FIX-#7263: Empty docstrings should not be inherited (#7264)

Signed-off-by: Anatoly Myachev <anatoly.myachev@intel.com>

modin/core/execution/dask/implementations/pandas_on_dask/partitioning/virtual_partition.py

@@ -237,12 +237,12 @@ def wait(self):
         DaskWrapper.wait(self.list_of_blocks)
 
 
-@_inherit_docstrings(PandasOnDaskDataframeVirtualPartition.__init__)
+@_inherit_docstrings(PandasOnDaskDataframeVirtualPartition)
 class PandasOnDaskDataframeColumnPartition(PandasOnDaskDataframeVirtualPartition):
     axis = 0
 
 
-@_inherit_docstrings(PandasOnDaskDataframeVirtualPartition.__init__)
+@_inherit_docstrings(PandasOnDaskDataframeVirtualPartition)
 class PandasOnDaskDataframeRowPartition(PandasOnDaskDataframeVirtualPartition):
     axis = 1
 

modin/core/execution/python/implementations/pandas_on_python/partitioning/virtual_partition.py

@@ -48,11 +48,11 @@ class PandasOnPythonDataframeAxisPartition(PandasDataframeAxisPartition):
     partition_type = PandasOnPythonDataframePartition
 
 
-@_inherit_docstrings(PandasOnPythonDataframeAxisPartition.__init__)
+@_inherit_docstrings(PandasOnPythonDataframeAxisPartition)
 class PandasOnPythonDataframeColumnPartition(PandasOnPythonDataframeAxisPartition):
     axis = 0
 
 
-@_inherit_docstrings(PandasOnPythonDataframeAxisPartition.__init__)
+@_inherit_docstrings(PandasOnPythonDataframeAxisPartition)
 class PandasOnPythonDataframeRowPartition(PandasOnPythonDataframeAxisPartition):
     axis = 1

modin/core/execution/ray/implementations/pandas_on_ray/partitioning/virtual_partition.py

@@ -266,12 +266,12 @@ def wait(self):
         RayWrapper.wait(futures)
 
 
-@_inherit_docstrings(PandasOnRayDataframeVirtualPartition.__init__)
+@_inherit_docstrings(PandasOnRayDataframeVirtualPartition)
 class PandasOnRayDataframeColumnPartition(PandasOnRayDataframeVirtualPartition):
     axis = 0
 
 
-@_inherit_docstrings(PandasOnRayDataframeVirtualPartition.__init__)
+@_inherit_docstrings(PandasOnRayDataframeVirtualPartition)
 class PandasOnRayDataframeRowPartition(PandasOnRayDataframeVirtualPartition):
     axis = 1
 

modin/core/execution/unidist/implementations/pandas_on_unidist/partitioning/virtual_partition.py

@@ -259,12 +259,12 @@ def wait(self):
         UnidistWrapper.wait(futures)
 
 
-@_inherit_docstrings(PandasOnUnidistDataframeVirtualPartition.__init__)
+@_inherit_docstrings(PandasOnUnidistDataframeVirtualPartition)
 class PandasOnUnidistDataframeColumnPartition(PandasOnUnidistDataframeVirtualPartition):
     axis = 0
 
 
-@_inherit_docstrings(PandasOnUnidistDataframeVirtualPartition.__init__)
+@_inherit_docstrings(PandasOnUnidistDataframeVirtualPartition)
 class PandasOnUnidistDataframeRowPartition(PandasOnUnidistDataframeVirtualPartition):
     axis = 1
 

modin/core/storage_formats/base/query_compiler.py

@@ -1117,7 +1117,7 @@ def merge_asof(
         tolerance=None,
         allow_exact_matches: bool = True,
         direction: str = "backward",
-    ):
+    ):  # noqa: GL08
         # Pandas fallbacks for tricky cases:
         if (
             # No idea how this works or why it does what it does; and in fact
@@ -3621,7 +3621,9 @@ def groupby_fillna(
             drop=drop,
         )
 
