Revert "DEPR: ExtensionOpsMixin -> OpsMixin"

doc/source/whatsnew/v1.2.0.rst

@@ -492,7 +492,6 @@ Deprecations
 - Deprecated :meth:`Index.asi8` for :class:`Index` subclasses other than :class:`.DatetimeIndex`, :class:`.TimedeltaIndex`, and :class:`PeriodIndex` (:issue:`37877`)
 - The ``inplace`` parameter of :meth:`Categorical.remove_unused_categories` is deprecated and will be removed in a future version (:issue:`37643`)
 - The ``null_counts`` parameter of :meth:`DataFrame.info` is deprecated and replaced by ``show_counts``. It will be removed in a future version (:issue:`37999`)
-- :class:`ExtensionOpsMixin` and :class:`ExtensionScalarOpsMixin` are deprecated and will be removed in a future version.  Use ``pd.core.arraylike.OpsMixin`` instead (:issue:`37080`)
 
 .. ---------------------------------------------------------------------------
 

pandas/core/arrays/base.py

@@ -21,7 +21,6 @@
     Union,
     cast,
 )
-import warnings
 
 import numpy as np
 
@@ -1238,21 +1237,6 @@ class ExtensionOpsMixin:
        with NumPy arrays.
     """
 
-    def __init_subclass__(cls, **kwargs):
-        # We use __init_subclass__ to handle deprecations
-        super().__init_subclass__()
-
-        if cls.__name__ != "ExtensionScalarOpsMixin":
-            # We only want to warn for user-defined subclasses,
-            #  and cannot reference ExtensionScalarOpsMixin directly at this point.
-            warnings.warn(
-                "ExtensionOpsMixin and ExtensionScalarOpsMixin are deprecated "
-                "and will be removed in a future version. Use "
-                "pd.core.arraylike.OpsMixin instead.",
-                FutureWarning,
-                stacklevel=2,
-            )
-
     @classmethod
     def _create_arithmetic_method(cls, op):
         raise AbstractMethodError(cls)

pandas/tests/extension/decimal/array.py

@@ -7,13 +7,12 @@
 import numpy as np
 
 from pandas.core.dtypes.base import ExtensionDtype
-from pandas.core.dtypes.cast import maybe_cast_to_extension_array
 from pandas.core.dtypes.common import is_dtype_equal, is_list_like, pandas_dtype
 
 import pandas as pd
 from pandas.api.extensions import no_default, register_extension_dtype
 from pandas.core.arraylike import OpsMixin
-from pandas.core.arrays import ExtensionArray
+from pandas.core.arrays import ExtensionArray, ExtensionScalarOpsMixin
 from pandas.core.indexers import check_array_indexer
 
 
@@ -46,7 +45,7 @@ def _is_numeric(self) -> bool:
         return True
 
 
-class DecimalArray(OpsMixin, ExtensionArray):
+class DecimalArray(OpsMixin, ExtensionScalarOpsMixin, ExtensionArray):
     __array_priority__ = 1000
 
     def __init__(self, values, dtype=None, copy=False, context=None):
@@ -226,46 +225,13 @@ def convert_values(param):
 
         return np.asarray(res, dtype=bool)
 
-    _do_coerce = True  # overriden in DecimalArrayWithoutCoercion
-
-    def _arith_method(self, other, op):
-        def convert_values(param):
-            if isinstance(param, ExtensionArray) or is_list_like(param):
-                ovalues = param
-            else:  # Assume its an object
-                ovalues = [param] * len(self)
-            return ovalues
-
-        lvalues = self
-        rvalues = convert_values(other)
-
-        # If the operator is not defined for the underlying objects,
-        # a TypeError should be raised
-        res = [op(a, b) for (a, b) in zip(lvalues, rvalues)]
-
-        def _maybe_convert(arr):
-            if self._do_coerce:
-                # https://github.com/pandas-dev/pandas/issues/22850
-                # We catch all regular exceptions here, and fall back
-                # to an ndarray.
-                res = maybe_cast_to_extension_array(type(self), arr)
-                if not isinstance(res, type(self)):
-                    # exception raised in _from_sequence; ensure we have ndarray
-                    res = np.asarray(arr)
-            else:
-                res = np.asarray(arr)
-            return res
-
-        if op.__name__ in {"divmod", "rdivmod"}:
-            a, b = zip(*res)
-            return _maybe_convert(a), _maybe_convert(b)
-
-        return _maybe_convert(res)
-
 
 def to_decimal(values, context=None):
     return DecimalArray([decimal.Decimal(x) for x in values], context=context)
 
 
 def make_data():
     return [decimal.Decimal(random.random()) for _ in range(100)]
+
+
+DecimalArray._add_arithmetic_ops()

pandas/tests/extension/decimal/test_decimal.py

@@ -335,7 +335,12 @@ def _from_sequence(cls, scalars, dtype=None, copy=False):
 
 
 class DecimalArrayWithoutCoercion(DecimalArrayWithoutFromSequence):
-    _do_coerce = False
+    @classmethod
+    def _create_arithmetic_method(cls, op):
+        return cls._create_method(op, coerce_to_dtype=False)
+
+
+DecimalArrayWithoutCoercion._add_arithmetic_ops()
 
 
 def test_combine_from_sequence_raises():