Merge branch 'main' into deploy-condition-processor

.devcontainer/asset_list/docker-compose.yml

@@ -4,11 +4,11 @@ services:
   model-sal:
     user: "${UID}:${GID}"
     build:
-      context: ..
-      dockerfile: .devcontainer/Dockerfile
+      context: ../..
+      dockerfile: .devcontainer/asset_list/Dockerfile
     command: sleep infinity
     volumes:
-      - ..:/workspaces/model
+      - ../../:/workspaces/model
     networks:
       - model-net
 

.devcontainer/asset_list/requirements.txt

@@ -21,3 +21,4 @@ pydantic>=1.10.7,<2
 sqlmodel
 # Formatting
 black==26.1.0
+dotenv

.github/workflows/_build_image.yml

@@ -0,0 +1,78 @@
+name: Build Docker image
+
+on:
+  workflow_call:
+    inputs:
+      ecr_repo:
+        required: true
+        type: string
+      dockerfile_path:
+        required: true
+        type: string
+      build_context:
+        required: false
+        default: "."
+        type: string
+
+    outputs:
+      image_digest:
+        description: "Pushed image digest"
+        value: ${{ jobs.build.outputs.image_digest }}
+      ecr_repo_url:
+        description: "ECR repository URL"
+        value: ${{ jobs.build.outputs.ecr_repo_url }}
+
+    secrets:
+      AWS_ACCESS_KEY_ID:
+        required: true
+      AWS_SECRET_ACCESS_KEY:
+        required: true
+      AWS_REGION:
+        required: true
+
+jobs:
+  build:
+    runs-on: ubuntu-latest
+
+    outputs:
+      image_digest: ${{ steps.digest.outputs.image_digest }}
+      ecr_repo_url: ${{ steps.repo.outputs.ecr_repo_url }}
+
+    steps:
+      - uses: actions/checkout@v4
+
+      - uses: aws-actions/configure-aws-credentials@v4
+        with:
+          aws-access-key-id: ${{ secrets.AWS_ACCESS_KEY_ID }}
+          aws-secret-access-key: ${{ secrets.AWS_SECRET_ACCESS_KEY }}
+          aws-region: ${{ secrets.AWS_REGION }}
+
+      - uses: aws-actions/amazon-ecr-login@v2
+
+      - name: Resolve ECR repo URL
+        id: repo
+        run: |
+          AWS_ACCOUNT_ID=$(aws sts get-caller-identity --query Account --output text)
+
+          ECR_REPO_URL="${AWS_ACCOUNT_ID}.dkr.ecr.${AWS_REGION}.amazonaws.com/${{ inputs.ecr_repo }}"
+
+          echo "Resolved ECR repo URL (local var):"
+          echo "$ECR_REPO_URL"
+
+          echo "ecr_repo_url=$ECR_REPO_URL" >> "$GITHUB_OUTPUT"
+
+      - name: Build & push image
+        run: |
+          IMAGE_URI="${{ steps.repo.outputs.ecr_repo_url }}:${GITHUB_SHA}"
+          docker build -f ${{ inputs.dockerfile_path }} -t $IMAGE_URI ${{ inputs.build_context }}
+          docker push $IMAGE_URI
+
+      - name: Resolve image digest
+        id: digest
+        run: |
+          DIGEST=$(aws ecr describe-images \
+            --repository-name ${{ inputs.ecr_repo }} \
+            --image-ids imageTag=${GITHUB_SHA} \
+            --query 'imageDetails[0].imageDigest' \
+            --output text)
+          echo "image_digest=$DIGEST" >> "$GITHUB_OUTPUT"

.github/workflows/_deploy_lambda.yml

@@ -0,0 +1,91 @@
+name: Deploy Lambda (Terraform)
+
+on:
+  workflow_call:
+    inputs:
+      lambda_name:
+        required: true
+        type: string
+
+      lambda_path:
+        required: true
+        type: string
+
+      stage:
+        required: true
+        type: string
+
+      ecr_repo:
+        required: true
+        type: string
+
+      image_digest:
+        required: true
+        type: string
+
+    secrets:
+      AWS_ACCESS_KEY_ID:
+        required: true
+      AWS_SECRET_ACCESS_KEY:
+        required: true
+      AWS_REGION:
+        required: true
+
+jobs:
+  deploy:
+    runs-on: ubuntu-latest
+
+    steps:
+      - uses: actions/checkout@v4
+
+      - name: Debug inputs
+        run: |
+          echo "lambda_name=${{ inputs.lambda_name }}"
+          echo "lambda_path=${{ inputs.lambda_path }}"
+          echo "stage=${{ inputs.stage }}"
+          echo "ecr_repo_url=${{ inputs.ecr_repo_url }}"
+          echo "image_digest=${{ inputs.image_digest }}"
+
+
+      - uses: aws-actions/configure-aws-credentials@v4
+        with:
+          aws-access-key-id: ${{ secrets.AWS_ACCESS_KEY_ID }}
+          aws-secret-access-key: ${{ secrets.AWS_SECRET_ACCESS_KEY }}
+          aws-region: ${{ secrets.AWS_REGION }}
+
+      - uses: hashicorp/setup-terraform@v3
+
+      - uses: aws-actions/amazon-ecr-login@v2
+
+      - name: Resolve ECR repo URL
+        id: repo
+        env:
+          AWS_REGION: ${{ secrets.AWS_REGION }}
+        run: |
+          AWS_ACCOUNT_ID=$(aws sts get-caller-identity --query Account --output text)
+          ECR_REPO_URL="${AWS_ACCOUNT_ID}.dkr.ecr.${AWS_REGION}.amazonaws.com/${{ inputs.ecr_repo }}"
+          echo "ecr_repo_url=$ECR_REPO_URL" >> "$GITHUB_OUTPUT"
+
+      - name: Terraform Init
+        working-directory: ${{ inputs.lambda_path }}
+        run: terraform init -reconfigure
+
+      - name: Terraform Workspace
+        working-directory: ${{ inputs.lambda_path }}
+        run: |
+          terraform workspace select ${{ inputs.stage }} \
+            || terraform workspace new ${{ inputs.stage }}
+
+      - name: Terraform Plan
+        working-directory: ${{ inputs.lambda_path }}
+        run: |
+          terraform plan \
+            -var="stage=${{ inputs.stage }}" \
+            -var="lambda_name=${{ inputs.lambda_name }}" \
+            -var="ecr_repo_url=${{ steps.repo.outputs.ecr_repo_url }}" \
+            -var="image_digest=${{ inputs.image_digest }}" \
+            -out=lambdaplan
+
+      - name: Terraform Apply
+        working-directory: ${{ inputs.lambda_path }}
+        run: terraform apply -auto-approve lambdaplan

.github/workflows/deploy_terraform.yml

@@ -1,80 +1,98 @@
-name: Deploy terraform stack
+name: Deploy infrastructure
 
 on:
   push:
     branches:
-      - dev
-      - prod
+      - "**"
 
 jobs:
-  deploy:
+  determine_stage:
     runs-on: ubuntu-latest
+    outputs:
+      stage: ${{ steps.set-stage.outputs.stage }}
+
     steps:
-      - name: Checkout
-        uses: actions/checkout@v2
-
-      - name: Setup AWS credentials file
+      - name: Determine stage from branch
+        id: set-stage
+        shell: bash
         run: |
-          mkdir -p ~/.aws
-          echo "[DevAdmin]" > ~/.aws/credentials
-          echo "aws_access_key_id = ${{ secrets.DEV_AWS_ACCESS_KEY_ID }}" >> ~/.aws/credentials
-          echo "aws_secret_access_key = ${{ secrets.DEV_AWS_SECRET_ACCESS_KEY }}" >> ~/.aws/credentials
-          echo "[ProdAdmin]" >> ~/.aws/credentials
-          echo "aws_access_key_id = ${{ secrets.PROD_AWS_ACCESS_KEY_ID }}" >> ~/.aws/credentials
-          echo "aws_secret_access_key = ${{ secrets.PROD_AWS_SECRET_ACCESS_KEY }}" >> ~/.aws/credentials
+          BRANCH="${GITHUB_REF_NAME}"
 
-      - name: Setup AWS config file
-        run: |
-          echo "[profile DevAdmin]" > ~/.aws/config
-          echo "region = eu-west-2" >> ~/.aws/config
-          echo "[profile ProdAdmin]" >> ~/.aws/config
-          echo "region = eu-west-2" >> ~/.aws/config
+          if [[ "$BRANCH" == "prod" ]]; then
+            echo "stage=prod" >> "$GITHUB_OUTPUT"
 
-      - name: Setup Terraform
-        uses: hashicorp/setup-terraform@v1
-        with:
-          terraform_version: 1.5.2
+          elif [[ "$BRANCH" == "dev" ]]; then
+            echo "stage=dev" >> "$GITHUB_OUTPUT"
 
-      - name: Configure AWS credentials (DevAdmin)
-        uses: aws-actions/configure-aws-credentials@v1
+          else
+            echo "stage=dev" >> "$GITHUB_OUTPUT"
+          fi
+
+  # ============================================================
+  # 1️⃣ Shared Terraform (infra)
+  # ============================================================
+  shared_terraform:
+    needs: determine_stage
+    runs-on: ubuntu-latest
+    env:
+      STAGE: ${{ needs.determine_stage.outputs.stage }}
+
+    steps:
+      - uses: actions/checkout@v4
+
+      - uses: aws-actions/configure-aws-credentials@v4
         with:
           aws-access-key-id: ${{ secrets.DEV_AWS_ACCESS_KEY_ID }}
           aws-secret-access-key: ${{ secrets.DEV_AWS_SECRET_ACCESS_KEY }}
-          aws-region: eu-west-2
-        env:
-          AWS_PROFILE: "DevAdmin"
+          aws-region: ${{ secrets.DEV_AWS_REGION }}
+
+      - uses: hashicorp/setup-terraform@v3
 
       - name: Terraform Init
-        run: cd infrastructure/terraform && terraform init
+        working-directory: infrastructure/terraform/shared
+        run: terraform init -reconfigure
 
       - name: Terraform Workspace
-        run: |
-          BRANCH_NAME=$(echo "${{ github.ref }}" | sed -e "s/^refs\/heads\///")
-          cd infrastructure/terraform
-          terraform workspace select ${BRANCH_NAME} || terraform workspace new ${BRANCH_NAME}
+        working-directory: infrastructure/terraform/shared
+        run: terraform workspace select ${STAGE} || terraform workspace new ${STAGE}
 
       - name: Terraform Plan
-        run: |
-          BRANCH_NAME=$(echo "${{ github.ref }}" | sed -e "s/^refs\/heads\///")
-          cd infrastructure/terraform && terraform plan -var-file=${BRANCH_NAME}.tfvars
+        working-directory: infrastructure/terraform/shared
+        run: terraform plan -var-file=${STAGE}.tfvars -out=tfplan
 
-      - name: Deploy to Dev
-        if: github.ref == 'refs/heads/dev'
-        run: cd infrastructure/terraform && terraform apply -var-file=dev.tfvars -auto-approve
-        env:
-          name: dev
+      - name: Terraform Apply
+        if: env.STAGE == 'prod'
+        working-directory: infrastructure/terraform/shared
+        run: terraform apply -auto-approve tfplan
 
