Merge branch 'main' into anchor-sal

.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

.github/workflows/_build_image.yml

@@ -13,6 +13,9 @@ on:
         required: false
         default: "."
         type: string
+      build_args:
+        required: false
+        type: string
 
     outputs:
       image_digest:
@@ -29,11 +32,22 @@ on:
         required: true
       AWS_REGION:
         required: true
+      DEV_DB_HOST:
+        required: false
+      DEV_DB_PORT:
+        required: false
+      DEV_DB_NAME:
+        required: false
 
 jobs:
   build:
     runs-on: ubuntu-latest
 
+    env:
+      DEV_DB_HOST: ${{ secrets.DEV_DB_HOST }}
+      DEV_DB_PORT: ${{ secrets.DEV_DB_PORT }}
+      DEV_DB_NAME: ${{ secrets.DEV_DB_NAME }}
+
     outputs:
       image_digest: ${{ steps.digest.outputs.image_digest }}
       ecr_repo_url: ${{ steps.repo.outputs.ecr_repo_url }}
@@ -64,7 +78,22 @@ jobs:
       - name: Build & push image
         run: |
           IMAGE_URI="${{ steps.repo.outputs.ecr_repo_url }}:${GITHUB_SHA}"
-          docker build -f ${{ inputs.dockerfile_path }} -t $IMAGE_URI ${{ inputs.build_context }}
+
+          # Writes build args and removes line breaks
+          BUILD_ARGS=""
+          while IFS= read -r line; do
+            # skip empty lines
+            [ -n "$line" ] || continue
+            temp=$(eval echo "$line")
+            BUILD_ARGS="$BUILD_ARGS --build-arg $temp"
+          done <<< "${{ inputs.build_args }}"
+          
+          docker build \
+            -f ${{ inputs.dockerfile_path }} \
+            $BUILD_ARGS \
+            -t $IMAGE_URI \
+            ${{ inputs.build_context }}
+      
           docker push $IMAGE_URI
 
       - name: Resolve image digest

.github/workflows/deploy_terraform.yml

@@ -16,6 +16,7 @@ jobs:
         id: set-stage
         shell: bash
         run: |
+          env
           BRANCH="${GITHUB_REF_NAME}"
 
           if [[ "$BRANCH" == "prod" ]]; then
@@ -73,8 +74,8 @@ jobs:
     uses: ./.github/workflows/_build_image.yml
     with:
       ecr_repo: address2uprn-${{ needs.determine_stage.outputs.stage }}
-      dockerfile_path: backend/address2UPRN/Dockerfile
+      dockerfile_path: backend/address2UPRN/handler/Dockerfile
-      build_context: backend/address2UPRN
+      build_context: .
     secrets:
       AWS_ACCESS_KEY_ID: ${{ secrets.DEV_AWS_ACCESS_KEY_ID }}
       AWS_SECRET_ACCESS_KEY: ${{ secrets.DEV_AWS_SECRET_ACCESS_KEY }}
@@ -96,3 +97,76 @@ jobs:
       AWS_ACCESS_KEY_ID: ${{ secrets.DEV_AWS_ACCESS_KEY_ID }}
       AWS_SECRET_ACCESS_KEY: ${{ secrets.DEV_AWS_SECRET_ACCESS_KEY }}
       AWS_REGION: ${{ secrets.DEV_AWS_REGION }}
+
+
+  # ============================================================
+  # 2️⃣ Build Postcode Splitter image and Push
+  # ============================================================
+  postcodeSplitter_image:
+    needs: [determine_stage, shared_terraform]
+    uses: ./.github/workflows/_build_image.yml
+    with:
+      ecr_repo: postcode_splitter-${{ needs.determine_stage.outputs.stage }}
+      dockerfile_path: backend/postcode_splitter/handler/Dockerfile
+      build_context: .
+    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 }}
+
+  # ============================================================
+  # 3️⃣ Deploy Postcode Splitter Lambda
+  # ============================================================
+  postcodeSplitter_lambda:
+    needs: [postcodeSplitter_image, determine_stage]
+    uses: ./.github/workflows/_deploy_lambda.yml
+    with:
+      lambda_name: postcodeSplitter
+      lambda_path: infrastructure/terraform/lambda/postcodeSplitter
+      stage: ${{ needs.determine_stage.outputs.stage }}
+      ecr_repo: postcode_splitter-${{ needs.determine_stage.outputs.stage }}
+      image_digest: ${{ needs.postcodeSplitter_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: ${{ secrets.DEV_AWS_REGION }}
+
+  # ============================================================
+  # Condition ETL image and Push
+  # ============================================================
+  condition_etl_image:
+    needs: [determine_stage, shared_terraform]
+    uses: ./.github/workflows/_build_image.yml
+    with:
+      ecr_repo: condition-etl-${{ needs.determine_stage.outputs.stage }}
+      dockerfile_path: backend/condition/handler/Dockerfile
+      build_context: .
+      build_args: |
+        DEV_DB_HOST=$DEV_DB_HOST
+        DEV_DB_PORT=$DEV_DB_PORT
+        DEV_DB_NAME=$DEV_DB_NAME
+    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 }}
+      DEV_DB_HOST: ${{ secrets.DEV_DB_HOST }}
+      DEV_DB_PORT: ${{ secrets.DEV_DB_PORT }}
+      DEV_DB_NAME: ${{ secrets.DEV_DB_NAME }}
+
+  # ============================================================
+  # Deploy Condition ETL Lambda
+  # ============================================================
+  condition_etl_lambda:
+    needs: [condition_etl_image, determine_stage]
+    uses: ./.github/workflows/_deploy_lambda.yml
+    with:
+      lambda_name: condition-etl
+      lambda_path: infrastructure/terraform/lambda/condition-etl
+      stage: ${{ needs.determine_stage.outputs.stage }}
+      ecr_repo: condition-etl-${{ needs.determine_stage.outputs.stage }}
+      image_digest: ${{ needs.condition_etl_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

@@ -69,14 +69,51 @@ def app():
     Property UPRN
     """
 
-    data_folder = "/workspaces/home/Downloads"
+    data_folder = "/Users/khalimconn-kowlessar/Documents/hestia/Customers/Aspire"
-    data_filename = "Anchor 1.xlsx"
+    data_filename = "ASPIRE ASSET LIST.xlsx"
+    sheet_name = "Asset List"
+    postcode_column = "Postcode"
+    address1_column = None
+    address1_method = "house_number_extraction"
+    fulladdress_column = "Address"
+    address_cols_to_concat = []
+    missing_postcodes_method = None
+    landlord_year_built = None
+    landlord_os_uprn = None
+    landlord_property_type = "Property Type"
+    landlord_built_form = None
+    landlord_wall_construction = None
+    landlord_roof_construction = None
+    landlord_heating_system = None
+    landlord_existing_pv = None
+    landlord_property_id = "LLUPRN"
+    landlord_sap = None
+    outcomes_filename = None
+    outcomes_sheetname = None
+    outcomes_postcode = None
+    outcomes_houseno = None
+    outcomes_id = None
+    outcomes_address = None
+    master_filepaths = []
+    master_id_colnames = []
+    master_to_asset_list_filepath = None
+    phase = False
+    ecosurv_landlords = None
+    asset_list_header = 0
+    landlord_block_reference = None
+
+    # Peabody data for cleaning
+    data_folder = (
+        "/Users/khalimconn-kowlessar/Documents/hestia/Customers/Peabody/Nov 2025 Consulting "
+        "Project/data_validation"
+    )
+    data_filename = "to_standardise_uprns.xlsx"
     sheet_name = "Sheet1"
     postcode_column = "Postcode"
-    address1_column = "House Number"
+    address1_column = None
-    address1_method = None
+    address1_method = "house_number_extraction"
-    fulladdress_column = None
+    fulladdress_column = "Address"
-    address_cols_to_concat = ["House Number", "Address Line 1", "Address Line 2"]
+    address_cols_to_concat = None
     missing_postcodes_method = None
     landlord_year_built = None
     landlord_os_uprn = None

asset_list/mappings/built_form.py

@@ -520,4 +520,14 @@ BUILT_FORM_MAPPINGS = {
     '2.EXT.WALL FLAT': 'mid-terrace',
     '2 EXT. WALL FLAT': 'mid-terrace',
 
+    'Maisonette: Detached: Ground Floor': 'detached',
+    'Maisonette: Enclosed End Terrace: Top Floor': 'enclosed end-terrace',
+    'Flat: End Terrace: Basement': 'end-terrace',
+    'Flat: Mid Terrace: Basement': 'mid-terrace',
+    'Flat: Enclosed Mid Terrace: Basement': 'enclosed mid-terrace',
+    'House: Semi Detached: Top Floor': 'semi-detached',
+    'House: End Terrace: Ground Floor': 'end-terrace',
+    'Maisonette: Enclosed End Terrace: Mid Floor': 'enclosed end-terrace',
+    'Bungalow: EnclosedEndTerrace': 'enclosed end-terrace'
+
 }

asset_list/mappings/exising_pv.py

@@ -17,5 +17,10 @@ EXISTING_PV_MAPPINGS = {
     'PV: 10% roof area, PV: 2kWp array': 'already has PV',
     'PV: 50% roof area': 'already has PV',
     'Solar PV': 'already has PV',
-    'SOLAR PV': 'already has PV'
+    'SOLAR PV': 'already has PV',
+
+    'PV: 40% roof area, PV: 2kWp array': 'already has PV',
+    'PV: 33% roof area, PV: 2kWp array': 'already has PV',
+    'PV: 30% roof area': 'already has PV'
+
 }

asset_list/mappings/heating_systems.py

@@ -494,6 +494,10 @@ HEATING_MAPPINGS = {
     'Gas (including LPG) room heaters: Gas fire, open flue, 1980 or later (open fronted), sitting proud of, '
     'and sealed to, fireplace opening': 'room heaters',
     'Boiler: A rated Regular Boiler, System 2: Boiler: C rated Regular Boiler': 'boiler - other fuel',
-    'Boiler: G rated Combi': 'gas condensing combi'
+    'Boiler: G rated Combi': 'gas condensing combi',
+
+    'Boiler: A rated Combi, System 2: Boiler: A rated Combi': 'gas combi boiler',
+    'System 2: Boiler: A rated Regular Boiler, Boiler: A rated Regular Boiler': 'gas boiler, radiators',
+    'Boiler: A rated Combi, System 2: Boiler: C rated Combi': 'gas combi boiler'
 
 }

asset_list/mappings/property_type.py

@@ -427,6 +427,23 @@ PROPERTY_MAPPING = {
     'End Terrace': 'unknown',
     'Detached': 'unknown',
     'Mid-terrace': 'unknown',
-    'MID - TERRACE': 'unknown'
+    'MID - TERRACE': 'unknown',
+    'COMOFF': 'unknown',
+    'LOTS': 'unknown',
+
+    'Maisonette: Detached: Ground Floor': 'maisonette',
+    'Maisonette: Enclosed End Terrace: Top Floor': 'maisonette',
+    'Flat: End Terrace: Basement': 'flat',
+    'Bungalow: EnclosedEndTerrace': 'bungalow',
+    'Flat: Mid Terrace: Basement': 'flat',
+    'House: Semi Detached: Top Floor': 'house',
+    'House: End Terrace: Ground Floor': 'house',
+    'Maisonette: Enclosed End Terrace: Mid Floor': 'maisonette',
+    'Flat: Enclosed Mid Terrace: Basement': 'flat',
+
+    'Warden Bungalow': 'bungalow',
+    'Warden Flat': 'flat',
+    'Upper Floor Flat': 'flat',
+    'Extracare Scheme': 'other'
 
 }

asset_list/mappings/roof.py

@@ -301,4 +301,13 @@ ROOF_CONSTRUCTION_MAPPINGS = {
     'PitchedWithSlopingCeiling: As Built': 'pitched insulated',
     'PitchedNormalLoftAccess: As Built': 'pitched unknown insulation',
 
+    'Flat: 150mm, Flat: Unknown': 'flat insulated',
+    'AnotherDwellingAbove: Unknown, Flat: Unknown': 'another dwelling above',
+    'AnotherDwellingAbove, AnotherDwellingAbove: Unknown': 'another dwelling above',
+    'PitchedNormalNoLoftAccess: Unknown, PitchedWithSlopingCeiling: As Built': 'pitched unknown access to loft',
+    'Flat: No Insulation': 'flat uninsulated',
+    'AnotherDwellingAbove: Unknown, PitchedNormalLoftAccess: 250mm': 'another dwelling above',
+    'PitchedNormalLoftAccess: 175mm': 'pitched insulated',
+    'AnotherDwellingAbove: 300mm': 'another dwelling above'
+
 }

asset_list/mappings/walls.py

@@ -354,6 +354,15 @@ WALL_CONSTRUCTION_MAPPINGS = {
     'System built Internal': 'insulated system built',
 
     'Cavity: AsBuilt (1976-1982), TimberFrame: AsBuilt': 'cavity unknown insulation',
-    'Cavity: FilledCavityPlusExternal': 'filled cavity'
+    'Cavity: FilledCavityPlusExternal': 'filled cavity',
+
+    'Cavity, Filled Cavity': 'filled cavity',
+    'Solid Brick, As Built': 'solid brick unknown insulation',
+    'Cavity, As Built': 'cavity unknown insulation',
+    'Sandstone, As Built': 'sandstone or limestone unknown insulation',
+    'Timber Frame, As Built': 'timber frame unknown insulation',
+    'Solid Brick, Internal Insulation': 'insulated solid brick',
+    'Granite or Whinstone, As Built': 'granite or whinstone unknown insulation',
+    'Solid Brick, External': 'insulated solid brick'
 
 }

backend/.env.local

@@ -1,22 +0,0 @@
-DB_HOST=db
-DB_PORT=5432
-DB_NAME=tech_team_local_db
-DB_USERNAME=postgres
-DB_PASSWORD=makingwarmerhomes
-
-
-#not used
-GOOGLE_SOLAR_API_KEY="test"
-SAP_PREDICTIONS_BUCKET="test"
-CARBON_PREDICTIONS_BUCKET="test"
-HEAT_PREDICTIONS_BUCKET="test"
-HEATING_KWH_PREDICTIONS_BUCKET="test"
-HOTWATER_KWH_PREDICTIONS_BUCKET="test"
-API_KEY="test"
-ENVIRONMENT="test"
-SECRET_KEY="test"
-PLAN_TRIGGER_BUCKET="test"
-DATA_BUCKET="test"
-EPC_AUTH_TOKEN="test"
-ENGINE_SQS_URL="test"
-ENERGY_ASSESSMENTS_BUCKET="test"

backend/.env.test

@@ -0,0 +1,22 @@
+DB_HOST=db
+DB_PORT=5432
+DB_NAME=tech_team_local_db
+DB_USERNAME=postgres
+DB_PASSWORD=makingwarmerhomes
+
+
+#not used
+GOOGLE_SOLAR_API_KEY=test
+SAP_PREDICTIONS_BUCKET=test
+CARBON_PREDICTIONS_BUCKET=test
+HEAT_PREDICTIONS_BUCKET=test
+HEATING_KWH_PREDICTIONS_BUCKET=test
+HOTWATER_KWH_PREDICTIONS_BUCKET=test
+API_KEY=test
+ENVIRONMENT=test
+SECRET_KEY=test
+PLAN_TRIGGER_BUCKET=test
+DATA_BUCKET=test
+EPC_AUTH_TOKEN=test
+ENGINE_SQS_URL=test
+ENERGY_ASSESSMENTS_BUCKET=test

backend/Property.py

@@ -1256,7 +1256,8 @@ class Property:
             "biodiesel": "Smokeless Fuel",
             "b30d": "B30K Biofuel",
             "coal": "Coal",
-            "oil": "Oil"
+            "oil": "Oil",
+            "unknown": None  # Handle - anything post 2020 is electricity else gas
         }
 
         self.heating_energy_source = list({
@@ -1326,7 +1327,16 @@ class Property:
         if self.heating_energy_source == "Varied (Community Scheme)":
 
             if self.main_fuel["fuel_type"] in fuel_map:  # We assume when None as it's unknown
-                self.heating_energy_source = fuel_map[self.main_fuel["fuel_type"]]
+                mapped_to = fuel_map[self.main_fuel["fuel_type"]]
+                if mapped_to is None and self.main_fuel["fuel_type"] == "unknown":
+                    # Handle logic based on age band
+                    if self.year_built >= 2020:
+                        self.heating_energy_source = "Electricity"
+                    else:
+                        self.heating_energy_source = "Natural Gas (Community Scheme)"
+
+                else:
+                    self.heating_energy_source = mapped_to
             else:
                 raise NotImplementedError(f"Unhandled fuel {self.main_fuel['fuel_type']}")
 

backend/address2UPRN/Dockerfile

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

backend/address2UPRN/handler/Dockerfile

@@ -0,0 +1,23 @@
+FROM public.ecr.aws/lambda/python:3.10
+
+# Set working directory (Lambda task root)
+WORKDIR /var/task
+
+# -----------------------------
+# Copy requirements FIRST (for Docker layer caching)
+# -----------------------------
+COPY backend/address2UPRN/handler/requirements.txt .
+
+# Install dependencies into Lambda runtime
+RUN pip install --no-cache-dir -r requirements.txt
+
+# -----------------------------
+# Copy application code
+# -----------------------------
+COPY utils/ utils/
+COPY backend/address2UPRN/main.py .
+
+# -----------------------------
+# Lambda handler
+# -----------------------------
+CMD ["main.handler"]

backend/address2UPRN/handler/requirements.txt

@@ -0,0 +1,3 @@
+epc-api-python==1.0.2
+tqdm
+pandas

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)

backend/app/config.py

@@ -1,8 +1,22 @@
+import os
 from functools import lru_cache
-from pydantic_settings import BaseSettings
+from pydantic_settings import BaseSettings, SettingsConfigDict
 from typing import Optional
 
 
+def resolve_env_file() -> Optional[str]:
+    env = os.getenv("ENVIRONMENT", "local")
+
+    if env == "local":
+        return "backend/.env"
+
+    if env == "test":
+        return "backend/.env.test"
+
+    # prod = no env file
+    return None
+
+
 class Settings(BaseSettings):
     API_KEY: str
     API_KEY_NAME: str = "X-API-KEY"
@@ -41,8 +55,10 @@ class Settings(BaseSettings):
     AWS_SECRET_KEY_ID: Optional[str] = None
     AWS_DEFAULT_REGION: Optional[str] = None
 
-    class Config:
+    model_config = SettingsConfigDict(
-        env_file = "backend/.env.local"
+        env_file=resolve_env_file(),
+        env_file_encoding="utf-8",
+    )
 
 
 @lru_cache()

backend/app/plan/utils.py

@@ -24,7 +24,7 @@ def get_cleaned():
 
     cleaned = read_from_s3(
         s3_file_name="cleaned_epc_data/cleaned.bson",
-        bucket_name="retrofit-data-{environment}".format(environment=get_settings().ENVIRONMENT)
+        bucket_name=get_settings().DATA_BUCKET
     )
 
     cleaned = msgpack.unpackb(cleaned, raw=False)

backend/condition/condition_trigger_request.py

@@ -0,0 +1,33 @@
+from enum import Enum
+from typing import Optional
+from pydantic import BaseModel
+
+
+class ConditionFileType(Enum):
+    LBWF = "LBWF"
+    Peabody = "Peabody"
+    # TODO: make these asset management systems rather than client names
+
+
+class ConditionTriggerRequest(BaseModel):
+    file_type: ConditionFileType
+    trigger_file_bucket: str  # TODO: get this from settings
+    trigger_file_key: str
+
+    uprn_lookup_file_bucket: Optional[str] = None  # TODO: get this from settings
+    uprn_lookup_file_key: Optional[str] = None
+
+
+# {
+#     "file_type": "Peabody",
+#     "trigger_file_bucket": "condition-data-dev",
+#     "trigger_file_key": "input/peabody/2026_01_06 - Peabody - Stock Condition Data - Survey Records - D  Lower.xlsx",
+#     "uprn_lookup_file_bucket": "condition-data-dev",
+#     "uprn_lookup_file_key": "input/peabody/uprn-lookup/PeabodyPropertymatched_Dec25_propref_UPRN.csv"
+# }
+
+# {
+#     "file_type": "LBWF",
+#     "trigger_file_bucket": "condition-data-dev",
+#     "trigger_file_key": "input/lbwf/LBWF - Example Asset Data September 2025.xlsx",
+# }

backend/condition/domain/mapping/lbwf/lbwf_mapper.py

@@ -1,4 +1,4 @@
-from typing import Any, Dict, List, Optional, Tuple
+from typing import Any, Dict, Optional, Tuple
 from datetime import date
 
 from backend.condition.domain.aspect_condition import AspectCondition

backend/condition/file_type.py

@@ -1,16 +0,0 @@
-from enum import Enum
-
-class FileType(Enum):
-    LBWF = "lbwf"
-    Peabody = "peabody"
-
-def detect_file_type(filepath: str) -> FileType:
-    path = filepath.lower()
-
-    if "lbwf" in path:
-        return FileType.LBWF
-    
-    if "peabody" in path:
-        return FileType.Peabody
-    
-    raise ValueError("Unrecognised file path")

backend/condition/handler.py

@@ -1,16 +0,0 @@
-from typing import Mapping, Any
-from io import BytesIO
-
-from utils.logger import setup_logger
-from backend.condition.processor import process_file
-
-
-logger = setup_logger()
-
-def handler(event: Mapping[str, Any], context: Any) -> None:
-    # Temporary stub for PoC wiring
-    dummy_stream = BytesIO(b"")
-
-    source_key = event.get("source_key", "unknown-source")
-
-    process_file(dummy_stream, source_key)

backend/condition/handler/Dockerfile

@@ -0,0 +1,48 @@
+FROM public.ecr.aws/lambda/python:3.11
+# For local running:
+# FROM python:3.11.10-bullseye
+
+ARG DEV_DB_HOST
+ARG DEV_DB_PORT
+ARG DEV_DB_NAME
+
+
+# Set working directory (Lambda task root)
+WORKDIR /var/task
+
+# Environment
+ENV DB_HOST=${DEV_DB_HOST}
+ENV DB_PORT=${DEV_DB_PORT}
+ENV DB_NAME=${DEV_DB_NAME}
+
+COPY backend/.env.test backend/.env
+
+# -----------------------------
+# Copy requirements FIRST (for Docker layer caching)
+# -----------------------------
+COPY backend/condition/handler/requirements.txt .
+
+# Install dependencies into Lambda runtime
+RUN pip install --no-cache-dir -r requirements.txt
+
+# -----------------------------
+# Copy application code
+# -----------------------------
+COPY utils/ utils/
+COPY backend/condition/ backend/condition/
+
+COPY backend/app/db/models/condition.py backend/app/db/models/condition.py
+COPY backend/app/db/connection.py backend/app/db/connection.py
+COPY backend/app/config.py backend/app/config.py
+
+COPY backend/__init__.py backend/__init__.py
+COPY backend/app/__init__.py backend/app/__init__.py
+COPY backend/app/db/__init__.py backend/app/db/__init__.py
+
+
+# -----------------------------
+# Lambda handler
+# -----------------------------
+CMD ["backend/condition/handler/handler.handler"]
+# For local running
+# CMD ["python", "-m", "backend.condition.handler.handler"]

backend/condition/handler/handler.py

@@ -0,0 +1,51 @@
+import json
+from typing import Mapping, Any
+from io import BytesIO
+
+from backend.condition.condition_trigger_request import ConditionTriggerRequest
+from backend.condition.lookups.uprn_lookup_s3 import UprnLookupS3
+from backend.condition.processor import process_file
+from utils.logger import setup_logger
+from utils.s3 import read_io_from_s3
+
+
+logger = setup_logger()
+
+
+def handler(event: Mapping[str, Any], context: Any) -> None:
+
+    for record in event.get("Records", []):
+        try:
+            body_dict = json.loads(record["body"])
+            logger.debug("Validating request body")
+            payload = ConditionTriggerRequest.model_validate(body_dict)
+
+            logger.debug("Successfully validated request body")
+
+            if payload.uprn_lookup_file_bucket and payload.uprn_lookup_file_key:
+                logger.debug("Getting UPRN lookup file from s3")
+                uprn_lookup = UprnLookupS3(
+                    bucket=payload.uprn_lookup_file_bucket,
+                    key=payload.uprn_lookup_file_key,
+                )  # TODO: replace with postgres implementation
+                logger.debug("Successfully got UPRN lookup file from s3")
+            else:
+                uprn_lookup = None
+
+            logger.debug("Getting conditions data from s3")
+            file_bytes: BytesIO = read_io_from_s3(
+                bucket_name=payload.trigger_file_bucket,
+                file_key=payload.trigger_file_key,
+            )
+            logger.debug(
+                "Successfully got conditions data from s3. Moving on to process file..."
+            )
+
+            process_file(
+                file_stream=file_bytes,
+                file_type=payload.file_type,
+                uprn_lookup=uprn_lookup,
+            )
+
+        except Exception as e:
+            logger.error(f"Failed to process record: {e}")

backend/condition/handler/requirements.txt

@@ -0,0 +1,9 @@
+openpyxl
+sqlmodel
+pydantic-settings
+psycopg2-binary==2.9.10
+
+# pandas isn't used, but needed for importing from utils.s3
+pandas==2.2.2
+numpy==1.26.4
+openpyxl

backend/condition/local_runner.py

@@ -1,5 +1,7 @@
 from pathlib import Path
 
+from backend.condition.condition_trigger_request import ConditionFileType
+from backend.condition.lookups.uprn_lookup_csv import UprnLookupLocal
 from backend.condition.processor import process_file
 
