Merge pull request #931 from Hestia-Homes/main

Deploy patch

backend/app/plan/router.py

@@ -174,6 +174,8 @@ async def trigger_plan_entrypoint(body: PlanTriggerRequest):
                 service="plan_engine",
                 inputs=data,
                 task_only=True,
+                source=SourceEnum.PORTFOLIO,
+                source_id=str(body.portfolio_id),
             )
 
             subtask_interface = SubTaskInterface()
@@ -222,6 +224,8 @@ async def trigger_plan_entrypoint(body: PlanTriggerRequest):
                 service="plan_engine",
                 inputs=data,
                 task_only=False,
+                source=SourceEnum.PORTFOLIO,
+                source_id=str(body.portfolio_id),
             )
             data["task_id"] = str(task_id)
             data["subtask_id"] = str(subtask_id)

backend/export/property_scenarios/main.py

@@ -134,10 +134,18 @@ def handler(event: Mapping[str, Any], context: Optional[Any]) -> Mapping[str, Un
     body_dict = {
         "task_id": "test",
         "subtask_id": "test",
-        "portfolio_id": 569,
+        "portfolio_id": 655,
         "scenario_ids": [],
         "default_plans_only": True,
     }
+
+    body_dict = {
+        "task_id": "test",
+        "subtask_id": "test",
+        "portfolio_id": 655,
+        "scenario_ids": [1174],
+        "default_plans_only": False,
+    }
     :param event: Lambda event containing export request details
     :param context: Lambda context (not used in this handler but included for completeness)
     :return: HTTP response indicating success or failure of the export operation

backend/tests/test_rebaselining_pipeline.py

@@ -2,6 +2,10 @@ import os
 import pickle
 import pandas as pd
 import pytest
+from datetime import datetime
+from backend.ml_models.api import ModelApi
+from backend.app.utils import sap_to_epc
+from backend.app.config import get_prediction_buckets
 
 
 def load_sample_certificates():
@@ -60,12 +64,6 @@ def load_cleaning_data():
 
 @pytest.mark.integration
 def test_rebaselining_pipeline_with_real_data():
-    import pandas as pd
-    from datetime import datetime
-    from backend.ml_models.api import ModelApi
-    from backend.app.utils import sap_to_epc
-    from backend.app.config import get_prediction_buckets
-
     df = load_sample_certificates()
     cleaning_data = load_cleaning_data()
     input_properties = [make_property_from_row(row, cleaning_data=cleaning_data) for _, row in df.iterrows()]

recommendations/Costs.py

@@ -209,7 +209,7 @@ class Costs:
                 # Try and get the region after converting the keys to lower
                 self.region = {
                     k.lower(): v for k, v in county_to_region_map.items()
-                }.get(self.property.property.epc_record.local_authority_label.lower(), None)
+                }.get(self.property.epc_record.local_authority_label.lower(), None)
 
             if self.region is None:
                 logger.warning("No region found for county %s, defaulting to South East England",