Test chained assignment detection for Python 3.14

pandas/_libs/internals.pyx

@@ -1,6 +1,9 @@
 from collections import defaultdict
+import sys
+import warnings
 
 cimport cython
+from cpython cimport PY_VERSION_HEX
 from cpython.object cimport PyObject
 from cpython.pyport cimport PY_SSIZE_T_MAX
 from cpython.slice cimport PySlice_GetIndicesEx
@@ -20,6 +23,7 @@ from numpy cimport (
 cnp.import_array()
 
 from pandas._libs.algos import ensure_int64
+from pandas.errors import ChainedAssignmentError
 
 from pandas._libs.util cimport (
     is_array,
@@ -996,3 +1000,59 @@ cdef class BlockValuesRefs:
                 return self._has_reference_maybe_locked()
         ELSE:
             return self._has_reference_maybe_locked()
+
+
+cdef extern from "Python.h":
+    """
+    #if PY_VERSION_HEX < 0x030E0000
+    int __Pyx_PyUnstable_Object_IsUniqueReferencedTemporary(PyObject *ref)
+    {
+        return 0;
+    }
+    #else
+    #define __Pyx_PyUnstable_Object_IsUniqueReferencedTemporary \
+        PyUnstable_Object_IsUniqueReferencedTemporary
+    #endif
+    """
+    int PyUnstable_Object_IsUniqueReferencedTemporary\
+        "__Pyx_PyUnstable_Object_IsUniqueReferencedTemporary"(object o) except -1
+
+
+cdef inline bint _is_unique_referenced_temporary(object obj) except -1:
+    if PY_VERSION_HEX >= 0x030E0000:
+        return PyUnstable_Object_IsUniqueReferencedTemporary(obj)
+    else:
+        return sys.getrefcount(obj) <= 1
+
+
+# # Python version compatibility for PyUnstable_Object_IsUniqueReferencedTemporary
+# IF PY_VERSION_HEX >= 0x030E0000:
+#     # Python 3.14+ has PyUnstable_Object_IsUniqueReferencedTemporary
+#     cdef inline bint _is_unique_referenced_temporary(object obj) except -1:
+#         return PyUnstable_Object_IsUniqueReferencedTemporary(obj)
+# ELSE:
+#     # Fallback for older Python versions using sys.getrefcount
+#     cdef inline bint _is_unique_referenced_temporary(object obj) except -1:
+#         # sys.getrefcount includes the reference from getrefcount itself
+#         # So if refcount is 2, it means only one external reference exists
+#         return sys.getrefcount(obj) == 2
+
+
+# @cython.auto_pickle(False)
+cdef class SetitemMixin:
+
+    def __setitem__(self, key, value):
+        cdef bint is_unique = _is_unique_referenced_temporary(self)
+        # print("Refcount self: ", sys.getrefcount(self))
+        # print("Is unique referenced temporary: ", is_unique)
+        if is_unique:
+            warnings.warn(
+                "A value is trying to be set on a copy of a DataFrame or Series "
+                "through chained assignment.",
+                ChainedAssignmentError,
+                stacklevel=1,
+                )
+        self._setitem(key, value)
+
+    def __delitem__(self, key) -> None:
+        self._delitem(key)

pandas/_libs/tslib.pyx

@@ -267,6 +267,7 @@ cpdef array_to_datetime(
     str unit_for_numerics=None,
 ):
     """
+    TODO no longer up to date
     Converts a 1D array of date-like values to a numpy array of either:
         1) datetime64[ns] data
         2) datetime.datetime objects, if OutOfBoundsDatetime or TypeError

pandas/compat/pickle_compat.py

@@ -22,6 +22,7 @@
     PeriodArray,
     TimedeltaArray,
 )
+from pandas.core.generic import NDFrame
 from pandas.core.internals import BlockManager
 
 if TYPE_CHECKING:
@@ -90,6 +91,10 @@ def load_reduce(self) -> None:
                 cls = args[0]
                 stack[-1] = NDArrayBacked.__new__(*args)
                 return
+            elif args and issubclass(args[0], NDFrame):
+                cls = args[0]
+                stack[-1] = cls.__new__(cls)
+                return
             raise
 
