gurudesh/pytracebugs huggingface dataset:
# Buggy code
def _fold_reduce(self, axis, func):
    """
    Apply function that reduce Manager to series but require knowledge of full axis.

    Parameters
    ----------
        axis : 0 or 1
            The axis to apply the function to (0 - index, 1 - columns).
        func : callable
            The function to reduce the Manager by. This function takes in a Manager.

    Returns
    -------
    BasePandasFrame
        Pandas series containing the reduced data.
    """
    func = self._build_mapreduce_func(axis, func)
    new_parts = self._frame_mgr_cls.map_axis_partitions(axis, self._partitions, func)
    return self._compute_map_reduce_metadata(axis, new_parts)


# Traceback (Exception)
Traceback (most recent call last):
File "test.py", line 15, in <module>
print(f"modin:\n{modin_df.sum(min_count=1)}")
File "modin\pandas\base.py", line 3512, in __str__
return repr(self)
File "modin\pandas\series.py", line 307, in __repr__
temp_df = self._build_repr_df(num_rows, num_cols)
File "modin\pandas\base.py", line 108, in _build_repr_df
return self.iloc[indexer]._query_compiler.to_pandas()
File "modin\backends\pandas\query_compiler.py", line 191, in to_pandas
return self._modin_frame.to_pandas()
File "modin\engines\base\frame\data.py", line 1801, in to_pandas
"Internal and external indices do not match.",
File "modin\error_message.py", line 54, in catch_bugs_and_request_email
" caused this error.\n{}".format(extra_log)
Exception: Internal Error. Please email bug_reports@modin.org with the traceback and command that caused this error.
Internal and external indices do not match.

# Fixed code
def _fold_reduce(self, axis, func, preserve_index=True):
    """
    Apply function that reduce Manager to series but require knowledge of full axis.

    Parameters
    ----------
        axis : 0 or 1
            The axis to apply the function to (0 - index, 1 - columns).
        func : callable
            The function to reduce the Manager by. This function takes in a Manager.
        preserve_index : boolean
            The flag to preserve labels for the reduced axis.

    Returns
    -------
    BasePandasFrame
        Pandas series containing the reduced data.
    """
    func = self._build_mapreduce_func(axis, func)
    new_parts = self._frame_mgr_cls.map_axis_partitions(axis, self._partitions, func)
    return self._compute_map_reduce_metadata(
        axis, new_parts, preserve_index=preserve_index
    )
# Buggy code
def filter_full_axis(self, axis, func):
    """Filter data based on the function provided along an entire axis.

    Args:
        axis: The axis to filter over.
        func: The function to use for the filter. This function should filter the
            data itself.

    Returns:
        A new dataframe.
    """
    new_partitions = self._frame_mgr_cls.map_axis_partitions(
        axis, self._partitions, func, keep_partitioning=True
    )
    if axis == 0:
        new_index = self.index
        new_lengths = self._row_lengths
        new_widths = None  # We do not know what the resulting widths will be
        new_columns = self._frame_mgr_cls.get_indices(
            1, new_partitions, lambda df: df.columns
        )
    else:
        new_columns = self.columns
        new_lengths = None  # We do not know what the resulting lengths will be
        new_widths = self._column_widths
        new_index = self._frame_mgr_cls.get_indices(
            0, new_partitions, lambda df: df.index
        )
    return self.__constructor__(
        new_partitions,
        new_index,
        new_columns,
        new_lengths,
        new_widths,
        self.dtypes if axis == 0 else None,
    )


# Traceback (Exception)
Traceback (most recent call last):
File "test.py", line 15, in <module>
print(f"modin:\n{modin_df.sum(min_count=1)}")
File "modin\pandas\base.py", line 3512, in __str__
return repr(self)
File "modin\pandas\series.py", line 307, in __repr__
temp_df = self._build_repr_df(num_rows, num_cols)
File "modin\pandas\base.py", line 108, in _build_repr_df
return self.iloc[indexer]._query_compiler.to_pandas()
File "modin\backends\pandas\query_compiler.py", line 191, in to_pandas
return self._modin_frame.to_pandas()
File "modin\engines\base\frame\data.py", line 1801, in to_pandas
"Internal and external indices do not match.",
File "modin\error_message.py", line 54, in catch_bugs_and_request_email
" caused this error.\n{}".format(extra_log)
Exception: Internal Error. Please email bug_reports@modin.org with the traceback and command that caused this error.
Internal and external indices do not match.

# Fixed code
def filter_full_axis(self, axis, func):
    """Filter data based on the function provided along an entire axis.

    Args:
        axis: The axis to filter over.
        func: The function to use for the filter. This function should filter the
            data itself.

    Returns:
        A new dataframe.
    """
    new_partitions = self._frame_mgr_cls.map_axis_partitions(
        axis, self._partitions, func, keep_partitioning=True
    )
    new_axes, new_lengths = [0, 0], [0, 0]

    new_axes[axis] = self.axes[axis]
    new_axes[axis ^ 1] = self._compute_axis_labels(axis ^ 1, new_partitions)

    new_lengths[axis] = self._axes_lengths[axis]
    new_lengths[axis ^ 1] = None  # We do not know what the resulting widths will be

    return self.__constructor__(
        new_partitions,
        *new_axes,
        *new_lengths,
        self.dtypes if axis == 0 else None,
    )
# Buggy code
def kurt(self, axis=None, skipna=None, level=None, numeric_only=None, **kwargs):
    axis = self._get_axis_number(axis)
    if level is not None:
        func_kwargs = {
            "skipna": skipna,
            "level": level,
            "numeric_only": numeric_only,
        }

        return self.__constructor__(
            query_compiler=self._query_compiler.apply("kurt", axis, **func_kwargs)
        )

    if numeric_only:
        self._validate_dtypes(numeric_only=True)
    return self._reduce_dimension(
        self._query_compiler.kurt(
            axis=axis,
            skipna=skipna,
            level=level,
            numeric_only=numeric_only,
            **kwargs,
        )
    )


