fix ci

modin/core/execution/ray/generic/io/io.py

@@ -21,12 +21,48 @@ class RayIO(BaseIO):
 
     @classmethod
     def from_ray(cls, ray_obj):
+        """
+        Create a Modin `query_compiler` from a Ray Dataset.
+
+        Parameters
+        ----------
+        ray_obj : ray.data.Dataset
+            The Ray Dataset to convert from.
+
+        Returns
+        -------
+        BaseQueryCompiler
+            QueryCompiler containing data from the Ray Dataset.
+
+        Notes
+        -----
+        This function must be implemented in every subclass 
+        otherwise NotImplementedError will be raised.
+        """
         raise NotImplementedError(
             f"Modin dataset cann't be created from `ray.data.Dataset` using {cls}."
         )
 
     @classmethod
     def to_ray(cls, modin_obj):
+        """
+        Convert a Modin DataFrame to a Ray Dataset.
+
+        Parameters
+        ----------
+        modin_obj : modin.DataFrame
+            The Modin DataFrame to convert.
+
+        Returns
+        -------
+        ray.data.Dataset
+            Converted object with type depending on input.
+
+        Notes
+        -----
+        This function must be implemented in every subclass 
+        otherwise NotImplementedError will be raised.
+        """
         raise NotImplementedError(
             f"`ray.data.Dataset` cann't be created from Modin DataFrame using {cls}."
         )

modin/core/execution/ray/implementations/pandas_on_ray/io/io.py

@@ -39,6 +39,10 @@
     PandasSQLParser,
 )
 from modin.core.storage_formats.pandas.query_compiler import PandasQueryCompiler
+from modin.distributed.dataframe.pandas.partitions import (
+    from_partitions,
+    unwrap_partitions,
+)
 from modin.experimental.core.io import (
     ExperimentalCSVGlobDispatcher,
     ExperimentalCustomTextDispatcher,
@@ -53,10 +57,6 @@
     ExperimentalPandasPickleParser,
     ExperimentalPandasXmlParser,
 )
-from modin.distributed.dataframe.pandas.partitions import (
-    from_partitions,
-    unwrap_partitions,
-)
 
 from ..dataframe import PandasOnRayDataframe
 from ..partitioning import PandasOnRayDataframePartition

modin/core/io/io.py

@@ -720,7 +720,7 @@ def to_parquet(cls, obj, path, **kwargs):  # noqa: PR01
         return obj.to_parquet(path, **kwargs)
 
     @classmethod
-    def to_ray(cls, modin_df):
+    def to_ray(cls, modin_obj):
         """
         Convert a Modin DataFrame to a Ray Dataset.
 

modin/pandas/dataframe.py

@@ -44,7 +44,7 @@
 from modin.error_message import ErrorMessage
 from modin.logging import disable_logging
 from modin.pandas import Categorical
-from modin.pandas.io import from_non_pandas, from_pandas, to_pandas, from_ray, to_ray
+from modin.pandas.io import from_non_pandas, from_pandas, to_pandas, to_ray
 from modin.utils import (
     MODIN_UNNAMED_SERIES_LABEL,
     _inherit_docstrings,
@@ -921,27 +921,6 @@ def from_dict(
             )
         )
 
-    @classmethod
-    def from_ray(cls, ray_obj):
-        """
-        Convert a Ray Dataset into Modin DataFrame.
-
-        Parameters
-        ----------
-        ray_obj : ray.data.Dataset
-            The Ray Dataset to convert from.
-
-        Returns
-        -------
-        DataFrame
-            A new Modin DataFrame object.
-
-        Notes
-        -----
-        Ray Dataset may only be converted to Modin Dataframe if Modin uses a Ray engine.
-        """
-        return from_ray(ray_obj)
-
     @classmethod
     def from_records(
         cls,
@@ -2254,11 +2233,6 @@ def to_ray(self):
         """
         Convert a Modin DataFrame to a Ray Dataset.
 
-        Parameters
-        ----------
-        modin_obj : modin.DataFrame
-            The Modin DataFrame to convert.
-
         Returns
         -------
         ray.data.Dataset

modin/pandas/test/test_api.py

@@ -152,7 +152,7 @@ def test_dataframe_api_equality():
 
     ignore_in_pandas = ["timetuple"]
     # modin - namespace for using experimental functionality
-    ignore_in_modin = ["modin", "to_pandas"]
+    ignore_in_modin = ["modin", "to_pandas", "to_ray"]
     missing_from_modin = set(pandas_dir) - set(modin_dir)
     assert not len(
         missing_from_modin - set(ignore_in_pandas)
@@ -164,7 +164,7 @@ def test_dataframe_api_equality():
     ), "Differences found in API: {}".format(set(modin_dir) - set(pandas_dir))
 
     # These have to be checked manually
-    allowed_different = ["to_hdf", "hist", "modin", "to_pandas"]
+    allowed_different = ["to_hdf", "hist", "modin", "to_pandas", "to_ray"]
 
     assert_parameters_eq((pandas.DataFrame, pd.DataFrame), modin_dir, allowed_different)
 

modin/pandas/test/test_io.py

@@ -47,7 +47,7 @@
     TestReadFromSqlServer,
 )
 from modin.db_conn import ModinDatabaseConnection, UnsupportedDatabaseException
-from modin.pandas.io import from_arrow, to_pandas, from_ray
+from modin.pandas.io import from_arrow, from_ray, to_pandas
 from modin.test.test_utils import warns_that_defaulting_to_pandas
 
 from .utils import (
@@ -3246,26 +3246,21 @@ def test_to_ray():
             RuntimeError,
             match="Modin Dataframe may only be converted to a Ray Dataset if Modin uses a Ray engine.",
         ):
-            _= modin_df.to_ray()
+            _ = modin_df.to_ray()
 
 
+@pytest.mark.skipif(
+    condition=Engine.get() != "Ray",
+    reason="Ray Dataset creation is only available for Ray engine",
+)
 @pytest.mark.filterwarnings(default_to_pandas_ignore_string)
 def test_from_ray():
     index = pandas.DatetimeIndex(
         pandas.date_range("2000", freq="h", periods=len(TEST_DATA["col1"]))
     )
     modin_df, pandas_df = create_test_dfs(TEST_DATA, index=index)
 
-    from ray.data import from_pandas
+    ray_df = ray.data.from_pandas(pandas_df)
 
-    ray_df = from_pandas(pandas_df)
-
-    if Engine.get() == "Ray":
-        result_df = from_ray(ray_df)
-        df_equals(result_df, modin_df)
-    else:
-        with pytest.raises(
-            RuntimeError,
-            match="Modin Dataframe may only be converted to a Ray Dataset if Modin uses a Ray engine.",
-        ):
-            _ = from_ray(ray_df)
+    result_df = from_ray(ray_df)
+    df_equals(result_df, modin_df)