-      - name: Configure AWS credentials (ProdAdmin)
-        uses: aws-actions/configure-aws-credentials@v1
-        with:
-          aws-access-key-id: ${{ secrets.PROD_AWS_ACCESS_KEY_ID }}
-          aws-secret-access-key: ${{ secrets.PROD_AWS_SECRET_ACCESS_KEY }}
-          aws-region: eu-west-2
-        env:
-          AWS_PROFILE: "ProdAdmin"
+  # ============================================================
+  # 2️⃣ Build Address 2 UPRN image and Push
+  # ============================================================
+  address2uprn_image:
+    needs: [determine_stage, shared_terraform]
+    uses: ./.github/workflows/_build_image.yml
+    with:
+      ecr_repo: address2uprn-${{ needs.determine_stage.outputs.stage }}
+      dockerfile_path: backend/address2UPRN/Dockerfile
+      build_context: backend/address2UPRN
+    secrets:
+      AWS_ACCESS_KEY_ID: ${{ secrets.DEV_AWS_ACCESS_KEY_ID }}
+      AWS_SECRET_ACCESS_KEY: ${{ secrets.DEV_AWS_SECRET_ACCESS_KEY }}
+      AWS_REGION: ${{ secrets.DEV_AWS_REGION }}
 
-      - name: Deploy to Prod
-        if: github.ref == 'refs/heads/prod'
-        run: cd infrastructure/terraform && terraform apply -var-file=prod.tfvars -auto-approve
-        env:
-          name: prod
+  # ============================================================
+  # 3️⃣ Deploy Address 2 UPRN Lambda
+  # ============================================================
+  address2uprn_lambda:
+    needs: [address2uprn_image, determine_stage]
+    uses: ./.github/workflows/_deploy_lambda.yml
+    with:
+      lambda_name: address2uprn
+      lambda_path: infrastructure/terraform/lambda/address2UPRN
+      stage: ${{ needs.determine_stage.outputs.stage }}
+      ecr_repo: address2uprn-${{ needs.determine_stage.outputs.stage }}
+      image_digest: ${{ needs.address2uprn_image.outputs.image_digest }}
+    secrets:
+      AWS_ACCESS_KEY_ID: ${{ secrets.DEV_AWS_ACCESS_KEY_ID }}
+      AWS_SECRET_ACCESS_KEY: ${{ secrets.DEV_AWS_SECRET_ACCESS_KEY }}
+      AWS_REGION: ${{ secrets.DEV_AWS_REGION }}

asset_list/app.py

@@ -12,23 +12,34 @@ from asset_list.utils import get_data
 
 from dotenv import load_dotenv
 from backend.SearchEpc import SearchEpc
+
 load_dotenv(dotenv_path="backend/.env")
-EPC_AUTH_TOKEN = os.getenv("EPC_AUTH_TOKEN", "a2Nvbm5rb3dsZXNzYXJAZ21haWwuY29tOjY5MGJiMWM0NmIyOGI5ZDUxYzAxMzQzYzNiZGNlZGJjZDNmODQwMzA=")
+EPC_AUTH_TOKEN = os.getenv(
+    "EPC_AUTH_TOKEN",
+)
 
 
-def extract_address1(asset_list, full_address_col, postcode_col, method="first_two_words"):
+def extract_address1(
+    asset_list, full_address_col, postcode_col, method="first_two_words"
+):
     if method == "first_two_words":
-        asset_list["address1_extracted"] = asset_list[full_address_col].str.split(" ").str[:2].str.join(" ")
+        asset_list["address1_extracted"] = (
+            asset_list[full_address_col].str.split(" ").str[:2].str.join(" ")
+        )
         return asset_list
 
     if method == "first_word":
-        asset_list["address1_extracted"] = asset_list[full_address_col].str.split(" ").str[0]
+        asset_list["address1_extracted"] = (
+            asset_list[full_address_col].str.split(" ").str[0]
+        )
         return asset_list
 
     if method == "house_number_extraction":
         asset_list["address1_extracted"] = asset_list.apply(
-            lambda x: SearchEpc.get_house_number(address=x[full_address_col], postcode=x[postcode_col]),
-            axis=1
+            lambda x: SearchEpc.get_house_number(
+                address=x[full_address_col], postcode=x[postcode_col]
+            ),
+            axis=1,
         )
         return asset_list
 
@@ -57,15 +68,11 @@ def app():
     EPC recommendations
     Property UPRN
     """
-<<<<<<< HEAD
-    data_folder = ("/workspaces/model/asset_list")
-    data_filename = "assets.xlsx"
-=======
 
     data_folder = "/Users/khalimconn-kowlessar/Documents/hestia/Customers/Hackney"
     data_filename = "Domna SHF Wave 3 (3).xlsx"
     sheet_name = "Domna Wave 3"
-    postcode_column = 'Postcode'
+    postcode_column = "Postcode"
     address1_column = "Address 1"
     address1_method = None
     fulladdress_column = None
@@ -96,15 +103,16 @@ def app():
     landlord_block_reference = None
 
     # Peabody data for cleaning
-    data_folder = ("/Users/khalimconn-kowlessar/Documents/hestia/Customers/Peabody/Nov 2025 Consulting "
-                   "Project/data_validation")
+    data_folder = (
+        "/Users/khalimconn-kowlessar/Documents/hestia/Customers/Peabody/Nov 2025 Consulting "
+        "Project/data_validation"
+    )
     data_filename = "to_standardise_uprns.xlsx"
->>>>>>> 3874da6177cbcc37f7a488bec0a06e387906653c
     sheet_name = "Sheet1"
-    postcode_column = 'Postcode'
+    postcode_column = "Postcode"
     address1_column = None
-    address1_method = 'house_number_extraction'
-    fulladdress_column = 'Address'
+    address1_method = "house_number_extraction"
+    fulladdress_column = "Address"
     address_cols_to_concat = None
     missing_postcodes_method = None
     landlord_year_built = None
@@ -155,49 +163,62 @@ def app():
         landlord_existing_pv=landlord_existing_pv,
         landlord_sap=landlord_sap,
         landlord_block_reference=landlord_block_reference,
-        phase=phase
+        phase=phase,
     )
     asset_list.init_standardise()
 
     # We produce the new maps, which can be saved for future useage
     new_property_type_map = {
-        k: v for k, v in (
-            asset_list.variable_mappings[asset_list.landlord_property_type] if
-            asset_list.landlord_property_type else {}
+        k: v
+        for k, v in (
+            asset_list.variable_mappings[asset_list.landlord_property_type]
+            if asset_list.landlord_property_type
+            else {}
         ).items()
         if k not in PROPERTY_MAPPING
     }
     new_built_form_map = {
-        k: v for k, v in (
-            asset_list.variable_mappings[asset_list.landlord_built_form] if
-            asset_list.landlord_built_form else {}
+        k: v
+        for k, v in (
+            asset_list.variable_mappings[asset_list.landlord_built_form]
+            if asset_list.landlord_built_form
+            else {}
         ).items()
         if k not in BUILT_FORM_MAPPINGS
     }
     new_wall_map = {
-        k: v for k, v in (
-            asset_list.variable_mappings[asset_list.landlord_wall_construction] if
-            asset_list.landlord_wall_construction else {}
+        k: v
+        for k, v in (
+            asset_list.variable_mappings[asset_list.landlord_wall_construction]
+            if asset_list.landlord_wall_construction
+            else {}
         ).items()
         if k not in WALL_CONSTRUCTION_MAPPINGS
     }
     new_heating_map = {
-        k: v for k, v in (
-            asset_list.variable_mappings[asset_list.landlord_heating_system] if
-            asset_list.landlord_heating_system else {}
+        k: v
+        for k, v in (
+            asset_list.variable_mappings[asset_list.landlord_heating_system]
+            if asset_list.landlord_heating_system
+            else {}
         ).items()
         if k not in HEATING_MAPPINGS
     }
     new_existing_pv_map = {
-        k: v for k, v in (
-            asset_list.variable_mappings[asset_list.landlord_existing_pv] if asset_list.landlord_existing_pv else {}
+        k: v
+        for k, v in (
+            asset_list.variable_mappings[asset_list.landlord_existing_pv]
+            if asset_list.landlord_existing_pv
+            else {}
         ).items()
         if k not in EXISTING_PV_MAPPINGS
     }
     new_roof_construction_map = {
-        k: v for k, v in (
-            asset_list.variable_mappings[asset_list.landlord_roof_construction] if
-            asset_list.landlord_roof_construction else {}
+        k: v
+        for k, v in (
+            asset_list.variable_mappings[asset_list.landlord_roof_construction]
+            if asset_list.landlord_roof_construction
+            else {}
         ).items()
         if k not in ROOF_CONSTRUCTION_MAPPINGS
     }
@@ -211,7 +232,7 @@ def app():
         outcomes_address=outcomes_address,
         outcomes_postcode=outcomes_postcode,
         outcomes_houseno=outcomes_houseno,
-        outcomes_id=outcomes_id
+        outcomes_id=outcomes_id,
     )
 
     asset_list.flag_survey_master(
@@ -245,14 +266,16 @@ def app():
         skip = max(chunk_indexes)
 
     if any(x in folder_contents for x in downloaded_files):
-        skip = max([i for i in chunk_indexes if filename.format(i=i) in folder_contents])
+        skip = max(
+            [i for i in chunk_indexes if filename.format(i=i) in folder_contents]
+        )
 
     for i in range(0, len(asset_list.standardised_asset_list), chunk_size):
         print(f"Processing chunk {i} to {i + chunk_size}")
         if skip is not None and not force_retrieve_data:
             if i <= skip:
                 continue
-        chunk = asset_list.standardised_asset_list[i:i + chunk_size]
+        chunk = asset_list.standardised_asset_list[i : i + chunk_size]
         epc_data_chunk, errors_chunk, no_epc_chunk = get_data(
             df=chunk,
             row_id_name=asset_list.DOMNA_PROPERTY_ID,
@@ -264,7 +287,7 @@ def app():
             built_form_column=AssetList.STANDARD_BUILT_FORM,
             manual_uprn_map=manual_uprn_map,
             epc_api_only=epc_api_only,
-            epc_auth_token=EPC_AUTH_TOKEN
+            epc_auth_token=EPC_AUTH_TOKEN,
         )
 