 
@@ -20,15 +22,27 @@ def main() -> None:
         / "peabody"
         / "2026_01_06 - Peabody - Stock Condition Data - Survey Records - D  Lower.xlsx"
     )
-    filepaths = [lbwf_path, peabody_path]
+    peabody_uprn_lookup_path: Path = (
-    # filepaths = [lbwf_path]
+        path / "peabody" / "PeabodyPropertymatched_Dec25_propref_UPRN.csv"
+    )
+    # filepaths = [lbwf_path, peabody_path]
+    filepaths = [lbwf_path]
     # filepaths = [peabody_path]
 
+    uprn_lookup = UprnLookupLocal(csv_path=peabody_uprn_lookup_path.as_posix())
+
+    def get_file_type(file_path: str) -> ConditionFileType:
+        if "peabody" in file_path:
+            return ConditionFileType.Peabody
+        if "lbwf" in file_path:
+            return ConditionFileType.LBWF
+
     for fp in filepaths:
         with fp.open("rb") as f:
             process_file(
                 file_stream=f,
-                source_key=fp.as_posix(),
+                file_type=get_file_type(fp.as_posix()),
+                uprn_lookup=uprn_lookup,
             )
 
 

backend/condition/lookups/uprn_lookup.py

@@ -0,0 +1,8 @@
+from abc import ABC, abstractmethod
+from typing import BinaryIO, Dict
+
+
+class UprnLookup(ABC):
+    @abstractmethod
+    def get_property_ref_to_uprn_lookup(self) -> Dict[str, int]:
+        pass

backend/condition/lookups/uprn_lookup_csv.py

@@ -0,0 +1,23 @@
+import csv
+from io import TextIOWrapper
+from typing import BinaryIO, Dict, TextIO
+from backend.condition.lookups.uprn_lookup import UprnLookup
+
+
+class UprnLookupLocal(UprnLookup):
+    def __init__(self, csv_path: str):
+        self.csv_path = csv_path
+
+    def get_property_ref_to_uprn_lookup(self) -> Dict[str, int]:
+        with open(self.csv_path, "rb") as f:
+            return self.parse_csv(f)
+
+    def parse_csv(self, file_stream: BinaryIO) -> Dict[str, int]:
+        text_stream: TextIO = TextIOWrapper(file_stream, encoding="utf-8")
+        mapping: Dict[str, int] = {}
+        reader = csv.DictReader(text_stream)
+        for row in reader:
+            if not row["reference"] or not row["out_uprn"]:
+                continue
+            mapping[row["reference"].strip()] = int(row["out_uprn"].strip())
+        return mapping

backend/condition/lookups/uprn_lookup_s3.py

@@ -0,0 +1,29 @@
+import csv
+from io import BytesIO, TextIOWrapper
+from typing import BinaryIO, Dict, TextIO
+
+from backend.condition.lookups.uprn_lookup import UprnLookup
+from utils.s3 import read_io_from_s3
+
+
+class UprnLookupS3(UprnLookup):
+    def __init__(self, bucket: str = "", key: str = ""):
+        self.bucket = bucket
+        self.key = key
+
+    def get_property_ref_to_uprn_lookup(self) -> Dict[str, int]:
+        file_bytes: BytesIO = read_io_from_s3(
+            bucket_name=self.bucket, file_key=self.key
+        )
+
+        return self._parse_csv_bytes(file_bytes)
+
+    def _parse_csv_bytes(self, file_stream: BinaryIO) -> Dict[str, int]:
+        text_stream: TextIO = TextIOWrapper(file_stream, encoding="utf-8")
+        mapping: Dict[str, int] = {}
+        reader = csv.DictReader(text_stream)
+        for row in reader:
+            if not row["reference"] or not row["out_uprn"]:
+                continue
+            mapping[row["reference"].strip()] = int(row["out_uprn"].strip())
+        return mapping

backend/condition/parsing/factory.py

@@ -1,27 +1,35 @@
+from typing import Optional
+from backend.condition.condition_trigger_request import ConditionFileType
 from backend.condition.domain.mapping.lbwf.lbwf_mapper import LbwfMapper
 from backend.condition.domain.mapping.mapper import Mapper
 from backend.condition.domain.mapping.peabody.peabody_mapper import PeabodyMapper
-from backend.condition.file_type import FileType
+from backend.condition.lookups.uprn_lookup import UprnLookup
 from backend.condition.parsing.parser import Parser
 from backend.condition.parsing.lbwf_parser import LbwfParser
 from backend.condition.parsing.peabody_parser import PeabodyParser
 
 
-def select_parser(file_type: FileType) -> Parser:
+def select_parser(
-    if file_type is FileType.LBWF:
+    file_type: ConditionFileType, uprn_lookup: Optional[UprnLookup] = None
+) -> Parser:
+    if file_type is ConditionFileType.LBWF:
         return LbwfParser()
 
-    if file_type is FileType.Peabody:
+    if file_type is ConditionFileType.Peabody:
-        return PeabodyParser()
+        if not uprn_lookup:
+            raise ValueError(
+                "Cannot instantiate Peabody Parser without UPRN lookup being provided"
+            )
+        return PeabodyParser(uprn_lookup=uprn_lookup)
 
     raise ValueError("Unrecognised file type, unable to instantiate Parser")
 
 
-def select_mapper(file_type: FileType) -> Mapper:
+def select_mapper(file_type: ConditionFileType) -> Mapper:
-    if file_type is FileType.LBWF:
+    if file_type is ConditionFileType.LBWF:
         return LbwfMapper()
 
-    if file_type is FileType.Peabody:
+    if file_type is ConditionFileType.Peabody:
         return PeabodyMapper()
 
     raise ValueError("Unrecognised file type, unable to instantiate Mapper")

backend/condition/parsing/lbwf_parser.py

@@ -18,7 +18,6 @@ class LbwfParser(Parser):
     def parse(
         self,
         file_stream: BinaryIO,
-        location_ref_to_uprn_map: Optional[Dict[str, int]] = None,
     ) -> Any:
         wb: Workbook = load_workbook(file_stream)
         address_to_uprn_map: Dict[str, int] = LbwfParser._generate_address_to_uprn_dict(

backend/condition/parsing/parser.py

@@ -8,6 +8,5 @@ class Parser(ABC):
     def parse(
         self,
         file_stream: BinaryIO,
-        location_ref_to_uprn_map: Optional[Dict[str, int]] = None,
     ) -> Any:
         pass

backend/condition/parsing/peabody_parser.py

@@ -4,6 +4,7 @@ from typing import Any, BinaryIO, Dict, List, Optional, Tuple, DefaultDict
 from openpyxl import Workbook, load_workbook
 from collections import defaultdict
 
+from backend.condition.lookups.uprn_lookup import UprnLookup
 from backend.condition.parsing.parser import Parser
 from backend.condition.parsing.records.peabody.peabody_asset_condition import (
     PeabodyAssetCondition,
@@ -15,42 +16,29 @@ logger = setup_logger()
 
 
 class PeabodyParser(Parser):
+    def __init__(self, uprn_lookup: UprnLookup):
+        self.uprn_lookup: UprnLookup = uprn_lookup  # TODO: move this to the ABC?
+
     def parse(
         self,
         file_stream: BinaryIO,
-        location_ref_to_uprn_map: Optional[Dict[str, int]] = None,
     ) -> Any:
-        wb: Workbook = load_workbook(file_stream)
+        file_stream.seek(0)
-
+        logger.debug("[PeabodyParser] Loading workbook...")
-        if location_ref_to_uprn_map is None:
+        wb: Workbook = load_workbook(file_stream, read_only=True, data_only=True)
-            location_ref_to_uprn_map: Dict[str, int] = (
+        logger.debug("[PeabodyParser] Successfully loaded workbook. Parsing assets...")
-                PeabodyParser._build_location_ref_to_uprn_map()
-            )
-
         assets = PeabodyParser._parse_assets(wb)
+        logger.debug(
+            "[PeabodyParser] Successfully parsed assets. Parsing UPRN lookup..."
+        )
 
+        location_ref_to_uprn_map = self.uprn_lookup.get_property_ref_to_uprn_lookup()
+        logger.debug("[PeabodyParser] Successfully parsed UPRN lookup")
         return PeabodyParser._group_assets_into_properties(
             assets=assets,
             location_ref_to_uprn_map=location_ref_to_uprn_map,
         )
 
-    @staticmethod
-    def _build_location_ref_to_uprn_map() -> Dict[str, int]:
-        location_ref_to_uprn_filepath: Path = (
-            Path(__file__).resolve().parents[1]
-            / "sample_data"
-            / "peabody"
-            / "PeabodyPropertymatched_Dec25_propref_UPRN.csv"
-        )
-        location_ref_to_uprn_map: Dict[str, int] = {}
-
-        with location_ref_to_uprn_filepath.open(newline="") as f:
-            reader: Any = csv.DictReader(f)
-            for row in reader:
-                location_ref_to_uprn_map[row["reference"]] = int(row["out_uprn"])
-
-        return location_ref_to_uprn_map
-
     @staticmethod
     def _parse_assets(wb: Workbook) -> List[PeabodyAssetCondition]:
         assets_sheet = wb["Survey Records - D & Lower"]
@@ -67,7 +55,7 @@ class PeabodyParser(Parser):
                 )
                 if not asset.is_block_level:
                     # Block-level condition surveys are out of scope for now
-                    # until we have a wider think on how to handle block
+                    # until we have a wider think on how to handle blocks
                     assets.append(asset)  # TODO: handle block-level assets
 
             except Exception as e:
@@ -92,13 +80,14 @@ class PeabodyParser(Parser):
             assets_by_location_reference[asset.lo_reference].append(asset)
 
         properties: List[PeabodyProperty] = []
+        failed_mappings_count = 0
 
         for location_ref, grouped_assets in assets_by_location_reference.items():
 
             uprn = location_ref_to_uprn_map.get(location_ref)
 
             if uprn is None:
-                logger.warning(f"No UPRN found for Location Reference: {location_ref}")
+                failed_mappings_count += 1
                 continue
 
             properties.append(
@@ -108,6 +97,7 @@ class PeabodyParser(Parser):
                 )
             )
 
+        logger.warning(f"No UPRN found for {failed_mappings_count} Location References")
         return properties
 
     @staticmethod

backend/condition/persistence/condition_postgres.py

@@ -19,18 +19,19 @@ class ConditionPostgres:
     def bulk_insert_surveys(
         self, surveys: List[PropertyConditionSurvey], batch_size: Optional[int] = 100
     ) -> None:
-        logger.info(
+        logger.debug(
-            f"Preparing to load {len(surveys)} property surveys to Postgres. Mapping to SQLModel objects..."
+            f"[ConditionPostgres] Preparing to load {len(surveys)} property surveys to Postgres. Mapping to SQLModel objects..."
         )
         survey_models: List[PropertyConditionSurveyModel] = [
             ConditionPostgres.map_survey_to_model(s) for s in surveys
         ]
         total: int = len(survey_models)
-        logger.info(
+        logger.debug(
-            f"Finished mapping {total} surveys. Writing to database in batches of {batch_size}..."
+            f"[ConditionPostgres] Finished mapping {total} surveys. Writing to database in batches of {batch_size}..."
         )
 
         with db_session() as session:
+            logger.info("[ConditionPostgres] Successfully made connection to database")
             for start in range(0, total, batch_size):
                 end = min(start + batch_size, total)
                 batch = survey_models[start:end]

backend/condition/processor.py

@@ -1,26 +1,31 @@
-from typing import Any, BinaryIO, List
+from typing import Any, BinaryIO, List, Optional
 from datetime import datetime
 
+from backend.condition.condition_trigger_request import ConditionFileType
+from backend.condition.lookups.uprn_lookup import UprnLookup
 from utils.logger import setup_logger
 from backend.condition.domain.mapping.mapper import Mapper
 from backend.condition.domain.property_condition_survey import PropertyConditionSurvey
 from backend.condition.parsing.parser import Parser
 from backend.condition.persistence.condition_postgres import ConditionPostgres
-from backend.condition.file_type import FileType, detect_file_type
 from backend.condition.parsing.factory import select_parser, select_mapper
 
 logger = setup_logger()
 
 
-def process_file(file_stream: BinaryIO, source_key: str) -> None:
+def process_file(
-    logger.info(f"[processor] Received file: {source_key}")
+    file_stream: BinaryIO,
-
+    file_type: ConditionFileType,
+    uprn_lookup: Optional[UprnLookup],
+) -> None:
     # Instantiation
-    file_type: FileType = detect_file_type(source_key)
+    logger.debug(f"[processor] Instantiating classes...")
-    parser: Parser = select_parser(file_type)
+    parser: Parser = select_parser(file_type, uprn_lookup)
     mapper: Mapper = select_mapper(file_type)
     persistence = ConditionPostgres()
 
+    logger.debug(f"[processor] Finished instantiating classes. Calling Parser...")
+
     # Orchestration
     raw_properties: List[Any] = parser.parse(file_stream)
 

backend/condition/tests/lookups/test_uprn_lookup_csv.py

@@ -0,0 +1,34 @@
+import pytest
+from typing import Dict
+from tempfile import NamedTemporaryFile
+
+from backend.condition.lookups.uprn_lookup_csv import UprnLookupLocal
+
+
+@pytest.fixture
+def prop_ref_uprn_csv_file() -> str:
+    csv_content = """reference,out_uprn
+    ABC123,10000000001
+    DEF456,10000000002
+    GHI789,10000000003
+    """
+    with NamedTemporaryFile(mode="w+", delete=False, suffix=".csv") as tmp:
+        tmp.write(csv_content)
+        tmp.flush()
+        return tmp.name
+
+
+def test_generate_prop_ref_uprn_from_csv_file(prop_ref_uprn_csv_file: str) -> None:
+    # arrange
+    uprn_lookup = UprnLookupLocal(prop_ref_uprn_csv_file)
+    expected_map: Dict[str, int] = {
+        "ABC123": 10000000001,
+        "DEF456": 10000000002,
+        "GHI789": 10000000003,
+    }
+
+    # act
+    actual_map: Dict[str, int] = uprn_lookup.get_property_ref_to_uprn_lookup()
+
+    # assert
+    assert actual_map == expected_map

backend/condition/tests/parsing/test_parsing_factory.py

@@ -1,11 +1,13 @@
 import pytest
 
+from backend.condition.condition_trigger_request import ConditionFileType
+from backend.condition.lookups.uprn_lookup_csv import UprnLookupLocal
 from backend.condition.parsing.factory import select_parser
-from backend.condition.file_type import FileType
+
 
 def test_selects_lbwf_parser():
     # arrange
-    file_type = FileType.LBWF
+    file_type = ConditionFileType.LBWF
     expected_class_name = "LbwfParser"
 
     # act
@@ -14,13 +16,15 @@ def test_selects_lbwf_parser():
     # assert
     assert expected_class_name == actual_class_name
 
+
 def test_selects_peabody_parser():
     # arrange
-    file_type = FileType.Peabody
+    file_type = ConditionFileType.Peabody
     expected_class_name = "PeabodyParser"
+    uprn_lookup = UprnLookupLocal(csv_path="test")
 
     # act
-    actual_class_name = select_parser(file_type).__class__.__name__
+    actual_class_name = select_parser(file_type, uprn_lookup).__class__.__name__
 
     # assert
-    assert expected_class_name == actual_class_name
+    assert expected_class_name == actual_class_name

backend/condition/tests/parsing/test_peabody_parser.py

@@ -1,9 +1,11 @@
+from tempfile import NamedTemporaryFile
 import pytest
 from typing import Any, Dict
 from io import BytesIO
 from openpyxl import Workbook
 from datetime import datetime
 
+from backend.condition.lookups.uprn_lookup_csv import UprnLookupLocal
 from backend.condition.parsing.peabody_parser import PeabodyParser
 from backend.condition.parsing.records.peabody.peabody_asset_condition import (
     PeabodyAssetCondition,
@@ -145,23 +147,28 @@ def peabody_assets_xlsx_bytes() -> BytesIO:
 
 
 @pytest.fixture
-def location_ref_to_uprn_map() -> Dict[str, int]:
+def prop_ref_uprn_csv_file() -> str:
-    return {
+    csv_content = """reference,out_uprn
-        "B000RAND": 1,
+    B000RAND,1
-        "B000BLOCK": 2,
+    B000BLOCK,2
-        "B000FAKE": 3,
+    B000FAKE,3
-        "B000MIS": 4,
+    B000MIS,4
-    }
+    """
+    with NamedTemporaryFile(mode="w+", delete=False, suffix=".csv") as tmp:
+        tmp.write(csv_content)
+        tmp.flush()
+        return tmp.name
 
 
 def test_peabody_parser_parses_conditions(
-    peabody_assets_xlsx_bytes, location_ref_to_uprn_map
+    peabody_assets_xlsx_bytes, prop_ref_uprn_csv_file
 ):
     # arrange
-    parser = PeabodyParser()
+    uprn_lookup = UprnLookupLocal(csv_path=prop_ref_uprn_csv_file)
+    parser = PeabodyParser(uprn_lookup=uprn_lookup)
 
     # act
-    result: Any = parser.parse(peabody_assets_xlsx_bytes, location_ref_to_uprn_map)
+    result: Any = parser.parse(peabody_assets_xlsx_bytes)
 
