class_docstr: Base column for decimal32, decimal64 or decimal128 columns
class_docstr_tok: ["Base","column","for","decimal32",",","decimal64","or","decimal128","columns"]
code: def _binaryop(self, other: ColumnBinaryOperand, op: str):
      reflect, op = self._check_reflected_op(op)
      other = self._wrap_binop_normalization(other)
      if other is NotImplemented:
          return NotImplemented
      lhs, rhs = (other, self) if reflect else (self, other)
  
      # Binary Arithmetics between decimal columns. `Scale` and `precision`
      # are computed outside of libcudf
      if op in {"__add__", "__sub__", "__mul__", "__div__"}:
          output_type = _get_decimal_type(lhs.dtype, rhs.dtype, op)
          result = libcudf.binaryop.binaryop(lhs, rhs, op, output_type)
          # TODO:  Why is this necessary? Why isn't the result's
          # precision already set correctly based on output_type?
          result.dtype.precision = output_type.precision
      elif op in {
          "__eq__",
          "__ne__",
          "__lt__",
          "__gt__",
          "__le__",
          "__ge__",
      }:
          result = libcudf.binaryop.binaryop(lhs, rhs, op, bool)
      else:
          raise TypeError(
              f"{op} not supported for the following dtypes: "
              f"{self.dtype}, {other.dtype}"
          )
  
      return result
  
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 6 for calling the DecimalBaseColumn obj's underlying member method code with example usage: obj._binaryop(other, op) and returns: result, NotImplemented