         # We now retrieve any failed properties
@@ -287,7 +310,9 @@ def app():
 
         # Append the failed data to the main data
         # Store the chunk locally as a csv
-        pd.DataFrame(epc_data_chunk).to_csv(os.path.join(data_folder, f"Chunks/Chunk {i}.csv"), index=False)
+        pd.DataFrame(epc_data_chunk).to_csv(
+            os.path.join(data_folder, f"Chunks/Chunk {i}.csv"), index=False
+        )
         # Store the errors and no-data locally
         with open(os.path.join(data_folder, f"Chunks/Chunk {i} errors.json"), "w") as f:
             json.dump(errors_chunk, f)
@@ -318,7 +343,9 @@ def app():
 
     unique_recommendations = set()
     for _, row in recommendations_df.iterrows():
-        unique_recommendations.update([rec["improvement-summary-text"] for rec in row["recommendations"]])
+        unique_recommendations.update(
+            [rec["improvement-summary-text"] for rec in row["recommendations"]]
+        )
 
     columns = [asset_list.DOMNA_PROPERTY_ID] + list(unique_recommendations)
     transformed_data = []
@@ -338,20 +365,24 @@ def app():
     transformed_df = pd.DataFrame(transformed_data)
     for col in [
         "Floor insulation (solid floor)",
-        "Floor insulation", "Floor insulation (suspended floor)"
+        "Floor insulation",
+        "Floor insulation (suspended floor)",
     ]:
         if col not in transformed_df.columns:
             transformed_df[col] = False
     transformed_df = transformed_df[
         [
-            asset_list.DOMNA_PROPERTY_ID, "Floor insulation (solid floor)",
-            "Floor insulation", "Floor insulation (suspended floor)"
+            asset_list.DOMNA_PROPERTY_ID,
+            "Floor insulation (solid floor)",
+            "Floor insulation",
+            "Floor insulation (suspended floor)",
         ]
     ]
 
     transformed_df["epc_has_floor_recommendation"] = (
-        transformed_df["Floor insulation (solid floor)"] | transformed_df["Floor insulation"] |
-        transformed_df["Floor insulation (suspended floor)"]
+        transformed_df["Floor insulation (solid floor)"]
+        | transformed_df["Floor insulation"]
+        | transformed_df["Floor insulation (suspended floor)"]
     )
 
     # Get the find my epc data
@@ -364,21 +395,20 @@ def app():
             find_my_epc_data.append(
                 {
                     asset_list.DOMNA_PROPERTY_ID: x[asset_list.DOMNA_PROPERTY_ID],
-                    **x["find_my_epc_data"]
+                    **x["find_my_epc_data"],
                 }
             )
         else:
             find_my_epc_data.append(
-                {
-                    asset_list.DOMNA_PROPERTY_ID: x[asset_list.DOMNA_PROPERTY_ID]
-                }
+                {asset_list.DOMNA_PROPERTY_ID: x[asset_list.DOMNA_PROPERTY_ID]}
             )
 
     find_my_epc_data = pd.DataFrame(find_my_epc_data)
 
     find_my_epc_data = find_my_epc_data.merge(
         transformed_df[[asset_list.DOMNA_PROPERTY_ID, "epc_has_floor_recommendation"]],
-        how="left", on=asset_list.DOMNA_PROPERTY_ID
+        how="left",
+        on=asset_list.DOMNA_PROPERTY_ID,
     )
 
     # We check if we get the solar pv column:
@@ -388,24 +418,26 @@ def app():
     # Retrieve just the data we need
     epc_df = epc_df[
         [asset_list.DOMNA_PROPERTY_ID] + list(asset_list.EPC_API_DATA_NAMES.keys())
-        ].rename(
-        columns=asset_list.EPC_API_DATA_NAMES
-    )
+    ].rename(columns=asset_list.EPC_API_DATA_NAMES)
 
     # Look for columns not in the find my EPC data, which will have happened if we didn't
     # retrieve it in the first place
-    missed_find_epc_cols = [c for c in list(asset_list.FIND_EPC_DATA_NAMES.keys()) if c not in find_my_epc_data.columns]
+    missed_find_epc_cols = [
+        c
+        for c in list(asset_list.FIND_EPC_DATA_NAMES.keys())
+        if c not in find_my_epc_data.columns
+    ]
     if missed_find_epc_cols:
         for c in missed_find_epc_cols:
             find_my_epc_data[c] = None
 
     epc_df = epc_df.merge(
         find_my_epc_data[
-            [asset_list.DOMNA_PROPERTY_ID, "epc_has_floor_recommendation"] + list(asset_list.FIND_EPC_DATA_NAMES.keys())
-            ]
-        .rename(columns=asset_list.FIND_EPC_DATA_NAMES),
+            [asset_list.DOMNA_PROPERTY_ID, "epc_has_floor_recommendation"]
+            + list(asset_list.FIND_EPC_DATA_NAMES.keys())
+        ].rename(columns=asset_list.FIND_EPC_DATA_NAMES),
         how="left",
-        on=asset_list.DOMNA_PROPERTY_ID
+        on=asset_list.DOMNA_PROPERTY_ID,
     )
 
     asset_list.merge_data(epc_df)
@@ -422,7 +454,10 @@ def app():
     asset_list.get_work_figures()
 
     # Store as an excel
-    filename = os.path.join(data_folder, ".".join(data_filename.split(".")[:-1])) + " - Standardised.xlsx"
+    filename = (
+        os.path.join(data_folder, ".".join(data_filename.split(".")[:-1]))
+        + " - Standardised.xlsx"
+    )
     # Store the data in two tabs. One for the asset list with the EPC data and the second with the flat data
 
     # Determine inspections priority
@@ -446,26 +481,42 @@ def app():
     # )
 
     with pd.ExcelWriter(filename) as writer:
-        asset_list.standardised_asset_list.to_excel(writer, sheet_name="Standardised Asset List", index=False)
+        asset_list.standardised_asset_list.to_excel(
+            writer, sheet_name="Standardised Asset List", index=False
+        )
         if asset_list.block_analysis_df is not None:
-            asset_list.block_analysis_df.to_excel(writer, sheet_name="Block Analysis", index=False)
+            asset_list.block_analysis_df.to_excel(
+                writer, sheet_name="Block Analysis", index=False
+            )
         # If we have outcomes, we add a tab with the outcomes
         if not asset_list.outcomes_for_output.empty:
-            asset_list.outcomes_for_output.to_excel(writer, sheet_name="Outcomes", index=False)
+            asset_list.outcomes_for_output.to_excel(
+                writer, sheet_name="Outcomes", index=False
+            )
 
         if not asset_list.unmatched_submissions.empty:
-            asset_list.unmatched_submissions.to_excel(writer, sheet_name="Unmatched Submissions", index=False)
+            asset_list.unmatched_submissions.to_excel(
+                writer, sheet_name="Unmatched Submissions", index=False
+            )
 
         if not asset_list.outcomes_no_match.empty:
-            asset_list.outcomes_no_match.to_excel(writer, sheet_name="Unmatched Outcomes", index=False)
+            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)
+            asset_list.ecosurv_no_match.to_excel(
+                writer, sheet_name="Unmatched Ecosurv", index=False
+            )
 
         if not asset_list.geographical_areas.empty:
-            asset_list.geographical_areas.to_excel(writer, sheet_name="Geographical Areas", index=False)
+            asset_list.geographical_areas.to_excel(
+                writer, sheet_name="Geographical Areas", index=False
+            )
 
         # Store dupes
         if asset_list.duplicated_addresses is not None:
             if not asset_list.duplicated_addresses.empty:
-                asset_list.duplicated_addresses.to_excel(writer, sheet_name="Duplicate Properties", index=False)
+                asset_list.duplicated_addresses.to_excel(
+                    writer, sheet_name="Duplicate Properties", index=False
+                )

backend/address2UPRN/Dockerfile

@@ -0,0 +1,7 @@
+FROM public.ecr.aws/lambda/python:3.10
+
+# Copy function code
+COPY main.py .
+
+# Set the handler
+CMD ["main.handler"]

backend/address2UPRN/main.py

@@ -14,6 +14,9 @@ EPC_AUTH_TOKEN = os.getenv(
     "EPC_AUTH_TOKEN",
 )
 
+if EPC_AUTH_TOKEN is None:
+    raise RuntimeError("EPC_AUTH_TOKEN not defined in env")
+
 import re
 from difflib import SequenceMatcher
 from typing import Set
@@ -38,6 +41,34 @@ def levenshtein(a: str, b: str) -> float:
     def tokenise(s: str) -> Set[str]:
         return set(s.split())
 
+    def extract_building_number(s: str) -> str | None:
+        """
+        Extract the main building number (NOT flat/unit).
+        Assumes formats like:
+        - '42 moreton road'
+        - 'flat 3 42 moreton road'
+        """
+        tokens = s.split()
+
+        # remove flat/unit context
+        cleaned = []
+        skip_next = False
+        for t in tokens:
+            if t in ("flat", "apt", "apartment", "unit"):
+                skip_next = True
+                continue
+            if skip_next:
+                skip_next = False
+                continue
+            cleaned.append(t)
+
+        # first remaining number is building number
+        for t in cleaned:
+            if re.fullmatch(r"\d+[a-z]?", t):
+                return t
+
+        return None
+
     a_norm = normalise_address(a)
     b_norm = normalise_address(b)
 
@@ -52,6 +83,13 @@ def levenshtein(a: str, b: str) -> float:
     if nums_a and nums_b and nums_a.isdisjoint(nums_b):
         return 0.0
 
+    # 🔒 HARD GUARD: building number must match
+    bld_a = extract_building_number(a_norm)
+    bld_b = extract_building_number(b_norm)
+
+    if bld_a and bld_b and bld_a != bld_b:
+        return 0.0
+
     # --- order-sensitive flat/building guard ---
     seq_a = extract_number_sequence(a_norm)
     seq_b = extract_number_sequence(b_norm)
@@ -418,6 +456,10 @@ def run_all_test():
         get_uprn("46 Oswald Street", "E5 0BT"), False
     )  # this one return "flat 1, in 1 semley gate"
     get_uprn_candidates(get_epc_data_with_postcode("e5 0bt"), "48 Oswald Street")
+    get_uprn_candidates(
+        get_epc_data_with_postcode("Cr2 7dl"),
+        "FLAT 3; 42 MORETON ROAD, SOUTH CROYDON, SURREY",
+    )
 
 
 if __name__ == "__main__":
@@ -511,6 +553,11 @@ if __name__ == "__main__":
     )
 
 
+def handler(event, context):
+    print("hello world")
+    return {"statusCode": 200, "body": "hello world"}
+
+
 # TO do function dispatcher,
 
