Making it possible to pass valutations as a separate data input and injecting it into the property"

backend/Property.py

@@ -75,6 +75,7 @@ class Property:
         postcode,
         address,
         epc_record,
+        property_valuation=None,
         already_installed=None,
         non_invasive_recommendations=None,
         measures=None,
@@ -111,6 +112,8 @@ class Property:
         else:
             self.measures = ast.literal_eval(measures) if measures else None
 
+        self.valuation = property_valuation
+
         self.uprn = epc_record.get("uprn")
         self.uprn_source = self.data.get("uprn-source")
 

backend/app/plan/router.py

@@ -289,7 +289,7 @@ def create_epc_records(epc_searcher: SearchEpc, energy_assessment: dict):
     }, energy_assessment_is_newer
 
 
-def get_on_site_data(body: PlanTriggerRequest):
+def get_request_property_data(body: PlanTriggerRequest):
     """
     This function will read in the on-site data from the S3 bucket
     :param body: The request body
@@ -311,10 +311,18 @@ def get_on_site_data(body: PlanTriggerRequest):
             bucket_name=get_settings().PLAN_TRIGGER_BUCKET, filepath=body.non_invasive_recommendations_file_path
         )
 
-    return patches, already_installed, non_invasive_recommendations
+    valuation_data = []
+    if body.valuation_file_path:
+        valuation_data = read_csv_from_s3(
+            bucket_name=get_settings().PLAN_TRIGGER_BUCKET, filepath=body.valuation_file_path
+        )
+
+    return patches, already_installed, non_invasive_recommendations, valuation_data
 
 
-def extract_property_on_site_recommendations(config, patches, already_installed, non_invasive_recommendations, uprn):
+def extract_property_request_data(
+    config, patches, already_installed, non_invasive_recommendations, valuation_data, uprn
+):
     patch_has_uprn = "uprn" in patches[0] if patches else True
     if patch_has_uprn:
         patch = next((
@@ -360,7 +368,12 @@ def extract_property_on_site_recommendations(config, patches, already_installed,
 
         property_non_invasive_recommendations["recommendations"] = str(transformed)
 
-    return patch, property_already_installed, property_non_invasive_recommendations
+    property_valution = next((
+        x for x in valuation_data if
+        (str(x["uprn"]) == str(uprn))
+    ), {})
+
+    return patch, property_already_installed, property_non_invasive_recommendations, property_valution
 
 
 router = APIRouter(
@@ -384,7 +397,7 @@ async def trigger_plan(body: PlanTriggerRequest):
         logger.info("Getting the inputs")
         plan_input = read_csv_from_s3(bucket_name=get_settings().PLAN_TRIGGER_BUCKET, filepath=body.trigger_file_path)
         # If we have patches or overrides, we should read them in here
-        patches, already_installed, non_invasive_recommendations = get_on_site_data(body)
+        patches, already_installed, non_invasive_recommendations, valuation_data = get_request_property_data(body)
 
         cleaning_data = read_dataframe_from_s3_parquet(
             bucket_name=get_settings().DATA_BUCKET, file_key="sap_change_model/cleaning_dataset.parquet",
@@ -411,7 +424,7 @@ async def trigger_plan(body: PlanTriggerRequest):
 
             # We check for an energy assessment we have performed on this property:
             energy_assessment = get_latest_assessment_by_uprn(session, uprn if uprn is not None else epc_searcher.uprn)
-            
+
             # Create a record in db
             property_id, is_new = create_property(
                 session, body.portfolio_id, epc_searcher.address_clean, epc_searcher.postcode_clean,
@@ -438,9 +451,14 @@ async def trigger_plan(body: PlanTriggerRequest):
                 epc_searcher, energy_assessment
             )
 
-            patch, property_already_installed, property_non_invasive_recommendations = (
-                extract_property_on_site_recommendations(
-                    config, patches, already_installed, non_invasive_recommendations, uprn
+            patch, property_already_installed, property_non_invasive_recommendations, property_valuation = (
+                extract_property_request_data(
+                    config=config,
+                    patches=patches,
+                    already_installed=already_installed,
+                    non_invasive_recommendations=non_invasive_recommendations,
+                    valuation_data=valuation_data,
+                    uprn=epc_searcher.uprn,
                 )
             )
 
@@ -460,6 +478,7 @@ async def trigger_plan(body: PlanTriggerRequest):
                     postcode=epc_searcher.postcode_clean,
                     epc_record=prepared_epc,
                     already_installed=property_already_installed,
+                    property_valuation=property_valuation,
                     non_invasive_recommendations=property_non_invasive_recommendations,
                     energy_assessment=energy_assessment,
                     **Property.extract_kwargs(config),  # TODO: Depraecate this

backend/ml_models/Valuation.py

@@ -1,4 +1,5 @@
 import numpy as np
+from scipy.constants import value
 
 
 class PropertyValuation:
@@ -203,7 +204,10 @@ class PropertyValuation:
 
     @classmethod
     def estimate(cls, property_instance, target_epc):
-        value = cls.UPRN_VALUE_LOOKUP.get(property_instance.uprn)
+        value = (
+            property_instance.valuation if property_instance.valuation else
+            cls.UPRN_VALUE_LOOKUP.get(property_instance.uprn)
+        )
 
         if not value:
             return {

recommendations/WallRecommendations.py

@@ -339,11 +339,11 @@ class WallRecommendations(Definitions):
             "starting_u_value": None,
             "new_u_value": None,
             "sap_points": extension_cavity_insulation_recommendation["sap_points"],
-            "heat_demand": None,
-            "kwh_savings": None,
-            "energy_savings": None,
-            "energy_cost_savings": None,
-            "co2_equivalent_savings": None,
+            "heat_demand": 0,
+            "kwh_savings": 0,
+            "energy_savings": 0,
+            "energy_cost_savings": 0,
+            "co2_equivalent_savings": 0,
             "already_installed": False,
             "simulation_config": {},
             "description_simulation": {},