# Traceback (Exception)
Traceback (most recent call last):
File "test.py", line 15, in <module>
print(f"modin:\n{modin_df.sum(min_count=1)}")
File "modin\pandas\base.py", line 3512, in __str__
return repr(self)
File "modin\pandas\series.py", line 307, in __repr__
temp_df = self._build_repr_df(num_rows, num_cols)
File "modin\pandas\base.py", line 108, in _build_repr_df
return self.iloc[indexer]._query_compiler.to_pandas()
File "modin\backends\pandas\query_compiler.py", line 191, in to_pandas
return self._modin_frame.to_pandas()
File "modin\engines\base\frame\data.py", line 1801, in to_pandas
"Internal and external indices do not match.",
File "modin\error_message.py", line 54, in catch_bugs_and_request_email
" caused this error.\n{}".format(extra_log)
Exception: Internal Error. Please email bug_reports@modin.org with the traceback and command that caused this error.
Internal and external indices do not match.

# Fixed code
def kurt(self, axis=None, skipna=None, level=None, numeric_only=None, **kwargs):
    axis = self._get_axis_number(axis)
    if level is not None:
        func_kwargs = {
            "skipna": skipna,
            "level": level,
            "numeric_only": numeric_only,
        }

        return self.__constructor__(
            query_compiler=self._query_compiler.apply("kurt", axis, **func_kwargs)
        )

    if numeric_only is not None and not numeric_only:
        self._validate_dtypes(numeric_only=True)

    data = self._get_numeric_data(axis) if numeric_only else self

    return self._reduce_dimension(
        data._query_compiler.kurt(
            axis=axis,
            skipna=skipna,
            level=level,
            numeric_only=numeric_only,
            **kwargs,
        )
    )
# Buggy code
def mean(self, axis=None, skipna=None, level=None, numeric_only=None, **kwargs):
    axis = self._get_axis_number(axis)
    data = self._validate_dtypes_sum_prod_mean(axis, numeric_only, ignore_axis=False)
    return data._reduce_dimension(
        data._query_compiler.mean(
            axis=axis,
            skipna=skipna,
            level=level,
            numeric_only=numeric_only,
            **kwargs,
        )
    )


# Traceback (Exception)
Traceback (most recent call last):
File "test.py", line 15, in <module>
print(f"modin:\n{modin_df.sum(min_count=1)}")
File "modin\pandas\base.py", line 3512, in __str__
return repr(self)
File "modin\pandas\series.py", line 307, in __repr__
temp_df = self._build_repr_df(num_rows, num_cols)
File "modin\pandas\base.py", line 108, in _build_repr_df
return self.iloc[indexer]._query_compiler.to_pandas()
File "modin\backends\pandas\query_compiler.py", line 191, in to_pandas
return self._modin_frame.to_pandas()
File "modin\engines\base\frame\data.py", line 1801, in to_pandas
"Internal and external indices do not match.",
File "modin\error_message.py", line 54, in catch_bugs_and_request_email
" caused this error.\n{}".format(extra_log)
Exception: Internal Error. Please email bug_reports@modin.org with the traceback and command that caused this error.
Internal and external indices do not match.

# Fixed code
def mean(self, axis=None, skipna=None, level=None, numeric_only=None, **kwargs):
    return self._stat_operation("mean", axis, skipna, level, numeric_only, **kwargs)
# Buggy code
def _index_name(self, col):
    if col.startswith("__index__"):
        return None
    return col


# Traceback (ValueError)
Traceback (most recent call last):
File "../reproducer.py", line 15, in <module>
md_df = pd.DataFrame(data, index=mi_index)
File "/localdisk/dchigare/repos/modin_bp/modin/pandas/dataframe.py", line 142, in __init__
self._query_compiler = from_pandas(pandas_df)._query_compiler
File "/localdisk/dchigare/repos/modin_bp/modin/pandas/utils.py", line 37, in from_pandas
return DataFrame(query_compiler=EngineDispatcher.from_pandas(df))
File "/localdisk/dchigare/repos/modin_bp/modin/data_management/factories/dispatcher.py", line 97, in from_pandas
return cls.__engine._from_pandas(df)
File "/localdisk/dchigare/repos/modin_bp/modin/data_management/factories/factories.py", line 71, in _from_pandas
return cls.io_cls.from_pandas(df)
File "/localdisk/dchigare/repos/modin_bp/modin/engines/base/io/io.py", line 31, in from_pandas
return cls.query_compiler_cls.from_pandas(df, cls.frame_cls)
File "/localdisk/dchigare/repos/modin_bp/modin/experimental/backends/omnisci/query_compiler.py", line 42, in from_pandas
return cls(data_cls.from_pandas(df))
File "/localdisk/dchigare/repos/modin_bp/modin/experimental/engines/omnisci_on_ray/frame/data.py", line 1142, in from_pandas
df = df.reset_index()
File "/localdisk/dchigare/miniconda3/envs/modin_on_omnisci/lib/python3.7/site-packages/pandas/core/frame.py", line 4854, in reset_index
new_obj.insert(0, name, level_values)
File "/localdisk/dchigare/miniconda3/envs/modin_on_omnisci/lib/python3.7/site-packages/pandas/core/frame.py", line 3623, in insert
self._mgr.insert(loc, column, value, allow_duplicates=allow_duplicates)
File "/localdisk/dchigare/miniconda3/envs/modin_on_omnisci/lib/python3.7/site-packages/pandas/core/internals/managers.py", line 1177, in insert
raise ValueError(f"cannot insert {item}, already exists")
ValueError: cannot insert __index__, already exists

# Fixed code
def _index_name(self, col):
    if col == "__index__":
        return None

    match = re.search("__index__\\d+_(.*)", col)
    if match:
        name = match.group(1)
        if name == "__None__":
            return None
        return name

    return col
# Buggy code
def concat(cls, axis, left_parts, right_parts):
    """Concatenate the blocks with another set of blocks.