 # get_uprn_candidates(get_epc_data_with_postcode("E9 5NH"),"Flat 1, 5 Semley Gate" and Flat 5, 1 Semley Gate)

backend/address2UPRN/tests/test_data.csv

@@ -115,11 +115,16 @@ FLAT 43 Goodstone Court,HA1 4FL,10070269095
 8 Genteel House Samara Drive,UB1 1FJ,12189842
 9 Genteel House Samara Drive,UB1 1FJ,12189843
 10 Genteel House Samara Drive,UB1 1FJ,12189844
-1 ASH TREE HOUSE,SE5 0TE,10009803979
-3 ASH TREE HOUSE,SE5 0TE,10009803981
-5 ASH TREE HOUSE,SE5 0TE,10009803983
-8 ASH TREE HOUSE,SE5 0TE,10009803986
-12 ASH TREE HOUSE,SE5 0TE,10009803990
+1 ASH TREE HOUSE,SE5 0TE,None
+"Flat 1 Ash Tree House, 2, Thompson Avenue",SE5 0TE,10009803979
+3 ASH TREE HOUSE,SE5 0TE,None
+Flat 3 ASH TREE HOUSE,SE5 0TE,10009803981
+5 ASH TREE HOUSE,SE5 0TE,None
+Flat 5 ASH TREE HOUSE,SE5 0TE,10009803983
+Flat 8 ASH TREE HOUSE,SE5 0TE,10009803986
+8 ASH TREE HOUSE,SE5 0TE,None
+Flat 12 ASH TREE HOUSE,SE5 0TE,10009803990
+12 ASH TREE HOUSE,SE5 0TE,None
 FLAT 1 599 HARROW ROAD,W10 4RA,217113930
 FLAT 2 599 HARROW ROAD,W10 4RA,217113931
 FLAT 3 599 HARROW ROAD,W10 4RA,None
@@ -164,4 +169,198 @@ FLAT 8 599 HARROW ROAD,W10 4RA,None
 24b Honley Road,SE6 2HZ,None
 FLAT B 158 LEAHURST ROAD,SE13 5NL,100021976974
 2 COLLEGE HOUSE,CM7 1JS,100091449870
-3 COLLEGE HOUSE,CM7 1JS,100091449871
+3 COLLEGE HOUSE,CM7 1JS,100091449871
+1 Anita Street,M4 5DU,None
+2 Anita Street,M4 5DU,77123061
+5 Anita Street,M4 5DU,77123081
+6 Anita Street,M4 5DU,77123082
+8 Anita Street,M4 5DU,None
+9 Anita Street,M4 5DU,None
+10 Anita Street,M4 5DU,77123051
+12 Anita Street,M4 5DU,77123053
+19 Anita Street,M4 5DU,None
+22 Anita Street,M4 5DU,None
+26 Anita Street,M4 5DU,77123068
+28 Anita Street,M4 5DU,None
+30 Anita Street,M4 5DU,None
+32 Anita Street,M4 5DU,None
+33 Anita Street,M4 5DU,77123076
+34 Anita Street,M4 5DU,None
+35 Anita Street,M4 5DU,77123078
+36 Anita Street,M4 5DU,77123079
+23 George Leigh Street,M4 5DR,77123171
+25 George Leigh Street,M4 5DR,None
+35 George Leigh Street,M4 5DR,77123177
+39 George Leigh Street,M4 5DR,77123179
+41 George Leigh Street,M4 5DR,None
+43 George Leigh Street,M4 5DR,None
+49 George Leigh Street,M4 5DR,None
+51 George Leigh Street,M4 5DR,77123185
+55 George Leigh Street,M4 5DR,None
+57 George Leigh Street,M4 5DR,None
+"1a, Victoria Square",M4 5DX,77211153
+2a Victoria Square ,M4 5DX,None
+"4a, Victoria Square",M4 5DX,77211155
+5a Victoria Square,M4 5DX,77211156
+ 6a Victoria Square,M4 5DX,77211157
+7a Victoria Square,M4 5DX,77211158
+8a Victoria Square,M4 5DX,77211159
+9a Victoria Square,M4 5DX,77211160
+10a Victoria Square,M4 5DX,77211161
+11a Victoria Square,M4 5DX,77211162
+12a Victoria Square,M4 5DX,77211163
+13a Victoria Square,M4 5DX,77211164
+14a Victoria Square,M4 5DX,77211165
+15a Victoria Square,M4 5DX,77211166
+16a Victoria Square,M4 5DX,77211167
+17a Victoria Square,M4 5DX,77211168
+18a Victoria Square,M4 5DX,77211169
+19a Victoria Square,M4 5DX,77211170
+20a Victoria Square,M4 5DX,77211171
+21a Victoria Square,M4 5DY,77211172
+22a Victoria Square,M4 5DY,None
+23a Victoria Square,M4 5DY,77211174
+24a Victoria Square,M4 5DY,77211175
+25a Victoria Square,M4 5DY,77211176
+26a Victoria Square,M4 5DY,77211177
+27a Victoria Square,M4 5DY,77211178
+28a Victoria Square,M4 5DY,None
+29a Victoria Square,M4 5DY,77211180
+30a Victoria Square,M4 5DY,77211181
+31a Victoria Square,M4 5DY,77211182
+32a Victoria Square,M4 5DY,77211183
+33a Victoria Square,M4 5DY,77211184
+34a Victoria Square,M4 5DY,77211185
+35a Victoria Square,M4 5DY,None
+36a Victoria Square,M4 5DY,77211187
+37a Victoria Square,M4 5DY,77211188
+38a Victoria Square,M4 5DY,77211189
+39a Victoria Square,M4 5DY,77211190
+40a Victoria Square,M4 5DY,None
+41a Victoria Square,M4 5DY,77211192
+42a Victoria Square,M4 5DY,77211193
+43a Victoria Square,M4 5DY,77211194
+44a Victoria Square,M4 5DY,77211195
+45a Victoria Square,M4 5DY,77211196
+46a Victoria Square,M4 5DY,77211197
+47a Victoria Square,M4 5DY,77211198
+48a Victoria Square,M4 5DY,77211199
+49a Victoria Square,M4 5DY,77211200
+50a Victoria Square,M4 5DY,77211201
+51a Victoria Square,M4 5DY,77211202
+52a Victoria Square,M4 5DY,77211203
+53a Victoria Square,M4 5DY,77211204
+54a Victoria Square,M4 5DY,77211205
+55a Victoria Square,M4 5DY,77211206
+56a Victoria Square,M4 5DZ,77211207
+57a Victoria Square,M4 5DZ,None
+58a Victoria Square,M4 5DZ,77211209
+59a Victoria Square,M4 5DZ,77211210
+60a Victoria Square,M4 5DZ,77211211
+61a Victoria Square,M4 5DZ,77211212
+62a Victoria Square,M4 5DZ,77211213
+63a Victoria Square,M4 5DZ,None
+64a Victoria Square,M4 5DZ,77211215
+65a Victoria Square,M4 5DZ,77211216
+66a Victoria Square,M4 5DZ,None
+67a Victoria Square,M4 5DZ,None
+68a Victoria Square,M4 5DZ,77211219
+69a Victoria Square,M4 5DZ,77211220
+70a Victoria Square,M4 5DZ,77211221
+71a Victoria Square,M4 5DZ,77211222
+72a Victoria Square,M4 5DZ,77211223
+73a Victoria Square,M4 5DZ,77211224
+74a Victoria Square,M4 5DZ,None
+75a Victoria Square,M4 5DZ,77211226
+76a Victoria Square,M4 5DZ,77211227
+77a Victoria Square,M4 5DZ,None
+78a Victoria Square,M4 5DZ,77211229
+79a Victoria Square,M4 5DZ,77211230
+80a Victoria Square,M4 5DZ,77211231
+81a Victoria Square,M4 5DZ,77211232
+82 Victoria Square,M4 5DZ,None
+83a Victoria Square,M4 5DZ,77211234
+84a Victoria Square,M4 5DZ,None
+85a Victoria Square,M4 5DZ,77211236
+86a Victoria Square,M4 5DZ,77211237
+87a Victoria Square,M4 5DZ,77211238
+88a Victoria Square,M4 5DZ,None
+89a Victoria Square,M4 5DZ,77211240
+90a Victoria Square,M4 5DZ,77211241
+91a Victoria Square,M4 5DZ,77211242
+92a Victoria Square,M4 5DZ,77211243
+93a Victoria Square,M4 5EA,77211244
+94a Victoria Square,M4 5EA,None
+95a Victoria Square,M4 5EA,77211246
+96a Victoria Square,M4 5EA,77211247
+97a Victoria Square,M4 5EA,77211248
+98a Victoria Square,M4 5EA,77211249
+99a Victoria Square,M4 5EA,77211250
+100a Victoria Square,M4 5EA,77211251
+101a Victoria Square,M4 5EA,None
+102a Victoria Square,M4 5EA,None
+103a Victoria Square,M4 5EA,77211254
+104a Victoria Square,M4 5EA,77211255
+105a Victoria Square,M4 5EA,None
+106a Victoria Square,M4 5EA,77211257
+107a Victoria Square,M4 5EA,77211258
+108a Victoria Square,M4 5EA,77211259
+109a Victoria Square,M4 5EA,77211260
+110a Victoria Square,M4 5EA,77211261
+111a Victoria Square,M4 5EA,77211262
+112a Victoria Square,M4 5EA,None
+113a Victoria Square,M4 5EA,77211264
+114a Victoria Square,M4 5EA,77211265
+115a Victoria Square,M4 5EA,77211266
+116a Victoria Square,M4 5EA,77211267
+117a Victoria Square,M4 5EA,None
+118a Victoria Square,M4 5EA,None
+119a Victoria Square,M4 5EA,77211270
+120a Victoria Square,M4 5EA,77211271
+121a Victoria Square,M4 5EA,77211272
+122a Victoria Square,M4 5EA,77211273
+123a Victoria Square,M4 5EA,77211274
+124a Victoria Square,M4 5EA,None
+125a Victoria Square,M4 5EA,77211276
+126a Victoria Square,M4 5EA,77211277
+127a Victoria Square,M4 5EA,77211278
+128a Victoria Square,M4 5EA,77211279
+129a Victoria Square,M4 5EA,77211280
+130a Victoria Square,M4 5FA,77211281
+131a Victoria Square,M4 5FA,77211282
+132a Victoria Square,M4 5FA,77211283
+133a Victoria Square,M4 5FA,None
+134a Victoria Square,M4 5FA,77211285
+135a Victoria Square,M4 5FA,77211286
+136a Victoria Square,M4 5FA,77211287
+137a Victoria Square,M4 5FA,77211288
+138a Victoria Square,M4 5FA,77211289
+139a Victoria Square,M4 5FA,77211290
+140a Victoria Square,M4 5FA,77211291
+141a Victoria Square,M4 5FA,77211292
+142a Victoria Square,M4 5FA,77211293
+143a Victoria Square,M4 5FA,77211294
+144a Victoria Square,M4 5FA,77211295
+145a Victoria Square,M4 5FA,None
+146a Victoria Square,M4 5FA,77211297
+147a Victoria Square,M4 5FA,77211298
+148a Victoria Square,M4 5FA,77211299
+149a Victoria Square,M4 5FA,77211300
+150a Victoria Square,M4 5FA,77211301
+151a Victoria Square,M4 5FA,None
+152a Victoria Square,M4 5FA,77211303
+153a Victoria Square,M4 5FA,None
+154a Victoria Square,M4 5FA,77211305
+155a Victoria Square,M4 5FA,None
+156a Victoria Square,M4 5FA,77211307
+157a Victoria Square,M4 5FA,77211308
+158a Victoria Square,M4 5FA,77211309
+159a Victoria Square,M4 5FA,None
+160a Victoria Square,M4 5FA,77211311
+161a Victoria Square,M4 5FA,None
+162a Victoria Square,M4 5FA,None
+163a Victoria Square,M4 5FA,77211314
+164a Victoria Square,M4 5FA,77211315
+165a Victoria Square,M4 5FA,77211316
+166a Victoria Square,M4 5FA,None
+"FLAT 3; 42 MORETON ROAD, SOUTH CROYDON, SURREY",CR2 7DL,None

