updated doc for the kwargs and partiton keys

Author: yogesh266

ads/feature_store/docs/source/feature_group.rst

@@ -18,15 +18,19 @@ A ``FeatureGroup`` instance will be created.
     :caption: Python
 
     from ads.feature_store.feature_group import FeatureGroup
+    # Dictionary containing arguments for the feature group for the transformation function.
+    transformation_kwargs = {}
 
     feature_group_flights = (
         FeatureGroup()
         .with_feature_store_id(feature_store.id)
         .with_primary_keys(["col1"])
+        .with_partition_keys(["col1", "col2"])
         .with_name("flights_feature_group")
         .with_entity_id("<entity_id>")
         .with_compartment_id("ocid1.compartment..<unique_id>")
         .with_schema_details_from_dataframe(dataframe)
+        .with_transformation_kwargs(transformation_kwargs)
     )
 
   .. code-tab:: Python3
@@ -52,6 +56,9 @@ A ``FeatureGroup`` instance will be created.
       primaryKeys:
         items:
         - name: col1
+      partitionKeys:
+        items:
+        - name: col1
       statisticsConfig:
         isEnabled: true
     type: featureGroup

ads/feature_store/docs/source/quickstart.rst

@@ -73,19 +73,24 @@ Background reading to understand the concepts of Feature Store and OCI Data Scie
 
 
     # step2: Create feature store
-    def transactions_df(dataframe):
+    def transactions_df(dataframe, **kwargs):
+        columns = kwargs.get('columns', '*')  # Default to select all columns if 'columns' not provided
+        where_clause = kwargs.get('where_clause', '')  # Default to empty where clause if 'where_clause' not provided
+
         sql_query = f"""
                     SELECT
-                        col1,
-                        col2
+                        {columns}
                     FROM
-                        {dataframe}
+                        {table_name}
+                    {where_clause}
                 """
         return sql_query
 
+    transformation = feature_store.create_transformation(
+        transformation_mode=TransformationMode.SQL,
+        source_code_func=transactions_df
+    )
 
-    transformation = feature_store.create_transformation(transformation_mode=TransformationMode.SQL,
-                                                         source_code_func=transactions_df)
 
     # step3: Create expectation
     expectation_suite = ExpectationSuite(expectation_suite_name="feature_definition")
@@ -102,14 +107,17 @@ Background reading to understand the concepts of Feature Store and OCI Data Scie
     stats_config = StatisticsConfig().with_is_enabled(False)
 
     # step5: Create feature group
+    transformation_args = {"columns": "col1, col2", "where_clause": "col3 > 100"}
     feature_group = entity.create_feature_group(
-                        ["name"],
+                        primary_keys=["name"],
+                        partition_keys=["name"],
                         input_feature_details,
-                        expectation_suite,
-                        ExpectationType.LENIENT,
-                        stats_config,
+                        expectation_suite=expectation_suite,
+                        expectation_type=ExpectationType.LENIENT,
+                        statistics_config=stats_config,
                         name="<feature_group_name>",
-                        transformation_id=transformation.id
+                        transformation_id=transformation.id,
+                        transformation_kwargs=transformation_args
                     )