    Note: Assumes that the blocks are already the same shape on the
        dimension being concatenated. A ValueError will be thrown if this
        condition is not met.

    Args:
        axis: The axis to concatenate to.
        right_parts: the other blocks to be concatenated. This is a
            BaseFrameManager object.

    Returns:
        A new BaseFrameManager object, the type of object that called this.
    """
    if type(right_parts) is list:
        return np.concatenate([left_parts] + right_parts, axis=axis)
    else:
        return np.append(left_parts, right_parts, axis=axis)


# Traceback (ValueError)
Traceback (most recent call last):
File "test_setitem6.py", line 4, in <module>
df1.loc["row1"]["col1"] = 11
File "/localdisk/gashiman/modin/modin/pandas/series.py", line 335, in __setitem__
self._parent.loc[self.name] = self
File "/localdisk/gashiman/modin/modin/pandas/indexing.py", line 279, in __setitem__
super(_LocIndexer, self).__setitem__(row_lookup, col_lookup, item)
File "/localdisk/gashiman/modin/modin/pandas/indexing.py", line 162, in __setitem__
new_qc = self.qc.setitem(1, self.qc.index[row_lookup[0]], item)
File "/localdisk/gashiman/modin/modin/backends/pandas/query_compiler.py", line 1285, in setitem
value._modin_frame._concat(0, [mask], "inner", False)
File "/localdisk/gashiman/modin/modin/engines/base/frame/data.py", line 1273, in _concat
new_partitions = self._frame_mgr_cls.concat(axis, left_parts, right_parts)
File "/localdisk/gashiman/modin/modin/engines/base/frame/partition_manager.py", line 223, in concat
return np.concatenate([left_parts] + right_parts, axis=axis)
File "<__array_function__ internals>", line 5, in concatenate
ValueError: all the input arrays must have same number of dimensions, but the array at index 0 has 2 dimension(s) and the array at index 1 has 1 dimension(s)

# Fixed code
def concat(cls, axis, left_parts, right_parts):
    """Concatenate the blocks with another set of blocks.

    Note: Assumes that the blocks are already the same shape on the
        dimension being concatenated. A ValueError will be thrown if this
        condition is not met.

    Args:
        axis: The axis to concatenate to.
        right_parts: the other blocks to be concatenated. This is a
            BaseFrameManager object.

    Returns:
        A new BaseFrameManager object, the type of object that called this.
    """
    if type(right_parts) is list:
        # `np.array` with partitions of empty ModinFrame has a shape (0,)
        # but `np.concatenate` can concatenate arrays only if its shapes at
        # specified axis are equals, so filtering empty frames to avoid concat error
        right_parts = [o for o in right_parts if o.size != 0]
        return np.concatenate([left_parts] + right_parts, axis=axis)
    else:
        return np.append(left_parts, right_parts, axis=axis)
# Buggy code
def _binary_op(self, op, other, **kwargs):
    # _axis indicates the operator will use the default axis
    if kwargs.pop("_axis", None) is None:
        if kwargs.get("axis", None) is not None:
            kwargs["axis"] = axis = self._get_axis_number(kwargs.get("axis", None))
        else:
            kwargs["axis"] = axis = 1
    else:
        axis = 0
    if kwargs.get("level", None) is not None:
        # Broadcast is an internally used argument
        kwargs.pop("broadcast", None)
        return self._default_to_pandas(
            getattr(getattr(pandas, self.__name__), op), other, **kwargs
        )
    other = self._validate_other(other, axis, numeric_or_object_only=True)
    new_query_compiler = getattr(self._query_compiler, op)(other, **kwargs)
    return self._create_or_update_from_compiler(new_query_compiler)


# 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 _binary_op(self, op, other, **kwargs):
    # _axis indicates the operator will use the default axis
    if kwargs.pop("_axis", None) is None:
        if kwargs.get("axis", None) is not None:
            kwargs["axis"] = axis = self._get_axis_number(kwargs.get("axis", None))
        else:
            kwargs["axis"] = axis = 1
    else:
        axis = 0
    if kwargs.get("level", None) is not None:
        # Broadcast is an internally used argument
        kwargs.pop("broadcast", None)
        return self._default_to_pandas(
            getattr(getattr(pandas, type(self).__name__), op), other, **kwargs
        )
    other = self._validate_other(other, axis, numeric_or_object_only=True)
    new_query_compiler = getattr(self._query_compiler, op)(other, **kwargs)
    return self._create_or_update_from_compiler(new_query_compiler)
# Buggy code
def _get_axis_number(self, axis):
    return (
        getattr(pandas, self.__name__)()._get_axis_number(axis)
        if axis is not None
        else 0
    )


# 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 _get_axis_number(self, axis):
    return (
        getattr(pandas, type(self).__name__)()._get_axis_number(axis)
        if axis is not None
        else 0
    )
# Buggy code
def __getitem__(self, key):
    if len(self) == 0:
        return self._default_to_pandas("__getitem__", key)
    # see if we can slice the rows
    # This lets us reuse code in Pandas to error check
    indexer = convert_to_index_sliceable(
        getattr(pandas, self.__name__)(index=self.index), key
    )
    if indexer is not None:
        return self._getitem_slice(indexer)
    else:
        return self._getitem(key)


