CLN: datetimelike EA and Index cleanups (pandas-dev#30591)

Author: jbrockmendel

pandas/core/arrays/period.py

@@ -476,11 +476,6 @@ def to_timestamp(self, freq=None, how="start"):
     # --------------------------------------------------------------------
     # Array-like / EA-Interface Methods
 
-    def _formatter(self, boxed=False):
-        if boxed:
-            return str
-        return "'{}'".format
-
     @Appender(dtl.DatetimeLikeArrayMixin._validate_fill_value.__doc__)
     def _validate_fill_value(self, fill_value):
         if isna(fill_value):
@@ -492,6 +487,9 @@ def _validate_fill_value(self, fill_value):
             raise ValueError(f"'fill_value' should be a Period. Got '{fill_value}'.")
         return fill_value
 
+    def _values_for_argsort(self):
+        return self._data
+
     # --------------------------------------------------------------------
 
     def _time_shift(self, periods, freq=None):
@@ -582,6 +580,11 @@ def asfreq(self, freq=None, how="E"):
     # ------------------------------------------------------------------
     # Rendering Methods
 
+    def _formatter(self, boxed=False):
+        if boxed:
+            return str
+        return "'{}'".format
+
     def _format_native_types(self, na_rep="NaT", date_format=None, **kwargs):
         """
         actually format my specific types
@@ -774,9 +777,6 @@ def _check_timedeltalike_freq_compat(self, other):
 
         _raise_on_incompatible(self, other)
 
-    def _values_for_argsort(self):
-        return self._data
-
 
 PeriodArray._add_comparison_ops()
 

pandas/core/arrays/timedeltas.py

@@ -378,6 +378,9 @@ def astype(self, dtype, copy=True):
             return self
         return dtl.DatetimeLikeArrayMixin.astype(self, dtype, copy=copy)
 
+    # ----------------------------------------------------------------
+    # Reductions
+
     def sum(
         self,
         axis=None,

pandas/core/base.py

@@ -625,7 +625,7 @@ class IndexOpsMixin:
     # ndarray compatibility
     __array_priority__ = 1000
     _deprecations: FrozenSet[str] = frozenset(
-        ["tolist", "item"]  # tolist is not deprecated, just suppressed in the __dir__
+        ["tolist"]  # tolist is not deprecated, just suppressed in the __dir__
     )
 
     def transpose(self, *args, **kwargs):

pandas/core/indexes/datetimelike.py

@@ -122,7 +122,6 @@ class DatetimeIndexOpsMixin(ExtensionOpsMixin):
     )
     resolution = cache_readonly(DatetimeLikeArrayMixin.resolution.fget)  # type: ignore
 
-    _maybe_mask_results = ea_passthrough(DatetimeLikeArrayMixin._maybe_mask_results)
     __iter__ = ea_passthrough(DatetimeLikeArrayMixin.__iter__)
     mean = ea_passthrough(DatetimeLikeArrayMixin.mean)
 

pandas/core/indexes/datetimes.py

@@ -35,7 +35,6 @@
     DatetimeIndexOpsMixin,
     DatetimelikeDelegateMixin,
     DatetimeTimedeltaMixin,
-    ea_passthrough,
 )
 from pandas.core.indexes.numeric import Int64Index
 from pandas.core.ops import get_op_result_name
@@ -1135,8 +1134,6 @@ def slice_indexer(self, start=None, end=None, step=None, kind=None):
     is_normalized = cache_readonly(DatetimeArray.is_normalized.fget)  # type: ignore
     _resolution = cache_readonly(DatetimeArray._resolution.fget)  # type: ignore
 
-    _has_same_tz = ea_passthrough(DatetimeArray._has_same_tz)
-
     def __getitem__(self, key):
         result = self._data.__getitem__(key)
         if is_scalar(result):
@@ -1202,6 +1199,7 @@ def insert(self, loc, item):
             self._assert_can_do_op(item)
             if not self._has_same_tz(item) and not isna(item):
                 raise ValueError("Passed item and index have different timezone")
+
             # check freq can be preserved on edge cases
             if self.size and self.freq is not None:
                 if item is NaT:

pandas/core/indexes/period.py

@@ -20,7 +20,6 @@
 )
 
 from pandas.core.accessor import delegate_names
-from pandas.core.algorithms import unique1d
 from pandas.core.arrays.period import PeriodArray, period_array, validate_dtype_freq
 from pandas.core.base import _shared_docs
 import pandas.core.common as com
@@ -622,18 +621,6 @@ def _get_unique_index(self, dropna=False):
             res = res.dropna()
         return res
 
-    @Appender(Index.unique.__doc__)
-    def unique(self, level=None):
-        # override the Index.unique method for performance GH#23083
-        if level is not None:
-            # this should never occur, but is retained to make the signature
-            # match Index.unique
-            self._validate_index_level(level)
-
-        values = self._ndarray_values
-        result = unique1d(values)
-        return self._shallow_copy(result)
-
     def get_loc(self, key, method=None, tolerance=None):
         """
         Get integer location for requested label

pandas/core/indexes/timedeltas.py

@@ -30,7 +30,6 @@
     DatetimeIndexOpsMixin,
     DatetimelikeDelegateMixin,
     DatetimeTimedeltaMixin,
-    ea_passthrough,
 )
 from pandas.core.indexes.numeric import Int64Index
 from pandas.core.ops import get_op_result_name
@@ -50,9 +49,12 @@ class TimedeltaDelegateMixin(DatetimelikeDelegateMixin):
         "__neg__",
         "__pos__",
         "__abs__",
+        "sum",
+        "std",
+        "median",
     ]
     _raw_properties = {"components"}
-    _raw_methods = {"to_pytimedelta"}
+    _raw_methods = {"to_pytimedelta", "sum", "std", "median"}
 
 
 @delegate_names(
@@ -151,9 +153,6 @@ def _join_i8_wrapper(joinf, **kwargs):
     _datetimelike_ops = TimedeltaArray._datetimelike_ops
     _datetimelike_methods = TimedeltaArray._datetimelike_methods
     _other_ops = TimedeltaArray._other_ops
-    sum = ea_passthrough(TimedeltaArray.sum)
-    std = ea_passthrough(TimedeltaArray.std)
-    median = ea_passthrough(TimedeltaArray.median)
 
     # -------------------------------------------------------------------
     # Constructors

pandas/core/internals/blocks.py

@@ -380,7 +380,6 @@ def apply(self, func, **kwargs):
             return nbs
 
         if not isinstance(result, Block):
-            # Exclude the 0-dim case so we can do reductions
             result = self.make_block(values=_block_shape(result, ndim=self.ndim))
 
         return result