Deprecate the input parameter for FeatureViews

Signed-off-by: Felix Wang <[email protected]>

sdk/python/feast/feature_view.py

@@ -51,9 +51,7 @@ class FeatureView:
         ttl: The amount of time this group of features lives. A ttl of 0 indicates that
             this group of features lives forever. Note that large ttl's or a ttl of 0
             can result in extremely computationally intensive queries.
-        input: The source of data where this group of features is stored.
-        batch_source (optional): The batch source of data where this group of features
-            is stored.
+        batch_source: The batch source of data where this group of features is stored.
         stream_source (optional): The stream source of data where this group of features
             is stored.
         features (optional): The set of features defined as part of this FeatureView.
@@ -67,7 +65,6 @@ class FeatureView:
     tags: Optional[Dict[str, str]]
     ttl: timedelta
     online: bool
-    input: DataSource
     batch_source: DataSource
     stream_source: Optional[DataSource] = None
     created_timestamp: Optional[datetime] = None
@@ -80,8 +77,7 @@ def __init__(
         name: str,
         entities: List[str],
         ttl: Union[Duration, timedelta],
-        input: Optional[DataSource] = None,
-        batch_source: Optional[DataSource] = None,
+        batch_source: DataSource,
         stream_source: Optional[DataSource] = None,
         features: Optional[List[Feature]] = None,
         tags: Optional[Dict[str, str]] = None,
@@ -93,26 +89,17 @@ def __init__(
         Raises:
             ValueError: A field mapping conflicts with an Entity or a Feature.
         """
-        if input is not None:
-            warnings.warn(
-                (
-                    "The argument 'input' is being deprecated. Please use 'batch_source' "
-                    "instead. Feast 0.13 and onwards will not support the argument 'input'."
-                ),
-                DeprecationWarning,
-            )
-
-        _input = input or batch_source
-        assert _input is not None
-
         _features = features or []
 
         cols = [entity for entity in entities] + [feat.name for feat in _features]
         for col in cols:
-            if _input.field_mapping is not None and col in _input.field_mapping.keys():
+            if (
+                batch_source.field_mapping is not None
+                and col in batch_source.field_mapping.keys()
+            ):
                 raise ValueError(
-                    f"The field {col} is mapped to {_input.field_mapping[col]} for this data source. "
-                    f"Please either remove this field mapping or use {_input.field_mapping[col]} as the "
+                    f"The field {col} is mapped to {batch_source.field_mapping[col]} for this data source. "
+                    f"Please either remove this field mapping or use {batch_source.field_mapping[col]} as the "
                     f"Entity or Feature name."
                 )
 
@@ -127,8 +114,7 @@ def __init__(
             self.ttl = ttl
 
         self.online = online
-        self.input = _input
-        self.batch_source = _input
+        self.batch_source = batch_source
         self.stream_source = stream_source
 
         self.materialization_intervals = []
@@ -311,7 +297,7 @@ def most_recent_end_time(self) -> Optional[datetime]:
 
     def infer_features_from_batch_source(self, config: RepoConfig):
         """
-        Infers the set of features associated to this feature view from the input source.
+        Infers the set of features associated to this feature view from the batch source.
 
         Args:
             config: Configuration object used to configure the feature store.

sdk/python/feast/infra/offline_stores/offline_utils.py

@@ -105,7 +105,7 @@ def get_feature_view_query_context(
         join_keys = []
         entity_selections = []
         reverse_field_mapping = {
-            v: k for k, v in feature_view.input.field_mapping.items()
+            v: k for k, v in feature_view.batch_source.field_mapping.items()
         }
         for entity_name in feature_view.entities:
             entity = registry.get_entity(entity_name, project)
@@ -120,8 +120,8 @@ def get_feature_view_query_context(
         else:
             ttl_seconds = 0
 
-        event_timestamp_column = feature_view.input.event_timestamp_column
-        created_timestamp_column = feature_view.input.created_timestamp_column
+        event_timestamp_column = feature_view.batch_source.event_timestamp_column
+        created_timestamp_column = feature_view.batch_source.created_timestamp_column
 
         context = FeatureViewQueryContext(
             name=feature_view.name,
@@ -135,7 +135,7 @@ def get_feature_view_query_context(
                 created_timestamp_column, created_timestamp_column
             ),
             # TODO: Make created column optional and not hardcoded
-            table_subquery=feature_view.input.get_table_query_string(),
+            table_subquery=feature_view.batch_source.get_table_query_string(),
             entity_selections=entity_selections,
         )
         query_context.append(context)

sdk/python/tests/example_repos/example_feature_repo_with_duplicated_featureview_names.py

@@ -10,7 +10,7 @@
     name="driver_hourly_stats",  # Intentionally use the same FeatureView name
     entities=["driver_id"],
     online=False,
-    input=driver_hourly_stats,
+    batch_source=driver_hourly_stats,
     ttl=Duration(seconds=10),
     tags={},
 )
@@ -19,7 +19,7 @@
     name="driver_hourly_stats",  # Intentionally use the same FeatureView name
     entities=["driver_id"],
     online=False,
-    input=driver_hourly_stats,
+    batch_source=driver_hourly_stats,
     ttl=Duration(seconds=10),
     tags={},
 )

sdk/python/tests/integration/feature_repos/universal/feature_views.py

@@ -10,5 +10,5 @@ def correctness_feature_view(data_source: DataSource) -> FeatureView:
         entities=["driver"],
         features=[Feature("value", ValueType.FLOAT)],
         ttl=timedelta(days=5),
-        input=data_source,
+        batch_source=data_source,
     )