class_docstr: Base column for decimal32, decimal64 or decimal128 columns
class_docstr_tok: ["Base","column","for","decimal32",",","decimal64","or","decimal128","columns"]
code: def normalize_binop_value(self, other):
      if isinstance(other, ColumnBase):
          if isinstance(other, cudf.core.column.NumericalColumn):
              if not is_integer_dtype(other.dtype):
                  raise TypeError(
                      "Decimal columns only support binary operations with "
                      "integer numerical columns."
                  )
              other = other.as_decimal_column(
                  self.dtype.__class__(
                      self.dtype.__class__.MAX_PRECISION, 0
                  )
              )
          elif not isinstance(other, DecimalBaseColumn):
              return NotImplemented
          elif not isinstance(self.dtype, other.dtype.__class__):
              # This branch occurs if we have a DecimalBaseColumn of a
              # different size (e.g. 64 instead of 32).
              if _same_precision_and_scale(self.dtype, other.dtype):
                  other = other.astype(self.dtype)
          return other
      if isinstance(other, cudf.Scalar) and isinstance(
          # TODO: Should it be possible to cast scalars of other numerical
          # types to decimal?
          other.dtype,
          cudf.core.dtypes.DecimalDtype,
      ):
          if _same_precision_and_scale(self.dtype, other.dtype):
              other = other.astype(self.dtype)
          return other
      elif is_scalar(other) and isinstance(other, (int, Decimal)):
          other = Decimal(other)
          metadata = other.as_tuple()
          precision = max(len(metadata.digits), metadata.exponent)
          scale = -metadata.exponent
          return cudf.Scalar(
              other, dtype=self.dtype.__class__(precision, scale)
          )
      return NotImplemented
  
imports: from __future__ import annotations
  import warnings
  from decimal import Decimal
  from typing import Any, Optional, Sequence, Union, cast
  import cupy
  import numpy
  import pyarrow
  from typing_extensions import Self
  import cudf
  from cudf import _lib
  from cudf._lib.strings.convert.convert_fixed_point import from_decimal
  from cudf._typing import ColumnBinaryOperand, Dtype
  from cudf.api.types import is_integer_dtype, is_scalar
  from cudf.core.buffer import as_buffer
  from cudf.core.column import ColumnBase
  from cudf.core.dtypes import Decimal32Dtype, Decimal64Dtype, Decimal128Dtype, DecimalDtype
  from cudf.core.mixins import BinaryOperand
  from cudf.utils.utils import pa_mask_buffer_to_mask
  from .numerical_base import NumericalBaseColumn
label_desc: Use image node_id 8 for calling the DecimalBaseColumn obj's underlying member method code with example usage: obj.normalize_binop_value(other) and returns: NotImplemented, other, other, cudf, NotImplemented