code: def maybe_prepare_scalar_for_op(obj, shape: Shape):
      """
      Cast non-pandas objects to pandas types to unify behavior of arithmetic
      and comparison operations.
  
      Parameters
      ----------
      obj: object
      shape : tuple[int]
  
      Returns
      -------
      out : object
  
      Notes
      -----
      Be careful to call this *after* determining the `name` attribute to be
      attached to the result of the arithmetic operation.
      """
      if type(obj) is datetime.timedelta:
          # GH#22390  cast up to Timedelta to rely on Timedelta
          # implementation; otherwise operation against numeric-dtype
          # raises TypeError
          return Timedelta(obj)
      elif type(obj) is datetime.datetime:
          # cast up to Timestamp to rely on Timestamp implementation, see Timedelta above
          return Timestamp(obj)
      elif isinstance(obj, np.datetime64):
          # GH#28080 numpy casts integer-dtype to datetime64 when doing
          #  array[int] + datetime64, which we do not allow
          if isna(obj):
              from pandas.core.arrays import DatetimeArray
  
              # Avoid possible ambiguities with pd.NaT
              # GH 52295
              if is_unitless(obj.dtype):
                  obj = obj.astype("datetime64[ns]")
              elif not is_supported_unit(
                  get_unit_from_dtype(obj.dtype)
              ):
                  unit = get_unit_from_dtype(obj.dtype)
                  closest_unit = npy_unit_to_abbrev(
                      get_supported_reso(unit)
                  )
                  obj = obj.astype(f"datetime64[{closest_unit}]")
              right = np.broadcast_to(obj, shape)
              return DatetimeArray(right)
  
          return Timestamp(obj)
  
      elif isinstance(obj, np.timedelta64):
          if isna(obj):
              from pandas.core.arrays import TimedeltaArray
  
              # wrapping timedelta64("NaT") in Timedelta returns NaT,
              #  which would incorrectly be treated as a datetime-NaT, so
              #  we broadcast and wrap in a TimedeltaArray
              # GH 52295
              if is_unitless(obj.dtype):
                  obj = obj.astype("timedelta64[ns]")
              elif not is_supported_unit(
                  get_unit_from_dtype(obj.dtype)
              ):
                  unit = get_unit_from_dtype(obj.dtype)
                  closest_unit = npy_unit_to_abbrev(
                      get_supported_reso(unit)
                  )
                  obj = obj.astype(f"timedelta64[{closest_unit}]")
              right = np.broadcast_to(obj, shape)
              return TimedeltaArray(right)
  
          # In particular non-nanosecond timedelta64 needs to be cast to
          #  nanoseconds, or else we get undesired behavior like
          #  np.timedelta64(3, 'D') / 2 == np.timedelta64(1, 'D')
          return Timedelta(obj)
  
      return obj
  
imports: from __future__ import annotations
  import datetime
  from functools import partial
  import operator
  from typing import Any
  import numpy
  from pandas._libs import NaT, Timedelta, Timestamp, lib, ops
  from pandas._libs.tslibs import BaseOffset, get_supported_reso, get_unit_from_dtype, is_supported_unit, is_unitless, npy_unit_to_abbrev
  from pandas._typing import ArrayLike, Shape
  from pandas.core.dtypes.cast import construct_1d_object_array_from_listlike, find_common_type
  from pandas.core.dtypes.common import ensure_object, is_bool_dtype, is_integer_dtype, is_list_like, is_numeric_v_string_like, is_object_dtype, is_scalar
  from pandas.core.dtypes.generic import ABCExtensionArray, ABCIndex, ABCSeries
  from pandas.core.dtypes.missing import isna, notna
  from pandas.core.computation import expressions
  from pandas.core.construction import ensure_wrapped_if_datetimelike
  from pandas.core.ops import missing, roperator
  from pandas.core.ops.dispatch import should_extension_dispatch
  from pandas.core.ops.invalid import invalid_comparison
label_desc: Use image node_id 9 for calling a global function with example usage: maybe_prepare_scalar_for_op(obj, shape) and returns: obj, Timedelta, Timestamp, Timestamp, DatetimeArray, Timedelta, TimedeltaArray