     dispatch[pickle.REDUCE[0]] = load_reduce  # type: ignore[assignment]

pandas/core/frame.py

@@ -47,6 +47,7 @@
     properties,
 )
 from pandas._libs.hashtable import duplicated
+from pandas._libs.internals import SetitemMixin
 from pandas._libs.lib import is_range_indexer
 from pandas.compat import PYPY
 from pandas.compat._constants import REF_COUNT
@@ -58,7 +59,6 @@
 )
 from pandas.errors.cow import (
     _chained_assignment_method_msg,
-    _chained_assignment_msg,
 )
 from pandas.util._decorators import (
     Appender,
@@ -511,7 +511,7 @@
 
 
 @set_module("pandas")
-class DataFrame(NDFrame, OpsMixin):
+class DataFrame(SetitemMixin, NDFrame, OpsMixin):
     """
     Two-dimensional, size-mutable, potentially heterogeneous tabular data.
 
@@ -660,6 +660,11 @@ class DataFrame(NDFrame, OpsMixin):
     #  and ExtensionArray.  Should NOT be overridden by subclasses.
     __pandas_priority__ = 4000
 
+    # override those to avoid inheriting from SetitemMixin (cython generates
+    # them by default)
+    __reduce__ = object.__reduce__
+    __setstate__ = NDFrame.__setstate__
+
     @property
     def _constructor(self) -> type[DataFrame]:
         return DataFrame
@@ -4212,7 +4217,7 @@ def isetitem(self, loc, value) -> None:
         arraylike, refs = self._sanitize_column(value)
         self._iset_item_mgr(loc, arraylike, inplace=False, refs=refs)
 
-    def __setitem__(self, key, value) -> None:
+    def _setitem(self, key, value) -> None:
         """
         Set item(s) in DataFrame by key.
 
@@ -4296,11 +4301,11 @@ def __setitem__(self, key, value) -> None:
         z  3  50
         # Values for 'a' and 'b' are completely ignored!
         """
-        if not PYPY:
-            if sys.getrefcount(self) <= 3:
-                warnings.warn(
-                    _chained_assignment_msg, ChainedAssignmentError, stacklevel=2
-                )
+        # if not PYPY:
+        #     if sys.getrefcount(self) <= 3:
+        #         warnings.warn(
+        #             _chained_assignment_msg, ChainedAssignmentError, stacklevel=2
+        #         )
 
         key = com.apply_if_callable(key, self)
 

pandas/core/generic.py

@@ -4257,8 +4257,9 @@ def _slice(self, slobj: slice, axis: AxisInt = 0) -> Self:
         result = result.__finalize__(self)
         return result
 
+    # __delitem__ is implemented in SetitemMixin and dispatches to this method
     @final
-    def __delitem__(self, key) -> None:
+    def _delitem(self, key) -> None:
         """
         Delete item
         """

pandas/core/indexing.py

@@ -2581,6 +2581,12 @@ def __getitem__(self, key):
         return super().__getitem__(key)
 
     def __setitem__(self, key, value) -> None:
+        if not PYPY:
+            if sys.getrefcount(self.obj) <= 2:
+                warnings.warn(
+                    _chained_assignment_msg, ChainedAssignmentError, stacklevel=2
+                )
+
         if self.ndim == 2 and not self._axes_are_unique:
             # GH#33041 fall back to .loc
             if not isinstance(key, tuple) or not all(is_scalar(x) for x in key):
@@ -2605,6 +2611,15 @@ def _convert_key(self, key):
                 raise ValueError("iAt based indexing can only have integer indexers")
         return key
 