# 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 __getitem__(self, key):
    if len(self) == 0:
        return self._default_to_pandas("__getitem__", key)
    # see if we can slice the rows
    # This lets us reuse code in Pandas to error check
    indexer = convert_to_index_sliceable(
        getattr(pandas, type(self).__name__)(index=self.index), key
    )
    if indexer is not None:
        return self._getitem_slice(indexer)
    else:
        return self._getitem(key)
# Buggy code
def __repr__(self):
    num_rows = pandas.get_option("max_rows") or 60
    num_cols = pandas.get_option("max_columns") or 20
    temp_df = self._build_repr_df(num_rows, num_cols)
    if isinstance(temp_df, pandas.DataFrame):
        temp_df = temp_df.iloc[:, 0]
    temp_str = repr(temp_df)
    if self.name is not None:
        name_str = "Name: {}, ".format(str(self.name))
    else:
        name_str = ""
    if len(self.index) > num_rows:
        len_str = "Length: {}, ".format(len(self.index))
    else:
        len_str = ""
    dtype_str = "dtype: {}".format(temp_str.rsplit("dtype: ", 1)[-1])
    if len(self) == 0:
        return "Series([], {}{}".format(name_str, dtype_str)
    return temp_str.rsplit("\nName:", 1)[0] + "\n{}{}{}".format(
        name_str, len_str, dtype_str
    )


# Traceback (IndexError)
Traceback (most recent call last):
File "t2.py", line 5, in <module>
print(s)
File "C:\Users\dchigare\Desktop\REPOS\modin\modin\pandas\base.py", line 3471, in __str__
return repr(self)
File "C:\Users\dchigare\Desktop\REPOS\modin\modin\pandas\series.py", line 298, in __repr__
temp_df = temp_df.iloc[:, 0]
File "C:\Program Files (x86)\Microsoft Visual Studio\Shared\Python37_64\lib\site-packages\pandas\core\indexing.py", line 1762, in __getitem__
return self._getitem_tuple(key)
File "C:\Program Files (x86)\Microsoft Visual Studio\Shared\Python37_64\lib\site-packages\pandas\core\indexing.py", line 2067, in _getitem_tuple
self._has_valid_tuple(tup)
File "C:\Program Files (x86)\Microsoft Visual Studio\Shared\Python37_64\lib\site-packages\pandas\core\indexing.py", line 703, in _has_valid_tuple
self._validate_key(k, i)
File "C:\Program Files (x86)\Microsoft Visual Studio\Shared\Python37_64\lib\site-packages\pandas\core\indexing.py", line 1994, in _validate_key
self._validate_integer(key, axis)
File "C:\Program Files (x86)\Microsoft Visual Studio\Shared\Python37_64\lib\site-packages\pandas\core\indexing.py", line 2063, in _validate_integer
raise IndexError("single positional indexer is out-of-bounds")
IndexError: single positional indexer is out-of-bounds

# Fixed code
def __repr__(self):
    num_rows = pandas.get_option("max_rows") or 60
    num_cols = pandas.get_option("max_columns") or 20
    temp_df = self._build_repr_df(num_rows, num_cols)
    if isinstance(temp_df, pandas.DataFrame) and not temp_df.empty:
        temp_df = temp_df.iloc[:, 0]
    temp_str = repr(temp_df)
    if self.name is not None:
        name_str = "Name: {}, ".format(str(self.name))
    else:
        name_str = ""
    if len(self.index) > num_rows:
        len_str = "Length: {}, ".format(len(self.index))
    else:
        len_str = ""
    dtype_str = "dtype: {}".format(
        str(self.dtype) + ")" if temp_df.empty else temp_str.rsplit("dtype: ", 1)[-1]
    )
    if len(self) == 0:
        return "Series([], {}{}".format(name_str, dtype_str)
    return temp_str.rsplit("\nName:", 1)[0] + "\n{}{}{}".format(
        name_str, len_str, dtype_str
    )
# Buggy code
def apply(self, func, axis, *args, **kwargs):
    """Apply func across given axis.

    Args:
        func: The function to apply.
        axis: Target axis to apply the function along.

    Returns:
        A new PandasQueryCompiler.
    """
    if isinstance(func, str):
        return self._apply_text_func_elementwise(func, axis, *args, **kwargs)
    elif callable(func):
        return self._callable_func(func, axis, *args, **kwargs)
    elif isinstance(func, dict):
        return self._dict_func(func, axis, *args, **kwargs)
    elif is_list_like(func):
        return self._list_like_func(func, axis, *args, **kwargs)
    else:
        pass


# Traceback (Exception)
FutureWarning: pandas.core.index is deprecated and will be removed in a future version.  The public classes are available in the top-level namespace.
UserWarning: User-defined function verification is still under development in Modin. The function provided is not verified.
empty !
Traceback (most recent call last):
File "./test2.py", line 24, in <module>
rn = r.to_numpy()
File "~/.local/lib/python3.7/site-packages/modin/pandas/base.py", line 2962, in to_numpy
arr = self._query_compiler.to_numpy()
File "~/.local/lib/python3.7/site-packages/modin/backends/pandas/query_compiler.py", line 169, in to_numpy
len(arr) != len(self.index) or len(arr[0]) != len(self.columns)
File "~/.local/lib/python3.7/site-packages/modin/error_message.py", line 40, in catch_bugs_and_request_email
" caused this error.\n{}".format(extra_log)
Exception: Internal Error. Please email bug_reports@modin.org with the traceback and command that caused this error.

# Fixed code
def apply(self, func, axis, *args, **kwargs):
    """Apply func across given axis.

    Args:
        func: The function to apply.
        axis: Target axis to apply the function along.

