Cast non-pandas objects to pandas types to unify behavior of arithmetic
    and comparison operations.

    Parameters
    ----------
    obj: object

    Returns
    -------
    out : object

    Notes
    -----
    Be careful to call this *after* determining the `name` attribute to be
    attached to the result of the arithmetic operation.

def maybe_upcast_for_op(obj):
    """
    Cast non-pandas objects to pandas types to unify behavior of arithmetic
    and comparison operations.

    Parameters
    ----------
    obj: object

    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 pd.Timedelta(obj)
    elif isinstance(obj, np.timedelta64) and not isna(obj):
        # 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')
        # The isna check is to avoid casting timedelta64("NaT"), which would
        #  return NaT and incorrectly be treated as a datetime-NaT.
        return pd.Timedelta(obj)
    elif isinstance(obj, np.ndarray) and is_timedelta64_dtype(obj):
        # GH#22390 Unfortunately we need to special-case right-hand
        # timedelta64 dtypes because numpy casts integer dtypes to
        # timedelta64 when operating with timedelta64
        return pd.TimedeltaIndex(obj)
    return obj