+    def __setitem__(self, key, value) -> None:
+        if not PYPY:
+            if sys.getrefcount(self.obj) <= 2:
+                warnings.warn(
+                    _chained_assignment_msg, ChainedAssignmentError, stacklevel=2
+                )
+
+        return super().__setitem__(key, value)
+
 
 def _tuplify(ndim: int, loc: Hashable) -> tuple[Hashable | slice, ...]:
     """

pandas/core/series.py

@@ -32,6 +32,7 @@
     properties,
     reshape,
 )
+from pandas._libs.internals import SetitemMixin
 from pandas._libs.lib import is_range_indexer
 from pandas.compat import PYPY
 from pandas.compat._constants import REF_COUNT
@@ -43,7 +44,6 @@
 )
 from pandas.errors.cow import (
     _chained_assignment_method_msg,
-    _chained_assignment_msg,
 )
 from pandas.util._decorators import (
     Appender,
@@ -234,7 +234,7 @@
 # class "NDFrame")
 # definition in base class "NDFrame"
 @set_module("pandas")
-class Series(base.IndexOpsMixin, NDFrame):  # type: ignore[misc]
+class Series(SetitemMixin, base.IndexOpsMixin, NDFrame):  # type: ignore[misc]
     """
     One-dimensional ndarray with axis labels (including time series).
 
@@ -362,6 +362,11 @@ class Series(base.IndexOpsMixin, NDFrame):  # type: ignore[misc]
     )
     _mgr: SingleBlockManager
 
+    # override those to avoid inheriting from SetitemMixin (cython generates
+    # them by default)
+    __reduce__ = object.__reduce__
+    __setstate__ = NDFrame.__setstate__
+
     # ----------------------------------------------------------------------
     # Constructors
 
@@ -1058,12 +1063,12 @@ def _get_value(self, label, takeable: bool = False):
         else:
             return self.iloc[loc]
 
-    def __setitem__(self, key, value) -> None:
-        if not PYPY:
-            if sys.getrefcount(self) <= 3:
-                warnings.warn(
-                    _chained_assignment_msg, ChainedAssignmentError, stacklevel=2
-                )
+    def _setitem(self, key, value) -> None:
+        # if not PYPY:
+        #     if sys.getrefcount(self) <= 3:
+        #         warnings.warn(
+        #             _chained_assignment_msg, ChainedAssignmentError, stacklevel=2
+        #         )
 
         check_dict_or_set_indexers(key)
         key = com.apply_if_callable(key, self)

pandas/tests/copy_view/test_chained_assignment_deprecation.py

@@ -31,3 +31,71 @@ def test_frame_setitem(indexer):
 
     with tm.raises_chained_assignment_error():
         df[0:3][indexer] = 10
+
+
+@pytest.mark.parametrize(
+    "indexer", [0, [0, 1], slice(0, 2), np.array([True, False, True])]
+)
+def test_series_iloc_setitem(indexer):
+    df = DataFrame({"a": [1, 2, 3], "b": 1})
+
+    with tm.raises_chained_assignment_error():
+        df["a"].iloc[indexer] = 0
+
+
+@pytest.mark.parametrize(
+    "indexer", [0, [0, 1], slice(0, 2), np.array([True, False, True])]
+)
+def test_frame_iloc_setitem(indexer):
+    df = DataFrame({"a": [1, 2, 3, 4, 5], "b": 1})
+
+    with tm.raises_chained_assignment_error():
+        df[0:3].iloc[indexer] = 10
+
+
+@pytest.mark.parametrize(
+    "indexer", [0, [0, 1], slice(0, 2), np.array([True, False, True])]
+)
+def test_series_loc_setitem(indexer):
+    df = DataFrame({"a": [1, 2, 3], "b": 1})
+
+    with tm.raises_chained_assignment_error():
+        df["a"].loc[indexer] = 0
+
+
+@pytest.mark.parametrize(
+    "indexer", [0, [0, 1], (0, "a"), slice(0, 2), np.array([True, False, True])]
+)
+def test_frame_loc_setitem(indexer):
+    df = DataFrame({"a": [1, 2, 3, 4, 5], "b": 1})
+
+    with tm.raises_chained_assignment_error():
+        df[0:3].loc[indexer] = 10
+
+
+def test_series_at_setitem():
+    df = DataFrame({"a": [1, 2, 3], "b": 1})
+
+    with tm.raises_chained_assignment_error():
+        df["a"].at[0] = 0
+
+
+def test_frame_at_setitem():
+    df = DataFrame({"a": [1, 2, 3, 4, 5], "b": 1})
+
+    with tm.raises_chained_assignment_error():
+        df[0:3].at[0, "a"] = 10
+
+
+def test_series_iat_setitem():
+    df = DataFrame({"a": [1, 2, 3], "b": 1})
+
+    with tm.raises_chained_assignment_error():
+        df["a"].iat[0] = 0
+
+
+def test_frame_iat_setitem():
+    df = DataFrame({"a": [1, 2, 3, 4, 5], "b": 1})
+
+    with tm.raises_chained_assignment_error():
+        df[0:3].iat[0, 0] = 10

