CLN: ops, unnecessary mixin

pandas/core/arrays/datetimelike.py

@@ -75,6 +75,7 @@
     from pandas.core.arrays import DatetimeArray, TimedeltaArray
 
 DTScalarOrNaT = Union[DatetimeLikeScalar, NaTType]
+DatetimeLikeArrayT = TypeVar("DatetimeLikeArrayT", bound="DatetimeLikeArrayMixin")
 
 
 class InvalidComparison(Exception):
@@ -86,7 +87,20 @@ class InvalidComparison(Exception):
     pass
 
 
-class AttributesMixin:
+class DatetimeLikeArrayMixin(OpsMixin, NDArrayBackedExtensionArray):
+    """
+    Shared Base/Mixin class for DatetimeArray, TimedeltaArray, PeriodArray
+
+    Assumes that __new__/__init__ defines:
+        _data
+        _freq
+
+    and that the inheriting class has methods:
+        _generate_range
+    """
+
+    _is_recognized_dtype: Callable[[DtypeObj], bool]
+    _recognized_scalars: Tuple[Type, ...]
     _data: np.ndarray
 
     def __init__(self, data, dtype=None, freq=None, copy=False):
@@ -184,25 +198,6 @@ def _check_compatible_with(
         """
         raise AbstractMethodError(self)
 
-
-DatetimeLikeArrayT = TypeVar("DatetimeLikeArrayT", bound="DatetimeLikeArrayMixin")
-
-
-class DatetimeLikeArrayMixin(OpsMixin, AttributesMixin, NDArrayBackedExtensionArray):
-    """
-    Shared Base/Mixin class for DatetimeArray, TimedeltaArray, PeriodArray
-
-    Assumes that __new__/__init__ defines:
-        _data
-        _freq
-
-    and that the inheriting class has methods:
-        _generate_range
-    """
-
-    _is_recognized_dtype: Callable[[DtypeObj], bool]
-    _recognized_scalars: Tuple[Type, ...]
-
     # ------------------------------------------------------------------
     # NDArrayBackedExtensionArray compat
 
@@ -861,7 +856,9 @@ def _cmp_method(self, other, op):
             #  comparison otherwise it would fail to raise when
             #  comparing tz-aware and tz-naive
             with np.errstate(all="ignore"):
-                result = ops.comp_method_OBJECT_ARRAY(op, self.astype(object), other)
+                result = ops.comp_method_OBJECT_ARRAY(
+                    op, np.asarray(self.astype(object)), other
+                )
             return result
 
         other_i8 = self._unbox(other)

pandas/core/ops/__init__.py

@@ -28,8 +28,8 @@
 from pandas.core.ops.common import unpack_zerodim_and_defer  # noqa:F401
 from pandas.core.ops.docstrings import (
     _flex_comp_doc_FRAME,
-    _make_flex_doc,
     _op_descriptions,
+    make_flex_doc,
 )
 from pandas.core.ops.invalid import invalid_comparison  # noqa:F401
 from pandas.core.ops.mask_ops import kleene_and, kleene_or, kleene_xor  # noqa: F401
@@ -209,7 +209,7 @@ def align_method_SERIES(left: "Series", right, align_asobject: bool = False):
 
 def flex_method_SERIES(op):
     name = op.__name__.strip("_")
-    doc = _make_flex_doc(name, "series")
+    doc = make_flex_doc(name, "series")
 
     @Appender(doc)
     def flex_wrapper(self, other, level=None, fill_value=None, axis=0):
@@ -445,7 +445,7 @@ def flex_arith_method_FRAME(op):
     default_axis = "columns"
 
     na_op = get_array_op(op)
-    doc = _make_flex_doc(op_name, "dataframe")
+    doc = make_flex_doc(op_name, "dataframe")
 
     @Appender(doc)
     def f(self, other, axis=default_axis, level=None, fill_value=None):

pandas/core/ops/array_ops.py

@@ -57,7 +57,7 @@ def comp_method_OBJECT_ARRAY(op, x, y):
     return result.reshape(x.shape)
 
 
-def masked_arith_op(x: np.ndarray, y, op):
+def _masked_arith_op(x: np.ndarray, y, op):
     """
     If the given arithmetic operation fails, attempt it again on
     only the non-null elements of the input array(s).
@@ -116,7 +116,7 @@ def masked_arith_op(x: np.ndarray, y, op):
     return result
 
 
-def na_arithmetic_op(left, right, op, is_cmp: bool = False):
+def _na_arithmetic_op(left, right, op, is_cmp: bool = False):
     """
     Return the result of evaluating op on the passed in values.
 