     # assert
     assert len(result) == 3

backend/condition/tests/test_detect_file_type.py

@@ -1,22 +0,0 @@
-import pytest
-
-from backend.condition.file_type import FileType, detect_file_type
-
-def test_detects_lbwf_file_type():
-    # arrange
-    file_path_str = "uploads/lbwf/Exaple Asset Data.xlsx"
-    expected_file_type = FileType.LBWF
-
-    # act
-    actual_file_type: FileType = detect_file_type(file_path_str)
-
-    # assert
-    assert expected_file_type == actual_file_type
-
-def test_unknown_filepath_raises_value_error():
-    # arrange
-    file_path_str = "unknown/Example Asset Data.xlsx"
-
-    # act + assert
-    with pytest.raises(ValueError):
-        detect_file_type(file_path_str)

backend/engine/engine.py

@@ -978,13 +978,15 @@ async def model_engine(body: PlanTriggerRequest):
             recommendations_scoring_data.extend(p.recommendations_scoring_data)
 
         logger.info("Preparing data for scoring in sap change api")
-        recommendations_scoring_data = pd.DataFrame(recommendations_scoring_data).drop(
+        recommendations_scoring_data = pd.DataFrame(recommendations_scoring_data)
-            columns=[
+        if not recommendations_scoring_data.empty:
-                "rdsap_change", "heat_demand_change", "carbon_change", "sap_ending", "heat_demand_ending",
+            recommendations_scoring_data = recommendations_scoring_data.drop(
-                "carbon_ending"
+                columns=[
-            ]
+                    "rdsap_change", "heat_demand_change", "carbon_change", "sap_ending", "heat_demand_ending",
-        )
+                    "carbon_ending"
-        # Temp putting this here
+                ]
+            )
+        # TODO: Temp putting this here
         recommendations_scoring_data["is_post_sap10_ending"] = True
 
         all_predictions = await model_api.async_paginated_predictions(

backend/ml_models/api.py

@@ -313,4 +313,15 @@ class ModelApi:
                     logger.error(f"Batch {chunk}-{chunk + batch_size} failed (Attempt {attempts}): {e}")
                     await asyncio.sleep(2 ** attempts)  # exponential backoff
         await self.close_aiohttp_session()
+
+        # Ensure stable output structure for the datagrame to be utilised by other functions downstream
+        for k in all_predictions.keys():
+            if all_predictions[k].empty:
+                col_template = ['id', 'predictions', 'property_id', 'recommendation_id', 'phase'] if (
+                    extract_ids) else ['id', 'predictions']
+
+                all_predictions[k] = pd.DataFrame(
+                    columns=col_template
+                )
+
         return all_predictions

backend/onboarders/README.md

@@ -0,0 +1,102 @@
+# Retrofit Property Data Onboarding
+
+This repository contains an ETL pipeline for transforming raw retrofit property data from external source systems (
+currently Parity) into a standardised internal format, compatible for both address2uprn and engine.
+
+The pipeline is designed to:
+
+- Run as an AWS Lambda triggered by SQS
+- Read raw CSV/XLSX files from S3
+- Perform rule-based mappings
+- Infer as built property attributes, assumed based on age
+- Output a processed csv, back to s3 to be consumed by address2uprn
+
+### Structure
+
+SQS → Lambda handler → OnboarderFactory → System-specific Onboarder → Mapping → CSV to S3
+
+Each source system implements its own **Onboarder**, while sharing a common base and mapping process.
+
+---
+
+### Repository Structure
+
+onboarders/
+├── `handler.py` # Lambda entrypoint \
+├── `factory.py` # Onboarder factory \
+├── `base.py` # Shared onboarding base class \
+├── `parity.py` # Parity-specific transformation logic \
+├── `mappings/` \
+│ └── `parity/` # Parity domain mappings & classifiers \
+│ ├── `age_band.py` \
+│ ├── `property_type.py` \
+│ ├── `built_form.py` \
+│ ├── `walls.py` \
+│ ├── `roof.py` \
+│ ├── `floor.py` \
+│ ├── `glazing.py` \
+│ ├── `heating.py` \
+│ ├── `as_built_wall_classifiers.py` \
+│ ├── `as_built_roof_classifiers.py` \
+│ └── `as_built_floor_classifiers.py` \
+├── `tests/` \
+├── `requirements.txt` \
+└── `README.md`
+
+
+---
+
+### Lambda Entry Point (`handler.py`)
+
+The Lambda handler:
+
+1. Consumes SQS queue
+2. Validates the payload
+3. Instantiates the correct onboarder via `OnboarderFactory`
+4. Runs the transformation
+5. Writes the transformed CSV back to S3
+
+### Expected Event Payload
+
+```json
+{
+  "s3_uri": "s3://bucket/path/to/input.xlsx",
+  "system": "parity",
+  "format": "xlsx",
+  "sheet_name": "Sustainability"
+}
+
+```
+
+### Onboarder Base `(base.py)`
+
+OnboarderBase provides shared functionality across all systems.
+
+*Responsibilities*
+
+- Reading CSV/XLSX files from S3
+- Writing transformed CSVs to S3
+- Defining canonical output column names
+- Providing validation helpers
+- Common output - for the moment, onboards will be expected to return a csv
+
+### Parity Onboarder `(parity.py)`
+
+`ParityOnboarder` contains all Parity-specific transformation logic.
+
+Responsibilities*
+
+- Map raw Parity fields to internal EPC-aligned enums
+- Infer “as-built” constructions using age bands when insulation data is missing
+- Resolve energy efficiency ratings deterministically
+- Normalise output into a fixed schema
+
+The `transform()` method orchestrates the transformation process.
+
+### TODOs
+
+- In `backend/onboarders/mappings/parity/glazing.py` we currently map the partiy descriptions
+  to duples of descriptions and efficiency ratings. This is okay for the moment but we may consider
+  using a data class, just given how error-prone this is.
+- This is also true for heating mappings in `backend/onboarders/mappings/parity/heating.py`
+- Implement a AI-enabled version, to replace the standardised asset list

backend/onboarders/base.py

@@ -0,0 +1,84 @@
+import pandas as pd
+from utils.s3 import read_from_s3, read_excel_from_s3, save_csv_to_s3
+
+
+class OnboarderBase:
+    # Input dataset to be transformed
+    data: pd.DataFrame | None = None
+    bucket_name = None
+    input_file_name = None
+    output_file_name = None
+    # Description columns
+    landlord_wall_construction: str = "landlord_wall_construction"
+    landlord_roof_construction: str = "landlord_roof_construction"
+    landlord_floor_construction: str = "landlord_floor_construction"
+    landlord_windows_type: str = "landlord_windows_type"
+    landlord_heating_construction: str = "landlord_heating_construction"
+    landlord_fuel_type: str = "landlord_fuel_type"
+    landlord_heating_controls: str = "landlord_heating_controls"
+    landlord_hot_water_system: str = "landlord_hot_water_system"
+
+    # Efficiency columns
+    landlord_roof_efficiency: str = "landlord_roof_efficiency"
+    landlord_windows_efficiency: str = "landlord_windows_efficiency"
+    landlord_heating_controls_efficiency: str = "landlord_heating_controls_efficiency"
+    landlord_heating_efficiency: str = "landlord_heating_efficiency"
+    landlord_hot_water_efficiency: str = "landlord_hot_water_efficiency"
+    landlord_wall_efficiency: str = "landlord_wall_efficiency"
+
+    # Additional windows features
+    landlord_multi_glaze_proportion: str = "landlord_multi_glaze_proportion"
+    landlord_glazed_type: str = "landlord_glazed_type"
+    landlord_glazed_area: str = "landlord_glazed_area"
+
+    # Additional roof features
+    landlord_has_sloping_ceiling: str = "landlord_has_sloping_ceiling"
+
+    # Shape, dimensions, age
+    landlord_total_floor_area_m2: str = "landlord_total_floor_area_m2"
+    landlord_construction_age_band: str = "landlord_construction_age_band"
+    landlord_property_type: str = "landlord_property_type"
+    landlord_built_form: str = "landlord_built_form"
+
+    def read_s3(self, file_format, **kwargs):
+
+        if self.input_file_name is None or self.bucket_name is None:
+            raise ValueError("Bucket name and input file name must be set before reading from S3.")
+        if file_format == "xlsx":
+            self.data = read_excel_from_s3(
+                bucket_name=self.bucket_name,
+                file_key=self.input_file_name,
+                sheet_name=kwargs.get("sheet_name"),
+                header_row=kwargs.get("header_row", 0)
+            )
+        else:
+            self.data = read_from_s3(bucket_name=self.bucket_name, s3_file_name=self.input_file_name)
+    
+    def write(self):
+        if self.data is None:
+            raise ValueError("No data to write. Please run transform() before writing.")
+
+        if self.bucket_name is None or self.output_file_name is None:
+            raise ValueError("Bucket name and output file name must be set before writing to S3.")
+        # Store file as csv - will store in the same route location as the input file
+        save_csv_to_s3(dataframe=self.data, bucket_name=self.bucket_name, file_name=self.output_file_name)
+
+    @staticmethod
+    def assert_nulls_only_from_source_nulls(data: pd.DataFrame, original_column: str, mapped_column: str) -> bool:
+        # We only allow nulls if the original value was null
+        null_vals = data[pd.isnull(data[mapped_column])]
+        if null_vals.empty:
+            return True
+        # We make sure all original values were null
+        assert pd.isnull(null_vals[original_column]).all(), (
+            f"Some values in {mapped_column} were not mapped, but original values were not null"
+        )
+
+    @staticmethod
+    def assert_no_nulls(data: pd.DataFrame, column: str):
+        assert pd.isnull(data[column]).sum() == 0, f"column {column} contains null values, but should not"
+
+    def map_construction_age_band(self):
+        raise NotImplementedError(
+            "This method should be implemented by subclasses to map construction age bands to descriptions"
+        )

backend/onboarders/factory.py

@@ -0,0 +1,10 @@
+from onboarders.parity import ParityOnboarder
+
+
+class OnboarderFactory:
+    @staticmethod
+    def create_onboarder(onboarder_type, **kwargs):
+        if onboarder_type == "parity":
+            return ParityOnboarder(**kwargs)
+
+        raise ValueError(f"Unknown onboarder type: {onboarder_type}")

backend/onboarders/handler.py

@@ -0,0 +1,50 @@
+import json
+from pydantic import BaseModel, Field
+from typing import Optional, Literal
+from onboarders.factory import OnboarderFactory
+from utils.logger import setup_logger
+
+logger = setup_logger()
+
+
+class OnboardingEvent(BaseModel):
+    s3_uri: str = Field(..., description="S3 URI of the raw ARA input file")
+    system: Literal["parity", "generic"] = Field(..., description="Onboarding system identifier")
+    format: Literal["csv", "xlsx"]
+    sheet_name: Optional[str] = None
+
+
+def handler(event, context):
+    """
+    Lambda handler that triggers the model engine for each SQS message.
+    """
+    for record in event.get("Records", []):
+        try:
+            event_body = json.loads(record["body"])
+            # Sample input data
+            # event_body = {
+            #     "s3_uri": "s3://retrofit-data-dev/ara_raw_inputs/peabody/2025_11_11 - Peabody - Data Extracts for "
+            #               "Domna.xlsx",
+            #     "system": "parity",
+            #     "format": "xlsx",
+            #     "sheet_name": "Sustainability"
+            # }
+
+            logger.info("Processing record with body: %s", event_body)
+
+            validated_event = OnboardingEvent(**event_body)
+            onboarder = OnboarderFactory.create_onboarder(
+                validated_event.system,
+                fileuri=validated_event.s3_uri,
+                format=validated_event.format,
+                sheet_name=validated_event.sheet_name,
+                file_format=validated_event.format
+            )
+
+            logger.info("Transforming data")
+            onboarder.transform()
+            logger.info(f"Writing data to {onboarder.output_file_name}, bucket: {onboarder.bucket_name}")
+            onboarder.write()
+
+        except Exception as e:
+            logger.error(f"Failed to process record: {e}")

backend/onboarders/mappings/age_band.py

@@ -1,14 +0,0 @@
-party_map = {
-    "Before 1900": 'England and Wales: before 1900',
-    "1900-1929": 'England and Wales: 1900-1929',
-    "1930-1949": 'England and Wales: 1930-1949',
-    "1950-1966": 'England and Wales: 1950-1966',
-    "1967-1975": 'England and Wales: 1967-1975',
-    "1976-1982": 'England and Wales: 1976-1982',
-    "1983-1990": 'England and Wales: 1983-1990',
-    "1991-1995": 'England and Wales: 1991-1995',
-    "1996-2002": 'England and Wales: 1996-2002',
-    "2003-2006": 'England and Wales: 2003-2006',
-    "2007-2011": 'England and Wales: 2007-2011',
-    "2012 onwards": 'England and Wales: 2012-2021',
-}

backend/onboarders/mappings/built_form.py

@@ -1,15 +0,0 @@
-parity_map = {
-    "MidTerrace": "Mid-Terrace",
-    "EndTerrace": "End-Terrace",
-    "Detached": "Detached",
-    "SemiDetached": "Semi-Detached",
-    "EnclosedMidTerrace": "Enclosed Mid-Terrace",
-    "EnclosedEndTerrace": "Enclosed End-Terrace",
-}
-
-# MidTerrace            41462
-# EndTerrace            20910
-# Detached              16875
-# SemiDetached          14725
-# EnclosedMidTerrace     3176
-# EnclosedEndTerrace     2393

backend/onboarders/mappings/parity/age_band.py

@@ -0,0 +1,19 @@
+from datatypes.epc.construction_age_band import EpcConstructionAgeBand
+
+parity_map = {
+    "Before 1900": EpcConstructionAgeBand.before_1900,
+    "1900-1929": EpcConstructionAgeBand.from_1900_to_1929,
+    "1930-1949": EpcConstructionAgeBand.from_1930_to_1949,
+    "1950-1966": EpcConstructionAgeBand.from_1950_to_1966,
+    "1967-1975": EpcConstructionAgeBand.from_1967_to_1975,
+    "1976-1982": EpcConstructionAgeBand.from_1976_to_1982,
+    "1983-1990": EpcConstructionAgeBand.from_1983_to_1990,
+    "1991-1995": EpcConstructionAgeBand.from_1991_to_1995,
+    "1996-2002": EpcConstructionAgeBand.from_1996_to_2002,
+    "2003-2006": EpcConstructionAgeBand.from_2003_to_2006,
+    "2007-2011": EpcConstructionAgeBand.from_2007_to_2011,
+    "2012 onwards": EpcConstructionAgeBand.from_2012_onwards,
+    # Newer age bands, under SAP10
+    "2012-2022": EpcConstructionAgeBand.from_2012_to_2022,
+    "2023 onwards": EpcConstructionAgeBand.from_2023_onwards,
+}

backend/onboarders/mappings/parity/as_built_floor_classifiers.py

@@ -0,0 +1,60 @@
+from datatypes.epc.construction_age_band import EpcConstructionAgeBand
+from datatypes.epc.floor import EpcFloorDescriptions
+
+
+def unknown_floor_as_built(age_band: EpcConstructionAgeBand) -> EpcFloorDescriptions:
+    year = age_band.start_year()
+
+    if year >= 2003:
+        return EpcFloorDescriptions.solid_insulated_assumed
+
+    if year >= 1996:
+        return EpcFloorDescriptions.solid_limited_insulation_assumed
+
+    if year >= 1930:
+        return EpcFloorDescriptions.solid_no_insulation_assumed
+
+    return EpcFloorDescriptions.suspended_no_insulation_assumed
+
+
+def unknown_floor_retrofitted(age_band: EpcConstructionAgeBand) -> EpcFloorDescriptions:
+    year = age_band.start_year()
+
+    if year >= 1930:
+        return EpcFloorDescriptions.solid_insulated
+
+    return EpcFloorDescriptions.suspended_insulated
+
+
+def map_solid_floor_as_built(age_band: EpcConstructionAgeBand) -> EpcFloorDescriptions:
+    year = age_band.start_year()
+
+    if year >= 2003:
+        return EpcFloorDescriptions.solid_insulated_assumed
+    if year >= 1996:
+        return EpcFloorDescriptions.solid_limited_insulation_assumed
+    return EpcFloorDescriptions.solid_no_insulation_assumed
+
+
+def map_suspended_floor_as_built(age_band: EpcConstructionAgeBand) -> EpcFloorDescriptions:
+    year = age_band.start_year()
+
+    if year >= 2003:
+        return EpcFloorDescriptions.suspended_insulated_assumed
+    if year >= 1996:
+        return EpcFloorDescriptions.suspended_limited_insulation_assumed
+
+    return EpcFloorDescriptions.suspended_no_insulation_assumed
+
+
+as_built_floor_classifiers = {
+    "Solid": map_solid_floor_as_built,
+    "SuspendedTimber": map_suspended_floor_as_built,
+    "SuspendedNotTimber": map_suspended_floor_as_built,
+}
+
+unknown_as_built_floor_classifiers = {
+    "RetroFitted": unknown_floor_retrofitted,
+    "AsBuilt": unknown_floor_as_built,
+    "Unknown": unknown_floor_as_built,
+}

backend/onboarders/mappings/parity/as_built_roof_classifiers.py

@@ -0,0 +1,56 @@
+from datatypes.epc.roof import EpcRoofDescriptions
+from datatypes.epc.construction_age_band import EpcConstructionAgeBand
+
+
+def map_flat_roof(age_band: EpcConstructionAgeBand) -> EpcRoofDescriptions:
+    """
+    For a flat, as built roof, these are the breakdowns:
+
+    2023 onwards               → Flat, insulated
+    2003–2022                  → Flat, insulated
+    1983–2002                  → Flat, insulated
+    1976–1982                  → Flat, limited insulation
+    1967–1975                  → Flat, limited insulation
+    1950–1966 and earlier      → Flat, no insulation
+    :param age_band: Input age band
+    :return: EpcRoofDescriptions
+    """
+
+    year = age_band.start_year()
+
+    if year >= 1983:
+        return EpcRoofDescriptions.flat_insulated
+
+    if year >= 1967:
+        return EpcRoofDescriptions.flat_limited_insulation
+
+    return EpcRoofDescriptions.flat_no_insulation
+
+
+def map_sloping_ceiling_roof(age_band: EpcConstructionAgeBand) -> EpcRoofDescriptions:
+    """
+    For a sloping ceiling, as built roof, these are the breakdowns:
+    2023 onwards               → Sloping pitched, insulated
+    2003–2022                  → Sloping pitched, insulated
+    1983–2002                  → Sloping pitched, insulated
+    1976–1982                  → Sloping pitched, limited insulation
+    1967–1975 and earlier      → Sloping pitched, no insulation
+    :param age_band: Input age band
+    :return: EpcRoofDescriptions
+    """
+    year = age_band.start_year()
+
+    if year >= 1983:
+        return EpcRoofDescriptions.sloping_pitched_insulated
+
+    if year >= 1976:
+        return EpcRoofDescriptions.sloping_pitched_limited_insulation
+
+    return EpcRoofDescriptions.sloping_pitched_no_insulation
+
+
+as_built_roof_classifiers = {
+    # Only need to apply this to flat and sloping ceiling roofs
+    "Flat": map_flat_roof,
+    "PitchedWithSlopingCeiling": map_sloping_ceiling_roof,
+}

backend/onboarders/mappings/parity/as_built_wall_classifiers.py

@@ -0,0 +1,113 @@
+from datatypes.epc.construction_age_band import EpcConstructionAgeBand
+from datatypes.epc.walls import EpcWallDescriptions
+
+
+def map_cavity_wall_insulation(age_band: EpcConstructionAgeBand):
+    if age_band.start_year() < 1976:
+        return EpcWallDescriptions.cavity_no_insulation_assumed
+
+    if age_band == EpcConstructionAgeBand.from_1976_to_1982:
+        return EpcWallDescriptions.cavity_partial_insulated_assumed
+
+    if age_band in EpcConstructionAgeBand.from_year_onwards(1983):
+        return EpcWallDescriptions.cavity_insulated_assumed
+
+    raise NotImplementedError(f"Age band {age_band} not handled for cavity wall as built insulation mapping")
+
+
+def map_solid_wall_insulation(age_band: EpcConstructionAgeBand):
+    if age_band.start_year() < 1976:
+        return EpcWallDescriptions.solid_brick_no_insulation_assumed
+
+    if age_band == EpcConstructionAgeBand.from_1976_to_1982:
+        return EpcWallDescriptions.solid_brick_partial_insulated_assumed
+
+    if age_band in EpcConstructionAgeBand.from_year_onwards(1983):
+        return EpcWallDescriptions.solid_brick_insulated_assumed
+
+    raise NotImplementedError(
+        f"Age band {age_band.value} not handled for solid wall insulation mapping"
+    )
+
+
+def map_timber_frame_wall_insulation(age_band: EpcConstructionAgeBand):
+    if age_band.start_year() < 1950:
+        return EpcWallDescriptions.timber_frame_no_insulation_assumed
+
+    if age_band.start_year() < 1976:
+        return EpcWallDescriptions.timber_frame_partial_insulated_assumed
+
+    if age_band in EpcConstructionAgeBand.from_year_onwards(1976):
+        return EpcWallDescriptions.timber_frame_insulated_assumed
+
+    raise NotImplementedError(
+        f"Age band {age_band.value} not handled for timber frame wall insulation mapping"
+    )
+
+
+def map_system_build_wall_insulation(age_band: EpcConstructionAgeBand):
+    if age_band.start_year() < 1976:
+        return EpcWallDescriptions.system_no_insulation_assumed
+
+    if age_band == EpcConstructionAgeBand.from_1976_to_1982:
+        return EpcWallDescriptions.system_partial_insulated_assumed
+
+    if age_band in EpcConstructionAgeBand.from_year_onwards(1983):
+        return EpcWallDescriptions.system_insulated_assumed
+
+    raise NotImplementedError(
+        f"Age band {age_band.value} not handled for system build wall insulation mapping"
+    )
+
+
+def map_granite_wall_insulation(age_band: EpcConstructionAgeBand):
+    if age_band.start_year() < 1976:
+        return EpcWallDescriptions.granite_whinstone_no_insulation_assumed
+
+    if age_band == EpcConstructionAgeBand.from_1976_to_1982:
+        return EpcWallDescriptions.granite_whinstone_partial_insulated_assumed
+
+    if age_band in EpcConstructionAgeBand.from_year_onwards(1983):
+        return EpcWallDescriptions.granite_whinestone_insulated_assumed
+
+    raise NotImplementedError(
+        f"Age band {age_band.value} not handled for granite wall insulation mapping"
+    )
+
+
+def map_sandstone_wall_insulation(age_band: EpcConstructionAgeBand):
+    if age_band.start_year() < 1976:
+        return EpcWallDescriptions.sandstone_limestone_no_insulation_assumed
+
+    if age_band == EpcConstructionAgeBand.from_1976_to_1982:
+        return EpcWallDescriptions.sandstone_limestone_partial_insulated_assumed
+
+    if age_band in EpcConstructionAgeBand.from_year_onwards(1983):
+        return EpcWallDescriptions.sandstone_limestone_insulated_assumed
+
+    raise NotImplementedError(
+        f"Age band {age_band.value} not handled for sandstone wall insulation mapping"
+    )
+
+
+def map_cob_wall_insulation(age_band: EpcConstructionAgeBand):
+    if age_band.start_year() < 1983:
+        return EpcWallDescriptions.cob_as_built_average
+
+    if age_band in EpcConstructionAgeBand.from_year_onwards(1983):
+        return EpcWallDescriptions.cob_as_built_good
+
+    raise NotImplementedError(
+        f"Age band {age_band.value} not handled for cob wall insulation mapping"
+    )
+
+
+as_built_wall_classifiers = {
+    "Cavity": map_cavity_wall_insulation,
+    "Solid Brick": map_solid_wall_insulation,
+    "Timber Frame": map_timber_frame_wall_insulation,
+    "System": map_system_build_wall_insulation,
+    "Granite": map_granite_wall_insulation,
+    "Sandstone": map_sandstone_wall_insulation,
+    "Cob": map_cob_wall_insulation,
+}

backend/onboarders/mappings/parity/built_form.py

@@ -0,0 +1,10 @@
+from datatypes.epc.property_type_built_form import BuiltForm
+
+parity_map = {
+    "MidTerrace": BuiltForm.mid_terrace,
+    "EndTerrace": BuiltForm.end_terrace,
+    "Detached": BuiltForm.detached,
+    "SemiDetached": BuiltForm.semi_detached,
+    "EnclosedMidTerrace": BuiltForm.enclosed_mid_terrace,
+    "EnclosedEndTerrace": BuiltForm.enclosed_end_terrace,
+}

backend/onboarders/mappings/parity/floor.py

@@ -0,0 +1,26 @@
+from numpy import nan
+from datatypes.epc.floor import EpcFloorDescriptions
+
+floor_map = {
+    # Solid floor
+    ('Solid', 'AsBuilt'): None,  # Mapped
+    ('Solid', 'Unknown'): None,  # Mapped
+    ('Solid', nan): None,  # Mapped
+    ('Solid', 'RetroFitted'): EpcFloorDescriptions.solid_insulated,
+
+    # Suspended floor
+    ('SuspendedTimber', nan): None,  # Mapped suspended_floor_as_built
+    ('SuspendedTimber', 'AsBuilt'): None,  # Mapped suspended_floor_as_built
+    ('SuspendedTimber', 'RetroFitted'): EpcFloorDescriptions.suspended_insulated,
+    ('SuspendedTimber', 'Unknown'): None,  # Mapped suspended_floor_as_built
+    ('SuspendedNotTimber', 'RetroFitted'): EpcFloorDescriptions.suspended_insulated,
+    ('SuspendedNotTimber', nan): None,  # Mapped suspended_floor_as_built
+    ('SuspendedNotTimber', 'Unknown'): None,  # Mapped suspended_floor_as_built
+    ('SuspendedNotTimber', 'AsBuilt'): None,  # Mapped suspended_floor_as_built
+
+    # Unknown type - mapped on age
+    ('Unknown', 'Unknown'): None,  # Mapped unknown_floor_as_built
+    ('Unknown', 'RetroFitted'): None,  # Mapped unknown_floor_retrofitted
+    (nan, nan): None,  # No actual information!
+    ('Unknown', 'AsBuilt'): None,  # Mapped unknown_floor_as_built
+}

