PERF: speed up tz-aware datetimearray ops by skipping useless validation

Author: qwhelan

doc/source/whatsnew/v0.24.0.rst

@@ -1295,6 +1295,7 @@ Performance Improvements
 - Improved performance of iterating over a :class:`Series`. Using :meth:`DataFrame.itertuples` now creates iterators
   without internally allocating lists of all elements (:issue:`20783`)
 - Improved performance of :class:`Period` constructor, additionally benefitting ``PeriodArray`` and ``PeriodIndex`` creation (:issue:`24084` and :issue:`24118`)
+- Improved performance of tz-aware :class:`DatetimeArray` binary operations (:issue:`24491`)
 
 .. _whatsnew_0240.docs:
 

pandas/core/arrays/datetimes.py

@@ -262,7 +262,9 @@ def _from_sequence(cls, data, dtype=None, copy=False,
             cls._validate_frequency(result, freq, ambiguous=ambiguous)
 
         elif freq_infer:
-            result.freq = to_offset(result.inferred_freq)
+            # Set _freq directly to bypass duplicative _validate_frequency
+            # check.
+            result._freq = to_offset(result.inferred_freq)
 
         return result
 

pandas/core/arrays/timedeltas.py

@@ -181,7 +181,9 @@ def _from_sequence(cls, data, dtype=_TD_DTYPE, copy=False,
             cls._validate_frequency(result, freq)
 
         elif freq_infer:
-            result.freq = to_offset(result.inferred_freq)
+            # Set _freq directly to bypass duplicative _validate_frequency
+            # check.
+            result._freq = to_offset(result.inferred_freq)
 
         return result