OK

pandas-dev · jreback · Nov 14, 2019 · Aug 9, 2019 · Aug 9, 2019 · Aug 9, 2019
commit 68bab4b8f57f1774a8b93f94554fb998366f0efe
diff --git a/pandas/core/arrays/categorical.py b/pandas/core/arrays/categorical.py
@@ -7,7 +7,7 @@
 
 from pandas._config import get_option
 
-from pandas._libs import algos as libalgos, hashtable as htable, lib
+from pandas._libs import algos as libalgos, hashtable as htable
 from pandas.compat.numpy import function as nv
 from pandas.util._decorators import (
     Appender,
@@ -38,7 +38,7 @@
     is_timedelta64_dtype,
 )
 from pandas.core.dtypes.dtypes import CategoricalDtype
-from pandas.core.dtypes.generic import ABCDataFrame, ABCIndexClass, ABCSeries
+from pandas.core.dtypes.generic import ABCIndexClass, ABCSeries
 from pandas.core.dtypes.inference import is_hashable
 from pandas.core.dtypes.missing import isna, notna
 
@@ -78,22 +78,18 @@
 )
 
 
-def _cat_compare_op(op):  # TODO: op-->opname
+def _cat_compare_op(opname):  # TODO: pass op instead of opname
 
-    @unpack_and_defer(op)
+    @unpack_and_defer(opname)
     def f(self, other):
         # On python2, you can usually compare any type to any type, and
         # Categoricals can be seen as a custom type, but having different
         # results depending whether categories are the same or not is kind of
         # insane, so be a bit stricter here and use the python3 idea of
         # comparing only things of equal type.
-        #if isinstance(other, (ABCDataFrame, ABCSeries, ABCIndexClass)):
-        #    return NotImplemented
-
-        #other = lib.item_from_zerodim(other)
 
         if not self.ordered:
-            if op in ["__lt__", "__gt__", "__le__", "__ge__"]:
+            if opname in ["__lt__", "__gt__", "__le__", "__ge__"]:
                 raise TypeError(
                     "Unordered Categoricals can only compare equality or not"
                 )
@@ -120,7 +116,7 @@ def f(self, other):
                 other_codes = other._codes
 
             mask = (self._codes == -1) | (other_codes == -1)
-            f = getattr(self._codes, op)
+            f = getattr(self._codes, opname)
             ret = f(other_codes)
             if mask.any():
                 # In other series, the leads to False, so do that here too
@@ -130,38 +126,38 @@ def f(self, other):
         if is_scalar(other):
             if other in self.categories:
                 i = self.categories.get_loc(other)
-                ret = getattr(self._codes, op)(i)
+                ret = getattr(self._codes, opname)(i)
 
                 # check for NaN in self
                 mask = self._codes == -1
                 ret[mask] = False
                 return ret
             else:
-                if op == "__eq__":
+                if opname == "__eq__":
                     return np.repeat(False, len(self))
-                elif op == "__ne__":
+                elif opname == "__ne__":
                     return np.repeat(True, len(self))
                 else:
                     msg = (
                         "Cannot compare a Categorical for op {op} with a "
                         "scalar, which is not a category."
                     )
-                    raise TypeError(msg.format(op=op))
+                    raise TypeError(msg.format(op=opname))
         else:
 
             # allow categorical vs object dtype array comparisons for equality
             # these are only positional comparisons
-            if op in ["__eq__", "__ne__"]:
-                return getattr(np.array(self), op)(np.array(other))
+            if opname in ["__eq__", "__ne__"]:
+                return getattr(np.array(self), opname)(np.array(other))
 
             msg = (
                 "Cannot compare a Categorical for op {op} with type {typ}."
                 "\nIf you want to compare values, use 'np.asarray(cat) "
                 "<op> other'."
             )
-            raise TypeError(msg.format(op=op, typ=type(other)))
+            raise TypeError(msg.format(op=opname, typ=type(other)))
 
-    f.__name__ = op
+    f.__name__ = opname
 
     return f
 

diff --git a/pandas/core/arrays/datetimelike.py b/pandas/core/arrays/datetimelike.py
@@ -35,7 +35,6 @@
     pandas_dtype,
 )
 from pandas.core.dtypes.generic import (
-    ABCDataFrame,
     ABCIndexClass,
     ABCPeriodArray,
     ABCSeries,
@@ -1197,9 +1196,6 @@ def _time_shift(self, periods, freq=None):
 
     @unpack_and_defer("__add__")
     def __add__(self, other):
-        other = lib.item_from_zerodim(other)
-        #if isinstance(other, (ABCSeries, ABCDataFrame, ABCIndexClass)):
-        #    return NotImplemented
 