infrastructure/terraform/lambda/_template/README.md

@@ -0,0 +1,51 @@
+## Checklist for adding a new Lambda
+
+### 1. Create the Lambda scaffold
+- Copy the template:
+
+  cp -r lambda/_template lambda/<lambda_name>
+
+---
+
+### 2. Add infrastructure prerequisites (shared stack)
+- Add a new ECR repository in:
+
+  infrastructure/terraform/shared/main.tf
+
+- Apply the shared stack
+    - This requires commenting 'if env.stage == "prod"' in .github/workflows/deploy_terraform.yml
+
+- Verify the ECR repository exists in AWS
+
+---
+
+### 3. Add Docker build configuration
+- Create a `Dockerfile` for the Lambda
+- Verify the Dockerfile path and build context
+- Add a new image build job in `deploy_terraform.yml` using `_build_image.yml`
+
+---
+
+### 4. Wire the Lambda deploy job (CI)
+- Add a deploy job using `_deploy_lambda.yml`
+- Ensure the deploy job depends on the image build job
+
+---
+
+### 5. Deploy
+- Push changes to GitHub
+- CI will:
+  1. Build and push the Docker image
+  2. Deploy the Lambda 
+  3. Verify everything deployed. Good things to check:
+    - ECR with image
+    - SQS
+    - Trigger SQS
+      - Cloud watch logs
+---
+### 5. Delete
+  1. Delete README if you used cp -r
+
+---
+
+## Please feel free to update this document to make it easier for the next person

infrastructure/terraform/lambda/_template/main.tf

@@ -0,0 +1,14 @@
+module "lambda" {
+  source = "../modules/lambda_with_sqs"
+
+  name  = REPLACE ME #"address2uprn" for example
+  stage = var.stage
+
+  image_uri = local.image_uri
+
+
+  environment = {
+    STAGE = var.stage
+    LOG_LEVEL = "info"
+  }
+}

infrastructure/terraform/lambda/_template/provider.tf

@@ -0,0 +1,16 @@
+terraform {
+  required_providers {
+    aws = {
+      source  = "hashicorp/aws"
+      version = "~> 4.16"
+    }
+  }
+
+  backend "s3" {
+    bucket = REPLACE_ME
+    key    = "terraform.tfstate"
+    region = "eu-west-2"
+  }
+
+  required_version = ">= 1.2.0"
+}

infrastructure/terraform/lambda/_template/variables.tf

@@ -0,0 +1,27 @@
+variable "lambda_name" {
+  type        = string
+  description = "Logical name of the lambda (e.g. address2uprn)"
+}
+
+variable "stage" {
+  description = "Deployment stage (e.g. dev, prod)"
+  type        = string
+}
+variable "ecr_repo_url" {
+  type        = string
+  description = "ECR repository URL (no tag, no digest)"
+}
+
+variable "image_digest" {
+  type        = string
+  description = "Image digest (sha256:...)"
+}
+
+
+locals {
+  image_uri = "${var.ecr_repo_url}@${var.image_digest}"
+}
+
+output "resolved_image_uri" {
+  value = local.image_uri
+}

infrastructure/terraform/lambda/address2UPRN/main.tf

@@ -0,0 +1,14 @@
+module "address2uprn" {
+  source = "../modules/lambda_with_sqs"
+
+  name  = "address2uprn"
+  stage = var.stage
+
+  image_uri = local.image_uri
+
+
+  environment = {
+    STAGE     = var.stage
+    LOG_LEVEL = "info"
+  }
+}

infrastructure/terraform/lambda/address2UPRN/provider.tf

@@ -0,0 +1,17 @@
+terraform {
+  required_providers {
+    aws = {
+      source  = "hashicorp/aws"
+      version = "~> 4.16"
+    }
+  }
+
+  backend "s3" {
+    bucket = "address2uprn-terraform-state"
+    key    = "terraform.tfstate"
+    region = "eu-west-2"
+  }
+
+  required_version = ">= 1.2.0"
+}
+

infrastructure/terraform/lambda/address2UPRN/variables.tf

@@ -0,0 +1,27 @@
+variable "lambda_name" {
+  type        = string
+  description = "Logical name of the lambda (e.g. address2uprn)"
+}
+
+variable "stage" {
+  description = "Deployment stage (e.g. dev, prod)"
+  type        = string
+}
+variable "ecr_repo_url" {
+  type        = string
+  description = "ECR repository URL (no tag, no digest)"
+}
+
+variable "image_digest" {
+  type        = string
+  description = "Image digest (sha256:...)"
+}
+
+
+locals {
+  image_uri = "${var.ecr_repo_url}@${var.image_digest}"
+}
+
+output "resolved_image_uri" {
+  value = local.image_uri
+}

infrastructure/terraform/lambda/modules/lambda_with_sqs/main.tf

@@ -0,0 +1,44 @@
+############################################
+# IAM role
+############################################
+module "role" {
+  source = "../../../modules/lambda_execution_role"
+  name   = "${var.name}-lambda-${var.stage}"
+}
+
+############################################
+# SQS queue + DLQ
+############################################
+module "queue" {
+  source = "../../../modules/sqs_queue"
+  name   = "${var.name}-queue-${var.stage}"
+}
+
+############################################
+# Lambda
+############################################
+module "lambda" {
+  source = "../../../modules/lambda_service"
+
+  name      = "${var.name}-${var.stage}"
+  role_arn = module.role.role_arn
+  image_uri = var.image_uri
+
+  timeout     = var.timeout
+  memory_size = var.memory_size
+
+  environment = var.environment
+}
+
+############################################
+# SQS → Lambda trigger
+############################################
+module "sqs_trigger" {
+  source = "../../../modules/lambda_sqs_trigger"
+
+  lambda_arn        = module.lambda.lambda_arn
+  lambda_role_name = module.role.role_name
+  queue_arn        = module.queue.queue_arn
+
+  batch_size = var.batch_size
+}

infrastructure/terraform/lambda/modules/lambda_with_sqs/outputs.tf

@@ -0,0 +1,11 @@
+output "lambda_arn" {
+  value = module.lambda.lambda_arn
+}
+
+output "queue_arn" {
+  value = module.queue.queue_arn
+}
+
+output "queue_url" {
+  value = module.queue.queue_url
+}

infrastructure/terraform/lambda/modules/lambda_with_sqs/variables.tf

@@ -0,0 +1,36 @@
+variable "name" {
+  type = string
+}
+
+variable "stage" {
+  type = string
+}
+
+variable "image_uri" {
+  type = string
+}
+
+variable "region" {
+  type    = string
+  default = "eu-west-2"
+}
+
+variable "timeout" {
+  type    = number
+  default = 60
+}
+
+variable "memory_size" {
+  type    = number
+  default = 1024
+}
+
+variable "environment" {
+  type    = map(string)
+  default = {}
+}
+
+variable "batch_size" {
+  type    = number
+  default = 10
+}

infrastructure/terraform/modules/container_registry/main.tf

@@ -0,0 +1,30 @@
+resource "aws_ecr_repository" "this" {
+  name = "${var.name}-${var.stage}"
+
+  image_tag_mutability = "MUTABLE"
+
+  image_scanning_configuration {
+    scan_on_push = true
+  }
+}
+
+resource "aws_ecr_lifecycle_policy" "this" {
+  repository = aws_ecr_repository.this.name
+
+  policy = jsonencode({
+    rules = [
+      {
+        rulePriority = 1
+        description  = "Expire old images"
+        selection = {
+          tagStatus   = "any"
+          countType   = "imageCountMoreThan"
+          countNumber = var.retain_count
+        }
+        action = {
+          type = "expire"
+        }
+      }
+    ]
+  })
+}

infrastructure/terraform/modules/container_registry/outputs.tf

@@ -0,0 +1,11 @@
+output "repository_name" {
+  value = aws_ecr_repository.this.name
+}
+
+output "repository_url" {
+  value = aws_ecr_repository.this.repository_url
+}
+
+output "repository_arn" {
+  value = aws_ecr_repository.this.arn
+}

infrastructure/terraform/modules/container_registry/variables.tf

@@ -0,0 +1,15 @@
+variable "name" {
+  description = "Base name of the repository (without stage)"
+  type        = string
+}
+
+variable "stage" {
+  description = "Deployment stage (e.g. dev, prod)"
+  type        = string
+}
+
+variable "retain_count" {
+  description = "Number of images to retain"
+  type        = number
+  default     = 10
+}

infrastructure/terraform/modules/ecr/main.tf

@@ -1,3 +1,6 @@
+# This ecr works for things deployed by serverless.
+# TODO: unify ecr and container_registry to one 
+
 resource "aws_ecr_repository" "my_repository" {
   name                 = "${var.ecr_name}"
   image_tag_mutability = "MUTABLE"

infrastructure/terraform/modules/ecr/outputs.tf

@@ -1,4 +1,10 @@
 output "ecr_repository_name" {
   description = "Name of the EPR repo in AWS"
   value       = aws_ecr_repository.my_repository.name
+}
+
+
+output "ecr_repository_url" {
+  description = "Full ECR repository URL"
+  value       = aws_ecr_repository.my_repository.repository_url
 }

infrastructure/terraform/modules/lambda_execution_role/main.tf

@@ -0,0 +1,37 @@
+data "aws_iam_policy_document" "assume" {
+  statement {
+    effect = "Allow"
+    principals {
+      type        = "Service"
+      identifiers = ["lambda.amazonaws.com"]
+    }
+    actions = ["sts:AssumeRole"]
+  }
+}
+
+resource "aws_iam_role" "this" {
+  name               = var.name
+  assume_role_policy = data.aws_iam_policy_document.assume.json
+}
+
+resource "aws_iam_role_policy_attachment" "basic_logs" {
+  role       = aws_iam_role.this.name
+  policy_arn = "arn:aws:iam::aws:policy/service-role/AWSLambdaBasicExecutionRole"
+}
+
+resource "aws_iam_role_policy" "ecr_pull" {
+  role = aws_iam_role.this.name
+
+  policy = jsonencode({
+    Version = "2012-10-17"
+    Statement = [{
+      Effect = "Allow"
+      Action = [
+        "ecr:GetAuthorizationToken",
+        "ecr:BatchGetImage",
+        "ecr:GetDownloadUrlForLayer"
+      ]
+      Resource = "*"
+    }]
+  })
+}

infrastructure/terraform/modules/lambda_execution_role/outputs.tf

@@ -0,0 +1,7 @@
+output "role_arn" {
+  value = aws_iam_role.this.arn
+}
+
+output "role_name" {
+  value = aws_iam_role.this.name
+}

infrastructure/terraform/modules/lambda_execution_role/variables.tf

@@ -0,0 +1,4 @@
+variable "name" {
+  description = "IAM role name for the Lambda execution role"
+  type        = string
+}

infrastructure/terraform/modules/lambda_service/main.tf

@@ -0,0 +1,15 @@
+resource "aws_lambda_function" "this" {
+  function_name = var.name
+  role          = var.role_arn
+
+  package_type = "Image"
+  image_uri    = var.image_uri
+
+  timeout     = var.timeout
+  memory_size = var.memory_size
+  publish     = true
+
+  environment {
+    variables = var.environment
+  }
+}

infrastructure/terraform/modules/lambda_service/outputs.tf

@@ -0,0 +1,3 @@
+output "lambda_arn" {
+  value = aws_lambda_function.this.arn
+}

infrastructure/terraform/modules/lambda_service/variables.tf

@@ -0,0 +1,18 @@
+variable "name" { type = string }
+variable "role_arn" { type = string }
+variable "image_uri" { type = string }
+
+variable "timeout" {
+  type    = number
+  default = 30
+}
+
+variable "memory_size" {
+  type    = number
+  default = 512
+}
+
+variable "environment" {
+  type    = map(string)
+  default = {}
+}