@@ -147,7 +147,7 @@ def na_arithmetic_op(left, right, op, is_cmp: bool = False):
             #  In this case we do not fall back to the masked op, as that
             #  will handle complex numbers incorrectly, see GH#32047
             raise
-        result = masked_arith_op(left, right, op)
+        result = _masked_arith_op(left, right, op)
 
     if is_cmp and (is_scalar(result) or result is NotImplemented):
         # numpy returned a scalar instead of operating element-wise
@@ -179,15 +179,15 @@ def arithmetic_op(left: ArrayLike, right: Any, op):
     #  on `left` and `right`.
     lvalues = maybe_upcast_datetimelike_array(left)
     rvalues = maybe_upcast_datetimelike_array(right)
-    rvalues = maybe_upcast_for_op(rvalues, lvalues.shape)
+    rvalues = _maybe_upcast_for_op(rvalues, lvalues.shape)
 
     if should_extension_dispatch(lvalues, rvalues) or isinstance(rvalues, Timedelta):
         # Timedelta is included because numexpr will fail on it, see GH#31457
         res_values = op(lvalues, rvalues)
 
     else:
         with np.errstate(all="ignore"):
-            res_values = na_arithmetic_op(lvalues, rvalues, op)
+            res_values = _na_arithmetic_op(lvalues, rvalues, op)
 
     return res_values
 
@@ -248,7 +248,7 @@ def comparison_op(left: ArrayLike, right: Any, op) -> ArrayLike:
             # suppress warnings from numpy about element-wise comparison
             warnings.simplefilter("ignore", DeprecationWarning)
             with np.errstate(all="ignore"):
-                res_values = na_arithmetic_op(lvalues, rvalues, op, is_cmp=True)
+                res_values = _na_arithmetic_op(lvalues, rvalues, op, is_cmp=True)
 
     return res_values
 
@@ -427,7 +427,7 @@ def maybe_upcast_datetimelike_array(obj: ArrayLike) -> ArrayLike:
     return obj
 
 
-def maybe_upcast_for_op(obj, shape: Tuple[int, ...]):
+def _maybe_upcast_for_op(obj, shape: Tuple[int, ...]):
     """
     Cast non-pandas objects to pandas types to unify behavior of arithmetic
     and comparison operations.

pandas/core/ops/docstrings.py

@@ -4,7 +4,7 @@
 from typing import Dict, Optional
 
 
-def _make_flex_doc(op_name, typ: str):
+def make_flex_doc(op_name: str, typ: str) -> str:
     """
     Make the appropriate substitutions for the given operation and class-typ
     into either _flex_doc_SERIES or _flex_doc_FRAME to return the docstring
@@ -427,33 +427,6 @@ def _make_flex_doc(op_name, typ: str):
 Series.{reverse} : {see_also_desc}.
 """
 
-_arith_doc_FRAME = """
-Binary operator %s with support to substitute a fill_value for missing data in
-one of the inputs
-
-Parameters
-----------
-other : Series, DataFrame, or constant
-axis : {0, 1, 'index', 'columns'}
-    For Series input, axis to match Series index on
-fill_value : None or float value, default None
-    Fill existing missing (NaN) values, and any new element needed for
-    successful DataFrame alignment, with this value before computation.
-    If data in both corresponding DataFrame locations is missing
-    the result will be missing
-level : int or name
-    Broadcast across a level, matching Index values on the
-    passed MultiIndex level
-
-Returns
--------
-result : DataFrame
-
-Notes
------
-Mismatched indices will be unioned together
-"""
-
 _flex_doc_FRAME = """
 Get {desc} of dataframe and other, element-wise (binary operator `{op_name}`).
 

scripts/validate_unwanted_patterns.py

@@ -33,9 +33,7 @@
     "_get_version",
     "__main__",
     "_transform_template",
-    "_arith_doc_FRAME",
     "_flex_comp_doc_FRAME",
-    "_make_flex_doc",
     "_op_descriptions",
     "_IntegerDtype",
     "_use_inf_as_na",