backend/onboarders/mappings/parity/glazing.py

@@ -0,0 +1,20 @@
+from datatypes.epc.efficiency import EpcEfficiency
+
+glazing_map = {
+    # (description, energy efficiency, multi_glaze_proportion, glazed_type, glazed_area
+    # For SAP 10 assessments, The glazed type and glazed area are not populated in the EPC API data any more
+    "Double 2002 or later": ("Fully double glazed", EpcEfficiency.AVERAGE, 1, None, None),
+    "Double before 2002": ("Fully double glazed", EpcEfficiency.POOR, 1, None, None),
+    "Double but age unknown": ("Fully double glazed", EpcEfficiency.POOR, 1, None, None),
+    "Single": ("Single glazed", EpcEfficiency.VERY_POOR, 0, None, None),
+    # For triple glazing, with age unknown, the performance is only average, whereas if it's a post 2022
+    # installation, it's classed as high performance glazing with good efficiency. We'll need to be considerate as to
+    # how we make updates to the windows data.
+    # Triple known data is high performance glazing with Good efficiency (at least)
+    "Triple": ("Fully triple glazed", EpcEfficiency.AVERAGE, 1, None, None),
+    # This is also classed as high performance glazing
+    "DoubleKnownData": ("High performance glazing", EpcEfficiency.GOOD, 1, None, None),
+    # Under SAP 10, secondary glazing is classed as poor efficiency (whereas under SAP 2012 it was generally good)
+    "Secondary": ("Full secondary glazing", EpcEfficiency.POOR, 1, None, None),
+    "TripleKnownData": ("High performance glazing", EpcEfficiency.GOOD, 1, None, None),
+}

backend/onboarders/mappings/parity/heating.py

@@ -0,0 +1,330 @@
+from datatypes.epc.main_heating import EpcHeatingSystems
+from datatypes.epc.efficiency import EpcEfficiency
+from datatypes.epc.fuel import EpcFuel
+from datatypes.epc.heating_controls import EpcHeatingControls
+from datatypes.epc.hotwater import EpcHotWaterSystems
+
+heating_map = {
+    # 0
+    ('Boilers', 'A', 'ElectricityNotCommunity', 'Optimal'): (
+        EpcHeatingSystems.boiler_and_radiators_electric, EpcEfficiency.VERY_POOR, EpcFuel.electricity_not_community,
+        EpcHeatingControls.programmer_room_thermostat_trvs, EpcEfficiency.GOOD,
+        EpcHotWaterSystems.from_main_system, EpcEfficiency.AVERAGE
+    ),
+    # 1
+    ('Boilers', 'A', 'ElectricityNotCommunity', 'Sub Optimal'): (
+        EpcHeatingSystems.boiler_and_radiators_electric, EpcEfficiency.VERY_POOR, EpcFuel.electricity_not_community,
+        EpcHeatingControls.programmers_trvs_bypass, EpcEfficiency.AVERAGE,
+        EpcHotWaterSystems.from_main_system, EpcEfficiency.AVERAGE
+    ),
+    # 2
+    ('Boilers', 'A', 'ElectricityNotCommunity', 'Top Spec'): (
+        EpcHeatingSystems.boiler_and_radiators_electric, EpcEfficiency.VERY_POOR, EpcFuel.electricity_not_community,
+        EpcHeatingControls.time_and_temperature_zone_control, EpcEfficiency.VERY_GOOD,
+        EpcHotWaterSystems.from_main_system, EpcEfficiency.AVERAGE
+    ),
+    # 3
+    ('Boilers', 'A', 'LPGNotCommunity', 'Optimal'): (
+        EpcHeatingSystems.boiler_and_radiators_lpg, EpcEfficiency.POOR, EpcFuel.lpg_not_community,
+        EpcHeatingControls.programmer_room_thermostat_trvs, EpcEfficiency.GOOD,
+        EpcHotWaterSystems.from_main_system, EpcEfficiency.AVERAGE
+    ),
+    # 4
+    ('Boilers', 'A', 'MainsGasNotCommunity', 'Optimal'): (
+        EpcHeatingSystems.boiler_radiators_mains_gas, EpcEfficiency.VERY_GOOD, EpcFuel.mains_gas_not_community,
+        EpcHeatingControls.programmer_room_thermostat_trvs, EpcEfficiency.GOOD,
+        EpcHotWaterSystems.from_main_system, EpcEfficiency.AVERAGE
+    ),
+    # 5
+    ('Boilers', 'A', 'MainsGasNotCommunity', 'Sub Optimal'): (
+        EpcHeatingSystems.boiler_radiators_mains_gas, EpcEfficiency.VERY_GOOD, EpcFuel.mains_gas_not_community,
+        EpcHeatingControls.programmers_trvs_bypass, EpcEfficiency.AVERAGE,
+        EpcHotWaterSystems.from_main_system, EpcEfficiency.AVERAGE
+    ),
+    # 6
+    ('Boilers', 'A', 'MainsGasNotCommunity', 'Top Spec'): (
+        EpcHeatingSystems.boiler_radiators_mains_gas, EpcEfficiency.VERY_GOOD, EpcFuel.mains_gas_not_community,
+        EpcHeatingControls.time_and_temperature_zone_control, EpcEfficiency.VERY_GOOD,
+        EpcHotWaterSystems.from_main_system, EpcEfficiency.AVERAGE
+    ),
+    # 7
+    ('Boilers', 'B', 'MainsGasNotCommunity', 'Optimal'): (
+        EpcHeatingSystems.boiler_radiators_mains_gas, EpcEfficiency.GOOD, EpcFuel.mains_gas_not_community,
+        EpcHeatingControls.programmer_room_thermostat_trvs, EpcEfficiency.GOOD,
+        EpcHotWaterSystems.from_main_system, EpcEfficiency.AVERAGE
+    ),
+    # 8
+    ('Boilers', 'B', 'MainsGasNotCommunity', 'Sub Optimal'): (
+        EpcHeatingSystems.boiler_radiators_mains_gas, EpcEfficiency.GOOD, EpcFuel.mains_gas_not_community,
+        EpcHeatingControls.programmers_trvs_bypass, EpcEfficiency.AVERAGE,
+        EpcHotWaterSystems.from_main_system, EpcEfficiency.AVERAGE
+    ),
+    # 9
+    ('Boilers', 'B', 'MainsGasNotCommunity', 'Top Spec'): (
+        EpcHeatingSystems.boiler_radiators_mains_gas, EpcEfficiency.GOOD, EpcFuel.mains_gas_not_community,
+        EpcHeatingControls.time_and_temperature_zone_control, EpcEfficiency.VERY_GOOD,
+        EpcHotWaterSystems.from_main_system, EpcEfficiency.AVERAGE
+    ),
+    # 10
+    ('Boilers', 'C', 'ElectricityNotCommunity', 'Optimal'): (
+        EpcHeatingSystems.boiler_and_radiators_electric, EpcEfficiency.VERY_POOR, EpcFuel.electricity_not_community,
+        EpcHeatingControls.programmer_room_thermostat_trvs, EpcEfficiency.GOOD,
+        EpcHotWaterSystems.from_main_system, EpcEfficiency.AVERAGE
+    ),
+    # 11
+    ('Boilers', 'C', 'ElectricityNotCommunity', 'Sub Optimal'): (
+        EpcHeatingSystems.boiler_and_radiators_electric, EpcEfficiency.VERY_POOR, EpcFuel.electricity_not_community,
+        EpcHeatingControls.programmers_trvs_bypass, EpcEfficiency.AVERAGE,
+        EpcHotWaterSystems.from_main_system, EpcEfficiency.AVERAGE
+    ),
+    # 12
+    ('Boilers', 'C', 'ElectricityNotCommunity', 'Top Spec'): (
+        EpcHeatingSystems.boiler_and_radiators_electric, EpcEfficiency.VERY_POOR, EpcFuel.electricity_not_community,
+        EpcHeatingControls.time_and_temperature_zone_control, EpcEfficiency.VERY_GOOD,
+        EpcHotWaterSystems.from_main_system, EpcEfficiency.AVERAGE
+    ),
+    # 13
+    ('Boilers', 'C', 'LPGNotCommunity', 'Optimal'): (
+        EpcHeatingSystems.boiler_and_radiators_lpg, EpcEfficiency.POOR, EpcFuel.lpg_not_community,
+        EpcHeatingControls.programmer_room_thermostat_trvs, EpcEfficiency.GOOD,
+        EpcHotWaterSystems.from_main_system, EpcEfficiency.AVERAGE
+    ),
+    # 14
+    ('Boilers', 'C', 'LPGNotCommunity', 'Sub Optimal'): (
+        EpcHeatingSystems.boiler_and_radiators_lpg, EpcEfficiency.POOR, EpcFuel.lpg_not_community,
+        EpcHeatingControls.programmers_trvs_bypass, EpcEfficiency.AVERAGE,
+        EpcHotWaterSystems.from_main_system, EpcEfficiency.AVERAGE
+    ),
+    # 15
+    ('Boilers', 'C', 'MainsGasNotCommunity', 'Optimal'): (
+        EpcHeatingSystems.boiler_radiators_mains_gas, EpcEfficiency.GOOD, EpcFuel.mains_gas_not_community,
+        EpcHeatingControls.programmer_room_thermostat_trvs, EpcEfficiency.GOOD,
+        EpcHotWaterSystems.from_main_system, EpcEfficiency.AVERAGE
+    ),
+    # 16
+    ('Boilers', 'C', 'MainsGasNotCommunity', 'Sub Optimal'): (
+        EpcHeatingSystems.boiler_radiators_mains_gas, EpcEfficiency.GOOD, EpcFuel.mains_gas_not_community,
+        EpcHeatingControls.programmers_trvs_bypass, EpcEfficiency.AVERAGE,
+        EpcHotWaterSystems.from_main_system, EpcEfficiency.AVERAGE
+    ),
+    # 17
+    ('Boilers', 'C', 'MainsGasNotCommunity', 'Top Spec'): (
+        EpcHeatingSystems.boiler_radiators_mains_gas, EpcEfficiency.GOOD, EpcFuel.mains_gas_not_community,
+        EpcHeatingControls.time_and_temperature_zone_control, EpcEfficiency.VERY_GOOD,
+        EpcHotWaterSystems.from_main_system, EpcEfficiency.AVERAGE
+    ),
+    ('Boilers', 'C', 'OilNotCommunity', 'Optimal'): (
+        EpcHeatingSystems.boiler_radiators_oil, EpcEfficiency.AVERAGE, EpcFuel.oil_not_community,
+        EpcHeatingControls.programmer_room_thermostat_trvs, EpcEfficiency.GOOD,
+        EpcHotWaterSystems.from_main_system, EpcEfficiency.AVERAGE
+    ),
+    # 19
+    ('Boilers', 'C', 'OilNotCommunity', 'Sub Optimal'): (
+        EpcHeatingSystems.boiler_radiators_oil, EpcEfficiency.AVERAGE, EpcFuel.oil_not_community,
+        EpcHeatingControls.programmers_trvs_bypass, EpcEfficiency.AVERAGE,
+        EpcHotWaterSystems.from_main_system, EpcEfficiency.AVERAGE
+    ),
+    # 20
+    ('Boilers', 'C', 'OilNotCommunity', 'Top Spec'): (
+        EpcHeatingSystems.boiler_radiators_oil, EpcEfficiency.AVERAGE, EpcFuel.oil_not_community,
+        EpcHeatingControls.time_and_temperature_zone_control, EpcEfficiency.VERY_GOOD,
+        EpcHotWaterSystems.from_main_system, EpcEfficiency.AVERAGE
+    ),
+    # 21
+    ('Boilers', 'D', 'MainsGasNotCommunity', 'Optimal'): (
+        EpcHeatingSystems.boiler_radiators_mains_gas, EpcEfficiency.GOOD, EpcFuel.mains_gas_not_community,
+        EpcHeatingControls.programmer_room_thermostat_trvs, EpcEfficiency.GOOD,
+        EpcHotWaterSystems.from_main_system, EpcEfficiency.AVERAGE
+    ),
+    # 22
+    ('Boilers', 'D', 'MainsGasNotCommunity', 'Sub Optimal'): (
+        EpcHeatingSystems.boiler_radiators_mains_gas, EpcEfficiency.GOOD, EpcFuel.mains_gas_not_community,
+        EpcHeatingControls.programmers_trvs_bypass, EpcEfficiency.AVERAGE,
+        EpcHotWaterSystems.from_main_system, EpcEfficiency.AVERAGE
+    ),
+    # 23
+    ('Boilers', 'D', 'MainsGasNotCommunity', 'Top Spec'): (
+        EpcHeatingSystems.boiler_radiators_mains_gas, EpcEfficiency.GOOD, EpcFuel.mains_gas_not_community,
+        EpcHeatingControls.time_and_temperature_zone_control, EpcEfficiency.VERY_GOOD,
+        EpcHotWaterSystems.from_main_system, EpcEfficiency.AVERAGE
+    ),
+    # 24
+    ('Boilers', 'E', 'ElectricityNotCommunity', 'Optimal'): (
+        EpcHeatingSystems.boiler_and_radiators_electric, EpcEfficiency.VERY_POOR, EpcFuel.electricity_not_community,
+        EpcHeatingControls.programmer_room_thermostat_trvs, EpcEfficiency.GOOD,
+        EpcHotWaterSystems.from_main_system, EpcEfficiency.AVERAGE
+    ),
+    # 25
+    ('Boilers', 'E', 'MainsGasNotCommunity', 'Optimal'): (
+        EpcHeatingSystems.boiler_radiators_mains_gas, EpcEfficiency.GOOD, EpcFuel.mains_gas_not_community,
+        EpcHeatingControls.programmer_room_thermostat_trvs, EpcEfficiency.GOOD,
+        EpcHotWaterSystems.from_main_system, EpcEfficiency.AVERAGE
+    ),
+    # 26
+    ('Boilers', 'E', 'MainsGasNotCommunity', 'Sub Optimal'): (
+        EpcHeatingSystems.boiler_radiators_mains_gas, EpcEfficiency.GOOD, EpcFuel.mains_gas_not_community,
+        EpcHeatingControls.programmers_trvs_bypass, EpcEfficiency.AVERAGE,
+        EpcHotWaterSystems.from_main_system, EpcEfficiency.AVERAGE
+    ),
+    # 27
+    ('Boilers', 'E', 'MainsGasNotCommunity', 'Top Spec'): (
+        EpcHeatingSystems.boiler_radiators_mains_gas, EpcEfficiency.GOOD, EpcFuel.mains_gas_not_community,
+        EpcHeatingControls.time_and_temperature_zone_control, EpcEfficiency.VERY_GOOD,
+        EpcHotWaterSystems.from_main_system, EpcEfficiency.AVERAGE
+    ),
+    # 28
+    ('Boilers', 'E', 'OilNotCommunity', 'Optimal'): (
+        EpcHeatingSystems.boiler_radiators_oil, EpcEfficiency.AVERAGE, EpcFuel.oil_not_community,
+        EpcHeatingControls.programmer_room_thermostat_trvs, EpcEfficiency.GOOD,
+        EpcHotWaterSystems.from_main_system, EpcEfficiency.AVERAGE
+    ),
+    # 29
+    ('Boilers', 'E', 'OilNotCommunity', 'Sub Optimal'): (
+        EpcHeatingSystems.boiler_radiators_oil, EpcEfficiency.AVERAGE, EpcFuel.oil_not_community,
+        EpcHeatingControls.programmers_trvs_bypass, EpcEfficiency.AVERAGE,
+        EpcHotWaterSystems.from_main_system, EpcEfficiency.AVERAGE
+    ),
+    # 30
+    ('Boilers', 'F', 'MainsGasNotCommunity', 'Optimal'): (
+        EpcHeatingSystems.boiler_radiators_mains_gas, EpcEfficiency.GOOD, EpcFuel.mains_gas_not_community,
+        EpcHeatingControls.programmer_room_thermostat_trvs, EpcEfficiency.GOOD,
+        EpcHotWaterSystems.from_main_system, EpcEfficiency.AVERAGE
+    ),
+    # 31
+    ('Boilers', 'F', 'MainsGasNotCommunity', 'Sub Optimal'): (
+        EpcHeatingSystems.boiler_radiators_mains_gas, EpcEfficiency.GOOD, EpcFuel.mains_gas_not_community,
+        EpcHeatingControls.programmers_trvs_bypass, EpcEfficiency.AVERAGE,
+        EpcHotWaterSystems.from_main_system, EpcEfficiency.AVERAGE
+    ),
+    # 32
+    ('Boilers', 'F', 'MainsGasNotCommunity', 'Top Spec'): (
+        EpcHeatingSystems.boiler_radiators_mains_gas, EpcEfficiency.GOOD, EpcFuel.mains_gas_not_community,
+        EpcHeatingControls.time_and_temperature_zone_control, EpcEfficiency.VERY_GOOD,
+        EpcHotWaterSystems.from_main_system, EpcEfficiency.AVERAGE
+    ),
+    # 33
+    ('Boilers', 'G', 'MainsGasNotCommunity', 'Optimal'): (
+        EpcHeatingSystems.boiler_radiators_mains_gas, EpcEfficiency.GOOD, EpcFuel.mains_gas_not_community,
+        EpcHeatingControls.programmer_room_thermostat_trvs, EpcEfficiency.GOOD,
+        EpcHotWaterSystems.from_main_system, EpcEfficiency.AVERAGE
+    ),
+    # 34
+    ('Boilers', 'G', 'MainsGasNotCommunity', 'Sub Optimal'): (
+        EpcHeatingSystems.boiler_radiators_mains_gas, EpcEfficiency.GOOD, EpcFuel.mains_gas_not_community,
+        EpcHeatingControls.programmers_trvs_bypass, EpcEfficiency.AVERAGE,
+        EpcHotWaterSystems.from_main_system, EpcEfficiency.AVERAGE
+    ),
+    # 35
+    ('Boilers', 'G', 'MainsGasNotCommunity', 'Top Spec'): (
+        EpcHeatingSystems.boiler_radiators_mains_gas, EpcEfficiency.AVERAGE, EpcFuel.mains_gas_not_community,
+        EpcHeatingControls.time_and_temperature_zone_control, EpcEfficiency.VERY_GOOD,
+        EpcHotWaterSystems.from_main_system, EpcEfficiency.AVERAGE
+    ),
+    # 36
+    ('Electric underfloor', 'A', 'ElectricityNotCommunity', 'Optimal'): (
+        EpcHeatingSystems.electric_underfloor_heating, EpcEfficiency.AVERAGE, EpcFuel.electricity_not_community,
+        EpcHeatingControls.programmer_room_thermostat_trvs, EpcEfficiency.GOOD,
+        EpcHotWaterSystems.electric_immersion_off_peak, EpcEfficiency.AVERAGE
+    ),
+    # 37
+    ('Electric underfloor', 'A', 'ElectricityNotCommunity', 'Sub Optimal'): (
+        EpcHeatingSystems.electric_underfloor_heating, EpcEfficiency.AVERAGE, EpcFuel.electricity_not_community,
+        EpcHeatingControls.programmers_trvs_bypass, EpcEfficiency.AVERAGE,
+        EpcHotWaterSystems.electric_immersion_off_peak, EpcEfficiency.AVERAGE
+    ),
+    # 38
+    ('Electric underfloor', 'A', 'ElectricityNotCommunity', 'Top Spec'): (
+        EpcHeatingSystems.electric_underfloor_heating, EpcEfficiency.AVERAGE, EpcFuel.electricity_not_community,
+        EpcHeatingControls.time_and_temperature_zone_control, EpcEfficiency.VERY_GOOD,
+        EpcHotWaterSystems.electric_immersion_off_peak, EpcEfficiency.AVERAGE
+    ),
+    # 39
+    ('Heat pumps (warm air)', 'A', 'ElectricityNotCommunity', 'Optimal'): (
+        EpcHeatingSystems.air_to_air_ashp, EpcEfficiency.AVERAGE, EpcFuel.electricity_not_community,
+        EpcHeatingControls.programmer_room_thermostat_trvs, EpcEfficiency.GOOD,
+        EpcHotWaterSystems.from_main_system, EpcEfficiency.AVERAGE
+    ),
+    # 40
+    ('Heat pumps (warm air)', 'A', 'ElectricityNotCommunity', 'Sub Optimal'): (
+        EpcHeatingSystems.air_to_air_ashp, EpcEfficiency.AVERAGE, EpcFuel.electricity_not_community,
+        EpcHeatingControls.programmers_trvs_bypass, EpcEfficiency.AVERAGE,
+        EpcHotWaterSystems.from_main_system, EpcEfficiency.AVERAGE
+    ),
+    # 41
+    ('Heat pumps (wet)', 'A', 'ElectricityNotCommunity', 'Optimal'): (
+        EpcHeatingSystems.ashp_radiators_electric, EpcEfficiency.GOOD, EpcFuel.electricity_not_community,
+        EpcHeatingControls.programmer_room_thermostat_trvs, EpcEfficiency.GOOD,
+        EpcHotWaterSystems.from_main_system, EpcEfficiency.AVERAGE
+    ),
+    # 42
+    ('Heat pumps (wet)', 'A', 'ElectricityNotCommunity', 'Sub Optimal'): (
+        EpcHeatingSystems.ashp_radiators_electric, EpcEfficiency.GOOD, EpcFuel.electricity_not_community,
+        EpcHeatingControls.programmers_trvs_bypass, EpcEfficiency.AVERAGE,
+        EpcHotWaterSystems.from_main_system, EpcEfficiency.AVERAGE
+    ),
+    # 43
+    ('Heat pumps (wet)', 'A', 'ElectricityNotCommunity', 'Top Spec'): (
+        EpcHeatingSystems.ashp_radiators_electric, EpcEfficiency.GOOD, EpcFuel.electricity_not_community,
+        EpcHeatingControls.time_and_temperature_zone_control, EpcEfficiency.VERY_GOOD,
+        EpcHotWaterSystems.from_main_system, EpcEfficiency.AVERAGE
+    ),
+    # 44
+    ('Room heaters', 'A', 'ElectricityNotCommunity', 'Optimal'): (
+        EpcHeatingSystems.room_heaters_electric, EpcEfficiency.POOR, EpcFuel.electricity_not_community,
+        EpcHeatingControls.programmer_and_appliance_thermostats, EpcEfficiency.GOOD,
+        EpcHotWaterSystems.electric_immersion_off_peak, EpcEfficiency.AVERAGE
+    ),
+    # 45
+    ('Room heaters', 'A', 'ElectricityNotCommunity', 'Sub Optimal'): (
+        EpcHeatingSystems.room_heaters_electric, EpcEfficiency.POOR, EpcFuel.electricity_not_community,
+        EpcHeatingControls.appliance_thermostats, EpcEfficiency.GOOD,
+        EpcHotWaterSystems.electric_immersion_off_peak, EpcEfficiency.AVERAGE
+    ),
+    # 46
+    ('Room heaters', 'C', 'MainsGasNotCommunity', 'Sub Optimal'): (
+        EpcHeatingSystems.room_heaters_mains_gas, EpcEfficiency.AVERAGE, EpcFuel.mains_gas_not_community,
+        EpcHeatingControls.appliance_thermostats, EpcEfficiency.GOOD,
+        EpcHotWaterSystems.electric_immersion_off_peak, EpcEfficiency.AVERAGE
+    ),
+    # 47 - water done from here
+    ('Room heaters', 'F', 'MainsGasNotCommunity', 'Sub Optimal'): (
+        EpcHeatingSystems.room_heaters_mains_gas, EpcEfficiency.POOR, EpcFuel.mains_gas_not_community,
+        EpcHeatingControls.appliance_thermostats, EpcEfficiency.GOOD,
+        EpcHotWaterSystems.electric_immersion_off_peak, EpcEfficiency.AVERAGE
+    ),
+    ('Room heaters', 'G', 'MainsGasNotCommunity', 'Optimal'): (
+        EpcHeatingSystems.room_heaters_mains_gas, EpcEfficiency.POOR, EpcFuel.mains_gas_not_community,
+        EpcHeatingControls.programmer_and_appliance_thermostats, EpcEfficiency.GOOD,
+        EpcHotWaterSystems.electric_immersion_off_peak, EpcEfficiency.AVERAGE
+    ),
+    ('Room heaters', 'G', 'MainsGasNotCommunity', 'Sub Optimal'): (
+        EpcHeatingSystems.room_heaters_mains_gas, EpcEfficiency.POOR, EpcFuel.mains_gas_not_community,
+        EpcHeatingControls.appliance_thermostats, EpcEfficiency.GOOD,
+        EpcHotWaterSystems.electric_immersion_off_peak, EpcEfficiency.AVERAGE
+    ),
+    ('Room heaters', 'G', 'SmokelessCoal', 'Sub Optimal'): (
+        EpcHeatingSystems.room_heaters_smokeless_fuel, EpcEfficiency.VERY_POOR, EpcFuel.smokeless_coal,
+        EpcHeatingControls.appliance_thermostats, EpcEfficiency.GOOD,
+        EpcHotWaterSystems.electric_immersion_off_peak, EpcEfficiency.AVERAGE
+    ),
+    ('Storage heaters', 'A', 'ElectricityNotCommunity', 'Optimal'): (
+        EpcHeatingSystems.electric_storage_heaters, EpcEfficiency.AVERAGE, EpcFuel.electricity_not_community,
+        EpcHeatingControls.automatic_charge_control, EpcEfficiency.AVERAGE,
+        EpcHotWaterSystems.electric_immersion_off_peak, EpcEfficiency.AVERAGE
+    ),
+    ('Storage heaters', 'A', 'ElectricityNotCommunity', 'Sub Optimal'): (
+        EpcHeatingSystems.electric_storage_heaters, EpcEfficiency.AVERAGE, EpcFuel.electricity_not_community,
+        EpcHeatingControls.manual_charge_control, EpcEfficiency.POOR,
+        EpcHotWaterSystems.electric_immersion_off_peak, EpcEfficiency.AVERAGE
+    ),
+    ('Warm Air (not heat pump)', 'G', 'ElectricityNotCommunity', 'Sub Optimal'): (
+        EpcHeatingSystems.warm_air_electricaire, EpcEfficiency.GOOD, EpcFuel.electricity_not_community,
+        EpcHeatingControls.programmer_and_atleast_two_room_thermostats, EpcEfficiency.GOOD,
+        EpcHotWaterSystems.electric_immersion_off_peak, EpcEfficiency.AVERAGE
+    ),
+    ('Warm Air (not heat pump)', 'G', 'MainsGasNotCommunity', 'Sub Optimal'): (
+        EpcHeatingSystems.warm_air_mains_gas, EpcEfficiency.GOOD, EpcFuel.mains_gas_not_community,
+        EpcHeatingControls.programmer_and_atleast_two_room_thermostats, EpcEfficiency.GOOD,
+        EpcHotWaterSystems.electric_immersion_off_peak, EpcEfficiency.AVERAGE
+    )
+}