    Returns:
        A new PandasQueryCompiler.
    """
    # if any of args contain modin object, we should
    # convert it to pandas
    args = try_cast_to_pandas(args)
    kwargs = try_cast_to_pandas(kwargs)
    if isinstance(func, str):
        return self._apply_text_func_elementwise(func, axis, *args, **kwargs)
    elif callable(func):
        return self._callable_func(func, axis, *args, **kwargs)
    elif isinstance(func, dict):
        return self._dict_func(func, axis, *args, **kwargs)
    elif is_list_like(func):
        return self._list_like_func(func, axis, *args, **kwargs)
    else:
        pass
# Buggy code
def _apply_text_func_elementwise(self, func, axis, *args, **kwargs):
    """Apply func passed as str across given axis in elementwise manner.

    Args:
        func: The function to apply.
        axis: Target axis to apply the function along.

    Returns:
        A new PandasQueryCompiler.
    """
    assert isinstance(func, str)
    kwargs["axis"] = axis
    new_modin_frame = self._modin_frame._apply_full_axis(
        axis, lambda df: getattr(df, func)(**kwargs)
    )
    return self.__constructor__(new_modin_frame)


# Traceback (Exception)
FutureWarning: pandas.core.index is deprecated and will be removed in a future version.  The public classes are available in the top-level namespace.
UserWarning: User-defined function verification is still under development in Modin. The function provided is not verified.
empty !
Traceback (most recent call last):
File "./test2.py", line 24, in <module>
rn = r.to_numpy()
File "~/.local/lib/python3.7/site-packages/modin/pandas/base.py", line 2962, in to_numpy
arr = self._query_compiler.to_numpy()
File "~/.local/lib/python3.7/site-packages/modin/backends/pandas/query_compiler.py", line 169, in to_numpy
len(arr) != len(self.index) or len(arr[0]) != len(self.columns)
File "~/.local/lib/python3.7/site-packages/modin/error_message.py", line 40, in catch_bugs_and_request_email
" caused this error.\n{}".format(extra_log)
Exception: Internal Error. Please email bug_reports@modin.org with the traceback and command that caused this error.

# Fixed code
def _apply_text_func_elementwise(self, func, axis, *args, **kwargs):
    """Apply func passed as str across given axis in elementwise manner.

    Args:
        func: The function to apply.
        axis: Target axis to apply the function along.

    Returns:
        A new PandasQueryCompiler.
    """
    assert isinstance(func, str)
    kwargs["axis"] = axis
    new_modin_frame = self._modin_frame._apply_full_axis(
        axis, lambda df: df.apply(func, *args, **kwargs)
    )
    return self.__constructor__(new_modin_frame)
# Buggy code
def _dict_func(self, func, axis, *args, **kwargs):
    """Apply function to certain indices across given axis.

    Args:
        func: The function to apply.
        axis: Target axis to apply the function along.

    Returns:
        A new PandasQueryCompiler.
    """
    if "axis" not in kwargs:
        kwargs["axis"] = axis

    def dict_apply_builder(df, func_dict={}):
        # Sometimes `apply` can return a `Series`, but we require that internally
        # all objects are `DataFrame`s.
        return pandas.DataFrame(df.apply(func_dict, *args, **kwargs))

    return self.__constructor__(
        self._modin_frame._apply_full_axis_select_indices(
            axis, dict_apply_builder, func, keep_remaining=False
        )
    )


# Traceback (Exception)
FutureWarning: pandas.core.index is deprecated and will be removed in a future version.  The public classes are available in the top-level namespace.
UserWarning: User-defined function verification is still under development in Modin. The function provided is not verified.
empty !
Traceback (most recent call last):
File "./test2.py", line 24, in <module>
rn = r.to_numpy()
File "~/.local/lib/python3.7/site-packages/modin/pandas/base.py", line 2962, in to_numpy
arr = self._query_compiler.to_numpy()
File "~/.local/lib/python3.7/site-packages/modin/backends/pandas/query_compiler.py", line 169, in to_numpy
len(arr) != len(self.index) or len(arr[0]) != len(self.columns)
File "~/.local/lib/python3.7/site-packages/modin/error_message.py", line 40, in catch_bugs_and_request_email
" caused this error.\n{}".format(extra_log)
Exception: Internal Error. Please email bug_reports@modin.org with the traceback and command that caused this error.

# Fixed code
def _dict_func(self, func, axis, *args, **kwargs):
    """Apply function to certain indices across given axis.

    Args:
        func: The function to apply.
        axis: Target axis to apply the function along.

    Returns:
        A new PandasQueryCompiler.
    """
    if "axis" not in kwargs:
        kwargs["axis"] = axis

    def dict_apply_builder(df, func_dict={}):
        # Sometimes `apply` can return a `Series`, but we require that internally
        # all objects are `DataFrame`s.
        return pandas.DataFrame(df.apply(func_dict, *args, **kwargs))

    func = {k: wrap_udf_function(v) if callable(v) else v for k, v in func.items()}
    return self.__constructor__(
        self._modin_frame._apply_full_axis_select_indices(
            axis, dict_apply_builder, func, keep_remaining=False
        )
    )
# Buggy code
def _list_like_func(self, func, axis, *args, **kwargs):
    """Apply list-like function across given axis.

    Args:
        func: The function to apply.
        axis: Target axis to apply the function along.

