CLN: de-duplicate _local_timestamps (#36609)

pandas/core/arrays/datetimes.py

@@ -76,9 +76,7 @@ def tz_to_dtype(tz):
 
 def _field_accessor(name, field, docstring=None):
     def f(self):
-        values = self.asi8
-        if self.tz is not None and not timezones.is_utc(self.tz):
-            values = self._local_timestamps()
+        values = self._local_timestamps()
 
         if field in self._bool_ops:
             if field.endswith(("start", "end")):
@@ -731,6 +729,8 @@ def _local_timestamps(self):
         This is used to calculate time-of-day information as if the timestamps
         were timezone-naive.
         """
+        if self.tz is None or timezones.is_utc(self.tz):
+            return self.asi8
         return tzconversion.tz_convert_from_utc(self.asi8, self.tz)
 
     def tz_convert(self, tz):
@@ -1167,10 +1167,7 @@ def month_name(self, locale=None):
         >>> idx.month_name()
         Index(['January', 'February', 'March'], dtype='object')
         """
-        if self.tz is not None and not timezones.is_utc(self.tz):
-            values = self._local_timestamps()
-        else:
-            values = self.asi8
+        values = self._local_timestamps()
 
         result = fields.get_date_name_field(values, "month_name", locale=locale)
         result = self._maybe_mask_results(result, fill_value=None)
@@ -1200,10 +1197,7 @@ def day_name(self, locale=None):
         >>> idx.day_name()
         Index(['Monday', 'Tuesday', 'Wednesday'], dtype='object')
         """
-        if self.tz is not None and not timezones.is_utc(self.tz):
-            values = self._local_timestamps()
-        else:
-            values = self.asi8
+        values = self._local_timestamps()
 
         result = fields.get_date_name_field(values, "day_name", locale=locale)
         result = self._maybe_mask_results(result, fill_value=None)
@@ -1217,10 +1211,7 @@ def time(self):
         # If the Timestamps have a timezone that is not UTC,
         # convert them into their i8 representation while
         # keeping their timezone and not using UTC
-        if self.tz is not None and not timezones.is_utc(self.tz):
-            timestamps = self._local_timestamps()
-        else:
-            timestamps = self.asi8
+        timestamps = self._local_timestamps()
 
         return ints_to_pydatetime(timestamps, box="time")
 
@@ -1241,10 +1232,7 @@ def date(self):
         # If the Timestamps have a timezone that is not UTC,
         # convert them into their i8 representation while
         # keeping their timezone and not using UTC
-        if self.tz is not None and not timezones.is_utc(self.tz):
-            timestamps = self._local_timestamps()
-        else:
-            timestamps = self.asi8
+        timestamps = self._local_timestamps()
 
         return ints_to_pydatetime(timestamps, box="date")
 
@@ -1283,10 +1271,7 @@ def isocalendar(self):
         """
         from pandas import DataFrame
 
-        if self.tz is not None and not timezones.is_utc(self.tz):
-            values = self._local_timestamps()
-        else:
-            values = self.asi8
+        values = self._local_timestamps()
         sarray = fields.build_isocalendar_sarray(values)
         iso_calendar_df = DataFrame(
             sarray, columns=["year", "week", "day"], dtype="UInt32"

pandas/core/indexes/datetimes.py

@@ -6,13 +6,7 @@
 import numpy as np
 
 from pandas._libs import NaT, Period, Timestamp, index as libindex, lib
-from pandas._libs.tslibs import (
-    Resolution,
-    ints_to_pydatetime,
-    parsing,
-    timezones,
-    to_offset,
-)
+from pandas._libs.tslibs import Resolution, ints_to_pydatetime, parsing, to_offset
 from pandas._libs.tslibs.offsets import prefix_mapping
 from pandas._typing import DtypeObj, Label
 from pandas.errors import InvalidIndexError
@@ -395,9 +389,7 @@ def _get_time_micros(self):
         -------
         ndarray[int64_t]
         """
-        values = self.asi8
-        if self.tz is not None and not timezones.is_utc(self.tz):
-            values = self._data._local_timestamps()
+        values = self._data._local_timestamps()
 
         nanos = values % (24 * 3600 * 1_000_000_000)
         micros = nanos // 1000