minor tweaks to engine during remote assessments

backend/app/assumptions.py

@@ -54,4 +54,5 @@ DESCRIPTIONS_TO_FUEL_TYPES = {
     "Gas instantaneous at point of use": {"fuel": "Natural Gas", "cop": 0.85},
     "Room heaters, wood logs": {"fuel": "Wood Logs", "cop": 1},
     "Boiler and radiators, coal": {"fuel": "Coal", "cop": 0.85},
+    "From main system, no cylinderstat": {"fuel": "Natural Gas", "cop": 0.85},
 }

backend/app/plan/router.py

@@ -338,7 +338,7 @@ def extract_property_request_data(
 
     # Because we have some non-invasive recommendations that match on address and postcode, but not UPRN
     # we need to check existence of uprn
-    has_uprn = "uprn" in non_invasive_recommendations[0] if non_invasive_recommendations else True
+    has_uprn = "uprn" in non_invasive_recommendations[0] if non_invasive_recommendations else False
     if has_uprn:
         has_uprn = non_invasive_recommendations[0]["uprn"] not in ["", None]
 

etl/customers/remote_assessments/app.py

@@ -4,7 +4,7 @@ from dotenv import load_dotenv
 from utils.s3 import save_csv_to_s3
 from etl.find_my_epc.AssetListEpcData import AssetListEpcData
 
-PORTFOLIO_ID = 129
+PORTFOLIO_ID = 132
 USER_ID = 8
 
 load_dotenv(dotenv_path="backend/.env")
@@ -19,9 +19,11 @@ def app():
 
     asset_list = [
         {
-            "address": "19",
-            "postcode": "IP21 4YJ",
-            "uprn": 2630134524,
+            "address": "3",
+            "postcode": "BB8 0JF",
+            "uprn": 100010509503,
+            "property_type": "House",
+            "built_form": "End-Terrace",
         }
     ]
     asset_list = pd.DataFrame(asset_list)
@@ -52,8 +54,8 @@ def app():
 
     valuation_data = [
         {
-            "uprn": 2630134524,
-            "valuation": 96_000
+            "uprn": 100010509503,
+            "valuation": 116_000
         }
     ]
     # Store valuation data to s3