    Returns:
        A new PandasQueryCompiler.
    """
    # When the function is list-like, the function names become the index/columns
    new_index = (
        [f if isinstance(f, str) else f.__name__ for f in func]
        if axis == 0
        else self.index
    )
    new_columns = (
        [f if isinstance(f, str) else f.__name__ for f in func]
        if axis == 1
        else self.columns
    )
    new_modin_frame = self._modin_frame._apply_full_axis(
        axis,
        lambda df: pandas.DataFrame(df.apply(func, axis, *args, **kwargs)),
        new_index=new_index,
        new_columns=new_columns,
    )
    return self.__constructor__(new_modin_frame)


# Traceback (Exception)
FutureWarning: pandas.core.index is deprecated and will be removed in a future version.  The public classes are available in the top-level namespace.
UserWarning: User-defined function verification is still under development in Modin. The function provided is not verified.
empty !
Traceback (most recent call last):
File "./test2.py", line 24, in <module>
rn = r.to_numpy()
File "~/.local/lib/python3.7/site-packages/modin/pandas/base.py", line 2962, in to_numpy
arr = self._query_compiler.to_numpy()
File "~/.local/lib/python3.7/site-packages/modin/backends/pandas/query_compiler.py", line 169, in to_numpy
len(arr) != len(self.index) or len(arr[0]) != len(self.columns)
File "~/.local/lib/python3.7/site-packages/modin/error_message.py", line 40, in catch_bugs_and_request_email
" caused this error.\n{}".format(extra_log)
Exception: Internal Error. Please email bug_reports@modin.org with the traceback and command that caused this error.

# Fixed code
def _list_like_func(self, func, axis, *args, **kwargs):
    """Apply list-like function across given axis.

    Args:
        func: The function to apply.
        axis: Target axis to apply the function along.

    Returns:
        A new PandasQueryCompiler.
    """
    # When the function is list-like, the function names become the index/columns
    new_index = (
        [f if isinstance(f, str) else f.__name__ for f in func]
        if axis == 0
        else self.index
    )
    new_columns = (
        [f if isinstance(f, str) else f.__name__ for f in func]
        if axis == 1
        else self.columns
    )
    func = [wrap_udf_function(f) if callable(f) else f for f in func]
    new_modin_frame = self._modin_frame._apply_full_axis(
        axis,
        lambda df: pandas.DataFrame(df.apply(func, axis, *args, **kwargs)),
        new_index=new_index,
        new_columns=new_columns,
    )
    return self.__constructor__(new_modin_frame)
# Buggy code
def _callable_func(self, func, axis, *args, **kwargs):
    """Apply callable functions across given axis.

    Args:
        func: The functions to apply.
        axis: Target axis to apply the function along.

    Returns:
        A new PandasQueryCompiler.
    """
    if isinstance(pandas.DataFrame().apply(func), pandas.Series):
        new_modin_frame = self._modin_frame._fold_reduce(
            axis, lambda df: df.apply(func, axis=axis, *args, **kwargs)
        )
    else:
        new_modin_frame = self._modin_frame._apply_full_axis(
            axis, lambda df: df.apply(func, axis=axis, *args, **kwargs)
        )
    return self.__constructor__(new_modin_frame)


# Traceback (Exception)
FutureWarning: pandas.core.index is deprecated and will be removed in a future version.  The public classes are available in the top-level namespace.
UserWarning: User-defined function verification is still under development in Modin. The function provided is not verified.
empty !
Traceback (most recent call last):
File "./test2.py", line 24, in <module>
rn = r.to_numpy()
File "~/.local/lib/python3.7/site-packages/modin/pandas/base.py", line 2962, in to_numpy
arr = self._query_compiler.to_numpy()
File "~/.local/lib/python3.7/site-packages/modin/backends/pandas/query_compiler.py", line 169, in to_numpy
len(arr) != len(self.index) or len(arr[0]) != len(self.columns)
File "~/.local/lib/python3.7/site-packages/modin/error_message.py", line 40, in catch_bugs_and_request_email
" caused this error.\n{}".format(extra_log)
Exception: Internal Error. Please email bug_reports@modin.org with the traceback and command that caused this error.

# Fixed code
def _callable_func(self, func, axis, *args, **kwargs):
    """Apply callable functions across given axis.

    Args:
        func: The functions to apply.
        axis: Target axis to apply the function along.

    Returns:
        A new PandasQueryCompiler.
    """
    func = wrap_udf_function(func)
    new_modin_frame = self._modin_frame._apply_full_axis(
        axis, lambda df: df.apply(func, axis=axis, *args, **kwargs)
    )
    return self.__constructor__(new_modin_frame)
# Buggy code
def _set_axis(self, axis, new_axis):
    """Replaces the current labels at the specified axis with the new one

    Parameters
    ----------
        axis : int,
            Axis to set labels along
        new_axis : Index,
            The replacement labels
    """
    if axis:
        self._set_columns(new_axis)
    else:
        self._set_index(new_axis)


# Traceback (Exception)
FutureWarning: pandas.core.index is deprecated and will be removed in a future version.  The public classes are available in the top-level namespace.
UserWarning: User-defined function verification is still under development in Modin. The function provided is not verified.
empty !
Traceback (most recent call last):
File "./test2.py", line 24, in <module>
rn = r.to_numpy()
File "~/.local/lib/python3.7/site-packages/modin/pandas/base.py", line 2962, in to_numpy
arr = self._query_compiler.to_numpy()
File "~/.local/lib/python3.7/site-packages/modin/backends/pandas/query_compiler.py", line 169, in to_numpy
len(arr) != len(self.index) or len(arr[0]) != len(self.columns)
File "~/.local/lib/python3.7/site-packages/modin/error_message.py", line 40, in catch_bugs_and_request_email
" caused this error.\n{}".format(extra_log)
Exception: Internal Error. Please email bug_reports@modin.org with the traceback and command that caused this error.

