CLN: algos.searchsorted

pandas/core/algorithms.py

@@ -11,7 +11,7 @@
 
 import numpy as np
 
-from pandas._libs import Timestamp, algos, hashtable as htable, iNaT, lib
+from pandas._libs import algos, hashtable as htable, iNaT, lib
 from pandas._typing import AnyArrayLike, ArrayLike, DtypeObj, FrameOrSeriesUnion
 from pandas.util._decorators import doc
 
@@ -59,7 +59,11 @@
 )
 from pandas.core.dtypes.missing import isna, na_value_for_dtype
 
-from pandas.core.construction import array, extract_array
+from pandas.core.construction import (
+    array,
+    ensure_wrapped_if_datetimelike,
+    extract_array,
+)
 from pandas.core.indexers import validate_indices
 
 if TYPE_CHECKING:
@@ -1906,10 +1910,7 @@ def searchsorted(arr, value, side="left", sorter=None) -> np.ndarray:
     ):
         # E.g. if `arr` is an array with dtype='datetime64[ns]'
         # and `value` is a pd.Timestamp, we may need to convert value
-        value_ser = array([value]) if is_scalar(value) else array(value)
-        value = value_ser[0] if is_scalar(value) else value_ser
-        if isinstance(value, Timestamp) and value.tzinfo is None:
-            value = value.to_datetime64()
+        arr = ensure_wrapped_if_datetimelike(arr)
 
     result = arr.searchsorted(value, side=side, sorter=sorter)
     return result

pandas/core/internals/blocks.py

@@ -1063,15 +1063,12 @@ def putmask(self, mask, new, axis: int = 0) -> List["Block"]:
             # We only get here for non-Extension Blocks, so _try_coerce_args
             #  is only relevant for DatetimeBlock and TimedeltaBlock
             if self.dtype.kind in ["m", "M"]:
-                blk = self
-                if not inplace:
-                    blk = self.copy()
-                arr = blk.array_values()
+                arr = self.array_values()
                 arr = cast("NDArrayBackedExtensionArray", arr)
                 if transpose:
                     arr = arr.T
                 arr.putmask(mask, new)
-                return [blk]
+                return [self]
 
             if lib.is_scalar(new):
                 new = convert_scalar_for_putitemlike(new, self.values.dtype)