pandas/tests/io/test_spss.py

@@ -11,10 +11,6 @@
 pyreadstat = pytest.importorskip("pyreadstat")
 
 
-# TODO(CoW) - detection of chained assignment in cython
-# https://github.com/pandas-dev/pandas/issues/51315
-@pytest.mark.filterwarnings("ignore::pandas.errors.ChainedAssignmentError")
-@pytest.mark.filterwarnings("ignore:ChainedAssignmentError:FutureWarning")
 @pytest.mark.parametrize("path_klass", [lambda p: p, Path])
 def test_spss_labelled_num(path_klass, datapath):
     # test file from the Haven project (https://haven.tidyverse.org/)
@@ -31,8 +27,6 @@ def test_spss_labelled_num(path_klass, datapath):
     tm.assert_frame_equal(df, expected)
 
 
-@pytest.mark.filterwarnings("ignore::pandas.errors.ChainedAssignmentError")
-@pytest.mark.filterwarnings("ignore:ChainedAssignmentError:FutureWarning")
 def test_spss_labelled_num_na(datapath):
     # test file from the Haven project (https://haven.tidyverse.org/)
     # Licence at LICENSES/HAVEN_LICENSE, LICENSES/HAVEN_MIT
@@ -48,8 +42,6 @@ def test_spss_labelled_num_na(datapath):
     tm.assert_frame_equal(df, expected)
 
 
-@pytest.mark.filterwarnings("ignore::pandas.errors.ChainedAssignmentError")
-@pytest.mark.filterwarnings("ignore:ChainedAssignmentError:FutureWarning")
 def test_spss_labelled_str(datapath):
     # test file from the Haven project (https://haven.tidyverse.org/)
     # Licence at LICENSES/HAVEN_LICENSE, LICENSES/HAVEN_MIT
@@ -65,8 +57,6 @@ def test_spss_labelled_str(datapath):
     tm.assert_frame_equal(df, expected)
 
 
-@pytest.mark.filterwarnings("ignore::pandas.errors.ChainedAssignmentError")
-@pytest.mark.filterwarnings("ignore:ChainedAssignmentError:FutureWarning")
 def test_spss_kwargs(datapath):
     # test file from the Haven project (https://haven.tidyverse.org/)
     # Licence at LICENSES/HAVEN_LICENSE, LICENSES/HAVEN_MIT
@@ -81,8 +71,6 @@ def test_spss_kwargs(datapath):
     tm.assert_frame_equal(df, expected)
 
 
-@pytest.mark.filterwarnings("ignore::pandas.errors.ChainedAssignmentError")
-@pytest.mark.filterwarnings("ignore:ChainedAssignmentError:FutureWarning")
 def test_spss_umlauts(datapath):
     # test file from the Haven project (https://haven.tidyverse.org/)
     # Licence at LICENSES/HAVEN_LICENSE, LICENSES/HAVEN_MIT
@@ -140,8 +128,6 @@ def test_invalid_dtype_backend():
         pd.read_spss("test", dtype_backend="numpy")
 
 
-@pytest.mark.filterwarnings("ignore::pandas.errors.ChainedAssignmentError")
-@pytest.mark.filterwarnings("ignore:ChainedAssignmentError:FutureWarning")
 def test_spss_metadata(datapath):
     # GH 54264
     fname = datapath("io", "data", "spss", "labelled-num.sav")