# Fixed code
def _set_axis(self, axis, new_axis, cache_only=False):
    """Replaces the current labels at the specified axis with the new one

    Parameters
    ----------
        axis : int,
            Axis to set labels along
        new_axis : Index,
            The replacement labels
        cache_only : bool,
            Whether to change only external indices, or propagate it
            into partitions
    """
    if axis:
        if not cache_only:
            self._set_columns(new_axis)
        else:
            self._columns_cache = ensure_index(new_axis)
    else:
        if not cache_only:
            self._set_index(new_axis)
        else:
            self._index_cache = ensure_index(new_axis)
# Buggy code
def _validate_axis_equality(self, axis: int):
    """
    Validates internal and external indices of modin_frame at the specified axis.

    Parameters
    ----------
        axis : int,
            Axis to validate indices along
    """
    internal_axis = self._frame_mgr_cls.get_indices(
        axis, self._partitions, lambda df: df.axes[axis]
    )
    is_equals = self.axes[axis].equals(internal_axis)
    if not is_equals:
        self._set_axis(axis, self.axes[axis])


# Traceback (Exception)
FutureWarning: pandas.core.index is deprecated and will be removed in a future version.  The public classes are available in the top-level namespace.
UserWarning: User-defined function verification is still under development in Modin. The function provided is not verified.
empty !
Traceback (most recent call last):
File "./test2.py", line 24, in <module>
rn = r.to_numpy()
File "~/.local/lib/python3.7/site-packages/modin/pandas/base.py", line 2962, in to_numpy
arr = self._query_compiler.to_numpy()
File "~/.local/lib/python3.7/site-packages/modin/backends/pandas/query_compiler.py", line 169, in to_numpy
len(arr) != len(self.index) or len(arr[0]) != len(self.columns)
File "~/.local/lib/python3.7/site-packages/modin/error_message.py", line 40, in catch_bugs_and_request_email
" caused this error.\n{}".format(extra_log)
Exception: Internal Error. Please email bug_reports@modin.org with the traceback and command that caused this error.

# Fixed code
def _validate_axis_equality(self, axis: int, force: bool = False):
    """
    Validates internal and external indices of modin_frame at the specified axis.

    Parameters
    ----------
        axis : int,
            Axis to validate indices along
        force : bool,
            Whether to update external indices with internal if their lengths
            do not match or raise an exception in that case.
    """
    internal_axis = self._frame_mgr_cls.get_indices(
        axis, self._partitions, lambda df: df.axes[axis]
    )
    is_equals = self.axes[axis].equals(internal_axis)
    is_lenghts_matches = len(self.axes[axis]) == len(internal_axis)
    if not is_equals:
        if force:
            new_axis = self.axes[axis] if is_lenghts_matches else internal_axis
            self._set_axis(axis, new_axis, cache_only=not is_lenghts_matches)
        else:
            self._set_axis(
                axis,
                self.axes[axis],
            )
# Buggy code
def __getitem__(self, key):
    row_loc, col_loc, ndim, self.row_scaler, self.col_scaler = _parse_tuple(key)
    self._check_dtypes(row_loc)
    self._check_dtypes(col_loc)

    row_lookup, col_lookup = self._compute_lookup(row_loc, col_loc)
    result = super(_iLocIndexer, self).__getitem__(row_lookup, col_lookup, ndim)
    if isinstance(result, Series):
        result._parent = self.df
        result._parent_axis = 0
    return result


# Traceback (TypeError)
Python 3.8.3 (default, Jun  9 2020, 17:49:41)
[GCC 8.3.0] on linux
Type "help", "copyright", "credits" or "license" for more information.
import modin.pandas as pandas
foo = pandas.DataFrame({"col": [1,2,3,4]})
UserWarning: Distributing <class 'dict'> object. This may take some time.
foo
col
0    1
1    2
2    3
3    4
foo.loc[lambda val: val.col%2==0]
Traceback (most recent call last):
File "<stdin>", line 1, in <module>
File "/root/.cache/pypoetry/virtualenvs/onepassword-etl-NcjVOHQt-py3.8/src/modin/modin/pandas/indexing.py", line 252, in __getitem__
row_lookup, col_lookup = self._compute_lookup(row_loc, col_loc)
File "/root/.cache/pypoetry/virtualenvs/onepassword-etl-NcjVOHQt-py3.8/src/modin/modin/pandas/indexing.py", line 345, in _compute_lookup
row_lookup = self.qc.index.get_indexer_for(row_loc)
File "/root/.cache/pypoetry/virtualenvs/onepassword-etl-NcjVOHQt-py3.8/lib/python3.8/site-packages/pandas/core/indexes/base.py", line 4502, in get_indexer_for
return self.get_indexer(target, **kwargs)
File "/root/.cache/pypoetry/virtualenvs/onepassword-etl-NcjVOHQt-py3.8/lib/python3.8/site-packages/pandas/core/indexes/range.py", line 358, in get_indexer
return super().get_indexer(
File "/root/.cache/pypoetry/virtualenvs/onepassword-etl-NcjVOHQt-py3.8/lib/python3.8/site-packages/pandas/core/indexes/base.py", line 2709, in get_indexer
target = ensure_index(target)
File "/root/.cache/pypoetry/virtualenvs/onepassword-etl-NcjVOHQt-py3.8/lib/python3.8/site-packages/pandas/core/indexes/base.py", line 5358, in ensure_index
return Index(index_like)
File "/root/.cache/pypoetry/virtualenvs/onepassword-etl-NcjVOHQt-py3.8/lib/python3.8/site-packages/pandas/core/indexes/base.py", line 438, in __new__
subarr = com.asarray_tuplesafe(data, dtype=object)
File "/root/.cache/pypoetry/virtualenvs/onepassword-etl-NcjVOHQt-py3.8/lib/python3.8/site-packages/pandas/core/common.py", line 222, in asarray_tuplesafe
values = list(values)
TypeError: 'function' object is not iterable


