debugging windows recommenddations integration

backend/app/db/models/materials.py

@@ -18,6 +18,7 @@ class MaterialType(enum.Enum):
     exposed_floor_insulation = "exposed_floor_insulation"
     flat_roof_insulation = "flat_roof_insulation"
     room_roof_insulation = "room_roof_insulation"
+    windows_glazing = "windows_glazing"
 
     iwi_wall_demolition = "iwi_wall_demolition"
     iwi_vapour_barrier = "iwi_vapour_barrier"

backend/app/plan/router.py

@@ -61,6 +61,7 @@ async def trigger_plan(body: PlanTriggerRequest):
         logger.info("Getting the inputs")
         epc_client = EpcClient(auth_token=get_settings().EPC_AUTH_TOKEN)
         plan_input = read_csv_from_s3(bucket_name=get_settings().PLAN_TRIGGER_BUCKET, filepath=body.trigger_file_path)
+
         uprn_filenames = read_dataframe_from_s3_parquet(
             bucket_name=get_settings().DATA_BUCKET, file_key="spatial/filename_meta.parquet"
         )
@@ -126,6 +127,10 @@ async def trigger_plan(body: PlanTriggerRequest):
 
         for p in input_properties:
 
+            # TODO: TEMP
+            if p.address1 == "The Hollies Farm House, Church Walk, Little Dalby":
+                continue
+
             # Property recommendations
             p.get_components(cleaned)
 

backend/app/plan/utils.py

@@ -175,11 +175,20 @@ def create_recommendation_scoring_data(
         scoring_dict["LOW_ENERGY_LIGHTING_ENDING"] = 100
         scoring_dict["LIGHTING_ENERGY_EFF_STARTING"] = "Very Good"
 
+    if recommendation["type"] == "windows_glazing":
+        scoring_dict["MULTI_GLAZE_PROPORTION_ENDING"] = 100
+        scoring_dict["WINDOWS_ENERGY_EFF_ENDING"] = "Average"
+        if scoring_dict["glazing_type_ENDING"] == "multiple":
+            pass
+        else:
+            raise NotImplementedError("Implement me")
+
     if recommendation["type"] not in [
         "mechanical_ventilation", "sealing_open_fireplace", "low_energy_lighting",
         "internal_wall_insulation", "external_wall_insulation", "cavity_wall_insulation",
         "loft_insulation", "room_roof_insulation", "flat_roof_insulation",
-        "solid_floor_insulation", "suspended_floor_insulation", "exposed_floor_insulation"
+        "solid_floor_insulation", "suspended_floor_insulation", "exposed_floor_insulation",
+        "windows_glazing"
     ]:
         raise NotImplementedError("Implement me")
 

recommendations/Recommendations.py

@@ -6,6 +6,7 @@ from recommendations.RoofRecommendations import RoofRecommendations
 from recommendations.VentilationRecommendations import VentilationRecommendations
 from recommendations.FireplaceRecommendations import FireplaceRecommendations
 from recommendations.LightingRecommendations import LightingRecommendations
+from recommendations.WindowsRecommendations import WindowsRecommendations
 from backend.ml_models.AnnualBillSavings import AnnualBillSavings
 
 
@@ -35,6 +36,7 @@ class Recommendations:
         )
         self.fireplace_recommender = FireplaceRecommendations(property_instance=property_instance)
         self.lighting_recommender = LightingRecommendations(property_instance=property_instance, materials=materials)
+        self.windows_recommender = WindowsRecommendations(property_instance=property_instance, materials=materials)
 
     def recommend(self):
 
@@ -77,6 +79,11 @@ class Recommendations:
         if self.lighting_recommender.recommendation:
             property_recommendations.append(self.lighting_recommender.recommendation)
 
+        # Windows recommendations
+        self.windows_recommender.recommend()
+        if self.windows_recommender.recommendation:
+            property_recommendations.append(self.windows_recommender.recommendation)
+
         # We insert temporary ids into the recommendations which is important for the optimiser later
         property_recommendations = self.insert_temp_recommendation_id(property_recommendations)
 

recommendations/WindowsRecommendations.py

@@ -56,7 +56,7 @@ class WindowsRecommendations:
 
         # We scale the number of windows based on the proportion of existing glazing
         if self.property.data["multi-glaze-proportion"] != "":
-            n_windows_scalar = 1 - (self.property.data["multi-glaze-proportion"] / 100)
+            n_windows_scalar = 1 - (int(self.property.data["multi-glaze-proportion"]) / 100)
         else:
             n_windows_scalar = self.COVERAGE_MAP.get(self.property.windows["glazing_coverage"], 1)
 
@@ -86,7 +86,7 @@ class WindowsRecommendations:
         self.recommendation = [
             {
                 "parts": [],
-                "type": "window_glazing",
+                "type": "windows_glazing",
                 "description": description,
                 "starting_u_value": None,
                 "new_u_value": None,