-    def groupby_diff(self, by, axis, groupby_kwargs, agg_args, agg_kwargs, drop=False):
+    def groupby_diff(
+        self, by, axis, groupby_kwargs, agg_args, agg_kwargs, drop=False
+    ):  # noqa: GL08
         return self.groupby_agg(
             by=by,
             agg_func="diff",
@@ -3634,7 +3636,7 @@ def groupby_diff(self, by, axis, groupby_kwargs, agg_args, agg_kwargs, drop=Fals
 
     def groupby_pct_change(
         self, by, axis, groupby_kwargs, agg_args, agg_kwargs, drop=False
-    ):
+    ):  # noqa: GL08
         return self.groupby_agg(
             by=by,
             agg_func="pct_change",
@@ -3942,7 +3944,7 @@ def groupby_ohlc(
         agg_args,
         agg_kwargs,
         is_df,
-    ):
+    ):  # noqa: GL08
         if not is_df:
             return self.groupby_agg(
                 by=by,
@@ -4606,7 +4608,7 @@ def shift(
         freq,
         axis,
         fill_value,
-    ):
+    ):  # noqa: GL08
         return DataFrameDefault.register(pandas.DataFrame.shift)(
             self, periods, freq, axis, fill_value
         )

modin/pandas/accessor.py

@@ -196,7 +196,7 @@ def __init__(self, name: str, accessor) -> None:
         self._name = name
         self._accessor = accessor
 
-    def __get__(self, obj, cls):
+    def __get__(self, obj, cls):  # noqa: GL08
         if obj is None:
             return self._accessor
         accessor_obj = self._accessor(obj)

modin/pandas/base.py

@@ -1127,7 +1127,7 @@ def between_time(
             )
         )
 
-    def _deprecate_downcast(self, downcast, method_name: str):
+    def _deprecate_downcast(self, downcast, method_name: str):  # noqa: GL08
         if downcast is not lib.no_default:
             warnings.warn(
                 f"The 'downcast' keyword in {method_name} is deprecated and "

modin/pandas/dataframe.py

@@ -1678,7 +1678,7 @@ def quantile(
     _AXIS_ORDERS = ["index", "columns"]
     _get_index_resolvers = pandas.DataFrame._get_index_resolvers
 
-    def _get_axis_resolvers(self, axis: str) -> dict:
+    def _get_axis_resolvers(self, axis: str) -> dict:  # noqa: GL08
         # forked from pandas because we only want to update the index if there's more
         # than one level of the index.
         # index or columns

modin/pandas/groupby.py

@@ -86,7 +86,7 @@
 
 
 @_inherit_docstrings(pandas.core.groupby.DataFrameGroupBy)
-class DataFrameGroupBy(ClassLogger):
+class DataFrameGroupBy(ClassLogger):  # noqa: GL08
     _pandas_class = pandas.core.groupby.DataFrameGroupBy
     _return_tuple_when_iterating = False
     _df: Union[DataFrame, Series]
@@ -209,7 +209,7 @@ def default_handler(*args, **kwargs):
         return attr
 
     @property
-    def ngroups(self):
+    def ngroups(self):  # noqa: GL08
         return len(self)
 
     def skew(self, axis=lib.no_default, skipna=True, numeric_only=False, **kwargs):
@@ -608,7 +608,7 @@ def filter(self, func, dropna=True, *args, **kwargs):
             lambda df: df.filter(func, dropna=dropna, *args, **kwargs)
         )
 
-    def _deprecate_axis(self, axis: int, name: str) -> None:
+    def _deprecate_axis(self, axis: int, name: str) -> None:  # noqa: GL08
         if axis == 1:
             warnings.warn(
                 f"{type(self).__name__}.{name} with axis=1 is deprecated and "
@@ -1061,7 +1061,7 @@ def get_group(self, name, obj=None):
             )
         )
 