         # scalar others
         if other is NaT:
@@ -1264,9 +1260,6 @@ def __radd__(self, other):
 
     @unpack_and_defer("__sub__")
     def __sub__(self, other):
-        other = lib.item_from_zerodim(other)
-        #if isinstance(other, (ABCSeries, ABCDataFrame, ABCIndexClass)):
-        #    return NotImplemented
 
         # scalar others
         if other is NaT:

diff --git a/pandas/core/arrays/datetimes.py b/pandas/core/arrays/datetimes.py
@@ -41,7 +41,6 @@
 )
 from pandas.core.dtypes.dtypes import DatetimeTZDtype
 from pandas.core.dtypes.generic import (
-    ABCDataFrame,
     ABCIndexClass,
     ABCPandasArray,
     ABCSeries,
@@ -160,10 +159,6 @@ def _dt_array_cmp(cls, op):
 
     @unpack_and_defer(opname)
     def wrapper(self, other):
-        #if isinstance(other, (ABCDataFrame, ABCSeries, ABCIndexClass)):
-        #    return NotImplemented
-
-        #other = lib.item_from_zerodim(other)
 
         if isinstance(other, (datetime, np.datetime64, str)):
             if isinstance(other, (datetime, np.datetime64)):

diff --git a/pandas/core/arrays/integer.py b/pandas/core/arrays/integer.py
@@ -21,7 +21,6 @@
     is_scalar,
 )
 from pandas.core.dtypes.dtypes import register_extension_dtype
-from pandas.core.dtypes.generic import ABCIndexClass, ABCSeries
 from pandas.core.dtypes.missing import isna, notna
 
 from pandas.core import nanops, ops
@@ -599,10 +598,6 @@ def _create_comparison_method(cls, op):
         def cmp_method(self, other):
             mask = None
 
-            #if isinstance(other, (ABCSeries, ABCIndexClass)):
-            #    # Rely on pandas to unbox and dispatch to us.
-            #    return NotImplemented
-
             if isinstance(other, IntegerArray):
                 other, mask = other._data, other._mask
 
@@ -611,8 +606,6 @@ def cmp_method(self, other):
                 if other.ndim > 0 and len(self) != len(other):
                     raise ValueError("Lengths must match to compare")
 
-            #other = lib.item_from_zerodim(other)
-
             # numpy will show a DeprecationWarning on invalid elementwise
             # comparisons, this will raise in the future
             with warnings.catch_warnings():
@@ -692,19 +685,12 @@ def integer_arithmetic_method(self, other):
 
             mask = None
 
-            #if isinstance(other, (ABCSeries, ABCIndexClass)):
-            #    # Rely on pandas to unbox and dispatch to us.
-            #    return NotImplemented
-
             if getattr(other, "ndim", 0) > 1:
                 raise NotImplementedError("can only perform ops with 1-d structures")
 
             if isinstance(other, IntegerArray):
                 other, mask = other._data, other._mask
 
-            #elif getattr(other, "ndim", None) == 0:
-            #    other = other.item()
-
             elif is_list_like(other):
                 other = np.asarray(other)
                 if not other.ndim:

diff --git a/pandas/core/arrays/period.py b/pandas/core/arrays/period.py
@@ -4,7 +4,6 @@
 
 import numpy as np
 
-from pandas._libs import lib
 from pandas._libs.tslibs import (
     NaT,
     NaTType,
@@ -35,7 +34,6 @@
 )
 from pandas.core.dtypes.dtypes import PeriodDtype
 from pandas.core.dtypes.generic import (
-    ABCDataFrame,
     ABCIndexClass,
     ABCPeriodArray,
     ABCPeriodIndex,
@@ -74,10 +72,6 @@ def _period_array_cmp(cls, op):
     def wrapper(self, other):
         op = getattr(self.asi8, opname)
 
-        other = lib.item_from_zerodim(other)
-        #if isinstance(other, (ABCDataFrame, ABCSeries, ABCIndexClass)):
-        #    return NotImplemented
-
         if is_list_like(other) and len(other) != len(self):
             raise ValueError("Lengths must match")
 

diff --git a/pandas/core/arrays/sparse.py b/pandas/core/arrays/sparse.py
@@ -39,7 +39,6 @@
 )
 from pandas.core.dtypes.dtypes import register_extension_dtype
 from pandas.core.dtypes.generic import (
-    ABCDataFrame,
     ABCIndexClass,
     ABCSeries,
     ABCSparseArray,
@@ -1739,12 +1738,6 @@ def _create_arithmetic_method(cls, op):
         @unpack_and_defer(op_name)
         def sparse_arithmetic_method(self, other):
 
-            #if isinstance(other, (ABCDataFrame, ABCSeries, ABCIndexClass)):
-            #    # Rely on pandas to dispatch to us.
-            #    return NotImplemented
-
-            #other = lib.item_from_zerodim(other)
-
             if isinstance(other, SparseArray):
                 return _sparse_array_op(self, other, op, op_name)
 
