Backport PR #51926 on branch 2.0.x (CoW: change ChainedAssignmentError exception to a warning)

doc/source/user_guide/copy_on_write.rst

@@ -114,10 +114,11 @@ two subsequent indexing operations, e.g.
 The column ``foo`` is updated where the column ``bar`` is greater than 5.
 This violates the CoW principles though, because it would have to modify the
 view ``df["foo"]`` and ``df`` in one step. Hence, chained assignment will
-consistently never work and raise a ``ChainedAssignmentError`` with CoW enabled:
+consistently never work and raise a ``ChainedAssignmentError`` warning
+with CoW enabled:
 
 .. ipython:: python
-    :okexcept:
+    :okwarning:
 
     df = pd.DataFrame({"foo": [1, 2, 3], "bar": [4, 5, 6]})
     df["foo"][df["bar"] > 5] = 100

doc/source/whatsnew/v2.0.0.rst

@@ -191,12 +191,12 @@ Copy-on-Write improvements
   of those Series objects for the columns of the DataFrame (:issue:`50777`)
 
 - Trying to set values using chained assignment (for example, ``df["a"][1:3] = 0``)
-  will now always raise an exception when Copy-on-Write is enabled. In this mode,
+  will now always raise an warning when Copy-on-Write is enabled. In this mode,
   chained assignment can never work because we are always setting into a temporary
   object that is the result of an indexing operation (getitem), which under
   Copy-on-Write always behaves as a copy. Thus, assigning through a chain
   can never update the original Series or DataFrame. Therefore, an informative
-  error is raised to the user instead of silently doing nothing (:issue:`49467`)
+  warning is raised to the user to avoid silently doing nothing (:issue:`49467`)
 
 - :meth:`DataFrame.replace` will now respect the Copy-on-Write mechanism
   when ``inplace=True``.

pandas/_testing/contexts.py

@@ -208,9 +208,9 @@ def raises_chained_assignment_error():
 
         return nullcontext()
     else:
-        import pytest
+        from pandas._testing import assert_produces_warning
 
-        return pytest.raises(
+        return assert_produces_warning(
             ChainedAssignmentError,
             match=(
                 "A value is trying to be set on a copy of a DataFrame or Series "

pandas/core/frame.py

@@ -3904,7 +3904,9 @@ def isetitem(self, loc, value) -> None:
     def __setitem__(self, key, value):
         if not PYPY and using_copy_on_write():
             if sys.getrefcount(self) <= 3:
-                raise ChainedAssignmentError(_chained_assignment_msg)
+                warnings.warn(
+                    _chained_assignment_msg, ChainedAssignmentError, stacklevel=2
+                )
 
         key = com.apply_if_callable(key, self)
 

pandas/core/indexing.py

@@ -10,6 +10,7 @@
     cast,
     final,
 )
+import warnings
 
 import numpy as np
 
@@ -831,7 +832,9 @@ def _ensure_listlike_indexer(self, key, axis=None, value=None) -> None:
     def __setitem__(self, key, value) -> None:
         if not PYPY and using_copy_on_write():
             if sys.getrefcount(self.obj) <= 2:
-                raise ChainedAssignmentError(_chained_assignment_msg)
+                warnings.warn(
+                    _chained_assignment_msg, ChainedAssignmentError, stacklevel=2
+                )
 
         check_dict_or_set_indexers(key)
         if isinstance(key, tuple):

pandas/core/series.py

@@ -1121,7 +1121,9 @@ def _get_value(self, label, takeable: bool = False):
     def __setitem__(self, key, value) -> None:
         if not PYPY and using_copy_on_write():
             if sys.getrefcount(self) <= 3:
-                raise ChainedAssignmentError(_chained_assignment_msg)
+                warnings.warn(
+                    _chained_assignment_msg, ChainedAssignmentError, stacklevel=2
+                )
 
         check_dict_or_set_indexers(key)
         key = com.apply_if_callable(key, self)

pandas/errors/__init__.py

@@ -320,9 +320,9 @@ class SettingWithCopyWarning(Warning):
     """
 
 
-class ChainedAssignmentError(ValueError):
+class ChainedAssignmentError(Warning):
     """
-    Exception raised when trying to set using chained assignment.
+    Warning raised when trying to set using chained assignment.
 
     When the ``mode.copy_on_write`` option is enabled, chained assignment can
     never work. In such a situation, we are always setting into a temporary

pandas/tests/io/test_spss.py

@@ -3,15 +3,15 @@
 import numpy as np
 import pytest
 
-import pandas.util._test_decorators as td
-
 import pandas as pd
 import pandas._testing as tm
 
 pyreadstat = pytest.importorskip("pyreadstat")
 
 
-@td.skip_copy_on_write_not_yet_implemented
+# 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.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/)
@@ -27,7 +27,7 @@ def test_spss_labelled_num(path_klass, datapath):
     tm.assert_frame_equal(df, expected)
 
 
-@td.skip_copy_on_write_not_yet_implemented
+@pytest.mark.filterwarnings("ignore::pandas.errors.ChainedAssignmentError")
 def test_spss_labelled_num_na(datapath):
     # test file from the Haven project (https://haven.tidyverse.org/)
     fname = datapath("io", "data", "spss", "labelled-num-na.sav")
@@ -42,7 +42,7 @@ def test_spss_labelled_num_na(datapath):
     tm.assert_frame_equal(df, expected)
 
 
-@td.skip_copy_on_write_not_yet_implemented
+@pytest.mark.filterwarnings("ignore::pandas.errors.ChainedAssignmentError")
 def test_spss_labelled_str(datapath):
     # test file from the Haven project (https://haven.tidyverse.org/)
     fname = datapath("io", "data", "spss", "labelled-str.sav")
@@ -57,7 +57,7 @@ def test_spss_labelled_str(datapath):
     tm.assert_frame_equal(df, expected)
 
 
-@td.skip_copy_on_write_not_yet_implemented
+@pytest.mark.filterwarnings("ignore::pandas.errors.ChainedAssignmentError")
 def test_spss_umlauts(datapath):
     # test file from the Haven project (https://haven.tidyverse.org/)
     fname = datapath("io", "data", "spss", "umlauts.sav")