infrastructure/terraform/modules/lambda_sqs_trigger/main.tf

@@ -0,0 +1,23 @@
+resource "aws_lambda_event_source_mapping" "this" {
+  event_source_arn = var.queue_arn
+  function_name    = var.lambda_arn
+  batch_size       = var.batch_size
+  enabled          = true
+}
+
+resource "aws_iam_role_policy" "allow_sqs" {
+  role = var.lambda_role_name
+
+  policy = jsonencode({
+    Version = "2012-10-17"
+    Statement = [{
+      Effect = "Allow"
+      Action = [
+        "sqs:ReceiveMessage",
+        "sqs:DeleteMessage",
+        "sqs:GetQueueAttributes"
+      ]
+      Resource = var.queue_arn
+    }]
+  })
+}

infrastructure/terraform/modules/lambda_sqs_trigger/variables.tf

@@ -0,0 +1,8 @@
+variable "lambda_arn" { type = string }
+variable "lambda_role_name" { type = string }
+variable "queue_arn" { type = string }
+
+variable "batch_size" {
+  type    = number
+  default = 10
+}

infrastructure/terraform/modules/sqs_queue/main.tf

@@ -0,0 +1,14 @@
+resource "aws_sqs_queue" "dlq" {
+  name = "${var.name}-dlq"
+}
+
+resource "aws_sqs_queue" "this" {
+  name = var.name
+
+  visibility_timeout_seconds = 120
+
+  redrive_policy = jsonencode({
+    deadLetterTargetArn = aws_sqs_queue.dlq.arn
+    maxReceiveCount     = var.max_receive_count
+  })
+}

infrastructure/terraform/modules/sqs_queue/outputs.tf

@@ -0,0 +1,7 @@
+output "queue_arn" {
+  value = aws_sqs_queue.this.arn
+}
+
+output "queue_url" {
+  value = aws_sqs_queue.this.url
+}

infrastructure/terraform/modules/sqs_queue/variables.tf

@@ -0,0 +1,6 @@
+variable "name" { type = string }
+
+variable "max_receive_count" {
+  type    = number
+  default = 5
+}

infrastructure/terraform/modules/tf_state_bucket/main.tf

@@ -0,0 +1,30 @@
+resource "aws_s3_bucket" "this" {
+  bucket = var.bucket_name
+}
+
+resource "aws_s3_bucket_versioning" "this" {
+  bucket = aws_s3_bucket.this.id
+
+  versioning_configuration {
+    status = "Enabled"
+  }
+}
+
+resource "aws_s3_bucket_server_side_encryption_configuration" "this" {
+  bucket = aws_s3_bucket.this.id
+
+  rule {
+    apply_server_side_encryption_by_default {
+      sse_algorithm = "AES256"
+    }
+  }
+}
+
+resource "aws_s3_bucket_public_access_block" "this" {
+  bucket = aws_s3_bucket.this.id
+
+  block_public_acls       = true
+  block_public_policy     = true
+  ignore_public_acls      = true
+  restrict_public_buckets = true
+}

infrastructure/terraform/modules/tf_state_bucket/outputs.tf

@@ -0,0 +1,7 @@
+output "bucket_name" {
+  value = aws_s3_bucket.this.bucket
+}
+
+output "bucket_arn" {
+  value = aws_s3_bucket.this.arn
+}

infrastructure/terraform/modules/tf_state_bucket/variables.tf

@@ -0,0 +1,3 @@
+variable "bucket_name" {
+  type = string
+}

infrastructure/terraform/shared/dev.tfvars

@@ -1,5 +1,4 @@
 stage = "dev"
-profile = "DevAdmin"
 region = "eu-west-2"
 
 # Domain

infrastructure/terraform/shared/main.tf

@@ -8,7 +8,6 @@ terraform {
   backend "s3" {
     bucket  = "assessment-model-terraform-state"
     region  = "eu-west-2"
-    profile = "DevAdmin"
     key     = "terraform.tfstate"
   }
 
@@ -16,7 +15,6 @@ terraform {
 }
 
 provider "aws" {
-  profile = var.profile
   region  = var.region
 }
 
@@ -91,101 +89,101 @@ resource "aws_db_instance" "default" {
 
 # Set up the bucket that recieve the csv uploads of epc to be retrofit
 module "s3_presignable_bucket" {
-  source          = "./modules/s3_presignable_bucket"
+  source          = "../modules/s3_presignable_bucket"
   bucketname      = "retrofit-plan-inputs-${var.stage}"
   environment     = var.stage
   allowed_origins = var.allowed_origins
 }
 
 module "s3_due_considerations_bucket" {
-  source          = "./modules/s3_presignable_bucket"
+  source          = "../modules/s3_presignable_bucket"
   bucketname      = "retrofit-due-considerations-${var.stage}"
   environment     = var.stage
   allowed_origins = var.allowed_origins
 }
 
 module "s3_eco_spreadseet_bucket" {
-  source          = "./modules/s3_presignable_bucket"
+  source          = "../modules/s3_presignable_bucket"
   bucketname      = "retrofit-eco-spreadsheet-${var.stage}"
   environment     = var.stage
   allowed_origins = var.allowed_origins
 }
 
 module "s3" {
-  source          = "./modules/s3"
+  source          = "../modules/s3"
   bucketname      = "retrofit-datalake-${var.stage}"
   allowed_origins = var.allowed_origins
 }
 
 module "model_directory" {
-  source          = "./modules/s3"
+  source          = "../modules/s3"
   bucketname      = "retrofit-model-directory-${var.stage}"
   allowed_origins = var.allowed_origins
 }
 
 module "retrofit_sap_predictions" {
-  source          = "./modules/s3"
+  source          = "../modules/s3"
   bucketname      = "retrofit-sap-predictions-${var.stage}"
   allowed_origins = var.allowed_origins
 }
 
 module "retrofit_sap_data" {
-  source          = "./modules/s3"
+  source          = "../modules/s3"
   bucketname      = "retrofit-data-${var.stage}"
   allowed_origins = var.allowed_origins
 }
 
 module "retrofit_carbon_predictions" {
-  source          = "./modules/s3"
+  source          = "../modules/s3"
   bucketname      = "retrofit-carbon-predictions-${var.stage}"
   allowed_origins = var.allowed_origins
 }
 
 module "retrofit_heat_predictions" {
-  source          = "./modules/s3"
+  source          = "../modules/s3"
   bucketname      = "retrofit-heat-predictions-${var.stage}"
   allowed_origins = var.allowed_origins
 }
 
 module "retrofit_lighting_cost_predictions" {
-  source          = "./modules/s3"
+  source          = "../modules/s3"
   bucketname      = "retrofit-lighting-cost-predictions-${var.stage}"
   allowed_origins = var.allowed_origins
 }
 
 module "retrofit_heating_cost_predictions" {
-  source          = "./modules/s3"
+  source          = "../modules/s3"
   bucketname      = "retrofit-heating-cost-predictions-${var.stage}"
   allowed_origins = var.allowed_origins
 }
 
 module "retrofit_hot_water_cost_predictions" {
-  source          = "./modules/s3"
+  source          = "../modules/s3"
   bucketname      = "retrofit-hot-water-cost-predictions-${var.stage}"
   allowed_origins = var.allowed_origins
 }
 
 module "retrofit_heating_kwh_predictions" {
-  source          = "./modules/s3"
+  source          = "../modules/s3"
   bucketname      = "retrofit-heating-kwh-predictions-${var.stage}"
   allowed_origins = var.allowed_origins
 }
 
 module "retrofit_hotwater_kwh_predictions" {
-  source          = "./modules/s3"
+  source          = "../modules/s3"
   bucketname      = "retrofit-hotwater-kwh-predictions-${var.stage}"
   allowed_origins = var.allowed_origins
 }
 
 module "retrofit_sap_baseline_predictions" {
-  source          = "./modules/s3"
+  source          = "../modules/s3"
   bucketname      = "retrofit-sap-baseline-predictions-${var.stage}"
   allowed_origins = var.allowed_origins
 }
 
 // We make this bucket presignable, because we want to generate download links for the frontend
 module "retrofit_energy_assessments" {
-  source          = "./modules/s3_presignable_bucket"
+  source          = "../modules/s3_presignable_bucket"
   bucketname      = "retrofit-energy-assessments-${var.stage}"
   allowed_origins = var.allowed_origins
   environment     = var.stage
@@ -193,7 +191,7 @@ module "retrofit_energy_assessments" {
 
 # Set up the route53 record for the API
 module "route53" {
-  source         = "./modules/route53"
+  source         = "../modules/route53"
   domain_name    = var.domain_name
   api_url_prefix = var.api_url_prefix
   providers = {
@@ -201,75 +199,76 @@ module "route53" {
   }
 }
 
+
 # Create an ECR repository for storage of the lambda's docker images
 module "ecr" {
   ecr_name = "fastapi-repository-${var.stage}"
-  source   = "./modules/ecr"
+  source   = "../modules/ecr"
 }
 
 module "lambda_sap_prediction_ecr" {
   ecr_name = "lambda-sap-prediction-${var.stage}"
-  source   = "./modules/ecr"
+  source   = "../modules/ecr"
 }
 
 module "due_considerations_ecr" {
   ecr_name = "due-considerations-${var.stage}"
-  source   = "./modules/ecr"
+  source   = "../modules/ecr"
 }
 
 module "eco_spreadsheet_ecr" {
   ecr_name = "eco-spreadsheet-${var.stage}"
-  source   = "./modules/ecr"
+  source   = "../modules/ecr"
 }
 
 module "lambda_carbon_prediction_ecr" {
   ecr_name = "lambda-carbon-prediction-${var.stage}"
-  source   = "./modules/ecr"
+  source   = "../modules/ecr"
 }
 
 module "lambda_heat_prediction_ecr" {
   ecr_name = "lambda-heat-prediction-${var.stage}"
-  source   = "./modules/ecr"
+  source   = "../modules/ecr"
 }
 
 # ECR repos for lighting cost, heating cost and hot water cost models
 module "lambda_lighting_cost_prediction_ecr" {
   ecr_name = "lighting-cost-prediction-${var.stage}"
-  source   = "./modules/ecr"
+  source   = "../modules/ecr"
 }
 
 module "lambda_heating_cost_prediction_ecr" {
   ecr_name = "heating-cost-prediction-${var.stage}"
-  source   = "./modules/ecr"
+  source   = "../modules/ecr"
 }
 
 module "lambda_hot_water_cost_prediction_ecr" {
   ecr_name = "hot-water-cost-prediction-${var.stage}"
-  source   = "./modules/ecr"
+  source   = "../modules/ecr"
 }
 
 # For heating and hot water kwh models
 module "lambda_heating_kwh_prediction_ecr" {
   ecr_name = "heating-kwh-prediction-${var.stage}"
-  source   = "./modules/ecr"
+  source   = "../modules/ecr"
 }
 
 module "lambda_hotwater_kwh_prediction_ecr" {
   ecr_name = "hotwater-kwh-prediction-${var.stage}"
-  source   = "./modules/ecr"
+  source   = "../modules/ecr"
 }
 
