save script

.devcontainer/asset_list/Dockerfile

@@ -27,8 +27,9 @@ RUN useradd -m -s /usr/bin/bash ${USER} \
 
 # # 4) Python deps - if you want to run assest list
 ENV PIP_NO_CACHE_DIR=1 PIP_DISABLE_PIP_VERSION_CHECK=1
-ADD asset_list/requirements.txt requirements.txt
+ADD .devcontainer/asset_list/requirements.txt requirements2.txt
-RUN pip install -r requirements.txt
+ADD asset_list/requirements.txt requirements1.txt
+RUN cat requirements1.txt requirements2.txt >> requirements.txt
 
 RUN pip install -r requirements.txt
 # 5) Workdir

.devcontainer/asset_list/requirements.txt

@@ -15,10 +15,9 @@ uvicorn[standard]
 pytest==9.0.2
 pytest-cov==7.0.0
 ipykernel>=6.25,<7
-pydantic-settings<2
 pyyaml>=6.0.1
-pydantic>=1.10.7,<2
 sqlmodel
 # Formatting
 black==26.1.0
 dotenv
+pydantic-settings

backend/.env.local

@@ -19,4 +19,22 @@ PLAN_TRIGGER_BUCKET="test"
 DATA_BUCKET="test"
 EPC_AUTH_TOKEN="test"
 ENGINE_SQS_URL="test"
+ENERGY_ASSESSMENTS_BUCKET="test"
+API_KEY="test"
+SECRET_KEY="test"
+ENVIRONMENT="test"
+DATA_BUCKET="test"
+PLAN_TRIGGER_BUCKET="test"
+ENGINE_SQS_URL="test"
+GOOGLE_SOLAR_API_KEY="test"
+DB_HOST="test"
+DB_PASSWORD="test"
+DB_USERNAME="test"
+DB_PORT="test"
+DB_NAME="test"
+SAP_PREDICTIONS_BUCKET="test"
+CARBON_PREDICTIONS_BUCKET="test"
+HEAT_PREDICTIONS_BUCKET="test"
+HEATING_KWH_PREDICTIONS_BUCKET="test"
+HOTWATER_KWH_PREDICTIONS_BUCKET="test"
 ENERGY_ASSESSMENTS_BUCKET="test"

backend/address2UPRN/main.py

@@ -212,6 +212,8 @@ def get_epc_data_with_postcode(postcode, size=500, attempt=1, max_attempts=3):
         method="get",
         params={"postcode": postcode},
     )
+    if not search_resp or "rows" not in search_resp:
+        return pd.DataFrame()
 
     results_df = pd.DataFrame(search_resp["rows"], columns=search_resp["column-names"])
 
@@ -298,7 +300,7 @@ def get_uprn_candidates(
     )
 
 
-def get_uprn(user_inputed_address: str, postcode: str):
+def get_uprn(user_inputed_address: str, postcode: str, return_address=False):
     """
     Return uprn (str)
     Return False if failed to find a sensible matching epc
@@ -337,6 +339,8 @@ def get_uprn(user_inputed_address: str, postcode: str):
     if found_uprn == "":
         return None
 
+    if return_address:
+        return found_uprn, address
     return found_uprn
 
 

backend/address2UPRN/script.py

@@ -1,17 +1,24 @@
 import pandas as pd
+from tqdm import tqdm
+from backend.address2UPRN.main import get_uprn
+
+# Enable tqdm for pandas
+tqdm.pandas()
+
+df = pd.read_excel("address2.xlsx")
 
 
-# use Address 1
+def extract_uprn(row):
-junte_df = pd.read_excel("hackney_uprn_failures.xlsx")
+    print(row["User Input"], row["Postcode"])
+    result = get_uprn(row["User Input"], row["Postcode"], return_address=True)
+
+    if result is None:
+        return pd.Series([None, None])
+
+    uprn, found_address = result
+    return pd.Series([uprn, found_address])
 
 
-# use domna_address_1
+df[["juntes uprn", "junte found address"]] = df.progress_apply(extract_uprn, axis=1)
-khalim_df = pd.read_excel("khalim_standard.xlsx")
-
-
-combined_df = junte_df.merge(khalim_df, how="left", left_on="Address 1", right_on='domna_address_1')
-
-# Find the row in khalim_df that does not app
-
-result = combined_df[~pd.isnull(combined_df["epc_os_uprn"])]
 
+df.to_excel("outputs2.xlsx", index=False)

sfr/principal_pitch/2_export_data.py

@@ -2,6 +2,10 @@
 This script prepares the data for the financial model
 """
 
+from dotenv import load_dotenv
+
+load_dotenv(".env.local")
+
 import pandas as pd
 import numpy as np
 from backend.app.utils import sap_to_epc
@@ -24,12 +28,12 @@ from sqlalchemy import func
 
 # PORTFOLIO_ID = 206
 # SCENARIOS = [389]
-PORTFOLIO_ID = 502  # Peabody
+PORTFOLIO_ID = 515
 SCENARIOS = [
-    986,
+    997,
 ]
 scenario_names = {
-    986: "EPC C",
+    997: "EPC C",
 }