# Fixed code
def __getitem__(self, key):
    if callable(key):
        return self.__getitem__(key(self.df))
    row_loc, col_loc, ndim, self.row_scaler, self.col_scaler = _parse_tuple(key)
    self._check_dtypes(row_loc)
    self._check_dtypes(col_loc)

    row_lookup, col_lookup = self._compute_lookup(row_loc, col_loc)
    result = super(_iLocIndexer, self).__getitem__(row_lookup, col_lookup, ndim)
    if isinstance(result, Series):
        result._parent = self.df
        result._parent_axis = 0
    return result
# Buggy code
def map_func(df, n=n, keep=keep, columns=columns):
    if columns is None:
        return pandas.DataFrame(
            getattr(pandas.Series, sort_type)(df.squeeze(axis=1), n=n, keep=keep)
        )
    return getattr(pandas.DataFrame, sort_type)(df, n=n, columns=columns, keep=keep)


# Traceback (Exception)
Traceback (most recent call last):
File "merge_test.py", line 6, in <module>
df3 = df1.merge(df2, on='name', how='inner')
File "/localdisk/gashiman/modin/modin/pandas/dataframe.py", line 1540, in merge
return result.reset_index(drop=True) if is_reset_index else result
File "/localdisk/gashiman/modin/modin/pandas/base.py", line 2301, in reset_index
new_query_compiler = self._query_compiler.reset_index(
File "/localdisk/gashiman/modin/modin/backends/pandas/query_compiler.py", line 442, in reset_index
new_self = self.copy()
File "/localdisk/gashiman/modin/modin/backends/pandas/query_compiler.py", line 217, in copy
return self.__constructor__(self._modin_frame.copy())
File "/localdisk/gashiman/modin/modin/engines/base/frame/data.py", line 532, in copy
return self.__constructor__(
File "/localdisk/gashiman/modin/modin/engines/base/frame/data.py", line 68, in __init__
ErrorMessage.catch_bugs_and_request_email(
File "/localdisk/gashiman/modin/modin/error_message.py", line 50, in catch_bugs_and_request_email
raise Exception(
Exception: Internal Error. Please email bug_reports@modin.org with the traceback and command that caused this error.
Column widths: 0 != 23

# Fixed code
def map_func(left, right=right, kwargs=kwargs):
    return pandas.merge(left, right, **kwargs)
# Buggy code
def length_fn_pandas(df):
    assert isinstance(df, pandas.DataFrame)
    return len(df) if len(df.columns) > 0 else 0


# Traceback (Exception)
Traceback (most recent call last):
File "merge_test.py", line 6, in <module>
df3 = df1.merge(df2, on='name', how='inner')
File "/localdisk/gashiman/modin/modin/pandas/dataframe.py", line 1540, in merge
return result.reset_index(drop=True) if is_reset_index else result
File "/localdisk/gashiman/modin/modin/pandas/base.py", line 2301, in reset_index
new_query_compiler = self._query_compiler.reset_index(
File "/localdisk/gashiman/modin/modin/backends/pandas/query_compiler.py", line 442, in reset_index
new_self = self.copy()
File "/localdisk/gashiman/modin/modin/backends/pandas/query_compiler.py", line 217, in copy
return self.__constructor__(self._modin_frame.copy())
File "/localdisk/gashiman/modin/modin/engines/base/frame/data.py", line 532, in copy
return self.__constructor__(
File "/localdisk/gashiman/modin/modin/engines/base/frame/data.py", line 68, in __init__
ErrorMessage.catch_bugs_and_request_email(
File "/localdisk/gashiman/modin/modin/error_message.py", line 50, in catch_bugs_and_request_email
raise Exception(
Exception: Internal Error. Please email bug_reports@modin.org with the traceback and command that caused this error.
Column widths: 0 != 23

# Fixed code
def length_fn_pandas(df):
    assert isinstance(df, pandas.DataFrame)
    return len(df) if len(df) > 0 else 0
# Buggy code
def width_fn_pandas(df):
    assert isinstance(df, pandas.DataFrame)
    return len(df.columns) if len(df) > 0 else 0


# Traceback (Exception)
Traceback (most recent call last):
File "merge_test.py", line 6, in <module>
df3 = df1.merge(df2, on='name', how='inner')
File "/localdisk/gashiman/modin/modin/pandas/dataframe.py", line 1540, in merge
return result.reset_index(drop=True) if is_reset_index else result
File "/localdisk/gashiman/modin/modin/pandas/base.py", line 2301, in reset_index
new_query_compiler = self._query_compiler.reset_index(
File "/localdisk/gashiman/modin/modin/backends/pandas/query_compiler.py", line 442, in reset_index
new_self = self.copy()
File "/localdisk/gashiman/modin/modin/backends/pandas/query_compiler.py", line 217, in copy
return self.__constructor__(self._modin_frame.copy())
File "/localdisk/gashiman/modin/modin/engines/base/frame/data.py", line 532, in copy
return self.__constructor__(
File "/localdisk/gashiman/modin/modin/engines/base/frame/data.py", line 68, in __init__
ErrorMessage.catch_bugs_and_request_email(
File "/localdisk/gashiman/modin/modin/error_message.py", line 50, in catch_bugs_and_request_email
raise Exception(
Exception: Internal Error. Please email bug_reports@modin.org with the traceback and command that caused this error.
Column widths: 0 != 23

# Fixed code
def width_fn_pandas(df):
    assert isinstance(df, pandas.DataFrame)
    return len(df.columns) if len(df.columns) > 0 else 0