# Buggy code
def all(self, axis=0, bool_only=None, skipna=True, level=None, **kwargs):
    """Return whether all elements are True over requested axis

    Note:
        If axis=None or axis=0, this call applies df.all(axis=1)
            to the transpose of df.
    """
    if axis is not None:
        axis = self._get_axis_number(axis)
        if bool_only and axis == 0:
            if hasattr(self, "dtype"):
                raise NotImplementedError(
                    "{}.{} does not implement numeric_only.".format(
                        self.__name__, "all"
                    )
                )
            data_for_compute = self[self.columns[self.dtypes == np.bool]]
            return data_for_compute.all(
                axis=axis, bool_only=False, skipna=skipna, level=level, **kwargs
            )
        if level is not None:
            if bool_only is not None:
                raise NotImplementedError(
                    "Option bool_only is not implemented with option level."
                )
            return self._handle_level_agg(axis, level, "all", skipna=skipna, **kwargs)
        return self._reduce_dimension(
            self._query_compiler.all(
                axis=axis, bool_only=bool_only, skipna=skipna, level=level, **kwargs
            )
        )
    else:
        if bool_only:
            raise ValueError("Axis must be 0 or 1 (got {})".format(axis))
        # Reduce to a scalar if axis is None.
        if level is not None:
            return self._handle_level_agg(axis, level, "all", skipna=skipna, **kwargs)
        else:
            result = self._reduce_dimension(
                self._query_compiler.all(
                    axis=0,
                    bool_only=bool_only,
                    skipna=skipna,
                    level=level,
                    **kwargs,
                )
            )
        if isinstance(result, BasePandasDataset):
            return result.all(
                axis=axis, bool_only=bool_only, skipna=skipna, level=level, **kwargs
            )
        return result


# Traceback (RecursionError)
Traceback (most recent call last):
File "1.py", line 14, in <module>
ref = df["a"].add(df["b"])
File "/localdisk/ilyaenko/modin/modin/pandas/series.py", line 376, in add
return super(Series, new_self).add(
File "/localdisk/ilyaenko/modin/modin/pandas/series.py", line 376, in add
return super(Series, new_self).add(
File "/localdisk/ilyaenko/modin/modin/pandas/series.py", line 376, in add
return super(Series, new_self).add(
[Previous line repeated 978 more times]
...
RecursionError: maximum recursion depth exceeded while calling a Python object

# Fixed code
def all(self, axis=0, bool_only=None, skipna=True, level=None, **kwargs):
    """Return whether all elements are True over requested axis

    Note:
        If axis=None or axis=0, this call applies df.all(axis=1)
            to the transpose of df.
    """
    if axis is not None:
        axis = self._get_axis_number(axis)
        if bool_only and axis == 0:
            if hasattr(self, "dtype"):
                raise NotImplementedError(
                    "{}.{} does not implement numeric_only.".format(
                        type(self).__name__, "all"
                    )
                )
            data_for_compute = self[self.columns[self.dtypes == np.bool]]
            return data_for_compute.all(
                axis=axis, bool_only=False, skipna=skipna, level=level, **kwargs
            )
        if level is not None:
            if bool_only is not None:
                raise NotImplementedError(
                    "Option bool_only is not implemented with option level."
                )
            return self._handle_level_agg(axis, level, "all", skipna=skipna, **kwargs)
        return self._reduce_dimension(
            self._query_compiler.all(
                axis=axis, bool_only=bool_only, skipna=skipna, level=level, **kwargs
            )
        )
    else:
        if bool_only:
            raise ValueError("Axis must be 0 or 1 (got {})".format(axis))
        # Reduce to a scalar if axis is None.
        if level is not None:
            return self._handle_level_agg(axis, level, "all", skipna=skipna, **kwargs)
        else:
            result = self._reduce_dimension(
                self._query_compiler.all(
                    axis=0,
                    bool_only=bool_only,
                    skipna=skipna,
                    level=level,
                    **kwargs,
                )
            )
        if isinstance(result, BasePandasDataset):
            return result.all(
                axis=axis, bool_only=bool_only, skipna=skipna, level=level, **kwargs
            )
        return result