 # Baselining models
 module "sap_baseline_ecr" {
   ecr_name = "sap-baseline-prediction-${var.stage}"
-  source   = "./modules/ecr"
+  source   = "../modules/ecr"
 }
 
 ##############################################
 # CDN - Cloudfront
 ##############################################
 module "cloudfront_distribution" {
-  source             = "./modules/cloudfront"
+  source             = "../modules/cloudfront"
   bucket_name        = module.s3.bucket_name
   bucket_id          = module.s3.bucket_id
   bucket_arn         = module.s3.bucket_arn
@@ -281,11 +280,35 @@ module "cloudfront_distribution" {
 # SES - Email sending
 ################################################
 module "ses" {
-  source      = "./modules/ses"
+  source      = "../modules/ses"
   domain_name = "domna.homes"
   stage       = var.stage
 }
 
 output "ses_dns_records" {
   value = module.ses.dns_records
+}
+
+################################################
+# Address2UPRN – Lambda ECR
+################################################
+module "address2uprn_state_bucket" {
+  source      = "../modules/tf_state_bucket"
+  bucket_name = "address2uprn-terraform-state"
+
+}
+
+output "address2uprn_state_bucket_name" {
+  value = module.address2uprn_state_bucket.bucket_name
+}
+
+module "address2uprn_registry" {
+  source = "../modules/container_registry"
+  name   = "address2uprn"
+  stage = var.stage
+
+}
+
+output "address2uprn_repository_url" {
+  value = module.address2uprn_registry.repository_url
 }

infrastructure/terraform/shared/variables.tf

@@ -3,11 +3,6 @@ variable stage {
   type        = string
 }
 
-variable "profile" {
-  description = "AWS profile to use"
-  type        = string
-}
-
 variable "region" {
   description = "AWS region"
   type        = string

sfr/principal_pitch/2_export_data.py

@@ -7,20 +7,29 @@ import numpy as np
 from backend.app.utils import sap_to_epc
 from sqlalchemy.orm import sessionmaker
 from backend.app.db.connection import db_engine, db_read_session
-from backend.app.db.models.recommendations import Recommendation, Plan, PlanRecommendations, RecommendationMaterials
-from backend.app.db.models.portfolio import PropertyModel, PropertyDetailsEpcModel, PropertyDetailsSpatial
+from backend.app.db.models.recommendations import (
+    Recommendation,
+    Plan,
+    PlanRecommendations,
+    RecommendationMaterials,
+)
+from backend.app.db.models.portfolio import (
+    PropertyModel,
+    PropertyDetailsEpcModel,
+    PropertyDetailsSpatial,
+)
 from backend.app.db.functions.materials_functions import get_materials
 from collections import defaultdict
 from sqlalchemy import func
 
 # PORTFOLIO_ID = 206
 # SCENARIOS = [389]
-PORTFOLIO_ID = 485  # Peabody
+PORTFOLIO_ID = 502  # Peabody
 SCENARIOS = [
-    970,
+    986,
 ]
 scenario_names = {
-    970: "EPC C - No solid floor, EQI, IWI",
+    986: "EPC C",
 }
 
 
@@ -31,22 +40,26 @@ def get_data(portfolio_id, scenario_ids):
     # --------------------
     # Properties
     # --------------------
-    properties_query = session.query(
-        PropertyModel,
-        PropertyDetailsEpcModel
-    ).join(
-        PropertyDetailsEpcModel,
-        PropertyModel.id == PropertyDetailsEpcModel.property_id
-    ).filter(
-        PropertyModel.portfolio_id == portfolio_id
-    ).all()
+    properties_query = (
+        session.query(PropertyModel, PropertyDetailsEpcModel)
+        .join(
+            PropertyDetailsEpcModel,
+            PropertyModel.id == PropertyDetailsEpcModel.property_id,
+        )
+        .filter(PropertyModel.portfolio_id == portfolio_id)
+        .all()
+    )
 
     properties_data = [
         {
-            **{col.name: getattr(p.PropertyModel, col.name)
-               for col in PropertyModel.__table__.columns},
-            **{col.name: getattr(p.PropertyDetailsEpcModel, col.name)
-               for col in PropertyDetailsEpcModel.__table__.columns},
+            **{
+                col.name: getattr(p.PropertyModel, col.name)
+                for col in PropertyModel.__table__.columns
+            },
+            **{
+                col.name: getattr(p.PropertyDetailsEpcModel, col.name)
+                for col in PropertyDetailsEpcModel.__table__.columns
+            },
         }
         for p in properties_query
     ]
@@ -58,13 +71,10 @@ def get_data(portfolio_id, scenario_ids):
         session.query(
             Plan.scenario_id,
             Plan.property_id,
-            func.max(Plan.created_at).label("latest_created_at")
+            func.max(Plan.created_at).label("latest_created_at"),
         )
         .filter(Plan.scenario_id.in_(scenario_ids))
-        .group_by(
-            Plan.scenario_id,
-            Plan.property_id
-        )
+        .group_by(Plan.scenario_id, Plan.property_id)
         .subquery()
     )
 
@@ -76,9 +86,9 @@ def get_data(portfolio_id, scenario_ids):
         session.query(Plan)
         .join(
             latest_plans_subq,
-            (Plan.scenario_id == latest_plans_subq.c.scenario_id) &
-            (Plan.property_id == latest_plans_subq.c.property_id) &
-            (Plan.created_at == latest_plans_subq.c.latest_created_at)
+            (Plan.scenario_id == latest_plans_subq.c.scenario_id)
+            & (Plan.property_id == latest_plans_subq.c.property_id)
+            & (Plan.created_at == latest_plans_subq.c.latest_created_at),
         )
         .all()
     )
@@ -103,28 +113,29 @@ def get_data(portfolio_id, scenario_ids):
     # --------------------
     # Recommendations (NO materials yet)
     # --------------------
-    recommendations_query = session.query(
-        Recommendation,
-        Plan.scenario_id,
-        PlanRecommendations.plan_id
-    ).join(
-        PlanRecommendations,
-        Recommendation.id == PlanRecommendations.recommendation_id
-    ).join(
-        Plan,
-        Plan.id == PlanRecommendations.plan_id
-    ).filter(
-        PlanRecommendations.plan_id.in_(plan_ids),
-        Recommendation.default.is_(True),
-        Recommendation.already_installed.is_(False)
-    ).all()
+    recommendations_query = (
+        session.query(Recommendation, Plan.scenario_id, PlanRecommendations.plan_id)
+        .join(
+            PlanRecommendations,
+            Recommendation.id == PlanRecommendations.recommendation_id,
+        )
+        .join(Plan, Plan.id == PlanRecommendations.plan_id)
+        .filter(
+            PlanRecommendations.plan_id.in_(plan_ids),
+            Recommendation.default.is_(True),
+            Recommendation.already_installed.is_(False),
+        )
+        .all()
+    )
 
     recommendations_data = [
         {
-            **{col.name: getattr(r.Recommendation, col.name)
-               for col in Recommendation.__table__.columns},
+            **{
+                col.name: getattr(r.Recommendation, col.name)
+                for col in Recommendation.__table__.columns
+            },
             "scenario_id": r.scenario_id,
-            "materials": []  # placeholder
+            "materials": [],  # placeholder
         }
         for r in recommendations_query
     ]
@@ -134,23 +145,25 @@ def get_data(portfolio_id, scenario_ids):
     # --------------------
     # Recommendation materials (SEPARATE QUERY)
     # --------------------
-    materials_query = session.query(
-        RecommendationMaterials
-    ).filter(
-        RecommendationMaterials.recommendation_id.in_(recommendation_ids)
-    ).all()
+    materials_query = (
+        session.query(RecommendationMaterials)
+        .filter(RecommendationMaterials.recommendation_id.in_(recommendation_ids))
+        .all()
+    )
 
     # Group materials by recommendation_id
     materials_by_recommendation = defaultdict(list)
 
     for m in materials_query:
-        materials_by_recommendation[m.recommendation_id].append({
-            "material_id": m.material_id,
-            "depth": m.depth,
-            "quantity": m.quantity,
-            "quantity_unit": m.quantity_unit,
-            "estimated_cost": m.estimated_cost,
-        })
+        materials_by_recommendation[m.recommendation_id].append(
+            {
+                "material_id": m.material_id,
+                "depth": m.depth,
+                "quantity": m.quantity,
+                "quantity_unit": m.quantity_unit,
+                "estimated_cost": m.estimated_cost,
+            }
+        )
 
     # Attach materials safely (no filtering side effects)
     for r in recommendations_data:
@@ -161,7 +174,9 @@ def get_data(portfolio_id, scenario_ids):
     return properties_data, plans_data, recommendations_data
 
 
-properties_data, plans_data, recommendations_data = get_data(portfolio_id=PORTFOLIO_ID, scenario_ids=SCENARIOS)
+properties_data, plans_data, recommendations_data = get_data(
+    portfolio_id=PORTFOLIO_ID, scenario_ids=SCENARIOS
+)
 
 properties_df = pd.DataFrame(properties_data)
 plans_df = pd.DataFrame(plans_data)
@@ -172,10 +187,8 @@ with db_read_session() as session:
 
 materials = pd.DataFrame(materials)
 
-material_lookup = (
-    materials
-    .set_index("id")[["type", "includes_battery"]]
-    .to_dict("index")
+material_lookup = materials.set_index("id")[["type", "includes_battery"]].to_dict(
+    "index"
 )
 
 
@@ -189,14 +202,14 @@ def has_solar_with_battery(materials_list):
     return False
 
 
-recommendations_df["has_solar_with_battery"] = (
-    recommendations_df["materials"].apply(has_solar_with_battery)
+recommendations_df["has_solar_with_battery"] = recommendations_df["materials"].apply(
+    has_solar_with_battery
 )
 
 recommendations_df["measure_type"] = np.where(
     recommendations_df["has_solar_with_battery"] == True,
     recommendations_df["measure_type"] + "_with_battery",
-    recommendations_df["measure_type"]
+    recommendations_df["measure_type"],
 )
 
 # Adjust material type to indicate if there is a battery included
@@ -211,50 +224,67 @@ from utils.s3 import read_csv_from_s3, read_excel_from_s3
 
 for scenario_id in SCENARIOS:
     # Get recs for this scenario
-    recommended_measures_df = recommendations_df[recommendations_df["scenario_id"] == scenario_id][
-        ["property_id", "measure_type", "estimated_cost", "default"]
+    recommended_measures_df = recommendations_df[
+        recommendations_df["scenario_id"] == scenario_id
+    ][["property_id", "measure_type", "estimated_cost", "default"]]
+    recommended_measures_df = recommended_measures_df[
+        recommended_measures_df["default"]
     ]
-    recommended_measures_df = recommended_measures_df[recommended_measures_df["default"]]
     recommended_measures_df = recommended_measures_df.drop(columns=["default"])
 
