A class method that returns a method that will correspond to an
        operator for an ExtensionArray subclass, by dispatching to the
        relevant operator defined on the individual elements of the
        ExtensionArray.

        Parameters
        ----------
        op : function
            An operator that takes arguments op(a, b)
        coerce_to_dtype :  bool, default True
            boolean indicating whether to attempt to convert
            the result to the underlying ExtensionArray dtype.
            If it's not possible to create a new ExtensionArray with the
            values, an ndarray is returned instead.

        Returns
        -------
        Callable[[Any, Any], Union[ndarray, ExtensionArray]]
            A method that can be bound to a class. When used, the method
            receives the two arguments, one of which is the instance of
            this class, and should return an ExtensionArray or an ndarray.

            Returning an ndarray may be necessary when the result of the
            `op` cannot be stored in the ExtensionArray. The dtype of the
            ndarray uses NumPy's normal inference rules.

        Example
        -------
        Given an ExtensionArray subclass called MyExtensionArray, use

        >>> __add__ = cls._create_method(operator.add)

        in the class definition of MyExtensionArray to create the operator
        for addition, that will be based on the operator implementation
        of the underlying elements of the ExtensionArray

def _create_method(cls, op, coerce_to_dtype=True):
        """
        A class method that returns a method that will correspond to an
        operator for an ExtensionArray subclass, by dispatching to the
        relevant operator defined on the individual elements of the
        ExtensionArray.

        Parameters
        ----------
        op : function
            An operator that takes arguments op(a, b)
        coerce_to_dtype :  bool, default True
            boolean indicating whether to attempt to convert
            the result to the underlying ExtensionArray dtype.
            If it's not possible to create a new ExtensionArray with the
            values, an ndarray is returned instead.

        Returns
        -------
        Callable[[Any, Any], Union[ndarray, ExtensionArray]]
            A method that can be bound to a class. When used, the method
            receives the two arguments, one of which is the instance of
            this class, and should return an ExtensionArray or an ndarray.

            Returning an ndarray may be necessary when the result of the
            `op` cannot be stored in the ExtensionArray. The dtype of the
            ndarray uses NumPy's normal inference rules.

        Example
        -------
        Given an ExtensionArray subclass called MyExtensionArray, use

        >>> __add__ = cls._create_method(operator.add)

        in the class definition of MyExtensionArray to create the operator
        for addition, that will be based on the operator implementation
        of the underlying elements of the ExtensionArray
        """

        def _binop(self, other):
            def convert_values(param):
                if isinstance(param, ExtensionArray) or is_list_like(param):
                    ovalues = param
                else:  # Assume its an object
                    ovalues = [param] * len(self)
                return ovalues

            if isinstance(other, (ABCSeries, ABCIndexClass)):
                # rely on pandas to unbox and dispatch to us
                return NotImplemented

            lvalues = self
            rvalues = convert_values(other)

            # If the operator is not defined for the underlying objects,
            # a TypeError should be raised
            res = [op(a, b) for (a, b) in zip(lvalues, rvalues)]

            def _maybe_convert(arr):
                if coerce_to_dtype:
                    # https://github.com/pandas-dev/pandas/issues/22850
                    # We catch all regular exceptions here, and fall back
                    # to an ndarray.
                    try:
                        res = self._from_sequence(arr)
                    except Exception:
                        res = np.asarray(arr)
                else:
                    res = np.asarray(arr)
                return res

            if op.__name__ in {'divmod', 'rdivmod'}:
                a, b = zip(*res)
                res = _maybe_convert(a), _maybe_convert(b)
            else:
                res = _maybe_convert(res)
            return res

        op_name = ops._get_op_name(op, True)
        return set_function_name(_binop, op_name, cls)