backend/onboarders/mappings/parity/property_type.py

@@ -0,0 +1,8 @@
+from datatypes.epc.property_type_built_form import PropertyType
+
+parity_map = {
+    "Flat": PropertyType.flat,
+    "Maisonette": PropertyType.maisonette,
+    "Bungalow": PropertyType.bungalow,
+    "House": PropertyType.house,
+}

backend/onboarders/mappings/parity/roof.py

@@ -0,0 +1,461 @@
+import pandas as pd
+from numpy import nan
+from typing import Union, Callable
+from collections.abc import Mapping
+from datatypes.epc.roof import EpcRoofDescriptions
+from datatypes.epc.efficiency import EpcEfficiency
+from datatypes.epc.construction_age_band import EpcConstructionAgeBand
+
+roof_map = {
+    # Dwelling above
+    ('AnotherDwellingAbove', 'Another Dwelling Above'): EpcRoofDescriptions.another_dwelling_above,
+    ('SameDwellingAbove', 'Same Dwelling Above'): EpcRoofDescriptions.another_dwelling_above,
+    # Pitched, normal loft access, with a loft thickness
+    ('PitchedNormalLoftAccess', 'mm25'): EpcRoofDescriptions.loft_25mm_insulation,
+    ('PitchedNormalLoftAccess', 'mm50'): EpcRoofDescriptions.loft_50mm_insulation,
+    ('PitchedNormalLoftAccess', 'mm75'): EpcRoofDescriptions.loft_75mm_insulation,
+    ('PitchedNormalLoftAccess', 'mm100'): EpcRoofDescriptions.loft_100mm_insulation,
+    ('PitchedNormalLoftAccess', 'mm150'): EpcRoofDescriptions.loft_150mm_insulation,
+    ('PitchedNormalLoftAccess', 'mm200'): EpcRoofDescriptions.loft_200mm_insulation,
+    ('PitchedNormalLoftAccess', 'mm250'): EpcRoofDescriptions.loft_250mm_insulation,
+    ('PitchedNormalLoftAccess', 'mm270'): EpcRoofDescriptions.loft_270mm_insulation,
+    ('PitchedNormalLoftAccess', 'mm300'): EpcRoofDescriptions.loft_300mm_insulation,
+    ('PitchedNormalLoftAccess', 'mm350'): EpcRoofDescriptions.loft_350mm_insulation,
+    ('PitchedNormalLoftAccess', 'mm400'): EpcRoofDescriptions.loft_400mm_plus_insulation,
+
+    # Pitched, no loft access, with a loft thickness
+    ('PitchedNormalNoLoftAccess', 'mm25'): EpcRoofDescriptions.loft_25mm_insulation,
+    ('PitchedNormalNoLoftAccess', 'mm50'): EpcRoofDescriptions.loft_50mm_insulation,
+    ('PitchedNormalNoLoftAccess', 'mm75'): EpcRoofDescriptions.loft_75mm_insulation,
+    ('PitchedNormalNoLoftAccess', 'mm100'): EpcRoofDescriptions.loft_100mm_insulation,
+    ('PitchedNormalNoLoftAccess', 'mm150'): EpcRoofDescriptions.loft_150mm_insulation,
+    ('PitchedNormalNoLoftAccess', 'mm200'): EpcRoofDescriptions.loft_200mm_insulation,
+    ('PitchedNormalNoLoftAccess', 'mm250'): EpcRoofDescriptions.loft_250mm_insulation,
+    ('PitchedNormalNoLoftAccess', 'mm270'): EpcRoofDescriptions.loft_270mm_insulation,
+    ('PitchedNormalNoLoftAccess', 'mm300'): EpcRoofDescriptions.loft_300mm_insulation,
+    ('PitchedNormalNoLoftAccess', 'mm350'): EpcRoofDescriptions.loft_350mm_insulation,
+    ('PitchedNormalNoLoftAccess', 'mm400'): EpcRoofDescriptions.loft_400mm_plus_insulation,
+
+    # All pitched options with asbuilt or unknown got to EpcRoofDescriptions.pitched_insulated_assumed
+    # With access
+    ('PitchedNormalLoftAccess', nan): EpcRoofDescriptions.pitched_insulated_assumed,
+    ('PitchedNormalLoftAccess', 'AsBuilt'): EpcRoofDescriptions.pitched_insulated_assumed,
+    ('PitchedNormalLoftAccess', 'Unknown'): EpcRoofDescriptions.pitched_insulated_assumed,
+    # No access
+    ('PitchedNormalNoLoftAccess', nan): EpcRoofDescriptions.pitched_insulated_assumed,
+    ('PitchedNormalNoLoftAccess', 'AsBuilt'): EpcRoofDescriptions.pitched_insulated_assumed,
+    ('PitchedNormalNoLoftAccess', 'Unknown'): EpcRoofDescriptions.pitched_insulated_assumed,
+
+    # Flat
+    ('Flat', 'NoInsulation'): EpcRoofDescriptions.flat_no_insulation,
+    # Flat - limited insulation
+    ('Flat', '12mm'): EpcRoofDescriptions.flat_limited_insulation,
+    ('Flat', 'mm25'): EpcRoofDescriptions.flat_limited_insulation,
+    ('Flat', 'mm50'): EpcRoofDescriptions.flat_limited_insulation,
+    # Flat insulated
+    ('Flat', 'mm75'): EpcRoofDescriptions.flat_insulated,
+    ('Flat', 'mm100'): EpcRoofDescriptions.flat_insulated,
+    ('Flat', 'mm150'): EpcRoofDescriptions.flat_insulated,
+    ('Flat', 'mm200'): EpcRoofDescriptions.flat_insulated,
+    ('Flat', 'mm250'): EpcRoofDescriptions.flat_insulated,
+    ('Flat', 'mm300'): EpcRoofDescriptions.flat_insulated,
+    ('Flat', 'mm350'): EpcRoofDescriptions.flat_insulated,
+    ('Flat', 'mm400'): EpcRoofDescriptions.flat_insulated,
+    # Flat - as built or unknown
+    ('Flat', 'AsBuilt'): None,  # To be classified
+    ('Flat', nan): None,  # To be classified
+    ('Flat', 'Unknown'): None,  # To be classified
+
+    # 12mm = very poor & has limited insulation description
+    # 25, 50 = poor & has limited insulation description
+    # 75, 100, 125mm = average (Flat, insulated)
+    # 150, 175, 200, 225, 250mm = good (Flat, insulated)
+    # 270mm+ = very good (Flat, insulated)
+
+    # Thatched
+    ('PitchedThatched', 'mm50'): EpcRoofDescriptions.thatched_with_additional_insulation,
+    ('PitchedThatched', 'mm150'): EpcRoofDescriptions.thatched_with_additional_insulation,
+    ('PitchedThatched', 'mm300'): EpcRoofDescriptions.thatched_with_additional_insulation,
+    ('PitchedThatched', 'Unknown'): EpcRoofDescriptions.thatched,  # efficiency classified based on age
+
+    # Sloping:
+    # Limited (12 very poor, 25-50 poor)
+    ('PitchedWithSlopingCeiling', 'mm12'): EpcRoofDescriptions.sloping_pitched_limited_insulation,
+    ('PitchedWithSlopingCeiling', 'mm25'): EpcRoofDescriptions.sloping_pitched_limited_insulation,
+    ('PitchedWithSlopingCeiling', 'mm50'): EpcRoofDescriptions.sloping_pitched_limited_insulation,
+    # Insulated 75mm+ (75 - 125 average, 150 - 250 good, 270+ very good)
+    ('PitchedWithSlopingCeiling', 'mm75'): EpcRoofDescriptions.sloping_pitched_insulated,
+    ('PitchedWithSlopingCeiling', 'mm100'): EpcRoofDescriptions.sloping_pitched_insulated,
+    ('PitchedWithSlopingCeiling', 'mm150'): EpcRoofDescriptions.sloping_pitched_insulated,
+    ('PitchedWithSlopingCeiling', 'mm200'): EpcRoofDescriptions.sloping_pitched_insulated,
+    ('PitchedWithSlopingCeiling', 'mm250'): EpcRoofDescriptions.sloping_pitched_insulated,
+    ('PitchedWithSlopingCeiling', 'mm270'): EpcRoofDescriptions.sloping_pitched_insulated,
+    ('PitchedWithSlopingCeiling', 'mm300'): EpcRoofDescriptions.sloping_pitched_insulated,
+    ('PitchedWithSlopingCeiling', 'mm350'): EpcRoofDescriptions.sloping_pitched_insulated,
+    ('PitchedWithSlopingCeiling', 'mm400'): EpcRoofDescriptions.sloping_pitched_insulated,
+    # As built/unknown
+    ('PitchedWithSlopingCeiling', 'AsBuilt'): None,  # To be classified
+    ('PitchedWithSlopingCeiling', nan): None,  # To be classified
+    ('PitchedWithSlopingCeiling', 'Unknown'): None,  #
+}
+
+roof_unknown_age_fallback = {
+    "Flat": EpcRoofDescriptions.flat_as_built_unknown,
+    "PitchedWithSlopingCeiling": EpcRoofDescriptions.sloping_pitched_as_built_unknown,
+    "PitchedThatched": EpcRoofDescriptions.thatched_as_built_unknown,
+    "PitchedNormalLoftAccess": EpcRoofDescriptions.loft_as_built_unknown,
+    "PitchedNormalNoLoftAccess": EpcRoofDescriptions.loft_as_built_unknown,
+}
+
+RoofEfficiencyRule = Union[
+    EpcEfficiency,
+    Callable[[EpcConstructionAgeBand, int | None], EpcEfficiency],
+]
+
+
+def flat_insulated_efficiency_age_band(age_band: EpcConstructionAgeBand) -> EpcEfficiency:
+    """
+    before 1900, 1900-1929, 1930-1949, 1950-1966, 1967-1975  -> Pitched, no insulation, Very Poor
+    1976-1982 -> Pitched, limited insulation, Poor
+    1983-1990, to 1996-2002 Pitched, insulated, Average
+    2003 - 2006, 2012-2022 -> Pitched, insulated, Good
+    2023 onwards -> Pitched, insulated, Very Good
+    :param age_band: EpcConstructionAgeBand
+    :return: EpcEfficiency
+    """
+
+    start_year = age_band.start_year()
+    if start_year >= 2023:
+        return EpcEfficiency.VERY_GOOD
+
+    if start_year >= 2003:
+        return EpcEfficiency.GOOD
+
+    if start_year >= 1983:
+        return EpcEfficiency.AVERAGE
+
+    if start_year >= 1976:
+        return EpcEfficiency.POOR
+
+    return EpcEfficiency.VERY_POOR
+
+
+def flat_insulated_efficiency_thickness(insulation_thickness: int | None) -> EpcEfficiency:
+    """
+    12mm -> Very Poor
+    25mm - 50mm -> Poor
+    75mm - 125mm -> Pitched, insulated, average
+    150mm - 250mm -> good
+    270mm+ -> very good
+    :param insulation_thickness: Insulation thickness in mm
+    :return: EpcEfficiency
+    """
+
+    if insulation_thickness is None:
+        raise ValueError("Insulation thickness is required for flat insulated efficiency calculation")
+
+    if insulation_thickness >= 270:
+        return EpcEfficiency.VERY_GOOD
+
+    if 150 <= insulation_thickness <= 250:
+        return EpcEfficiency.GOOD
+
+    if 75 <= insulation_thickness <= 125:
+        return EpcEfficiency.AVERAGE
+
+    if 25 <= insulation_thickness <= 50:
+        return EpcEfficiency.POOR
+
+    return EpcEfficiency.VERY_POOR
+
+
+def flat_efficiency(insulation_thickness: int | None, age_band: EpcConstructionAgeBand) -> EpcEfficiency:
+    """
+    Combines both age band and insulation thickness to determine flat roof efficiency.
+    :param insulation_thickness: Insulation thickness in mm
+    :param age_band: EpcConstructionAgeBand
+    :return: EpcEfficiency
+    """
+    if insulation_thickness is not None:
+        return flat_insulated_efficiency_thickness(insulation_thickness)
+
+    return flat_insulated_efficiency_age_band(age_band)
+
+
+def loft_insulated_efficiency(age_band: EpcConstructionAgeBand) -> EpcEfficiency:
+    """
+    2023 onwards -> Very Good
+    2012-2022 -> Very Good
+    2007-2011 -> Very Good
+    2003-2006 -> Very Good
+    1996-2002 -> Good
+    1991-1995 -> Good
+    1983-1990 -> Average
+    1976-1982 -> Average
+    1967-1975 -> Average
+    1950-1966 -> Average
+    1930-1949 -> Average
+    1900-1929 -> Average
+    before 1900 -> Average
+    :param age_band: Input age band, EpcConstructionAgeBand
+    :return: EpcEfficiency
+    """
+    year = age_band.start_year()
+    if year >= 2003:
+        return EpcEfficiency.VERY_GOOD
+    if year >= 1991:
+        return EpcEfficiency.GOOD
+
+    return EpcEfficiency.AVERAGE
+
+
+def thatched_efficiency_age_band(age_band: EpcConstructionAgeBand) -> EpcEfficiency:
+    """
+    Maps thatched roof efficiency based on construction age band.
+    :param age_band: EpcConstructionAgeBand
+    :return: EpcEfficiency
+    """
+    year = age_band.start_year()
+    if year >= 2023:
+        return EpcEfficiency.VERY_GOOD
+    if year >= 2003:
+        return EpcEfficiency.GOOD
+
+    return EpcEfficiency.AVERAGE
+
+
+def thatched_efficiency_thickness(insulation_thickness: int | None) -> EpcEfficiency:
+    """
+    Maps thatched roof efficiency based on insulation thickness.
+    :param insulation_thickness: Insulation thickness in mm
+    :return: EpcEfficiency
+    """
+    if insulation_thickness is None:
+        raise ValueError("Insulation thickness is required for thatched efficiency calculation")
+
+    if insulation_thickness >= 175:
+        return EpcEfficiency.VERY_GOOD
+
+    if insulation_thickness >= 25:
+        return EpcEfficiency.GOOD
+
+    return EpcEfficiency.AVERAGE
+
+
+def thatched_efficiency(
+    insulation_thickness: int | None,
+    age_band: EpcConstructionAgeBand,
+) -> EpcEfficiency:
+    """
+    Combines both age band and insulation thickness to determine thatched roof efficiency.
+    :param insulation_thickness: Insulation thickness in mm
+    :param age_band: EpcConstructionAgeBand
+    :return: EpcEfficiency
+    """
+    if insulation_thickness is not None:
+        return thatched_efficiency_thickness(insulation_thickness)
+
+    return thatched_efficiency_age_band(age_band)
+
+
+def sloping_ceiling_efficiency_age_band(age_band: EpcConstructionAgeBand) -> EpcEfficiency:
+    """
+    Maps sloping ceiling roof efficiency based on construction age band.
+    :param age_band: EpcConstructionAgeBand
+    :return: EpcEfficiency
+    """
+    year = age_band.start_year()
+    if year >= 2023:
+        return EpcEfficiency.VERY_GOOD
+    if year >= 2003:
+        return EpcEfficiency.GOOD
+    if year >= 1983:
+        return EpcEfficiency.AVERAGE
+    if year >= 1976:
+        return EpcEfficiency.POOR
+
+    return EpcEfficiency.VERY_POOR
+
+
+def sloping_ceiling_efficiency_thickness(insulation_thickness: int | None) -> EpcEfficiency:
+    """
+    Maps sloping ceiling roof efficiency based on insulation thickness.
+    :param insulation_thickness: Insulation thickness in mm
+    :return: EpcEfficiency
+    """
+    if insulation_thickness is None:
+        raise ValueError("Insulation thickness is required for sloping ceiling efficiency calculation")
+
+    if insulation_thickness >= 270:
+        return EpcEfficiency.VERY_GOOD
+
+    if insulation_thickness >= 150:
+        return EpcEfficiency.GOOD
+
+    if insulation_thickness >= 75:
+        return EpcEfficiency.AVERAGE
+
+    if insulation_thickness >= 25:
+        return EpcEfficiency.POOR
+
+    return EpcEfficiency.VERY_POOR
+
+
+def sloping_ceiling_efficiency(
+    insulation_thickness: int | None,
+    age_band: EpcConstructionAgeBand,
+) -> EpcEfficiency:
+    """
+    Combines both age band and insulation thickness to determine sloping ceiling roof efficiency.
+    :param insulation_thickness: Insulation thickness in mm
+    :param age_band: EpcConstructionAgeBand
+    :return: EpcEfficiency
+    """
+    if insulation_thickness is not None:
+        return sloping_ceiling_efficiency_thickness(insulation_thickness)
+
+    return sloping_ceiling_efficiency_age_band(age_band)
+
+
+def loft_insulated_at_rafters_efficiency_thickness(insulation_thickness: int | None) -> EpcEfficiency:
+    """
+    400mm, 350mm = very good
+    200-300mm = good
+    125-175 = average
+    50-100 = poor
+    25 and below= very poor
+    :return:
+    """
+    if insulation_thickness is None:
+        raise ValueError("Insulation thickness is required for loft insulated at rafters efficiency calculation")
+
+    if insulation_thickness >= 350:
+        return EpcEfficiency.VERY_GOOD
+
+    if insulation_thickness >= 200:
+        return EpcEfficiency.GOOD
+
+    if insulation_thickness >= 125:
+        return EpcEfficiency.AVERAGE
+
+    if insulation_thickness >= 50:
+        return EpcEfficiency.POOR
+
+    return EpcEfficiency.VERY_POOR
+
+
+def loft_insulated_at_rafters_efficiency_age_band(age_band: EpcConstructionAgeBand) -> EpcEfficiency:
+    """
+    # 2023 onwards -> Very Good
+    # 2003-2006, 2012-2022 -> Good
+    # 1983 - 1990, 1996-2002 -> Average
+    # 1976-1982 -> Poor
+    # 1967-1975 and earlier bands -> Very Poor
+    :param age_band: EpcConstructionAgeBand
+    :return: EpcEfficiency
+    """
+    year = age_band.start_year()
+    if year >= 2023:
+        return EpcEfficiency.VERY_GOOD
+    if year >= 2003:
+        return EpcEfficiency.GOOD
+    if year >= 1983:
+        return EpcEfficiency.AVERAGE
+    if year >= 1976:
+        return EpcEfficiency.POOR
+
+    return EpcEfficiency.VERY_POOR
+
+
+def loft_insulated_at_rafters_efficiency(
+    insulation_thickness: int | None,
+    age_band: EpcConstructionAgeBand,
+) -> EpcEfficiency:
+    """
+    Combines both age band and insulation thickness to determine loft insulated at rafters roof efficiency.
+    :param insulation_thickness: Insulation thickness in mm
+    :param age_band: EpcConstructionAgeBand
+    :return: EpcEfficiency
+    """
+    if insulation_thickness is not None:
+        return loft_insulated_at_rafters_efficiency_thickness(insulation_thickness)
+
+    return loft_insulated_at_rafters_efficiency_age_band(age_band)
+
+
+ROOF_DESCRIPTION_EFFICIENCIES: Mapping[EpcRoofDescriptions, RoofEfficiencyRule] = {
+    # Flat roof
+    EpcRoofDescriptions.flat_no_insulation: EpcEfficiency.VERY_POOR,
+    EpcRoofDescriptions.flat_limited_insulation: flat_efficiency,
+    EpcRoofDescriptions.flat_insulated: flat_efficiency,
+
+    # Loft:
+    # value mappings
+    EpcRoofDescriptions.loft_12mm_insulation: EpcEfficiency.VERY_POOR,
+    EpcRoofDescriptions.loft_25mm_insulation: EpcEfficiency.POOR,
+    EpcRoofDescriptions.loft_50mm_insulation: EpcEfficiency.POOR,
+    EpcRoofDescriptions.loft_75mm_insulation: EpcEfficiency.AVERAGE,
+    EpcRoofDescriptions.loft_100mm_insulation: EpcEfficiency.AVERAGE,
+    EpcRoofDescriptions.loft_125mm_insulation: EpcEfficiency.AVERAGE,
+    EpcRoofDescriptions.loft_150mm_insulation: EpcEfficiency.GOOD,
+    EpcRoofDescriptions.loft_175mm_insulation: EpcEfficiency.GOOD,
+    EpcRoofDescriptions.loft_200mm_insulation: EpcEfficiency.GOOD,
+    EpcRoofDescriptions.loft_250mm_insulation: EpcEfficiency.GOOD,
+    EpcRoofDescriptions.loft_270mm_insulation: EpcEfficiency.VERY_GOOD,
+    EpcRoofDescriptions.loft_300mm_insulation: EpcEfficiency.VERY_GOOD,
+    EpcRoofDescriptions.loft_350mm_insulation: EpcEfficiency.VERY_GOOD,
+    EpcRoofDescriptions.loft_400mm_plus_insulation: EpcEfficiency.VERY_GOOD,
+    EpcRoofDescriptions.pitched_no_insulation: EpcEfficiency.VERY_POOR,
+    # function mappings
+    EpcRoofDescriptions.pitched_insulated_assumed: loft_insulated_efficiency,
+
+    # Loft af rafters
+    EpcRoofDescriptions.loft_insulated_at_rafters: loft_insulated_at_rafters_efficiency,
+
+    # Another dwelling above
+    EpcRoofDescriptions.another_dwelling_above: EpcEfficiency.NA,
+
+    # Thatched
+    EpcRoofDescriptions.thatched: thatched_efficiency,
+    EpcRoofDescriptions.thatched_with_additional_insulation: thatched_efficiency,
+
+    # Sloping ceiling
+    EpcRoofDescriptions.sloping_pitched_insulated: sloping_ceiling_efficiency,
+    EpcRoofDescriptions.sloping_pitched_limited_insulation: sloping_ceiling_efficiency,
+    EpcRoofDescriptions.sloping_pitched_no_insulation: EpcEfficiency.VERY_POOR,
+
+}
+
+
+def resolve_roof_efficiency(
+    description: EpcRoofDescriptions,
+    age_band: EpcConstructionAgeBand | None,
+    insulation_thickness: int | None,
+) -> EpcEfficiency:
+    """
+    Resolve roof efficiency from description + age band + insulation thickness.
+    """
+
+    # Unknown / holding descriptions → efficiency unknown
+    if description in description.unknown_descriptions:
+        return EpcEfficiency.NA
+
+    rule = ROOF_DESCRIPTION_EFFICIENCIES.get(description)
+
+    if rule is None:
+        return EpcEfficiency.NA
+
+    # Fixed efficiency
+    if isinstance(rule, EpcEfficiency):
+        return rule
+
+    # Callable rule
+    if age_band is None or pd.isnull(age_band):
+        return EpcEfficiency.NA
+
+    try:
+        # Try (thickness, age_band)
+        return rule(insulation_thickness, age_band)
+    except TypeError:
+        # Fallback to (age_band)
+        return rule(age_band)

