made lambda async and 15 min timeout

asset_list/AssetList.py

@@ -1719,7 +1719,7 @@ class AssetList:
         solar_reason_map = {
             "solar_eligible": "Solar Eligible: ",
             "solar_eligible_needs_heating_upgrade": (
-                "Solar Eligible, Solid Floor, Needs Heating Upgrade: "
+                "Solar Eligible, Needs Heating Upgrade: "
             ),
             "solar_eligible_solid_wall_uninsulated": "Solar Eligible, Solid Wall Uninsulated, EPC E or Below: ",
         }
@@ -2140,10 +2140,8 @@ class AssetList:
             return
 
         # TODO: Fetch from Sharepoint
-        ecosurv_filepath = "/Users/khalimconn-kowlessar/Documents/hestia/Ecosurv/07.csv"
-        logger.info(
-            "Getting Ecosurv data from %s", ecosurv_filepath
-        )
+        ecosurv_filepath = "/Users/khalimconn-kowlessar/Documents/hestia/Ecosurv/15.04.csv"
+        logger.info("Getting Ecosurv data from %s", ecosurv_filepath)
         self.ecosurv = pd.read_csv(
             ecosurv_filepath,
             encoding="cp437"
@@ -2214,6 +2212,9 @@ class AssetList:
                 unmatched.append(row["Reference"])
                 continue
 
+        logger.info("Matched %s properties to ecosurv data", len(matched))
+        logger.info("%s properties in Ecosurv remain unmatched", len(unmatched))
+
         # We now match
         matched = pd.DataFrame(matched)
         self.standardised_asset_list = self.standardised_asset_list.merge(

asset_list/app.py

@@ -124,7 +124,7 @@ def app():
     ]
     master_to_asset_list_filepath = None
     phase = False
-    ecosuv_landlords = "paul butler|bromford"
+    ecosurv_landlords = "paul butler|bromford"
 
     # Torus
     data_folder = "/Users/khalimconn-kowlessar/Documents/hestia/Customers/Torus/Phase 1"
@@ -609,6 +609,8 @@ def app():
         master_to_asset_list_filepath=master_to_asset_list_filepath
     )
 
+    asset_list.flag_ecosurv(ecosurv_landlords)
+
     ### We retrieve the EPC data
 
     # We chunk up this data into 5000 rows at a time
@@ -950,5 +952,8 @@ def app():
         if not asset_list.outcomes_no_match.empty:
             asset_list.outcomes_no_match.to_excel(writer, sheet_name="Unmatched Outcomes", index=False)
 
+        if not asset_list.ecosurv_no_match.empty:
+            asset_list.ecosurv_no_match.to_excel(writer, sheet_name="Unmatched Ecosurv", index=False)
+
     # Store the Hubspot export as a csv
     hubspot_data.to_csv(os.path.join(data_folder, "Hubspot Export.csv"), index=False)

backend/app/plan/router.py

@@ -1,4 +1,5 @@
 import ast
+import asyncio
 import json
 from datetime import datetime
 
@@ -420,9 +421,23 @@ router = APIRouter(
 )
 
 
-@router.post("/trigger")
-async def trigger_plan(body: PlanTriggerRequest):
+@router.post("/trigger", status_code=202)
+async def trigger_plan_entrypoint(body: PlanTriggerRequest):
+    """
+    This function is the entrypoint for the plan trigger API. It will handle the request and call the
+    trigger_plan function.
+    :param body: The request body
+    :return:
+    """
     logger.info("API triggered with body: %s", body)
+    # Kick off the async background task
+    asyncio.create_task(model_engine(body))
+
+    return {"message": "Plan job accepted"}
+
+
+async def model_engine(body: PlanTriggerRequest):
+    logger.info("Model Engine triggered with body: %s", body)
 
     logger.info("Connecting to db")
     session = sessionmaker(bind=db_engine)()
@@ -1056,4 +1071,6 @@ async def trigger_plan(body: PlanTriggerRequest):
     finally:
         session.close()
 
+    logger.info("Model Engine completed successfully")
+
     return Response(status_code=200)

serverless.yml

@@ -81,4 +81,4 @@ functions:
       - http:
           path: /{proxy+}
           method: ANY
-    timeout: 120
+    timeout: 900 # Max timeout to 15 mins for engine runs