")

pandas/tests/copy_view/index/test_datetimeindex.py

@@ -1,12 +1,15 @@
+import numpy as np
 import pytest
 
 from pandas import (
     DatetimeIndex,
     Series,
     Timestamp,
+    array,
     date_range,
 )
 import pandas._testing as tm
+from pandas.tests.copy_view.util import get_array
 
 pytestmark = pytest.mark.filterwarnings(
     "ignore:Setting a value on a view:FutureWarning"
@@ -54,3 +57,30 @@ def test_index_values():
     idx = date_range("2019-12-31", periods=3, freq="D")
     result = idx.values
     assert result.flags.writeable is False
+
+
+def test_constructor_copy_input_datetime_ndarray_default():
+    # GH 63388
+    arr = np.array(["2020-01-01", "2020-01-02"], dtype="datetime64[ns]")
+    idx = DatetimeIndex(arr)
+    assert not np.shares_memory(arr, get_array(idx))
+
+
+def test_constructor_copy_input_datetime_ea_default():
+    # GH 63388
+    arr = array(["2020-01-01", "2020-01-02"], dtype="datetime64[ns]")
+    idx = DatetimeIndex(arr)
+    assert not tm.shares_memory(arr, idx.array)
+
+
+def test_series_from_temporary_datetimeindex_readonly_data():
+    # GH 63388
+    arr = np.array(["2020-01-01", "2020-01-02"], dtype="datetime64[ns]")
+    arr.flags.writeable = False
+    ser = Series(DatetimeIndex(arr))
+    assert not np.shares_memory(arr, get_array(ser))
+    ser.iloc[0] = Timestamp("2020-01-01")
+    expected = Series(
+        [Timestamp("2020-01-01"), Timestamp("2020-01-02")], dtype="datetime64[ns]"
+    )
+    tm.assert_series_equal(ser, expected)

pandas/tests/copy_view/index/test_intervalindex.py

@@ -0,0 +1,29 @@
+import numpy as np
+
+from pandas import (
+    Interval,
+    IntervalIndex,
+    Series,
+    array,
+)
+import pandas._testing as tm
+from pandas.tests.copy_view.util import get_array
+
+
+def test_constructor_copy_input_interval_ea_default():
+    # GH 63388
+    arr = array([Interval(0, 1), Interval(1, 2)])
+    idx = IntervalIndex(arr)
+    assert not tm.shares_memory(arr, idx.array)
+
+
+def test_series_from_temporary_intervalindex_readonly_data():
+    # GH 63388
+    arr = array([Interval(0, 1), Interval(1, 2)])
+    arr._left.flags.writeable = False
+    arr._right.flags.writeable = False
+    ser = Series(IntervalIndex(arr))
+    assert not np.shares_memory(arr._left, get_array(ser)._left)
+    ser.iloc[0] = Interval(5, 6)
+    expected = Series([Interval(5, 6), Interval(1, 2)], dtype="interval[int64, right]")
+    tm.assert_series_equal(ser, expected)

pandas/tests/copy_view/index/test_periodindex.py

@@ -1,12 +1,15 @@
+import numpy as np
 import pytest
 
 from pandas import (
     Period,
     PeriodIndex,
     Series,
+    array,
     period_range,
 )
 import pandas._testing as tm
+from pandas.tests.copy_view.util import get_array
 
 pytestmark = pytest.mark.filterwarnings(
     "ignore:Setting a value on a view:FutureWarning"
@@ -21,3 +24,24 @@ def test_periodindex(box):
     expected = idx.copy(deep=True)
     ser.iloc[0] = Period("2020-12-31")
     tm.assert_index_equal(idx, expected)
+
+
+def test_constructor_copy_input_period_ea_default():
+    # GH 63388
+    arr = array(["2020-01-01", "2020-01-02"], dtype="period[D]")
+    idx = PeriodIndex(arr)
+    assert not tm.shares_memory(arr, idx.array)
+
+
+def test_series_from_temporary_periodindex_readonly_data():
+    # GH 63388
+    arr = array(["2020-01-01", "2020-01-02"], dtype="period[D]")
+    arr._ndarray.flags.writeable = False
+    ser = Series(PeriodIndex(arr))
+    assert not np.shares_memory(arr._ndarray, get_array(ser))
+    ser.iloc[0] = Period("2022-01-01", freq="D")
+    expected = Series(
+        [Period("2022-01-01", freq="D"), Period("2020-01-02", freq="D")],
+        dtype="period[D]",
+    )
+    tm.assert_series_equal(ser, expected)