-    def __len__(self):
+    def __len__(self):  # noqa: GL08
         return len(self.indices)
 
     def all(self, skipna=True):
@@ -1728,7 +1728,7 @@ def groupby_on_multiple_columns(df, *args, **kwargs):
 
 
 @_inherit_docstrings(pandas.core.groupby.SeriesGroupBy)
-class SeriesGroupBy(DataFrameGroupBy):
+class SeriesGroupBy(DataFrameGroupBy):  # noqa: GL08
     _pandas_class = pandas.core.groupby.SeriesGroupBy
 
     @property
@@ -1810,7 +1810,7 @@ def value_counts(
         ascending: bool = False,
         bins=None,
         dropna: bool = True,
-    ):
+    ):  # noqa: GL08
         return self._default_to_pandas(
             lambda ser: ser.value_counts(
                 normalize=normalize,

modin/pandas/series_utils.py

@@ -550,7 +550,7 @@ def isnumeric(self):
     def isdecimal(self):
         return self._Series(query_compiler=self._query_compiler.str_isdecimal())
 
-    def __getitem__(self, key):
+    def __getitem__(self, key):  # noqa: GL08
         return self._Series(query_compiler=self._query_compiler.str___getitem__(key))
 
     def _default_to_pandas(self, op, *args, **kwargs):
@@ -577,7 +577,7 @@ def _default_to_pandas(self, op, *args, **kwargs):
 
 
 @_inherit_docstrings(pandas.core.indexes.accessors.CombinedDatetimelikeProperties)
-class DatetimeProperties(ClassLogger):
+class DatetimeProperties(ClassLogger):  # noqa: GL08
     _series: Series
     _query_compiler: BaseQueryCompiler
 
@@ -700,15 +700,15 @@ def tz(self) -> "tzinfo | None":
         return dtype.tz
 
     @property
-    def freq(self):
+    def freq(self):  # noqa: GL08
         return self._query_compiler.dt_freq().to_pandas().squeeze()
 
     @property
-    def unit(self):
+    def unit(self):  # noqa: GL08
         # use `iloc[0]` to return scalar
         return self._Series(query_compiler=self._query_compiler.dt_unit()).iloc[0]
 
-    def as_unit(self, *args, **kwargs):
+    def as_unit(self, *args, **kwargs):  # noqa: GL08
         return self._Series(
             query_compiler=self._query_compiler.dt_as_unit(*args, **kwargs)
         )
@@ -810,7 +810,7 @@ def isocalendar(self):
         return DataFrame(query_compiler=self._query_compiler.dt_isocalendar())
 
     @property
-    def qyear(self):
+    def qyear(self):  # noqa: GL08
         return self._Series(query_compiler=self._query_compiler.dt_qyear())
 
     @property

modin/utils.py

@@ -310,6 +310,9 @@ def _replace_doc(
     target_doc = target_obj.__doc__ or ""
     overwrite = overwrite or not target_doc
     doc = source_doc if overwrite else target_doc
+    if doc == "":
+        # Empty docstrings do not need to be inherited
+        return
 
     if parent_cls and not attr_name:
         if isinstance(target_obj, property):
@@ -434,6 +437,7 @@ def _documentable_obj(obj: object) -> bool:
         """Check if `obj` docstring could be patched."""
         return bool(
             callable(obj)
+            and not inspect.isclass(obj)
             or (isinstance(obj, property) and obj.fget)
             or (isinstance(obj, functools.cached_property))
             or (isinstance(obj, (staticmethod, classmethod)) and obj.__func__)

scripts/doc_checker.py

@@ -111,7 +111,9 @@ def check_optional_args(doc: Validator) -> list:
     list
         List of tuples with Modin error code and its description.
     """
-    if not doc.doc_parameters:
+    # `not doc.raw_doc and doc.clean_doc` - means that docstring was
+    # automatically generated by numpydoc with help of `pydoc.getdoc`.
+    if not doc.doc_parameters or (not doc.raw_doc and doc.clean_doc):
         return []
     optional_args = get_optional_args(doc)
     if not optional_args: