[Feature Store] Making features/entities optional in feature-set spec (…

…#902)
mlrun · Apr 29, 2021 · e272b16 · e272b16
1 parent cda9cd7
commit e272b16
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Showing 2 changed files with 7 additions and 7 deletions.
diff --git a/mlrun/api/db/sqldb/db.py b/mlrun/api/db/sqldb/db.py
@@ -1546,7 +1546,7 @@ def store_feature_set(
             session, FeatureSet, project, name, tag, uid
         )
 
-        feature_set_dict = feature_set.dict()
+        feature_set_dict = feature_set.dict(exclude_none=True)
 
         if not existing_feature_set:
             # Check if this is a re-tag of existing object - search by uid only
@@ -1600,7 +1600,7 @@ def _validate_and_enrich_record_for_creation(
         get_project_member().ensure_project(session, project)
         tag = new_object.metadata.tag or "latest"
 
-        object_dict = new_object.dict()
+        object_dict = new_object.dict(exclude_none=True)
         hash_key = fill_object_hash(object_dict, "uid", tag)
 
         if versioned:
@@ -1654,7 +1654,7 @@ def patch_feature_set(
                 f"Feature-set not found {feature_set_uri}"
             )
 
-        feature_set_struct = feature_set_record.dict()
+        feature_set_struct = feature_set_record.dict(exclude_none=True)
         # using mergedeep for merging the patch content into the existing dictionary
         strategy = patch_mode.to_mergedeep_strategy()
         mergedeep.merge(feature_set_struct, feature_set_update, strategy=strategy)
@@ -1832,7 +1832,7 @@ def store_feature_vector(
             session, FeatureVector, project, name, tag, uid
         )
 
-        feature_vector_dict = feature_vector.dict()
+        feature_vector_dict = feature_vector.dict(exclude_none=True)
 
         if not existing_feature_vector:
             # Check if this is a re-tag of existing object - search by uid only
@@ -1886,7 +1886,7 @@ def patch_feature_vector(
                 f"Feature-vector not found {feature_vector_uri}"
             )
 
-        feature_vector_struct = feature_vector_record.dict()
+        feature_vector_struct = feature_vector_record.dict(exclude_none=True)
         # using mergedeep for merging the patch content into the existing dictionary
         strategy = patch_mode.to_mergedeep_strategy()
         mergedeep.merge(feature_vector_struct, feature_vector_update, strategy=strategy)

diff --git a/mlrun/api/schemas/feature_store.py b/mlrun/api/schemas/feature_store.py
@@ -31,8 +31,8 @@ class Config:
 
 
 class FeatureSetSpec(ObjectSpec):
-    entities: List[Entity]
-    features: List[Feature]
+    entities: List[Entity] = []
+    features: List[Feature] = []
 
 
 class FeatureSet(BaseModel):