TYP: use OpsMixin for DecimalArray

pandas/tests/extension/decimal/array.py

@@ -7,10 +7,11 @@
 import numpy as np
 
 from pandas.core.dtypes.base import ExtensionDtype
-from pandas.core.dtypes.common import is_dtype_equal, pandas_dtype
+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, ExtensionScalarOpsMixin
 from pandas.core.indexers import check_array_indexer
 
@@ -44,7 +45,7 @@ def _is_numeric(self) -> bool:
         return True
 
 
-class DecimalArray(ExtensionArray, ExtensionScalarOpsMixin):
+class DecimalArray(OpsMixin, ExtensionScalarOpsMixin, ExtensionArray):
     __array_priority__ = 1000
 
     def __init__(self, values, dtype=None, copy=False, context=None):
@@ -197,6 +198,25 @@ def _reduce(self, name: str, skipna: bool = True, **kwargs):
             ) from err
         return op(axis=0)
 
+    def _cmp_method(self, other, op):
+        # For use with OpsMixin
+        def convert_values(param):
+            if isinstance(param, ExtensionArray) or is_list_like(param):
+                ovalues = param
+            else:
+                # Assume it's 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)]
+
+        return np.asarray(res, dtype=bool)
+
 
 def to_decimal(values, context=None):
     return DecimalArray([decimal.Decimal(x) for x in values], context=context)
@@ -207,4 +227,3 @@ def make_data():
 
 
 DecimalArray._add_arithmetic_ops()
-DecimalArray._add_comparison_ops()