remocing temp code which created a bug

backend/app/plan/router.py

@@ -411,9 +411,7 @@ 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)
-
-            if not energy_assessment["epc"]:
-                continue
+            
             # Create a record in db
             property_id, is_new = create_property(
                 session, body.portfolio_id, epc_searcher.address_clean, epc_searcher.postcode_clean,

backend/app/plan/schemas.py

@@ -52,6 +52,9 @@ NON_INVASIVE_SPECIFIC_MEASURES = [
     "draught_proofing",
     "mixed_glazing",  # This covers partial double glazing and secondary glazing
     "cavity_extract_and_refill",
+    # Indicates that there is one (need to handle the case where there are multiple)
+    # extension that requires cavity wall insulation
+    "extension_cavity_wall_insulation",
 ]
 
 # This allows us to extend high level categories for measures such as "wall_insulation" to the specific measures
@@ -78,6 +81,7 @@ class PlanTriggerRequest(BaseModel):
     already_installed_file_path: Optional[str] = None
     patches_file_path: Optional[str] = None
     non_invasive_recommendations_file_path: Optional[str] = None
+    valuation_file_path: Optional[str] = None
     exclusions: Optional[conlist(str, min_items=1)] = None
     inclusions: Optional[conlist(str, min_items=1)] = None
 

etl/customers/remote_assessments/app.py

@@ -0,0 +1,73 @@
+import pandas as pd
+from utils.s3 import save_csv_to_s3
+
+PORTFOLIO_ID = 111
+USER_ID = 8
+
+
+def app():
+    """
+    This application is used to initialise and run remote assessments
+    :return:
+    """
+
+    asset_list = [
+        {
+            "uprn": 100050770761,
+            "address": "12 Sheardown Street",
+            "postcode": "DN4 0BH"
+        }
+    ]
+    asset_list = pd.DataFrame(asset_list)
+
+    # Store the asset list in s3
+    filename = f"{USER_ID}/{PORTFOLIO_ID}/asset_list.csv"
+    save_csv_to_s3(
+        dataframe=asset_list,
+        bucket_name="retrofit-plan-inputs-dev",
+        file_name=filename
+    )
+
+    non_invasive_recommendations = [
+        {
+            "uprn": 100050770761,
+            "recommendations": [
+                {
+                    "type": "extension_cavity_wall_insulation",
+                    "sap_points": 2,
+                }
+            ]
+        }
+    ]
+    # Store non-invasive recommendations in S3
+    non_invasive_recommendations_filename = f"{USER_ID}/{PORTFOLIO_ID}/non_invasive_recommendations.csv"
+    save_csv_to_s3(
+        dataframe=pd.DataFrame(non_invasive_recommendations),
+        bucket_name="retrofit-plan-inputs-dev",
+        file_name=non_invasive_recommendations_filename
+    )
+
+    valuation_data = [{100050770761: 67_000}]
+    # Store valuation data to s3
+    valuation_filename = f"{USER_ID}/{PORTFOLIO_ID}/valuation.csv"
+    save_csv_to_s3(
+        dataframe=pd.DataFrame(valuation_data),
+        bucket_name="retrofit-plan-inputs-dev",
+        file_name=valuation_filename
+    )
+
+    body = {
+        "portfolio_id": str(PORTFOLIO_ID),
+        "housing_type": "Private",
+        "goal": "Increasing EPC",
+        "goal_value": "C",
+        "trigger_file_path": filename,
+        "already_installed_file_path": "",
+        "patches_file_path": "",
+        "non_invasive_recommendations_file_path": non_invasive_recommendations_filename,
+        "valuation_file_path": valuation_filename,
+        "scenario_name": "Full package remote assessment",
+        "multi_plan": True,
+        "budget": None,
+    }
+    print(body)