CoW: add readonly flag to ExtensionArrays, return read-only EA/ndarray in .array/EA.to_numpy()

pandas/_libs/ops.pyx

@@ -177,7 +177,7 @@ def vec_compare(ndarray[object] left, ndarray[object] right, object op) -> ndarr
 
 @cython.wraparound(False)
 @cython.boundscheck(False)
-def scalar_binop(object[:] values, object val, object op) -> ndarray:
+def scalar_binop(ndarray[object] values, object val, object op) -> ndarray:
     """
     Apply the given binary operator `op` between each element of the array
     `values` and the scalar `val`.
@@ -214,7 +214,7 @@ def scalar_binop(object[:] values, object val, object op) -> ndarray:
 
 @cython.wraparound(False)
 @cython.boundscheck(False)
-def vec_binop(object[:] left, object[:] right, object op) -> ndarray:
+def vec_binop(ndarray[object] left, ndarray[object] right, object op) -> ndarray:
     """
     Apply the given binary operator `op` pointwise to the elements of
     arrays `left` and `right`.

pandas/core/arrays/_mixins.py

@@ -252,6 +252,9 @@ def shift(self, periods: int = 1, fill_value=None) -> Self:
         return self._from_backing_data(new_values)
 
     def __setitem__(self, key, value) -> None:
+        if self._readonly:
+            raise ValueError("Cannot modify readonly array")
+
         key = check_array_indexer(self, key)
         value = self._validate_setitem_value(value)
         self._ndarray[key] = value

pandas/core/arrays/arrow/array.py

@@ -1967,6 +1967,9 @@ def __setitem__(self, key, value) -> None:
         -------
         None
         """
+        if self._readonly:
+            raise ValueError("Cannot modify readonly array")
+
         # GH50085: unwrap 1D indexers
         if isinstance(key, tuple) and len(key) == 1:
             key = key[0]

pandas/core/arrays/base.py

@@ -40,6 +40,7 @@
     validate_insert_loc,
 )
 
+from pandas.core.dtypes.astype import astype_is_view
 from pandas.core.dtypes.cast import maybe_cast_pointwise_result
 from pandas.core.dtypes.common import (
     is_list_like,
@@ -269,6 +270,8 @@ class ExtensionArray:
     #  strictly less than 2000 to be below Index.__pandas_priority__.
     __pandas_priority__ = 1000
 
+    _readonly = False
+
     # ------------------------------------------------------------------------
     # Constructors
     # ------------------------------------------------------------------------
@@ -482,6 +485,11 @@ def __setitem__(self, key, value) -> None:
         Returns
         -------
         None
+
+        Raises
+        ------
+        ValueError
+            If the array is readonly and modification is attempted.
         """
         # Some notes to the ExtensionArray implementer who may have ended up
         # here. While this method is not required for the interface, if you
@@ -501,6 +509,10 @@ def __setitem__(self, key, value) -> None:
         #   __init__ method coerces that value, then so should __setitem__
         # Note, also, that Series/DataFrame.where internally use __setitem__
         # on a copy of the data.
+        # Check if the array is readonly
+        if self._readonly:
+            raise ValueError("Cannot modify readonly array")
+
         raise NotImplementedError(f"{type(self)} does not implement __setitem__.")
 
     def __len__(self) -> int:
@@ -595,8 +607,14 @@ def to_numpy(
         result = np.asarray(self, dtype=dtype)
         if copy or na_value is not lib.no_default:
             result = result.copy()
+        elif self._readonly and astype_is_view(self.dtype, result.dtype):
+            # If the ExtensionArray is readonly, make the numpy array readonly too
+            result = result.view()
+            result.flags.writeable = False
+
         if na_value is not lib.no_default:
             result[self.isna()] = na_value  # type: ignore[index]
+
         return result
 
     # ------------------------------------------------------------------------

pandas/core/arrays/datetimelike.py

@@ -368,7 +368,12 @@ def __array__(
 
         if copy is True:
             return np.array(self._ndarray, dtype=dtype)
-        return self._ndarray
+
+        result = self._ndarray
+        if self._readonly:
+            result = result.view()
+            result.flags.writeable = False
+        return result
 
     @overload
     def __getitem__(self, key: ScalarIndexer) -> DTScalarOrNaT: ...

pandas/core/arrays/interval.py

@@ -729,6 +729,9 @@ def __getitem__(self, key: PositionalIndexer) -> Self | IntervalOrNA:
         return self._simple_new(left, right, dtype=self.dtype)  # type: ignore[arg-type]
 
     def __setitem__(self, key, value) -> None:
+        if self._readonly:
+            raise ValueError("Cannot modify readonly array")
+
         value_left, value_right = self._validate_setitem_value(value)
         key = check_array_indexer(self, key)
 

pandas/core/arrays/masked.py

@@ -23,6 +23,7 @@
 from pandas.errors import AbstractMethodError
 from pandas.util._decorators import doc
 