backend/onboarders/mappings/parity/walls.py

@@ -0,0 +1,211 @@
+from typing import Callable, Union
+from collections.abc import Mapping
+from datatypes.epc.walls import EpcWallDescriptions
+from datatypes.epc.construction_age_band import EpcConstructionAgeBand
+from datatypes.epc.efficiency import EpcEfficiency
+
+# Unique combinations
+wall_map = {
+    # Cavity walls
+    ('Cavity', 'FilledCavity'): EpcWallDescriptions.cavity_filled_cavity,
+    ('Cavity', 'Internal'): EpcWallDescriptions.cavity_internal_insulation,
+    ('Cavity', 'External'): EpcWallDescriptions.cavity_external_insulation,
+    ('Cavity', 'FilledCavityPlusInternal'): EpcWallDescriptions.cavity_filled_plus_internal,
+    ('Cavity', 'FilledCavityPlusExternal'): EpcWallDescriptions.cavity_filled_plus_external,
+    ('Cavity', 'AsBuilt'): None,  # To be classified
+    ('Cavity', 'Unknown'): None,  # To be classified
+
+    # System built walls
+    ('System', 'External'): EpcWallDescriptions.system_external_insulation,
+    ('System', 'Internal'): EpcWallDescriptions.system_internal_insulation,
+    ('System', 'AsBuilt'): None,  # To be classified
+    ('System', 'Unknown'): None,
+
+    # Timber Frame walls
+    ('Timber Frame', 'Internal'): EpcWallDescriptions.timber_frame_internal_insulation,
+    ('Timber Frame', 'External'): EpcWallDescriptions.timber_frame_external_insulation,
+    ('Timber Frame', 'AsBuilt'): None,  # To be classified
+    ('Timber Frame', 'Unknown'): None,
+
+    # Solid Brick walls
+    ('Solid Brick', 'External'): EpcWallDescriptions.solid_brick_external_insulation,
+    ('Solid Brick', 'Internal'): EpcWallDescriptions.solid_brick_internal_insulation,
+    ('Solid Brick', 'AsBuilt'): None,  # To be classified
+    ('Solid Brick', 'Unknown'): None,
+
+    # Granite walls
+    ('Granite', 'External'): EpcWallDescriptions.granite_whinstone_external_insulation,
+    ("Granite", 'Internal'): EpcWallDescriptions.granite_whinstone_internal_insulation,
+    ('Granite', 'AsBuilt'): None,
+    ('Granite', 'Unknown'): None,
+
+    # Sandstone walls
+    ('Sandstone', 'Internal'): EpcWallDescriptions.sandstone_limestone_internal_insulation,
+    ('Sandstone', 'External'): EpcWallDescriptions.sandstone_limestone_external_insulation,
+    ('Sandstone', 'Unknown'): None,
+    ('Sandstone', 'AsBuilt'): None,
+
+    # Cob walls
+    ('Cob', 'AsBuilt'): None,
+}
+
+wall_unknown_age_fallback = {
+    "Cavity": EpcWallDescriptions.cavity_as_built_unknown,
+    "Solid Brick": EpcWallDescriptions.solid_brick_as_built_unknown,
+    "Timber Frame": EpcWallDescriptions.timber_frame_as_built_unknown,
+    "System": EpcWallDescriptions.system_as_built_unknown,
+    "Granite": EpcWallDescriptions.granite_as_built_unknown,
+    "Sandstone": EpcWallDescriptions.sandstone_as_built_unknown,
+    "Cob": EpcWallDescriptions.cob_as_built_unknown,
+}
+
+
+def cavity_filled_efficiency(age_band: EpcConstructionAgeBand) -> EpcEfficiency:
+    """"
+    Maps cavity filled to efficiency based on construction age band.
+    :param age_band: EpcConstructionAgeBand
+    :return: EpcEfficiency
+    """
+    if age_band in {
+        EpcConstructionAgeBand.from_2023_onwards
+    }:
+        return EpcEfficiency.VERY_GOOD
+
+    return EpcEfficiency.GOOD
+
+
+def internal_external_insulation_efficiency(
+    age_band: EpcConstructionAgeBand,
+) -> EpcEfficiency:
+    """
+    Maps:
+    - cavity unfilled with internal/external insulation to efficiency based on construction age band. We assumed
+    based on 100mm insulation
+    - solid brick with internal/external insulation to efficiency based on construction age band. We assumed
+    based on 100mm insulation
+    - system built with internal/external insulation to efficiency based on construction age band. We assumed
+    based on 100mm insulation
+
+    All of these wall types have the same behaviour in elmhurst
+    :param age_band: EpcConstructionAgeBand
+    :return: EpcEfficiency
+    """
+    if age_band in {
+        EpcConstructionAgeBand.from_1983_to_1990,
+        EpcConstructionAgeBand.from_1991_to_1995,
+        EpcConstructionAgeBand.from_1996_to_2002,
+        EpcConstructionAgeBand.from_2003_to_2006,
+        EpcConstructionAgeBand.from_2007_to_2011,
+        EpcConstructionAgeBand.from_2012_to_2022,
+        EpcConstructionAgeBand.from_2023_onwards,
+    }:
+        return EpcEfficiency.VERY_GOOD
+
+    return EpcEfficiency.GOOD
+
+
+def timber_granite_sandstone_internal_external_efficiency(age_band: EpcConstructionAgeBand) -> EpcEfficiency:
+    """"
+    Maps:
+    - timber frame with internal/external wall insulation to efficiency based on construction age band.
+    - sandstone/limestone with internal/external wall insulation to efficiency based on construction age band.
+    - granite/whinstone with internal/external wall insulation to efficiency based on construction age band.
+    :param age_band: EpcConstructionAgeBand
+    :return: EpcEfficiency
+    """
+    if age_band in {
+        EpcConstructionAgeBand.from_2023_onwards
+    }:
+        return EpcEfficiency.VERY_GOOD
+
+    return EpcEfficiency.GOOD
+
+
+WallEfficiencyRule = Union[
+    EpcEfficiency,
+    Callable[[EpcConstructionAgeBand, int | None], EpcEfficiency],
+]
+
+WALL_DESCRIPTION_EFFICIENCIES: Mapping[EpcWallDescriptions, WallEfficiencyRule] = {
+    # Note: all function mappings have been defined based on Elmhurst
+    # Cavity
+    # value mappings
+    EpcWallDescriptions.cavity_no_insulation_assumed: EpcEfficiency.POOR,
+    EpcWallDescriptions.cavity_partial_insulated_assumed: EpcEfficiency.AVERAGE,
+    EpcWallDescriptions.cavity_insulated_assumed: EpcEfficiency.GOOD,
+    EpcWallDescriptions.cavity_filled_plus_internal: EpcEfficiency.VERY_GOOD,
+    EpcWallDescriptions.cavity_filled_plus_external: EpcEfficiency.VERY_GOOD,
+    # function mappings
+    EpcWallDescriptions.cavity_filled_cavity: cavity_filled_efficiency,
+    EpcWallDescriptions.cavity_internal_insulation: internal_external_insulation_efficiency,
+    EpcWallDescriptions.cavity_external_insulation: internal_external_insulation_efficiency,
+
+    # Solid brick
+    # value mappings
+    EpcWallDescriptions.solid_brick_no_insulation_assumed: EpcEfficiency.POOR,
+    EpcWallDescriptions.solid_brick_partial_insulated_assumed: EpcEfficiency.AVERAGE,
+    EpcWallDescriptions.solid_brick_insulated_assumed: EpcEfficiency.GOOD,
+    # function mappings
+    EpcWallDescriptions.solid_brick_internal_insulation: internal_external_insulation_efficiency,
+    EpcWallDescriptions.solid_brick_external_insulation: internal_external_insulation_efficiency,
+
+    # System
+    # value mappings
+    EpcWallDescriptions.system_no_insulation_assumed: EpcEfficiency.POOR,
+    EpcWallDescriptions.system_partial_insulated_assumed: EpcEfficiency.AVERAGE,
+    EpcWallDescriptions.system_insulated_assumed: EpcEfficiency.GOOD,
+    # function mappings
+    EpcWallDescriptions.system_internal_insulation: internal_external_insulation_efficiency,
+    EpcWallDescriptions.system_external_insulation: internal_external_insulation_efficiency,
+
+    # Timber frame
+    # value mappings
+    EpcWallDescriptions.timber_frame_no_insulation_assumed: EpcEfficiency.POOR,
+    EpcWallDescriptions.timber_frame_partial_insulated_assumed: EpcEfficiency.AVERAGE,
+    EpcWallDescriptions.timber_frame_insulated_assumed: EpcEfficiency.GOOD,
+    # function mappings
+    EpcWallDescriptions.timber_frame_internal_insulation: timber_granite_sandstone_internal_external_efficiency,
+    EpcWallDescriptions.timber_frame_external_insulation: timber_granite_sandstone_internal_external_efficiency,
+
+    # Granite / whinstone
+    EpcWallDescriptions.granite_whinstone_no_insulation_assumed: EpcEfficiency.VERY_POOR,
+    EpcWallDescriptions.granite_whinstone_partial_insulated_assumed: EpcEfficiency.AVERAGE,
+    EpcWallDescriptions.granite_whinestone_insulated_assumed: EpcEfficiency.GOOD,
+    # function mappings
+    EpcWallDescriptions.granite_whinstone_internal_insulation: timber_granite_sandstone_internal_external_efficiency,
+    EpcWallDescriptions.granite_whinstone_external_insulation: timber_granite_sandstone_internal_external_efficiency,
+
+    # Sandstone / limestone
+    EpcWallDescriptions.sandstone_limestone_no_insulation_assumed: EpcEfficiency.VERY_POOR,
+    EpcWallDescriptions.sandstone_limestone_partial_insulated_assumed: EpcEfficiency.AVERAGE,
+    EpcWallDescriptions.sandstone_limestone_insulated_assumed: EpcEfficiency.GOOD,
+    # function mappings
+    EpcWallDescriptions.sandstone_limestone_internal_insulation: timber_granite_sandstone_internal_external_efficiency,
+    EpcWallDescriptions.sandstone_limestone_external_insulation: timber_granite_sandstone_internal_external_efficiency,
+
+    # Cob (special case)
+    EpcWallDescriptions.cob_as_built_average: EpcEfficiency.AVERAGE,
+    EpcWallDescriptions.cob_as_built_good: EpcEfficiency.GOOD,
+
+    # Unknown mappings which are unhandled
+    EpcWallDescriptions.cavity_as_built_unknown: EpcEfficiency.NA,
+    EpcWallDescriptions.solid_brick_as_built_unknown: EpcEfficiency.NA,
+    EpcWallDescriptions.system_as_built_unknown: EpcEfficiency.NA,
+    EpcWallDescriptions.timber_frame_as_built_unknown: EpcEfficiency.NA,
+    EpcWallDescriptions.granite_as_built_unknown: EpcEfficiency.NA,
+    EpcWallDescriptions.sandstone_as_built_unknown: EpcEfficiency.NA,
+    EpcWallDescriptions.cob_as_built_unknown: EpcEfficiency.NA,
+
+}
+
+
+def resolve_wall_efficiency(
+    description: EpcWallDescriptions,
+    age_band: EpcConstructionAgeBand,
+) -> EpcEfficiency:
+    rule = WALL_DESCRIPTION_EFFICIENCIES[description]
+
+    if isinstance(rule, EpcEfficiency):
+        return rule
+
+    return rule(age_band)

backend/onboarders/mappings/property_type.py

@@ -1,6 +0,0 @@
-parity_map = {
-    "Flat": "Flat",
-    "Maisonette": "Maisonette",
-    "Bungalow": "Bungalow",
-    "House": "House",
-}

backend/onboarders/mappings/walls.py

@@ -1,3 +0,0 @@
-parity_map = {
-
-}

backend/onboarders/parity.py

@@ -1,93 +1,371 @@
+import re
+from tqdm import tqdm
 import pandas as pd
-from etl.epc.DataProcessor import construction_age_bounds_map
+from backend.onboarders.base import OnboarderBase
-from backend.onboarders.mappings.property_type import parity_map as property_map
+# Parity mappings
-from backend.onboarders.mappings.age_band import party_map as age_band_map
+from backend.onboarders.mappings.parity.property_type import parity_map as property_map
-from backend.onboarders.mappings.built_form import parity_map as built_form_map
+from backend.onboarders.mappings.parity.age_band import parity_map as age_band_map
-
+from backend.onboarders.mappings.parity.built_form import parity_map as built_form_map
-
+from backend.onboarders.mappings.parity.walls import wall_map, wall_unknown_age_fallback, WALL_DESCRIPTION_EFFICIENCIES
-def check_nulls(data, original_column, mapped_column):
+from onboarders.mappings.parity.roof import roof_map, roof_unknown_age_fallback, resolve_roof_efficiency
-    # We only allow nulls if the oroginal value was null
+from onboarders.mappings.parity.floor import floor_map
-    null_vals = data[pd.isnull(data[mapped_column])]
+from onboarders.mappings.parity.heating import heating_map
-    if null_vals.empty:
+from onboarders.mappings.parity.glazing import glazing_map
-        return True
+from backend.onboarders.mappings.parity.as_built_wall_classifiers import as_built_wall_classifiers
-    # We make sure all original values were null
+from backend.onboarders.mappings.parity.as_built_roof_classifiers import as_built_roof_classifiers
-    assert pd.isnull(null_vals[original_column]).all(), (
+from backend.onboarders.mappings.parity.as_built_floor_classifiers import (
-        f"Some values in {mapped_column} were not mapped, but original values were not null"
+    as_built_floor_classifiers, unknown_as_built_floor_classifiers
-    )
-
-
-# Sample input data
-
-data = pd.read_excel(
-    "/Users/khalimconn-kowlessar/Documents/hestia/Customers/Peabody/Nov 2025 Consulting Project/2025_11_11 - Peabody "
-    "- Data Extracts for Domna.xlsx",
-    sheet_name="Sustainability"
 )
+from datatypes.epc.roof import EpcRoofDescriptions
+from datatypes.epc.floor import EpcFloorDescriptions
+from datatypes.epc.construction_age_band import EpcConstructionAgeBand
+from datatypes.epc.walls import EpcWallDescriptions
+from datatypes.epc.efficiency import EpcEfficiency
 
-# We want to map the parity fields to standard EPC references. This will allow us to
+tqdm.pandas()
-# 1) Estimate EPCs, more accurately
-# 2) Patch incorrect EPCs with ease
-# 3) Indicate already installed measures
-
-# ------------ construction_age_band ------------
-# Map to EPC age bands
-# def construction_date_to_band(year):
-#     if pd.isnull(year):
-#         return None
-#     # Get the year from the date which is numpy datetime format
-#     for label, ranges in construction_age_bounds_map.items():
-#         if ranges["l"] <= year <= ranges["u"]:
-#             return label
-#     raise NotImplementedError("year out of bounds")
-#
-#
-# data["construction_age_band"] = pd.to_datetime(data["Construction Date"]).dt.year.apply(construction_date_to_band)
-
-data["construction_age_band"] = data["Construction Years"].map(age_band_map)
-
-check_nulls(data, "Construction Years", "construction_age_band")
-
-# ------------ property_type ------------
-data["property_type"] = data["Type"].map(property_map)
-
-assert pd.isnull(data["property_type"]).sum() == 0, "Some property types were not mapped"
-
-# ------------ built_form ------------
-data["built_form"] = data["Attachment"].map(built_form_map)
-
-assert pd.isnull(data["built_form"]).sum() == 0, "Some built forms were not mapped"
-
-# ------------ Wall Construction ------------
-
-data["walls_combined"] = data["Wall Construction"] + "+" + data["Wall Insulation"].fillna("Unknown Insulation")
-
-data["Wall Insulation"].value_counts()
-data["Wall Construction"].value_counts()
-
-as_built_map = {
-    "Cavity": {"insulated_age_bands": [], "partial_insulated_age_bands": []},
-    "Solid Brick": {"insulated_age_bands": [], "partial_insulated_age_bands": []},
-    "System": {"insulated_age_bands": [], "partial_insulated_age_bands": []},
-    "Timber Frame": {"insulated_age_bands": [], "partial_insulated_age_bands": []},
-    "Sandstone": {"insulated_age_bands": [], "partial_insulated_age_bands": []},
-    "Granite": {"insulated_age_bands": [], "partial_insulated_age_bands": []},
-    "Cob": {"insulated_age_bands": [], "partial_insulated_age_bands": []},
-}
 
 
-def map_wall_construction(wall_constuction, wall_insulation, construction_age_band):
+class ParityOnboarder(OnboarderBase):
-    if wall_insulation == "AsBuilt":
-        # Deduce based on wall construction and age band
-        bands = as_built_map.get(wall_constuction, None)
-        if bands is None:
-            raise NotImplementedError(f"Wall construction {wall_constuction} not in as built map")
 
-        # We check if the age band is in insulated or partial insulated, and if neither, we assume uninsulated
+    def __init__(
+        self,
+        fileuri: str,
+        file_format: str,
+        **kwargs
+    ):
+        # Extract bucket, and filekey; Will be in the format s3://bucket/key
+        self.bucket_name = fileuri.split("/")[2]
+        self.input_file_name = "/".join(fileuri.split("/")[3:])
+        # Also prepare output file name
+        self.output_file_name = self.input_file_name.replace("." + file_format, "") + "_transformed.csv"
 