@@ -1791,14 +1784,9 @@ def _create_comparison_method(cls, op):
         if op_name in {"and_", "or_"}:
             op_name = op_name[:-1]
 
+        @unpack_and_defer(op_name)
         def cmp_method(self, other):
 
-            if isinstance(other, (ABCDataFrame, ABCSeries, ABCIndexClass)):
-                # Rely on pandas to unbox and dispatch to us.
-                return NotImplemented
-
-            other = lib.item_from_zerodim(other)
-
             if not is_scalar(other) and not isinstance(other, type(self)):
                 # convert list-like to ndarray
                 other = np.asarray(other)

diff --git a/pandas/core/arrays/timedeltas.py b/pandas/core/arrays/timedeltas.py
@@ -83,9 +83,6 @@ def _td_array_cmp(cls, op):
 
     @unpack_and_defer(opname)
     def wrapper(self, other):
-        other = lib.item_from_zerodim(other)
-        #if isinstance(other, (ABCDataFrame, ABCSeries, ABCIndexClass)):
-        #    return NotImplemented
 
         if _is_convertible_to_td(other) or other is NaT:
             try:

diff --git a/pandas/core/indexes/range.py b/pandas/core/indexes/range.py
@@ -21,7 +21,7 @@
     is_scalar,
     is_timedelta64_dtype,
 )
-from pandas.core.dtypes.generic import ABCDataFrame, ABCSeries, ABCTimedeltaIndex
+from pandas.core.dtypes.generic import ABCTimedeltaIndex
 
 from pandas.core import ops
 from pandas.core.ops.common import unpack_and_defer
@@ -733,8 +733,6 @@ def __getitem__(self, key):
 
     @unpack_and_defer("__floordiv__")
     def __floordiv__(self, other):
-        #if isinstance(other, (ABCSeries, ABCDataFrame)):
-        #    return NotImplemented
 
         if is_integer(other) and other != 0:
             if len(self) == 0 or self.start % other == 0 and self.step % other == 0:
@@ -771,8 +769,6 @@ def _make_evaluate_binop(op, step=False):
             """
             @unpack_and_defer(op.__name__)
             def _evaluate_numeric_binop(self, other):
-                #if isinstance(other, (ABCSeries, ABCDataFrame)):
-                #    return NotImplemented
                 if isinstance(other, ABCTimedeltaIndex):
                     # Defer to TimedeltaIndex implementation
                     return NotImplemented

diff --git a/pandas/core/ops/__init__.py b/pandas/core/ops/__init__.py
@@ -680,12 +680,9 @@ def na_op(x, y):
 
     @unpack_and_defer(op_name)
     def wrapper(left, right):
-        #if isinstance(right, ABCDataFrame):
-        #    return NotImplemented
 
         left, right = _align_method_SERIES(left, right)
         res_name = get_op_result_name(left, right)
-        right = lib.item_from_zerodim(right)
         right = maybe_upcast_for_op(right, left.shape)
 
         if is_categorical_dtype(left):
@@ -819,7 +816,6 @@ def wrapper(self, other, axis=None):
             self._get_axis_number(axis)
 
         res_name = get_op_result_name(self, other)
-        other = lib.item_from_zerodim(other)
 
         # TODO: shouldn't we be applying finalize whenever
         #  not isinstance(other, ABCSeries)?
@@ -833,10 +829,6 @@ def wrapper(self, other, axis=None):
             # TODO: same for tuples?
             other = np.asarray(other)
 
-        #if isinstance(other, ABCDataFrame):  # pragma: no cover
-        #    # Defer to DataFrame implementation; fail early
-        #    return NotImplemented
-
         if isinstance(other, ABCSeries) and not self._indexed_same(other):
             raise ValueError("Can only compare identically-labeled Series objects")
 
@@ -949,11 +941,6 @@ def wrapper(self, other):
 
         self, other = _align_method_SERIES(self, other, align_asobject=True)
         res_name = get_op_result_name(self, other)
-        other = lib.item_from_zerodim(other)
-
-        #if isinstance(other, ABCDataFrame):
-        #    # Defer to DataFrame implementation; fail early
-        #    return NotImplemented
 
         if isinstance(other, (ABCSeries, ABCIndexClass)):
             is_other_int_dtype = is_integer_dtype(other.dtype)
@@ -1287,8 +1274,6 @@ def _arith_method_SPARSE_SERIES(cls, op, special):
 
     @unpack_and_defer(op_name)
     def wrapper(self, other):
-        #if isinstance(other, ABCDataFrame):
-        #    return NotImplemented
         if isinstance(other, ABCSeries):
             if not isinstance(other, ABCSparseSeries):
                 other = other.to_sparse(fill_value=self.fill_value)