Merge pull request #117 from splicemachine/DBAAS-5102

DBAAS-5102: create a route for GET /training-set-feature

Author: Ben Epstein

splicemachine/features/feature_store.py

@@ -439,8 +439,8 @@ def describe_feature_sets(self) -> None:
 
         print('Available feature sets')
         for desc in r:
-            fset = FeatureSet(**desc["feature_set"])
-            features = [Feature(**feature) for feature in desc["features"]]
+            features = [Feature(**feature) for feature in desc.pop('features')]
+            fset = FeatureSet(**desc)
             print('-' * 23)
             self._feature_set_describe(fset, features)
 
@@ -462,8 +462,8 @@ def describe_feature_set(self, schema_name: str, table_name: str) -> None:
         if not descs: raise SpliceMachineException(
             f"Feature Set {schema_name}.{table_name} not found. Check name and try again.")
         desc = descs[0]
-        fset = FeatureSet(**desc["feature_set"])
-        features = [Feature(**feature) for feature in desc["features"]]
+        features = [Feature(**feature) for feature in desc.pop("features")]
+        fset = FeatureSet(**desc)
         self._feature_set_describe(fset, features)
 
     def _feature_set_describe(self, fset: FeatureSet, features: List[Feature]):
@@ -483,8 +483,8 @@ def describe_training_views(self) -> None:
 
         print('Available training views')
         for desc in r:
-            tcx = TrainingView(**desc["training_view"])
-            features = [Feature(**f) for f in desc["features"]]
+            features = [Feature(**f) for f in desc.pop('features')]
+            tcx = TrainingView(**desc)
             print('-' * 23)
             self._training_view_describe(tcx, features)
 
@@ -500,8 +500,8 @@ def describe_training_view(self, training_view: str) -> None:
         descs = r
         if not descs: raise SpliceMachineException(f"Training view {training_view} not found. Check name and try again.")
         desc = descs[0]
-        tcx = TrainingView(**desc['training_view'])
-        feats = [Feature(**f) for f in desc['features']]
+        feats = [Feature(**f) for f in desc.pop('features')]
+        tcx = TrainingView(**desc)
         self._training_view_describe(tcx, feats)
 
     def _training_view_describe(self, tcx: TrainingView, feats: List[Feature]):
@@ -529,15 +529,16 @@ def get_training_set_from_deployment(self, schema_name: str, table_name: str):
 
         r = make_request(self._FS_URL, Endpoints.TRAINING_SET_FROM_DEPLOYMENT, RequestType.GET, self._basic_auth, 
             { "schema": schema_name, "table": table_name })
-        metadata = r["metadata"]
 
+        metadata = r['metadata']
         sql = r['sql']
-        features = metadata['FEATURES'].split(',')
-        tv_name = metadata['NAME']
-        start_time = metadata['TRAINING_SET_START_TS']
-        end_time = metadata['TRAINING_SET_END_TS']
+
+        tv_name = metadata['name']
+        start_time = metadata['training_set_start_ts']
+        end_time = metadata['training_set_end_ts']
+
         tv = TrainingView(**r['training_view']) if 'training_view' in r else None
-        features = [Feature(**f) for f in r["features"]]
+        features = [Feature(**f) for f in r['features']]
 
         if self.mlflow_ctx:
             self.link_training_set_to_mlflow(features, start_time, end_time, tv)
@@ -564,6 +565,17 @@ def get_deployments(self, schema_name: str = None, table_name: str = None, train
         """
         return make_request(self._FS_URL, Endpoints.DEPLOYMENTS, RequestType.GET, self._basic_auth, 
             { 'schema': schema_name, 'table': table_name, 'name': training_set })
+      
+    def get_training_set_features(self, training_set: str = None):
+        """
+        Returns a list of all features from an available Training Set, as well as details about that Training Set
+        :param training_set: training set name
+        :return: TrainingSet as dict
+        """
+        r = make_request(self._FS_URL, Endpoints.TRAINING_SET_FEATURES, RequestType.GET, self._basic_auth, 
+            { 'name': training_set })
+        r['features'] = [Feature(**f) for f in r['features']]
+        return r
 
     def _retrieve_model_data_sets(self, schema_name: str, table_name: str):
         """

splicemachine/features/utils/http_utils.py

@@ -36,6 +36,7 @@ class Endpoints:
     FEATURE_VECTOR: str = "feature-vector"
     FEATURE_VECTOR_SQL: str = "feature-vector-sql"
     TRAINING_SETS: str = "training-sets"
+    TRAINING_SET_FEATURES: str = "training-set-features"
     TRAINING_SET_FROM_DEPLOYMENT: str = "training-set-from-deployment"
     TRAINING_SET_FROM_VIEW: str = "training-set-from-view"
     TRAINING_VIEWS: str = "training-views"