adding additional attributes to property for posting to the database

backend/Property.py

@@ -38,6 +38,10 @@ class Property(BaseUtility):
         self.in_conservation_area = None
         self.year_built = None
 
+        self.energy = None
+        self.ventilation = None
+        self.solar_pv = None
+
         if epc_client:
             self.epc_client = epc_client
         else:
@@ -76,6 +80,70 @@ class Property(BaseUtility):
         """
         self.coordinates = {key.lower(): value for key, value in coordinates.items()}
 
+    def set_energy(self):
+        """
+        Extracts and formats data about the home's energy and co2 consumption
+        To being with, this is just formatting epc data
+
+        Data:
+        - primary_energy_consumption
+        This is based on the "energy-consumption-current" field in the EPC data.
+        Current estimated total energy consumption for the property in a 12 month period (kWh/m2). Displayed on EPC
+        as the current primary energy use per square metre of floor area.
+
+        - co2_emissions
+        This is based on the "co2-emissions-current" field in the EPC data.
+        CO₂ emissions per year in tonnes/year.
+        """
+
+        self.energy = {
+            "primary_energy_consumption": float(self.data["energy-consumption-current"]),
+            "co2_emissions": float(self.data["co2-emissions-current"]),
+        }
+
+    def set_ventilation(self):
+        """
+        Extracts and formats data about the home's ventilation
+        To being with, this is just formatting epc data
+
+        Data:
+        - ventilation
+        This is based on the "ventilation-type" field in the EPC data.
+        Ventilation type of the property.
+        """
+
+        ventilation = self.data["mechanical-ventilation"]
+        # perform some simple cleaning - when checking 300k properties, the only unique values were
+        # {'', 'mechanical, supply and extract', 'NO DATA!', 'natural', 'mechanical, extract only'}
+        if ventilation in self.DATA_ANOMALY_MATCHES or ventilation in [""]:
+            ventilation = None
+
+        self.ventilation = {
+            "ventilation": ventilation,
+        }
+
+    def set_solar_pv(self):
+        """
+        Extracts and formats data about the home's solar pv
+        To being with, this is just formatting epc data
+
+        Data:
+        - solar_pv
+        This is based on the "photo-supply" field in the EPC data.
+
+        When checking 100k properties, either the value was "" or a stringified number
+        """
+
+        solar_pv = self.data["photo-supply"]
+        if solar_pv == "":
+            solar_pv = None
+        else:
+            solar_pv = float(solar_pv)
+
+        self.solar_pv = {
+            "solar_pv": solar_pv,
+        }
+
     def get_components(self, cleaned):
         """
         Given the cleaning that has been performed, we'll use this to identify the property
@@ -90,6 +158,10 @@ class Property(BaseUtility):
         if not self.data:
             raise ValueError("Property does not contain data")
 
+        self.set_energy()
+        self.set_ventilation()
+        self.set_solar_pv()
+
         for description, attribute in cleaned.items():
 
             if self.data[description] in self.DATA_ANOMALY_MATCHES:

backend/app/plan/router.py

@@ -1,3 +1,4 @@
+import datetime
 from fastapi import APIRouter, Depends
 from backend.app.dependencies import validate_token
 from backend.app.plan.schemas import PlanTriggerRequest
@@ -93,6 +94,15 @@ async def trigger_plan(body: PlanTriggerRequest):
         if not is_new:
             continue
 
+        # TODO: push property targets
+        # TODO: Need to add heat demand target
+        property_targets = {
+            "property_id": property_id,
+            "portfolio_id": body.portfolio_id,
+            "created_at": datetime.datetime.now(),
+            "epc": body.goal_value,
+        }
+
         input_properties.append(
             Property(
                 postcode=config['postcode'],
@@ -187,4 +197,81 @@ async def trigger_plan(body: PlanTriggerRequest):
 
         recommendations.extend(wall_recomendations.recommendations)
 
+    # Once we're done, we'll store:
+    # 1) the property data
+    # 2) the property details (epc)
+    # 3) the recommendations
+
+    # Upload property data
+    for p in input_properties:
+        property_data = {
+            "creation_status": "COMPLETE",
+            "uprn": int(p.data["uprn"]),
+            "has_pre_condition_report": True,
+            "has_recommendations": True,
+            "property_type": p.data["property-type"],
+            "built_form": p.data["built-form"],
+            "local_authority": p.data["local-authority-label"],
+            "constituency": p.data["constituency-label"],
+            "number_of_rooms": p.data["number-habitable-rooms"],
+            "year_built": p.year_built,
+            "tenure": p.data["tenure"],
+            "current_epc_rating": p.data["current-energy-rating"],
+            "current_sap_points": p.data["current-energy-efficiency"]
+        }
+
+        def clean_upload_data(to_update, to_clean_values):
+            for k, v in to_update.items():
+                if v in to_clean_values:
+                    to_update[k] = None
+            return to_update
+
+        property_data = clean_upload_data(property_data, to_clean_values=p.DATA_ANOMALY_MATCHES)
+
+        rating_lookup = {
+            "Very Good": 5,
+            "Good": 4,
+            "Average": 3,
+            "Poor": 2,
+            "Very Poor": 1,
+            "N/A": None
+        }
+
+        property_details_epc = {
+            "property_id": p.id,
+            "portfolio_id": body.portfolio_id,
+            "full_address": p.data["address"],
+            "total_floor_area": float(p.data["total-floor-area"]),
+            "walls": p.walls["cleaned_description"],
+            "walls_rating": rating_lookup[p.data["walls-energy-eff"]],
+            "roof": p.roof["cleaned_description"],
+            "roof_rating": rating_lookup[p.data["roof-energy-eff"]],
+            "floor": p.floor["cleaned_description"],
+            "floor_rating": rating_lookup[p.data["floor-energy-eff"]],
+            "windows": p.windows["cleaned_description"],
+            "windows_rating": rating_lookup[p.data["windows-energy-eff"]],
+            "heating": p.main_heating["cleaned_description"],
+            "heating_rating": rating_lookup[p.data["mainheat-energy-eff"]],
+            "heating_controls": p.main_heating_controls["cleaned_description"],
+            "heating_controls_rating": rating_lookup[p.data["mainheatc-energy-eff"]],
+            "hot_water": p.hotwater["cleaned_description"],
+            "hot_water_rating": rating_lookup[p.data["hot-water-energy-eff"]],
+            "lighting": p.lighting["cleaned_description"],
+            "lighting_rating": rating_lookup[p.data["lighting-energy-eff"]],
+            "ventilation": p.ventilation["ventilation"],
+            "solar_pv": p.solar_pv["cleaned_description"],
+            "solar_hot_water": p.solar_hot_water["cleaned_description"],
+            "wind_turbine": p.wind_turbine["cleaned_description"],
+            "floor_height": p.data["floor-height"],
+            "heat_loss_corridor": p.data["heat-loss-corridor"],
+            "unheated_corridor_length": p.data["unheated-corridor-length"],
+            "number_of_open_fireplaces": int(p.data["number-open-fireplaces"]),
+            "number_of_extensions": int(p.data["extension-count"]),
+            "number_of_storeys": int(p.data["flat-storey-count"]),
+            "mains_gas": p.data["mains-gas-flag"],
+            "energy_tarrif": p.data["energy-tariff"],
+            "primary_energy_consumption": p.energy["primary-energy-consumption"],
+            "co2_emissions": p.energy["co2-emissions"],
+        }
+
     return {"recommendations": recommendations}