-    post_install_sap = recommendations_df[recommendations_df["scenario_id"] == scenario_id][
-        ["property_id", "default", "sap_points"]]
+    post_install_sap = recommendations_df[
+        recommendations_df["scenario_id"] == scenario_id
+    ][["property_id", "default", "sap_points"]]
     post_install_sap = post_install_sap[post_install_sap["default"]]
     # Sum up the sap points by property id
-    post_install_sap = post_install_sap.groupby(["property_id"])[["sap_points"]].sum().reset_index()
+    post_install_sap = (
+        post_install_sap.groupby(["property_id"])[["sap_points"]].sum().reset_index()
+    )
 
     # Find dupes by property id and measure type
-    dupes = recommended_measures_df.duplicated(subset=["property_id", "measure_type"], keep=False)
+    dupes = recommended_measures_df.duplicated(
+        subset=["property_id", "measure_type"], keep=False
+    )
     dupe_df = recommended_measures_df[dupes]
 
     if dupe_df.shape:
         # Drop dupes - happened due to a funny bug
         recommended_measures_df = recommended_measures_df.drop_duplicates(
-            subset=["property_id", "measure_type"], keep='first'
+            subset=["property_id", "measure_type"], keep="first"
         )
 
     recommendations_measures_pivot = recommended_measures_df.pivot(
-        index='property_id',
-        columns='measure_type',
-        values='estimated_cost'
+        index="property_id", columns="measure_type", values="estimated_cost"
     )
     recommendations_measures_pivot = recommendations_measures_pivot.reset_index()
 
     # Total cost is the row sum, excluding the property_id column
-    recommendations_measures_pivot["total_retrofit_cost"] = recommendations_measures_pivot.drop(
-        columns=["property_id"]
-    ).sum(axis=1)
+    recommendations_measures_pivot["total_retrofit_cost"] = (
+        recommendations_measures_pivot.drop(columns=["property_id"]).sum(axis=1)
+    )
 
-    df = properties_df[
-        [
-            "landlord_property_id", "property_id", "uprn", "address", "postcode", "property_type", "walls", "roof",
-            "heating", "windows", "current_epc_rating", "current_sap_points", "total_floor_area", "number_of_rooms",
-            "id"
+    df = (
+        properties_df[
+            [
+                "landlord_property_id",
+                "property_id",
+                "uprn",
+                "address",
+                "postcode",
+                "property_type",
+                "walls",
+                "roof",
+                "heating",
+                "windows",
+                "current_epc_rating",
+                "current_sap_points",
+                "total_floor_area",
+                "number_of_rooms",
+                "id",
+            ]
         ]
-    ].merge(
-        recommendations_measures_pivot, how="left", on="property_id"
-    ).merge(
-        post_install_sap, how="left", on="property_id"
+        .merge(recommendations_measures_pivot, how="left", on="property_id")
+        .merge(post_install_sap, how="left", on="property_id")
     )
 
     # df = df.drop(columns=["property_id"])
@@ -262,21 +292,25 @@ for scenario_id in SCENARIOS:
 
     df["predicted_post_works_sap"] = df["current_sap_points"] + df["sap_points"]
     df["predicted_post_works_sap"] = df["predicted_post_works_sap"]
-    df["predicted_post_works_epc"] = df["predicted_post_works_sap"].apply(lambda x: sap_to_epc(x))
+    df["predicted_post_works_epc"] = df["predicted_post_works_sap"].apply(
+        lambda x: sap_to_epc(x)
+    )
     df["uprn"] = df["uprn"].astype(str)
 
     relevant_plans = plans_df[plans_df["scenario_id"] == scenario_id]
     df2 = df.merge(
-        relevant_plans[["property_id", "post_sap_points", "post_epc_rating"]], how="left", on="property_id",
-        suffixes=("", "_plan")
+        relevant_plans[["property_id", "post_sap_points", "post_epc_rating"]],
+        how="left",
+        on="property_id",
+        suffixes=("", "_plan"),
     )
     print(df2["predicted_post_works_epc"].value_counts())
     print(df2["post_epc_rating"].value_counts())
 
     z = df2[
-        (df2["predicted_post_works_epc"] != "D") &
-        (df2["post_epc_rating"].astype(str) == "Epc.D")
-        ]
+        (df2["predicted_post_works_epc"] != "D")
+        & (df2["post_epc_rating"].astype(str) == "Epc.D")
+    ]
 
     df2["predicted_post_works_epc"].value_counts()
     df2["post_epc_rating"].astype(str).value_counts()
@@ -291,189 +325,6 @@ for scenario_id in SCENARIOS:
     df[df["predicted_post_works_sap"] == ""]
 
     # Create excel to store to
-<<<<<<< HEAD
-    filename = (f"{scenario_names[scenario_id]} - 20250113 final.xlsx")
+    filename = f"{scenario_names[scenario_id]} - 20250113 final.xlsx"
     with pd.ExcelWriter(filename) as writer:
         df.to_excel(writer, sheet_name="properties", index=False)
-=======
-    filename = ("/Users/khalimconn-kowlessar/Documents/hestia/Customers/Peabody/Nov 2025 Consulting "
-                f"Project/Final SAL/scenarios/{scenario_names[scenario_id]} - 20250114 final.xlsx")
-    with pd.ExcelWriter(filename) as writer:
-        df.to_excel(writer, sheet_name="properties", index=False)
-
-
-# asset_list = pd.DataFrame(asset_list)
-# asset_list = asset_list.rename(
-#     columns={
-#         "postcode": "domna_postcode"
-#     }
-# )
-# if "domna_full_address":
-#     # For Peabody
-#     asset_list["domna_full_address"] = asset_list["domna_address_1"]
-#
-# asset_list = asset_list[["domna_full_address", "domna_postcode", "epc_os_uprn", ]].copy()
-# asset_list = asset_list.rename(columns={"epc_os_uprn": "uprn"})
-# asset_list["uprn"] = asset_list["uprn"].astype("Int64").astype(str)
-# asset_list = asset_list.merge(
-#     df.drop(columns=["address", "postcode", "property_type", "total_floor_area"]),
-#     how="left",
-#     on="uprn"
-# )
-
-
-# Get conservation area data from property details spatial. based on the UPRNs
-def get_conservation_area_data(uprns):
-    session = sessionmaker(bind=db_engine)()
-    session.begin()
-
-    # Query to get conservation area data
-    spatial_query = session.query(
-        PropertyDetailsSpatial
-    ).filter(
-        PropertyDetailsSpatial.uprn.in_(uprns)  # Filter by UPRNs
-    ).all()
-
-    # Transform spatial data to include all fields dynamically
-    spatial_data = [
-        {col.name: getattr(spatial, col.name) for col in PropertyDetailsSpatial.__table__.columns}
-        for spatial in spatial_query
-    ]
-
-    session.close()
-    return pd.DataFrame(spatial_data)
-
-
-uprns = asset_list[
-    ~pd.isna(asset_list["uprn"]) & (asset_list["uprn"] != "<NA>")
-    ]["uprn"].astype(int).unique().tolist()
-conservation_area_data = get_conservation_area_data(uprns)
-conservation_area_data["uprn"] = conservation_area_data["uprn"].astype(str)
-asset_list = asset_list.merge(
-    conservation_area_data[["uprn", "conservation_status", "is_listed_building", "is_heritage_building"]],
-    how="left",
-    on="uprn"
-)
-
-# For exporting
-df.to_excel(
-    "/Users/khalimconn-kowlessar/Documents/hestia/Customers/Lincs Rural/EPC C -without floors proposed measures - "
-    "with ID.xlsx",
-    index=False
-)
-# asset_list.to_excel(
-#     "/Users/khalimconn-kowlessar/Documents/hestia/Customers/Lincs Rural/epc_measures.xlsx",
-#     index=False
-# )
-
-condition_costs = pd.read_excel(
-    "/Users/khalimconn-kowlessar/Documents/hestia/sfr/Spring JV/Condition costs.xlsx",
-    sheet_name="Prices - Khalim",
-    header=35
-)
-# Remove unnamed columns and reset index
-condition_costs = condition_costs.loc[:, ~condition_costs.columns.str.contains('^Unnamed')]
-condition_costs = condition_costs.reset_index(drop=True)
-
-
-# We now estimate condition cost
-def simulate_condition(asset_list, condition_costs):
-    """
-    This function is for testing, and will simulate condition cost from 1-10 for each property to see what the
-    costing array looks like.
-    :param df:
-    :return:
-    """
-
-    condition_df = []
-    for _, row in asset_list.iterrows():
-
-        n_bathrooms = row["bathrooms"]
-
-        conditions = {}
-        for condition in reversed(range(1, 11)):
-            condition_cost = condition_costs[
-                condition_costs["Condition"] == condition
-                ].drop(columns=["Condition"]).iloc[0]
-
-            # Each cost is scaled by floor area
-            condition_cost = condition_cost * row["total_floor_area"]
-            condition_cost["Bathroom"] = condition_cost["Bathroom"] * n_bathrooms
-
-            total_condition_cost = condition_cost.sum()
-            conditions["Condition " + str(condition)] = (total_condition_cost)
-
-        condition_df.append(
-            {
-                "uprn": row["uprn"],
-                **conditions
-            }
-        )
-
-    condition_df = pd.DataFrame(condition_df)
-
-    asset_list = asset_list.merge(
-        condition_df,
-        how="left",
-        on="uprn"
-    )
-
-    return asset_list
-
-
-# asset_list = simulate_condition(asset_list, condition_costs)
-
-# We calculate the condition cost based on the condition
-for _, row in asset_list.iterrows():
-
-    condition = row["condition_score"]
-    if condition in [None, ""]:
-        continue
-    condition = int(float(condition))
-
-    condition_cost = condition_costs[
-        condition_costs["Condition"] == condition
-        ].drop(columns=["Condition"]).iloc[0]
-
-    # Each cost is scaled by floor area
-    condition_cost = condition_cost * float(row["total_floor_area"])
-    n_bathrooms = row["n_bathrooms"]
-    condition_cost["Bathroom"] = condition_cost["Bathroom"] * float(n_bathrooms)
-
-    total_condition_cost = condition_cost.sum()
-    asset_list.loc[asset_list["uprn"] == row["uprn"], "domna_condition_cost"] = total_condition_cost
-
-# Store output
-asset_list.to_excel(
-    "/Users/khalimconn-kowlessar/Documents/hestia/sfr/Spring JV/20250624_portfolio_retrofit_packages.xlsx",
-    index=False
-)
-
-condition_cost_comparison = asset_list[
-    ["condition_score", "decoration_sum_min ", "decoration_sum_max", "domna_condition_cost"]
-]
-
-# Testing
-plans_df.head()
-
-example = pd.read_excel(
-    "/Users/khalimconn-kowlessar/Documents/hestia/Customers/Peabody/Nov 2025 Consulting Project/Final "
-    "SAL/scenarios/EPC C - no solid floor, no EWI or IWI, ashp 3.0 - 20250114 final.xlsx"
-)
-
-plans_df2 = plans_df.merge(
-    properties_df[["property_id", "landlord_property_id"]],
-    left_on="property_id",
-    right_on="property_id",
-    how="left"
-)
-
-plans_df2 = plans_df2[plans_df2["scenario_id"] == 909]
-
-dupes = plans_df2[plans_df2["property_id"].duplicated()]
-
-# merge on plans
-example = example.merge(
-    plans_df, how="left",
-)
->>>>>>> 3874da6177cbcc37f7a488bec0a06e387906653c