-# Variables we want to map
+        self.read_s3(file_format=file_format, **kwargs)
-# 'Org Ref', 'Address 1', 'Address 2', 'Address 3', 'Postcode', 'Type',
+        pass
-#        'Attachment', 'Construction Years', 'Wall Construction',
+
-#        'Wall Insulation', 'Roof Construction', 'Roof Insulation',
+    def map_construction_age_band(self):
-#        'Floor Construction', 'Floor Insulation', 'Glazing', 'Heating',
+        self.data[self.landlord_construction_age_band] = self.data["Construction Years"].map(age_band_map)
-#        'Boiler Efficiency', 'Main Fuel', 'Controls Adequacy', 'UPRN',
+        self.assert_nulls_only_from_source_nulls(
-#        'Total Floor Area (m2)'
+            self.data, "Construction Years", self.landlord_construction_age_band
+        )
+
+    def map_property_type(self):
+        self.data[self.landlord_property_type] = self.data["Type"].map(property_map)
+        self.assert_no_nulls(self.data, self.landlord_property_type)
+
+    def map_built_form(self):
+        self.data[self.landlord_built_form] = self.data["Attachment"].map(built_form_map)
+        self.assert_no_nulls(self.data, self.landlord_built_form)
+
+    @staticmethod
+    def _fill_wall_as_built(row: pd.Series) -> EpcWallDescriptions | None:
+        """
+        Utility function, used by map_wall_construction in parity transformation module
+        :param row: row of input sustainability data, being transformed
+        :return: EpcWallDescriptions, the as built wall description for the input row, based on the wall construction
+        type and age band
+        """
+        # Already resolved via direct mapping
+        if row.landlord_wall_construction is not None:
+            return row.landlord_wall_construction
+
+        wall_type = row["Wall Construction"]
+
+        # Missing construction age → conservative fallback
+        if pd.isnull(row.landlord_construction_age_band):
+            return wall_unknown_age_fallback.get(wall_type)
+
+        classifier = as_built_wall_classifiers.get(wall_type)
+        if classifier is None:
+            return None
+
+        return classifier(row.landlord_construction_age_band)
+
+    @staticmethod
+    def _resolve_wall_efficiency(
+        description: EpcWallDescriptions,
+        age_band: EpcConstructionAgeBand | None,
+    ) -> EpcEfficiency:
+        # Unknown / holding descriptions → efficiency unknown
+        if "unknown insulation" in description.value.lower():
+            return EpcEfficiency.NA
+
+        rule = WALL_DESCRIPTION_EFFICIENCIES.get(description)
+
+        if rule is None:
+            return EpcEfficiency.NA
+
+        if isinstance(rule, EpcEfficiency):
+            return rule
+
+        # Rule needs age band but we don't have one
+        if age_band is None or pd.isnull(age_band):
+            return EpcEfficiency.NA
+
+        return rule(age_band)
+
+    def map_wall_construction(self):
+        self.data[self.landlord_wall_construction] = (
+            self.data[["Wall Construction", "Wall Insulation"]]
+            .apply(tuple, axis=1)
+            .map(wall_map)
+        )
+
+        self.data[self.landlord_wall_construction] = self.data.progress_apply(self._fill_wall_as_built, axis=1)
+
+        # Sanity check
+        self.assert_no_nulls(self.data, self.landlord_wall_construction)
+
+        self.data[self.landlord_wall_efficiency] = self.data.progress_apply(
+            lambda row: self._resolve_wall_efficiency(
+                row.landlord_wall_construction,
+                row.landlord_construction_age_band,
+            ),
+            axis=1,
+        )
+        # Additional santify check
+        self.assert_no_nulls(self.data, self.landlord_wall_efficiency)
+
+    @staticmethod
+    def _fill_roof_as_built(row: pd.Series) -> EpcRoofDescriptions | None:
+        # Already resolved
+        if not pd.isnull(row.landlord_roof_construction):
+            return row.landlord_roof_construction
+
+        roof_type = row["Roof Construction"]
+
+        classifier = as_built_roof_classifiers.get(roof_type)
+        if classifier is None:
+            raise NotImplementedError(f"No roof classifier for roof type '{roof_type}'")
+
+        if pd.isnull(row.landlord_construction_age_band):
+            return roof_unknown_age_fallback.get(roof_type)
+
+        output = classifier(row.landlord_construction_age_band)
+        if output is None:
+            raise NotImplementedError(
+                f"Roof classification returned None for roof type '{roof_type}'"
+            )
+
+        return output
+
+    @staticmethod
+    def _extract_insulation_thickness(value: str | None) -> int | None:
+        """
+        Extract insulation thickness in mm from a string like 'mm150'.
+        Returns None if not present or not parseable.
+        """
+        if value is None or pd.isnull(value):
+            return None
+
+        match = re.search(r"(\d+)", str(value))
+        if not match:
+            return None
+
+        return int(match.group(1))
+
+    def map_roof_construction(self):
+        self.data[self.landlord_roof_construction] = (
+            self.data[["Roof Construction", "Roof Insulation"]]
+            .progress_apply(tuple, axis=1)
+            .map(roof_map)
+        )
+
+        self.data[self.landlord_roof_construction] = self.data.progress_apply(
+            self._fill_roof_as_built,
+            axis=1,
+        )
+
+        # sanity check
+        self.assert_no_nulls(self.data, self.landlord_roof_construction)
+
+        self.data["roof_insulation_thickness_mm"] = self.data["Roof Insulation"].apply(
+            self._extract_insulation_thickness
+        )
+
+        self.data[self.landlord_roof_efficiency] = self.data.progress_apply(
+            lambda row: resolve_roof_efficiency(
+                description=row.landlord_roof_construction,
+                age_band=row.landlord_construction_age_band,
+                insulation_thickness=row.roof_insulation_thickness_mm,
+            ),
+            axis=1,
+        )
+        # sanity check
+        self.assert_no_nulls(self.data, self.landlord_roof_efficiency)
+
+        # Flag sloping ceiling
+        self.data[self.landlord_has_sloping_ceiling] = self.data["Roof Construction"].apply(
+            lambda x: x == "PitchedWithSlopingCeiling"
+        )
+
+    @staticmethod
+    def _fill_floor_as_built(row: pd.Series):
+        # 1. Already resolved
+        if row.landlord_floor_construction is not None:
+            return row.landlord_floor_construction
+
+        age_band = row.landlord_construction_age_band
+        floor_type = row["Floor Construction"]
+        insulation = row["Floor Insulation"]
+
+        # 2. Missing age band → conservative fallback
+        if pd.isnull(age_band):
+            return EpcFloorDescriptions.unknown
+
+        # 3. Known floor types
+        if floor_type in ["Solid", "SuspendedTimber", "SuspendedNotTimber"]:
+            classifier = as_built_floor_classifiers[floor_type]
+            return classifier(age_band)
+
+        # 4. Unknown floor type
+        if floor_type == "Unknown":
+            classifier = unknown_as_built_floor_classifiers[insulation]
+            return classifier(age_band)
+
+        # 5. Truly missing / garbage input
+        return EpcFloorDescriptions.unknown
+
+    def map_floor_construction(self):
+        self.data[self.landlord_floor_construction] = (
+            self.data[["Floor Construction", "Floor Insulation"]]
+            .progress_apply(tuple, axis=1)
+            .map(floor_map)
+        )
+
+        self.data[self.landlord_floor_construction] = self.data.progress_apply(
+            self._fill_floor_as_built,
+            axis=1,
+        )
+
+        self.assert_no_nulls(self.data, self.landlord_floor_construction)
+
+    def map_glazing(self):
+        # TODO: probably doesn't make sense to store multi glazed proportion, glazed type or glazed area.
+        #       There is maybe an argument for landlord_multi_glaze_proportion as this could be variable,
+        #       however
+        self.data[
+            [
+                self.landlord_windows_type,
+                self.landlord_windows_efficiency,
+                self.landlord_multi_glaze_proportion,
+                self.landlord_glazed_type,
+                self.landlord_glazed_area
+            ]
+        ] = self.data["Glazing"].map(glazing_map).progress_apply(pd.Series)
+
+    def map_heating(self):
+        # TODO - when mapping heating controls, we should check the existing heating controls and the efficiency rating
+        #        For sub optimal heating controls, we're going to make an assumption as to what the heating controls are
+        #        and the energy efficiency rating we prescribe here may not be accurate. We therefore use this as an
+        #        upper limit
+        #        as opposed to a guaranteed efficiency rating. To stress, this is only relevant for sub optimal heating
+        #        controls. E.g. it may be programmer and room thermostat
+        self.data[
+            [
+                self.landlord_heating_construction,
+                self.landlord_heating_efficiency,
+                self.landlord_fuel_type,
+                self.landlord_heating_controls,
+                self.landlord_heating_controls_efficiency,
+                self.landlord_hot_water_system,
+                self.landlord_hot_water_efficiency
+            ]
+        ] = self.data[
+            [
+                "Heating",
+                "Boiler Efficiency",
+                "Main Fuel",
+                "Controls Adequacy"
+            ]
+        ].progress_apply(tuple, axis=1).map(heating_map).progress_apply(pd.Series)
+
+    def map_floor_area(self):
+        # This is just a rename
+        self.data = self.data.rename(
+            columns={"Total Floor Area (m2)": self.landlord_total_floor_area_m2}
+        )
+
+    def select_columns(self):
+        self.data = self.data[
+            [
+                "Org Ref",
+                "UPRN",
+                "Address 1",
+                "Address 2",
+                "Address 3",
+                "Postcode",
+                self.landlord_total_floor_area_m2,
+                self.landlord_construction_age_band,
+                self.landlord_property_type,
+                self.landlord_built_form,
+                self.landlord_wall_construction,
+                self.landlord_wall_efficiency,
+                self.landlord_roof_construction,
+                self.landlord_roof_efficiency,
+                self.landlord_has_sloping_ceiling,
+                self.landlord_floor_construction,
+                self.landlord_windows_type,
+                self.landlord_windows_efficiency,
+                self.landlord_multi_glaze_proportion,
+                self.landlord_glazed_type,
+                self.landlord_glazed_area,
+                self.landlord_heating_construction,
+                self.landlord_heating_efficiency,
+                self.landlord_fuel_type,
+                self.landlord_heating_controls,
+                self.landlord_heating_controls_efficiency,
+                self.landlord_hot_water_system,
+                self.landlord_hot_water_efficiency
+            ]
+        ].rename(
+            columns={
+                "Org Ref": "landlord_property_id",
+                "Address1": "address1",
+                "Address2": "address2",
+                "Address3": "address3",
+                "Postcode": "postcode",
+            }
+        )
+
+    def extract_values(self):
+        for columns in [
+            self.landlord_construction_age_band, self.landlord_property_type, self.landlord_built_form,
+            self.landlord_wall_construction, self.landlord_wall_efficiency, self.landlord_roof_construction,
+            self.landlord_roof_efficiency, self.landlord_floor_construction, self.landlord_windows_type,
+            self.landlord_windows_efficiency, self.landlord_heating_construction, self.landlord_heating_efficiency,
+            self.landlord_fuel_type, self.landlord_heating_controls, self.landlord_heating_controls_efficiency,
+            self.landlord_hot_water_system, self.landlord_hot_water_efficiency
+        ]:
+            self.data[columns] = self.data[columns].progress_apply(lambda x: x.value if hasattr(x, "value") else x)
+
+    def transform(self):
+        # ------------ construction_age_band ------------
+        self.map_construction_age_band()
+
+        # ------------ property_type ------------
+        self.map_property_type()
+
+        # ------------ built_form ------------
+        self.map_built_form()
+
+        # ------------ Wall Construction ------------
+        self.map_wall_construction()
+
+        # ------------ Roof Construction ------------
+        self.map_roof_construction()
+
+        # ------------ Floor Construction ------------
+        self.map_floor_construction()
+
+        # ------------ Glazing ------------
+        self.map_glazing()
+
+        # ------------ Heating, fuel, controls & hot water ------------
+        self.map_heating()
+
+        # ------------ Floor Area ------------
+        self.map_floor_area()
+
+        # ------------ Formating ------------
+        self.select_columns()
+        self.extract_values()

backend/onboarders/requirements.txt

@@ -0,0 +1,6 @@
+boto3
+numpy==2.1.2
+pandas==2.2.3
+tqdm==4.66.5
+pydantic==2.9.2
+openpyxl==3.1.2

backend/onboarders/tests/test_floor_remapping.py

@@ -0,0 +1,97 @@
+import pytest
+
+from datatypes.epc.construction_age_band import EpcConstructionAgeBand
+from datatypes.epc.floor import EpcFloorDescriptions
+
+from backend.onboarders.mappings.parity.as_built_floor_classifiers import (
+    unknown_floor_as_built,
+    unknown_floor_retrofitted,
+    map_solid_floor_as_built,
+    map_suspended_floor_as_built,
+)
+
+
+@pytest.mark.parametrize(
+    "age_band,expected",
+    [
+        # Before 1900 / 1900–1929 → suspended, no insulation
+        (EpcConstructionAgeBand.before_1900, EpcFloorDescriptions.suspended_no_insulation_assumed),
+        (EpcConstructionAgeBand.from_1900_to_1929, EpcFloorDescriptions.suspended_no_insulation_assumed),
+
+        # 1930–1995 → solid, no insulation
+        (EpcConstructionAgeBand.from_1930_to_1949, EpcFloorDescriptions.solid_no_insulation_assumed),
+        (EpcConstructionAgeBand.from_1950_to_1966, EpcFloorDescriptions.solid_no_insulation_assumed),
+        (EpcConstructionAgeBand.from_1967_to_1975, EpcFloorDescriptions.solid_no_insulation_assumed),
+        (EpcConstructionAgeBand.from_1976_to_1982, EpcFloorDescriptions.solid_no_insulation_assumed),
+        (EpcConstructionAgeBand.from_1983_to_1990, EpcFloorDescriptions.solid_no_insulation_assumed),
+        (EpcConstructionAgeBand.from_1991_to_1995, EpcFloorDescriptions.solid_no_insulation_assumed),
+
+        # 1996–2002 → solid, limited insulation
+        (EpcConstructionAgeBand.from_1996_to_2002, EpcFloorDescriptions.solid_limited_insulation_assumed),
+
+        # 2003+ → solid, insulated
+        (EpcConstructionAgeBand.from_2003_to_2006, EpcFloorDescriptions.solid_insulated_assumed),
+        (EpcConstructionAgeBand.from_2012_to_2022, EpcFloorDescriptions.solid_insulated_assumed),
+        (EpcConstructionAgeBand.from_2023_onwards, EpcFloorDescriptions.solid_insulated_assumed),
+    ],
+)
+def test_unknown_floor_as_built(age_band, expected):
+    assert unknown_floor_as_built(age_band) == expected
+
+
+@pytest.mark.parametrize(
+    "age_band,expected",
+    [
+        # Pre-1930 → suspended, insulated
+        (EpcConstructionAgeBand.before_1900, EpcFloorDescriptions.suspended_insulated),
+        (EpcConstructionAgeBand.from_1900_to_1929, EpcFloorDescriptions.suspended_insulated),
+
+        # 1930+ → solid, insulated
+        (EpcConstructionAgeBand.from_1930_to_1949, EpcFloorDescriptions.solid_insulated),
+        (EpcConstructionAgeBand.from_1950_to_1966, EpcFloorDescriptions.solid_insulated),
+        (EpcConstructionAgeBand.from_1976_to_1982, EpcFloorDescriptions.solid_insulated),
+        (EpcConstructionAgeBand.from_2023_onwards, EpcFloorDescriptions.solid_insulated),
+    ],
+)
+def test_unknown_floor_retrofitted(age_band, expected):
+    assert unknown_floor_retrofitted(age_band) == expected
+
+
+@pytest.mark.parametrize(
+    "age_band,expected",
+    [
+        # 1983–1995 → no insulation
+        (EpcConstructionAgeBand.from_1983_to_1990, EpcFloorDescriptions.solid_no_insulation_assumed),
+        (EpcConstructionAgeBand.from_1991_to_1995, EpcFloorDescriptions.solid_no_insulation_assumed),
+
+        # 1996–2002 → limited insulation
+        (EpcConstructionAgeBand.from_1996_to_2002, EpcFloorDescriptions.solid_limited_insulation_assumed),
+
+        # 2003+ → insulated
+        (EpcConstructionAgeBand.from_2003_to_2006, EpcFloorDescriptions.solid_insulated_assumed),
+        (EpcConstructionAgeBand.from_2012_to_2022, EpcFloorDescriptions.solid_insulated_assumed),
+        (EpcConstructionAgeBand.from_2023_onwards, EpcFloorDescriptions.solid_insulated_assumed),
+    ],
+)
+def test_solid_floor_as_built(age_band, expected):
+    assert map_solid_floor_as_built(age_band) == expected
+
+
+@pytest.mark.parametrize(
+    "age_band,expected",
+    [
+        # 1983–1995 → no insulation
+        (EpcConstructionAgeBand.from_1983_to_1990, EpcFloorDescriptions.suspended_no_insulation_assumed),
+        (EpcConstructionAgeBand.from_1991_to_1995, EpcFloorDescriptions.suspended_no_insulation_assumed),
+
+        # 1996–2002 → limited insulation
+        (EpcConstructionAgeBand.from_1996_to_2002, EpcFloorDescriptions.suspended_limited_insulation_assumed),
+
+        # 2003+ → insulated
+        (EpcConstructionAgeBand.from_2003_to_2006, EpcFloorDescriptions.suspended_insulated_assumed),
+        (EpcConstructionAgeBand.from_2012_to_2022, EpcFloorDescriptions.suspended_insulated_assumed),
+        (EpcConstructionAgeBand.from_2023_onwards, EpcFloorDescriptions.suspended_insulated_assumed),
+    ],
+)
+def test_suspended_floor_as_built(age_band, expected):
+    assert map_suspended_floor_as_built(age_band) == expected

backend/onboarders/tests/test_roof_remapping.py

@@ -0,0 +1,173 @@
+import pytest
+
+from datatypes.epc.construction_age_band import EpcConstructionAgeBand
+from datatypes.epc.roof import EpcRoofDescriptions
+from datatypes.epc.efficiency import EpcEfficiency
+
+from backend.onboarders.mappings.parity.as_built_roof_classifiers import (
+    map_flat_roof,
+    map_sloping_ceiling_roof,
+)
+from backend.onboarders.mappings.parity.roof import resolve_roof_efficiency
+
+
+# ---------------------------------------------------------------------
+# As-built roof description classification
+# ---------------------------------------------------------------------
+
+@pytest.mark.parametrize(
+    "age_band, expected",
+    [
+        (EpcConstructionAgeBand.before_1900, EpcRoofDescriptions.flat_no_insulation),
+        (EpcConstructionAgeBand.from_1950_to_1966, EpcRoofDescriptions.flat_no_insulation),
+        (EpcConstructionAgeBand.from_1967_to_1975, EpcRoofDescriptions.flat_limited_insulation),
+        (EpcConstructionAgeBand.from_1976_to_1982, EpcRoofDescriptions.flat_limited_insulation),
+        (EpcConstructionAgeBand.from_1983_to_1990, EpcRoofDescriptions.flat_insulated),
+        (EpcConstructionAgeBand.from_2007_to_2011, EpcRoofDescriptions.flat_insulated),
+        (EpcConstructionAgeBand.from_2023_onwards, EpcRoofDescriptions.flat_insulated),
+    ],
+)
+def test_classify_flat_roof(age_band, expected):
+    assert map_flat_roof(age_band) == expected
+
+
+@pytest.mark.parametrize(
+    "age_band, expected",
+    [
+        (EpcConstructionAgeBand.before_1900, EpcRoofDescriptions.sloping_pitched_no_insulation),
+        (EpcConstructionAgeBand.from_1967_to_1975, EpcRoofDescriptions.sloping_pitched_no_insulation),
+        (EpcConstructionAgeBand.from_1976_to_1982, EpcRoofDescriptions.sloping_pitched_limited_insulation),
+        (EpcConstructionAgeBand.from_1983_to_1990, EpcRoofDescriptions.sloping_pitched_insulated),
+        (EpcConstructionAgeBand.from_2012_to_2022, EpcRoofDescriptions.sloping_pitched_insulated),
+        (EpcConstructionAgeBand.from_2023_onwards, EpcRoofDescriptions.sloping_pitched_insulated),
+    ],
+)
+def test_classify_sloping_ceiling_roof(age_band, expected):
+    assert map_sloping_ceiling_roof(age_band) == expected
+
+
+# ---------------------------------------------------------------------
+# Roof efficiency — fixed & age-band driven
+# ---------------------------------------------------------------------
+
+@pytest.mark.parametrize(
+    "description, age_band, expected",
+    [
+        # Flat roof, no insulation
+        (EpcRoofDescriptions.flat_no_insulation, EpcConstructionAgeBand.before_1900, EpcEfficiency.VERY_POOR),
+
+        # Flat roof, limited insulation (age-band driven)
+        (EpcRoofDescriptions.flat_limited_insulation, EpcConstructionAgeBand.from_1976_to_1982, EpcEfficiency.POOR),
+        (
+            EpcRoofDescriptions.flat_limited_insulation, EpcConstructionAgeBand.from_1967_to_1975,
+            EpcEfficiency.VERY_POOR),
+
+        # Flat roof, insulated (age-band driven)
+        (EpcRoofDescriptions.flat_insulated, EpcConstructionAgeBand.from_1983_to_1990, EpcEfficiency.AVERAGE),
+        (EpcRoofDescriptions.flat_insulated, EpcConstructionAgeBand.from_2003_to_2006, EpcEfficiency.GOOD),
+        (EpcRoofDescriptions.flat_insulated, EpcConstructionAgeBand.from_2023_onwards, EpcEfficiency.VERY_GOOD),
+
+        # Pitched, insulated assumed (loft)
+        (EpcRoofDescriptions.pitched_insulated_assumed, EpcConstructionAgeBand.from_1996_to_2002, EpcEfficiency.GOOD),
+        (EpcRoofDescriptions.pitched_insulated_assumed, EpcConstructionAgeBand.from_2007_to_2011,
+         EpcEfficiency.VERY_GOOD),
+    ],
+)
+def test_roof_efficiency_age_band_only(description, age_band, expected):
+    assert resolve_roof_efficiency(
+        description=description,
+        age_band=age_band,
+        insulation_thickness=None,
+    ) == expected
+
+
+# ---------------------------------------------------------------------
+# Roof efficiency — insulation thickness driven
+# ---------------------------------------------------------------------
+
+@pytest.mark.parametrize(
+    "description, thickness, expected",
+    [
+        # Loft insulation
+        (EpcRoofDescriptions.loft_12mm_insulation, 12, EpcEfficiency.VERY_POOR),
+        (EpcRoofDescriptions.loft_25mm_insulation, 25, EpcEfficiency.POOR),
+        (EpcRoofDescriptions.loft_75mm_insulation, 75, EpcEfficiency.AVERAGE),
+        (EpcRoofDescriptions.loft_150mm_insulation, 150, EpcEfficiency.GOOD),
+        (EpcRoofDescriptions.loft_300mm_insulation, 300, EpcEfficiency.VERY_GOOD),
+
+        # Flat insulated — thickness overrides age band
+        (EpcRoofDescriptions.flat_insulated, 50, EpcEfficiency.POOR),
+        (EpcRoofDescriptions.flat_insulated, 100, EpcEfficiency.AVERAGE),
+        (EpcRoofDescriptions.flat_insulated, 200, EpcEfficiency.GOOD),
+        (EpcRoofDescriptions.flat_insulated, 300, EpcEfficiency.VERY_GOOD),
+
+        # Sloping ceiling
+        (EpcRoofDescriptions.sloping_pitched_insulated, 75, EpcEfficiency.AVERAGE),
+        (EpcRoofDescriptions.sloping_pitched_insulated, 150, EpcEfficiency.GOOD),
+        (EpcRoofDescriptions.sloping_pitched_insulated, 350, EpcEfficiency.VERY_GOOD),
+    ],
+)
+def test_roof_efficiency_thickness_based(description, thickness, expected):
+    assert resolve_roof_efficiency(
+        description=description,
+        age_band=EpcConstructionAgeBand.before_1900,  # should be ignored
+        insulation_thickness=thickness,
+    ) == expected
+
+
+# ---------------------------------------------------------------------
+# Thatched roofs
+# ---------------------------------------------------------------------
+
+@pytest.mark.parametrize(
+    "description, age_band, expected",
+    [
+        (EpcRoofDescriptions.thatched, EpcConstructionAgeBand.before_1900, EpcEfficiency.AVERAGE),
+        (EpcRoofDescriptions.thatched, EpcConstructionAgeBand.from_2003_to_2006, EpcEfficiency.GOOD),
+        (EpcRoofDescriptions.thatched, EpcConstructionAgeBand.from_2023_onwards, EpcEfficiency.VERY_GOOD),
+    ],
+)
+def test_thatched_efficiency_age_band(description, age_band, expected):
+    assert resolve_roof_efficiency(
+        description=description,
+        age_band=age_band,
+        insulation_thickness=None,
+    ) == expected
+
+
+@pytest.mark.parametrize(
+    "thickness, expected",
+    [
+        (12, EpcEfficiency.AVERAGE),
+        (50, EpcEfficiency.GOOD),
+        (150, EpcEfficiency.GOOD),
+        (200, EpcEfficiency.VERY_GOOD),
+    ],
+)
+def test_thatched_efficiency_thickness(thickness, expected):
+    assert resolve_roof_efficiency(
+        description=EpcRoofDescriptions.thatched_with_additional_insulation,
+        age_band=EpcConstructionAgeBand.before_1900,
+        insulation_thickness=thickness,
+    ) == expected
+
+
+# ---------------------------------------------------------------------
+# Unknown / holding descriptions
+# ---------------------------------------------------------------------
+
+@pytest.mark.parametrize(
+    "description",
+    [
+        EpcRoofDescriptions.flat_as_built_unknown,
+        EpcRoofDescriptions.loft_as_built_unknown,
+        EpcRoofDescriptions.thatched_as_built_unknown,
+        EpcRoofDescriptions.sloping_pitched_as_built_unknown,
+    ],
+)
+def test_unknown_roof_descriptions_return_na(description):
+    assert resolve_roof_efficiency(
+        description=description,
+        age_band=None,
+        insulation_thickness=None,
+    ) == EpcEfficiency.NA