+from pandas.core.dtypes.astype import astype_is_view
 from pandas.core.dtypes.base import ExtensionDtype
 from pandas.core.dtypes.common import (
     is_bool,
@@ -290,6 +291,9 @@ def _validate_setitem_value(self, value):
         raise TypeError(f"Invalid value '{value!s}' for dtype '{self.dtype}'")
 
     def __setitem__(self, key, value) -> None:
+        if self._readonly:
+            raise ValueError("Cannot modify readonly array")
+
         key = check_array_indexer(self, key)
 
         if is_scalar(value):
@@ -520,6 +524,9 @@ def to_numpy(
             with warnings.catch_warnings():
                 warnings.filterwarnings("ignore", category=RuntimeWarning)
                 data = self._data.astype(dtype, copy=copy)
+            if self._readonly and astype_is_view(self.dtype, dtype):
+                data = data.view()
+                data.flags.writeable = False
         return data
 
     @doc(ExtensionArray.tolist)
@@ -596,7 +603,12 @@ def __array__(
         if copy is False:
             if not self._hasna:
                 # special case, here we can simply return the underlying data
-                return np.array(self._data, dtype=dtype, copy=copy)
+                result = np.array(self._data, dtype=dtype, copy=copy)
+                # If the ExtensionArray is readonly, make the numpy array readonly too
+                if self._readonly:
+                    result = result.view()
+                    result.flags.writeable = False
+                return result
             raise ValueError(
                 "Unable to avoid copy while creating an array as requested."
             )

pandas/core/arrays/numpy_.py

@@ -12,7 +12,10 @@
 from pandas._libs.tslibs import is_supported_dtype
 from pandas.compat.numpy import function as nv
 
-from pandas.core.dtypes.astype import astype_array
+from pandas.core.dtypes.astype import (
+    astype_array,
+    astype_is_view,
+)
 from pandas.core.dtypes.cast import construct_1d_object_array_from_listlike
 from pandas.core.dtypes.common import pandas_dtype
 from pandas.core.dtypes.dtypes import NumpyEADtype
@@ -160,8 +163,19 @@ def __array__(
     ) -> np.ndarray:
         if copy is not None:
             # Note: branch avoids `copy=None` for NumPy 1.x support
-            return np.array(self._ndarray, dtype=dtype, copy=copy)
-        return np.asarray(self._ndarray, dtype=dtype)
+            result = np.array(self._ndarray, dtype=dtype, copy=copy)
+        else:
+            result = np.asarray(self._ndarray, dtype=dtype)
+
+        if (
+            self._readonly
+            and not copy
+            and (dtype is None or astype_is_view(self.dtype, dtype))
+        ):
+            result = result.view()
+            result.flags.writeable = False
+
+        return result
 
     def __array_ufunc__(self, ufunc: np.ufunc, method: str, *inputs, **kwargs):
         # Lightly modified version of
@@ -512,6 +526,9 @@ def to_numpy(
             result[mask] = na_value
         else:
             result = self._ndarray
+            if not copy and self._readonly:
+                result = result.view()
+                result.flags.writeable = False
 
         result = np.asarray(result, dtype=dtype)
 

pandas/core/arrays/period.py

@@ -393,7 +393,11 @@ def __array__(
             # For NumPy 1.x compatibility we cannot use copy=None.  And
             # `copy=False` has the meaning of `copy=None` here:
             if not copy:
-                return np.asarray(self.asi8, dtype=dtype)
+                result = np.asarray(self.asi8, dtype=dtype)
+                if self._readonly:
+                    result = result.view()
+                    result.flags.writeable = False
+                return result
             else:
                 return np.array(self.asi8, dtype=dtype)
 

pandas/core/arrays/sparse/array.py

@@ -562,7 +562,11 @@ def __array__(
             if copy is True:
                 return np.array(self.sp_values)
             else:
-                return self.sp_values
+                result = self.sp_values
+                if self._readonly:
+                    result = result.view()
+                    result.flags.writeable = False
+                return result
 
         if copy is False:
             raise ValueError(
@@ -591,6 +595,8 @@ def __array__(
         return out
 
     def __setitem__(self, key, value) -> None:
+        if self._readonly:
+            raise ValueError("Cannot modify readonly array")
         # I suppose we could allow setting of non-fill_value elements.
         # TODO(SparseArray.__setitem__): remove special cases in
         # ExtensionBlock.where
@@ -969,6 +975,8 @@ def __getitem__(
             # _NestedSequence[Union[bool, int]]], ...]]"
             data_slice = self.to_dense()[key]  # type: ignore[index]
         elif isinstance(key, slice):
+            if key == slice(None):
+                return type(self)._simple_new(self.sp_values, self.sp_index, self.dtype)
             # Avoid densifying when handling contiguous slices
             if key.step is None or key.step == 1:
                 start = 0 if key.start is None else key.start

