Update g1_v1 graph processing and schemas

graph_post_processing.py

@@ -26,6 +26,6 @@ def post_processing(data):
         for key in [
             "hd_score_m1", "hd_score_g1", "cluster_size_users_v2",
             "target_connected_30_sum", "email_cnt", "rejected_app_count",
-            "app_dt_day_cnt"
+            "app_dt_day_cnt", "hd_score_iso_m2"
         ]
     }

graph_pre_processing.py

@@ -15,7 +15,8 @@ def pre_processing(results):
         "target_connected_30_sum": float,
         "email_cnt": float,
         "rejected_app_count": float,
-        "app_dt_day_cnt": float
+        "app_dt_day_cnt": float,
+        "hd_score_iso_m2": float
     }
     data = {
         "hd_score_m1": result["hd_score_m1"],
@@ -25,6 +26,7 @@ def pre_processing(results):
         "rejected_app_count": result["rejected_app_count"],
         "app_dt_day_cnt": result["app_dt_day_cnt"],
         "cluster_size": result["cluster_size"],
+        "hd_score_iso_m2": result["hd_score_iso_m2"],
     }
 
     for col, dtype in dtypes.items():

requirements.txt

@@ -1,5 +1,5 @@
-joblib==1.4.2
-pandas==2.2.3
-xgboost==2.1.3
-typing==3.6.1
-
+joblib==1.4.2
+pandas==2.2.3
+xgboost==2.1.3
+typing==3.6.1
+

response_schema.json

@@ -29,6 +29,10 @@
     "app_dt_day_cnt": {
       "type": ["number", "null"],
       "description": "Number of application days counted."
+    },
+    "hd_score_iso_m2": {
+      "type": ["number", "null"],
+      "description": "HD fraud Score M2"
     }
   }
 }

test_block.py

@@ -11,7 +11,8 @@ data = [{
       "email_cnt": 1,
       "rejected_app_count": 2,
       "app_dt_day_cnt": 2,
-      "cluster_size": 3
+      "cluster_size": 3,
+      "hd_score_iso_m2": 1202
     }]
 
 class TestBlock(unittest.TestCase):