CLN: remove unnecessary dtype checks

pandas/core/arrays/categorical.py

@@ -1,3 +1,4 @@
+import operator
 from shutil import get_terminal_size
 import textwrap
 from typing import Type, Union, cast
@@ -77,7 +78,9 @@
 )
 
 
-def _cat_compare_op(opname):
+def _cat_compare_op(op):
+    opname = "__{op}__".format(op=op.__name__)
+
     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
@@ -1240,12 +1243,12 @@ def map(self, mapper):
                 new_categories = new_categories.insert(len(new_categories), np.nan)
             return np.take(new_categories, self._codes)
 
-    __eq__ = _cat_compare_op("__eq__")
-    __ne__ = _cat_compare_op("__ne__")
-    __lt__ = _cat_compare_op("__lt__")
-    __gt__ = _cat_compare_op("__gt__")
-    __le__ = _cat_compare_op("__le__")
-    __ge__ = _cat_compare_op("__ge__")
+    __eq__ = _cat_compare_op(operator.eq)
+    __ne__ = _cat_compare_op(operator.ne)
+    __lt__ = _cat_compare_op(operator.lt)
+    __gt__ = _cat_compare_op(operator.gt)
+    __le__ = _cat_compare_op(operator.le)
+    __ge__ = _cat_compare_op(operator.ge)
 
     # for Series/ndarray like compat
     @property

pandas/core/arrays/datetimelike.py

@@ -22,7 +22,6 @@
     is_datetime64tz_dtype,
     is_datetime_or_timedelta_dtype,
     is_dtype_equal,
-    is_extension_array_dtype,
     is_float_dtype,
     is_integer_dtype,
     is_list_like,
@@ -1230,29 +1229,17 @@ def __add__(self, other):
             if not is_period_dtype(self):
                 maybe_integer_op_deprecated(self)
             result = self._addsub_int_array(other, operator.add)
-        elif is_float_dtype(other):
-            # Explicitly catch invalid dtypes
-            raise TypeError(
-                "cannot add {dtype}-dtype to {cls}".format(
-                    dtype=other.dtype, cls=type(self).__name__
-                )
-            )
-        elif is_period_dtype(other):
-            # if self is a TimedeltaArray and other is a PeriodArray with
-            #  a timedelta-like (i.e. Tick) freq, this operation is valid.
-            #  Defer to the PeriodArray implementation.
-            # In remaining cases, this will end up raising TypeError.
-            return NotImplemented
-        elif is_extension_array_dtype(other):
-            # Categorical op will raise; defer explicitly
-            return NotImplemented
-        else:  # pragma: no cover
+        else:
+            # Includes Categorical, other ExtensionArrays
+            # For PeriodDtype, if self is a TimedeltaArray and other is a
+            #  PeriodArray with  a timedelta-like (i.e. Tick) freq, this
+            #  operation is valid.  Defer to the PeriodArray implementation.
+            #  In remaining cases, this will end up raising TypeError.
             return NotImplemented
 
         if is_timedelta64_dtype(result) and isinstance(result, np.ndarray):
             from pandas.core.arrays import TimedeltaArray
 
-            # TODO: infer freq?
             return TimedeltaArray(result)
         return result
 
@@ -1302,29 +1289,13 @@ def __sub__(self, other):
             if not is_period_dtype(self):
                 maybe_integer_op_deprecated(self)
             result = self._addsub_int_array(other, operator.sub)
-        elif isinstance(other, ABCIndexClass):
-            raise TypeError(
-                "cannot subtract {cls} and {typ}".format(
-                    cls=type(self).__name__, typ=type(other).__name__
-                )
-            )
-        elif is_float_dtype(other):
-            # Explicitly catch invalid dtypes
-            raise TypeError(
-                "cannot subtract {dtype}-dtype from {cls}".format(
-                    dtype=other.dtype, cls=type(self).__name__
-                )
-            )
-        elif is_extension_array_dtype(other):
-            # Categorical op will raise; defer explicitly
-            return NotImplemented
-        else:  # pragma: no cover
+        else:
+            # Includes ExtensionArrays, float_dtype
             return NotImplemented
 
         if is_timedelta64_dtype(result) and isinstance(result, np.ndarray):
             from pandas.core.arrays import TimedeltaArray
 
-            # TODO: infer freq?
             return TimedeltaArray(result)
         return result
 

pandas/core/arrays/datetimes.py

@@ -223,8 +223,6 @@ def wrapper(self, other):
                 result = op(self.view("i8"), other.view("i8"))
                 o_mask = other._isnan
 
-            result = com.values_from_object(result)
-
             if o_mask.any():
                 result[o_mask] = nat_result
 

pandas/tests/arithmetic/test_datetime64.py

@@ -1097,7 +1097,13 @@ def test_dt64arr_add_timestamp_raises(self, box_with_array):
     def test_dt64arr_add_sub_float(self, other, box_with_array):
         dti = DatetimeIndex(["2011-01-01", "2011-01-02"], freq="D")
         dtarr = tm.box_expected(dti, box_with_array)
-        msg = "|".join(["unsupported operand type", "cannot (add|subtract)"])
+        msg = "|".join(
+            [
+                "unsupported operand type",
+                "cannot (add|subtract)",
+                "ufunc '?(add|subtract)'? cannot use operands with types",
+            ]
+        )
         with pytest.raises(TypeError, match=msg):
             dtarr + other
         with pytest.raises(TypeError, match=msg):