pandas/core/arrays/string_.py

@@ -769,6 +769,9 @@ def _maybe_convert_setitem_value(self, value):
         return value
 
     def __setitem__(self, key, value) -> None:
+        if self._readonly:
+            raise ValueError("Cannot modify readonly array")
+
         value = self._maybe_convert_setitem_value(value)
 
         key = check_array_indexer(self, key)

pandas/core/dtypes/astype.py

@@ -24,8 +24,12 @@
     pandas_dtype,
 )
 from pandas.core.dtypes.dtypes import (
+    CategoricalDtype,
+    DatetimeTZDtype,
     ExtensionDtype,
+    IntervalDtype,
     NumpyEADtype,
+    PeriodDtype,
 )
 
 if TYPE_CHECKING:
@@ -283,6 +287,16 @@ def astype_is_view(dtype: DtypeObj, new_dtype: DtypeObj) -> bool:
         new_dtype = getattr(new_dtype, "numpy_dtype", new_dtype)
         return getattr(dtype, "unit", None) == getattr(new_dtype, "unit", None)
 
+    elif new_dtype == object and isinstance(
+        dtype, (DatetimeTZDtype, PeriodDtype, IntervalDtype)
+    ):
+        return False
+
+    elif isinstance(dtype, CategoricalDtype) and not isinstance(
+        new_dtype, CategoricalDtype
+    ):
+        return False
+
     numpy_dtype = getattr(dtype, "numpy_dtype", None)
     new_numpy_dtype = getattr(new_dtype, "numpy_dtype", None)
 

pandas/core/indexes/base.py

@@ -4972,6 +4972,8 @@ def array(self) -> ExtensionArray:
             from pandas.core.arrays.numpy_ import NumpyExtensionArray
 
             array = NumpyExtensionArray(array)
+        array = array.view()
+        array._readonly = True
         return array
 
     @property

pandas/core/internals/blocks.py

@@ -2359,7 +2359,9 @@ def external_values(values: ArrayLike) -> ArrayLike:
     if isinstance(values, np.ndarray):
         values = values.view()
         values.flags.writeable = False
-
-    # TODO(CoW) we should also mark our ExtensionArrays as read-only
+    else:
+        # ExtensionArrays
+        values = values.view()
+        values._readonly = True
 
     return values

pandas/core/series.py

@@ -820,7 +820,10 @@ def _references(self) -> BlockValuesRefs:
     @Appender(base.IndexOpsMixin.array.__doc__)  # type: ignore[prop-decorator]
     @property
     def array(self) -> ExtensionArray:
-        return self._mgr.array_values()
+        arr = self._mgr.array_values()
+        arr = arr.view()
+        arr._readonly = True
+        return arr
 
     def __len__(self) -> int:
         """

pandas/tests/arrays/integer/test_indexing.py

@@ -12,7 +12,7 @@ def test_array_setitem_nullable_boolean_mask():
 
 def test_array_setitem():
     # GH 31446
-    arr = pd.Series([1, 2], dtype="Int64").array
+    arr = pd.array([1, 2], dtype="Int64")
     arr[arr > 1] = 1
 
     expected = pd.array([1, 1], dtype="Int64")

pandas/tests/arrays/numpy_/test_numpy.py

@@ -159,13 +159,6 @@ def test_to_numpy():
 # Setitem
 
 
-def test_setitem_series():
-    ser = pd.Series([1, 2, 3])
-    ser.array[0] = 10
-    expected = pd.Series([10, 2, 3])
-    tm.assert_series_equal(ser, expected)
-
-
 def test_setitem(any_numpy_array):
     nparr = any_numpy_array
     arr = NumpyExtensionArray(nparr, copy=True)

pandas/tests/arrays/test_datetimelike.py

@@ -1248,8 +1248,8 @@ def test_invalid_nat_setitem_array(arr, non_casting_nats):
 @pytest.mark.parametrize(
     "arr",
     [
-        pd.date_range("2000", periods=4).array,
-        pd.timedelta_range("2000", periods=4).array,
+        pd.date_range("2000", periods=4).array.copy(),
+        pd.timedelta_range("2000", periods=4).array.copy(),
     ],
 )
 def test_to_numpy_extra(arr):

pandas/tests/base/test_conversion.py

@@ -285,7 +285,7 @@ def test_array(arr, attr, index_or_series):
         arr = getattr(arr, attr)
         result = getattr(result, attr)
 
-    assert result is arr
+    assert np.shares_memory(result, arr)
 
 
 def test_array_multiindex_raises():