backend/onboarders/tests/test_wall_remapping.py

@@ -0,0 +1,161 @@
+import pytest
+
+from datatypes.epc.construction_age_band import EpcConstructionAgeBand
+from datatypes.epc.walls import EpcWallDescriptions
+from datatypes.epc.efficiency import EpcEfficiency
+
+from backend.onboarders.mappings.parity.walls import resolve_wall_efficiency
+from backend.onboarders.mappings.parity.as_built_wall_classifiers import (
+    map_cavity_wall_insulation,
+    map_solid_wall_insulation,
+    map_timber_frame_wall_insulation,
+    map_system_build_wall_insulation,
+    map_granite_wall_insulation,
+    map_sandstone_wall_insulation,
+    map_cob_wall_insulation,
+)
+
+
+# ---------------------------------------------------------------------
+# As-built wall description classification
+# ---------------------------------------------------------------------
+
+@pytest.mark.parametrize(
+    "age_band, expected",
+    [
+        (EpcConstructionAgeBand.before_1900, EpcWallDescriptions.cavity_no_insulation_assumed),
+        (EpcConstructionAgeBand.from_1950_to_1966, EpcWallDescriptions.cavity_no_insulation_assumed),
+        (EpcConstructionAgeBand.from_1976_to_1982, EpcWallDescriptions.cavity_partial_insulated_assumed),
+        (EpcConstructionAgeBand.from_1983_to_1990, EpcWallDescriptions.cavity_insulated_assumed),
+        (EpcConstructionAgeBand.from_2023_onwards, EpcWallDescriptions.cavity_insulated_assumed),
+    ],
+)
+def test_map_cavity_wall_insulation(age_band, expected):
+    assert map_cavity_wall_insulation(age_band) == expected
+
+
+@pytest.mark.parametrize(
+    "age_band, expected",
+    [
+        (EpcConstructionAgeBand.before_1900, EpcWallDescriptions.solid_brick_no_insulation_assumed),
+        (EpcConstructionAgeBand.from_1976_to_1982, EpcWallDescriptions.solid_brick_partial_insulated_assumed),
+        (EpcConstructionAgeBand.from_1996_to_2002, EpcWallDescriptions.solid_brick_insulated_assumed),
+    ],
+)
+def test_map_solid_wall_insulation(age_band, expected):
+    assert map_solid_wall_insulation(age_band) == expected
+
+
+@pytest.mark.parametrize(
+    "age_band, expected",
+    [
+        (EpcConstructionAgeBand.before_1900, EpcWallDescriptions.timber_frame_no_insulation_assumed),
+        (EpcConstructionAgeBand.from_1950_to_1966, EpcWallDescriptions.timber_frame_partial_insulated_assumed),
+        (EpcConstructionAgeBand.from_1983_to_1990, EpcWallDescriptions.timber_frame_insulated_assumed),
+    ],
+)
+def test_map_timber_frame_wall_insulation(age_band, expected):
+    assert map_timber_frame_wall_insulation(age_band) == expected
+
+
+@pytest.mark.parametrize(
+    "age_band, expected",
+    [
+        (EpcConstructionAgeBand.before_1900, EpcWallDescriptions.system_no_insulation_assumed),
+        (EpcConstructionAgeBand.from_1976_to_1982, EpcWallDescriptions.system_partial_insulated_assumed),
+        (EpcConstructionAgeBand.from_2003_to_2006, EpcWallDescriptions.system_insulated_assumed),
+    ],
+)
+def test_map_system_wall_insulation(age_band, expected):
+    assert map_system_build_wall_insulation(age_band) == expected
+
+
+@pytest.mark.parametrize(
+    "age_band, expected",
+    [
+        (EpcConstructionAgeBand.before_1900, EpcWallDescriptions.granite_whinstone_no_insulation_assumed),
+        (EpcConstructionAgeBand.from_1976_to_1982, EpcWallDescriptions.granite_whinstone_partial_insulated_assumed),
+        (EpcConstructionAgeBand.from_2012_to_2022, EpcWallDescriptions.granite_whinestone_insulated_assumed),
+    ],
+)
+def test_map_granite_wall_insulation(age_band, expected):
+    assert map_granite_wall_insulation(age_band) == expected
+
+
+@pytest.mark.parametrize(
+    "age_band, expected",
+    [
+        (EpcConstructionAgeBand.before_1900, EpcWallDescriptions.sandstone_limestone_no_insulation_assumed),
+        (EpcConstructionAgeBand.from_1976_to_1982, EpcWallDescriptions.sandstone_limestone_partial_insulated_assumed),
+        (EpcConstructionAgeBand.from_2007_to_2011, EpcWallDescriptions.sandstone_limestone_insulated_assumed),
+    ],
+)
+def test_map_sandstone_wall_insulation(age_band, expected):
+    assert map_sandstone_wall_insulation(age_band) == expected
+
+
+@pytest.mark.parametrize(
+    "age_band, expected",
+    [
+        (EpcConstructionAgeBand.before_1900, EpcWallDescriptions.cob_as_built_average),
+        (EpcConstructionAgeBand.from_1976_to_1982, EpcWallDescriptions.cob_as_built_average),
+        (EpcConstructionAgeBand.from_1983_to_1990, EpcWallDescriptions.cob_as_built_good),
+    ],
+)
+def test_map_cob_wall_insulation(age_band, expected):
+    assert map_cob_wall_insulation(age_band) == expected
+
+
+# ---------------------------------------------------------------------
+# Wall efficiency resolution
+# ---------------------------------------------------------------------
+
+@pytest.mark.parametrize(
+    "description, age_band, expected",
+    [
+        # Fixed efficiencies
+        (EpcWallDescriptions.cavity_no_insulation_assumed, None, EpcEfficiency.POOR),
+        (EpcWallDescriptions.cavity_partial_insulated_assumed, None, EpcEfficiency.AVERAGE),
+        (EpcWallDescriptions.cavity_insulated_assumed, None, EpcEfficiency.GOOD),
+
+        # Function-based efficiencies
+        (
+            EpcWallDescriptions.cavity_filled_cavity,
+            EpcConstructionAgeBand.from_2023_onwards,
+            EpcEfficiency.VERY_GOOD,
+        ),
+        (
+            EpcWallDescriptions.cavity_filled_cavity,
+            EpcConstructionAgeBand.from_1991_to_1995,
+            EpcEfficiency.GOOD,
+        ),
+        (
+            EpcWallDescriptions.solid_brick_internal_insulation,
+            EpcConstructionAgeBand.from_2003_to_2006,
+            EpcEfficiency.VERY_GOOD,
+        ),
+        (
+            EpcWallDescriptions.solid_brick_internal_insulation,
+            EpcConstructionAgeBand.from_1950_to_1966,
+            EpcEfficiency.GOOD,
+        ),
+    ],
+)
+def test_resolve_wall_efficiency(description, age_band, expected):
+    assert resolve_wall_efficiency(description, age_band) == expected
+
+
+@pytest.mark.parametrize(
+    "description",
+    [
+        EpcWallDescriptions.cavity_as_built_unknown,
+        EpcWallDescriptions.solid_brick_as_built_unknown,
+        EpcWallDescriptions.system_as_built_unknown,
+        EpcWallDescriptions.timber_frame_as_built_unknown,
+        EpcWallDescriptions.granite_as_built_unknown,
+        EpcWallDescriptions.sandstone_as_built_unknown,
+        EpcWallDescriptions.cob_as_built_unknown,
+    ],
+)
+def test_unknown_wall_descriptions_return_na(description):
+    assert resolve_wall_efficiency(description, None) == EpcEfficiency.NA

backend/postcode_splitter/handler/Dockerfile

@@ -0,0 +1,9 @@
+FROM public.ecr.aws/lambda/python:3.10
+
+# Set working directory (Lambda task root)
+WORKDIR /var/task
+
+# -----------------------------
+# Lambda handler
+# -----------------------------
+CMD ["main.handler"]

backend/postcode_splitter/main.py

@@ -1,10 +1,12 @@
 import pandas as pd
 import requests
-from backend.address2UPRN.main import resolve_uprns_for_postcode_group, get_epc_data_with_postcode
+from backend.address2UPRN.main import (
+    resolve_uprns_for_postcode_group,
+    get_epc_data_with_postcode,
+)
 from tqdm import tqdm
 
 
-
 def sanitise_postcode(postcode: str) -> str | None:
     """
     Normalise postcode for grouping.
@@ -51,11 +53,7 @@ def main():
     # --- validate AFTER grouping (save API calls) ---
 
     # Get unique, non-null postcodes
-    unique_postcodes = (
+    unique_postcodes = df["postcode_clean"].dropna().unique()
-        df["postcode_clean"]
-        .dropna()
-        .unique()
-    )
 
     # Validate each postcode once, TODOadd a progress bar
     postcode_validity = {
@@ -66,7 +64,6 @@ def main():
     # Map validity back onto dataframe
     df["postcode_valid"] = df["postcode_clean"].map(postcode_validity)
 
-
     results = []
 
     for postcode, group_df in tqdm(
@@ -98,17 +95,33 @@ def main():
             results.append(tmp)
 
     final_df = pd.concat(results, ignore_index=True)
-    a = final_df[[
+    a = final_df[
-            "best_match_lexiscore","Address 1",
+        [
-            "best_match_address", "Postcode",
+            "best_match_lexiscore",
-            "UPRN", "best_match_uprn"
+            "Address 1",
-        ]] # add levi score to viewing
+            "best_match_address",
-    b = final_df[final_df["best_match_lexiscore"]>0] # add levi score to viewing
+            "Postcode",
-    b = b[[
+            "UPRN",
-            "best_match_lexiscore","Address 1",
+            "best_match_uprn",
-            "best_match_address", "Postcode",
+        ]
-            "UPRN", "best_match_uprn"
+    ]  # add levi score to viewing
-        ]] 
+    b = final_df[final_df["best_match_lexiscore"] > 0]  # add levi score to viewing
+    b = b[
+        [
+            "best_match_lexiscore",
+            "Address 1",
+            "best_match_address",
+            "Postcode",
+            "UPRN",
+            "best_match_uprn",
+        ]
+    ]
+
+
+def handler(event, context):
+    print("hello Postcode splitter world")
+    return {"statusCode": 200, "body": "hello world"}
+
 
 if __name__ == "__main__":
     main()

datatypes/epc/construction_age_band.py

@@ -0,0 +1,45 @@
+import re
+from enum import Enum
+from typing import List
+
+
+class EpcConstructionAgeBand(Enum):
+    before_1900: str = 'England and Wales: before 1900'
+    from_1900_to_1929: str = 'England and Wales: 1900-1929'
+    from_1930_to_1949: str = 'England and Wales: 1930-1949'
+    from_1950_to_1966: str = 'England and Wales: 1950-1966'
+    from_1967_to_1975: str = 'England and Wales: 1967-1975'
+    from_1976_to_1982: str = 'England and Wales: 1976-1982'
+    from_1983_to_1990: str = 'England and Wales: 1983-1990'
+    from_1991_to_1995: str = 'England and Wales: 1991-1995'
+    from_1996_to_2002: str = 'England and Wales: 1996-2002'
+    from_2003_to_2006: str = 'England and Wales: 2003-2006'
+    from_2007_to_2011: str = 'England and Wales: 2007-2011'
+    from_2012_onwards: str = 'England and Wales: 2012-onwards'
+    from_2012_to_2022: str = 'England and Wales: 2012-2022'
+    from_2023_onwards: str = 'England and Wales: 2023 onwards'
+
+    def start_year(self) -> int:
+        """
+        Extract the starting year of the age band.
+        """
+        value = self.value.lower()
+
+        if 'before' in value:
+            return 0
+        match = re.search(r'(\d{4})', value)
+        if not match:
+            raise ValueError(f"Cannot determine start year from '{self.value}'")
+
+        return int(match.group(1))
+
+    @classmethod
+    def from_year_onwards(cls, year: int) -> List["EpcConstructionAgeBand"]:
+        """
+        Return all age bands whose starting year is >= the given year.
+        """
+        return [
+            band
+            for band in cls
+            if band.start_year() >= year
+        ]

datatypes/epc/efficiency.py

@@ -0,0 +1,10 @@
+from enum import Enum
+
+
+class EpcEfficiency(Enum):
+    VERY_POOR: str = "Very Poor"
+    POOR: str = "Poor"
+    AVERAGE: str = "Average"
+    GOOD: str = "Good"
+    VERY_GOOD: str = "Very Good"
+    NA: str = "N/A"

datatypes/epc/floor.py

@@ -0,0 +1,17 @@
+from enum import Enum
+
+
+class EpcFloorDescriptions(Enum):
+    # Solid floor
+    solid_insulated = "Solid, insulated"
+    solid_insulated_assumed = "Solid, insulated (assumed)"
+    solid_no_insulation_assumed = "Solid, no insulation (assumed)"
+    solid_limited_insulation_assumed = "Solid, limited insulation (assumed)"
+
+    # Suspended floor
+    suspended_insulated = "Suspended, insulated"
+    suspended_insulated_assumed = "Suspended, insulated (assumed)"
+    suspended_no_insulation_assumed = "Suspended, no insulation (assumed)"
+    suspended_limited_insulation_assumed = "Suspended, limited insulation (assumed)"
+
+    unknown = None  # We don't resolve anything

datatypes/epc/fuel.py

@@ -0,0 +1,10 @@
+from enum import Enum
+
+
+class EpcFuel(Enum):
+    electricity_not_community = "electricity (not community)"
+    lpg_not_community = "LPG (not community)"
+    mains_gas_not_community = "mains gas (not community)"
+    oil_not_community = "oil (not community)"
+    manufactured_smokeless_fuel = "Solid fuel: manufactured smokeless fuel"
+    smokeless_coal = "smokeless coal"

datatypes/epc/heating_controls.py

@@ -0,0 +1,18 @@
+from enum import Enum
+
+
+class EpcHeatingControls(Enum):
+    programmer_room_thermostat_trvs = "Programmer, room thermostat and TRVs"
+    programmers_trvs_bypass = "Programmer, TRVs and bypass"
+    time_and_temperature_zone_control = "Time and temperature zone control"
+
+    # Room heaters
+    programmer_and_appliance_thermostats = "Programmer and appliance thermostats"
+    appliance_thermostats = "Appliance thermostats"
+
+    # Storage heaters
+    automatic_charge_control = "Automatic charge control"
+    manual_charge_control = "Manual charge control"
+
+    # Warm air
+    programmer_and_atleast_two_room_thermostats = "Programmer and at least two room thermostats"

datatypes/epc/hotwater.py

@@ -0,0 +1,8 @@
+from enum import Enum
+
+
+class EpcHotWaterSystems(Enum):
+    # from primary heating system
+    from_main_system = "From main system"
+    # Common for heater-based systems, e.g. room heaters or storage heaters
+    electric_immersion_off_peak = "Electric immersion, off-peak"

datatypes/epc/main_heating.py

@@ -0,0 +1,24 @@
+from enum import Enum
+
+
+class EpcHeatingSystems(Enum):
+    # boiler and radiators
+    boiler_and_radiators_electric = "Boiler and radiators, electric"
+    boiler_and_radiators_lpg = "Boiler and radiators, LPG"
+    boiler_radiators_mains_gas = "Boiler and radiators, mains gas"
+    boiler_radiators_oil = "Boiler and radiators, oil"
+    # underfloor
+    electric_underfloor_heating = "Electric underfloor heating"
+    # ashp
+    air_to_air_ashp = "Air source heat pump, warm air, electric"
+    ashp_radiators_electric = "Air source heat pump, radiators, electric"
+    # Room heaters
+    room_heaters_electric = "Room heaters, electric"
+    room_heaters_mains_gas = "Room heaters, mains gas"
+    room_heaters_smokeless_fuel = "Room heaters, smokeless fuel"
+    room_heaters_coal = "Room heaters, coal"
+    # Storage heaters
+    electric_storage_heaters = "Electric storage heaters"
+    # Warm air
+    warm_air_electricaire = "Warm air, Electricaire"
+    warm_air_mains_gas = "Warm air, mains gas"

datatypes/epc/property_type_built_form.py

@@ -0,0 +1,17 @@
+from enum import Enum
+
+
+class PropertyType(Enum):
+    flat = "Flat"
+    maisonette = "Maisonette"
+    bungalow = "Bungalow"
+    house = "House"
+
+
+class BuiltForm(Enum):
+    mid_terrace = "Mid-Terrace"
+    end_terrace = "End-Terrace"
+    detached = "Detached"
+    semi_detached = "Semi-Detached"
+    enclosed_mid_terrace = "Enclosed Mid-Terrace"
+    enclosed_end_terrace = "Enclosed End-Terrace"

datatypes/epc/roof.py

@@ -0,0 +1,86 @@
+from enum import Enum
+from typing import List
+
+
+class EpcRoofDescriptions(Enum):
+    # Loft
+    # Assumed options
+    pitched_insulated_assumed: str = "Pitched, insulated (assumed)"
+    pitched_no_insulation: str = "Pitched, no insulation"
+    # Insulation thickness options
+    loft_12mm_insulation: str = "Pitched, 12 mm loft insulation"
+    loft_25mm_insulation: str = "Pitched, 25 mm loft insulation"
+    loft_50mm_insulation: str = "Pitched, 50 mm loft insulation"
+    loft_75mm_insulation: str = "Pitched, 75 mm loft insulation"
+    loft_100mm_insulation: str = "Pitched, 100 mm loft insulation"
+    loft_125mm_insulation: str = "Pitched, 125 mm loft insulation"
+    loft_150mm_insulation: str = "Pitched, 150 mm loft insulation"
+    loft_175mm_insulation: str = "Pitched, 175 mm loft insulation"
+    loft_200mm_insulation: str = "Pitched, 200 mm loft insulation"
+    loft_250mm_insulation: str = "Pitched, 250 mm loft insulation"
+    loft_270mm_insulation: str = "Pitched, 270 mm loft insulation"
+    loft_300mm_insulation: str = "Pitched, 300 mm loft insulation"
+    loft_350mm_insulation: str = "Pitched, 350 mm loft insulation"
+    loft_400mm_plus_insulation: str = "Pitched, 400+ mm loft insulation"
+    # Insulated at rafters "Pitched, insulated at rafters"
+    # Rafters
+    # 400mm, 350mm = very good
+    # 200-300mm = good
+    # 125-175 = average
+    # 50-100 = poor
+    # 25 and below= very poor
+    loft_insulated_at_rafters: str = "Pitched, insulated at rafters"
+    # another dwelling above
+    another_dwelling_above: str = "(another dwelling above)"
+    # flat roof, which if there is observed insulation is just "flat, insulated", however there is a
+    # different efficiency rating depending on insulation thickness
+    # categories:
+    # 12mm = very poor & has limited insulation description
+    # 25, 50 = poor & has limited insulation description
+    # 75, 100, 125mm = average (Flat, insulated)
+    # 150, 175, 200, 225, 250mm = good (Flat, insulated)
+    # 270mm+ = very good (Flat, insulated)
+    # As built 2023 = Flat, insulated, Very good
+    # 2003 - 2006, up to 2012-2022 = Flat insulated, Good
+    # 1983-1990, 1996-2002 = Flat, insulated, Average
+    # 1976-1982 = Flat, limited insulation, poor
+    # 1967 - 1975 = Flat, limited insulation, Very Poor
+    # 1950-1966 and earlier bands = flat, no insulation, very poor
+
+    flat_insulated: str = "Flat, insulated"
+    flat_limited_insulation: str = "Flat, limited insulation"
+    flat_no_insulation: str = "Flat, no insulation"
+
+    # Thatched roof descriptions
+    # With Loft insulation at joists
+    # Thatched + 12mm = thatched, with additional insulation, average
+    # Thatched + 25, 50, 100, 150mm = thatched, with additional insulation, good
+    # Thatched + 175mm+ = thatched, with additional insulation, very good
+    # With loft insulation at rafters [out of scope atm]
+    # Unknown insulation
+    # Pre 1900, 1930-1949, 1967-1975, 1983-1990, 1996-2002 = "Thatched", Average
+    # 2003-2006, 2012-2022 = "Thatched", Good
+    # 2023 onwards = "Thatched", Very Good
+    thatched: str = "Thatched"  # We see this for no insulation, has average performance
+    thatched_with_additional_insulation: str = "Thatched, with additional insulation"
+
+    # Sloping ceiling
+    # For sloping ceiling tags, we don't use any (assumed) tags so that it's unambiguous that the roof is sloped
+    sloping_pitched_no_insulation: str = "Pitched, no insulation"
+    sloping_pitched_limited_insulation: str = "Pitched, limited insulation"
+    sloping_pitched_insulated: str = "Pitched, insulated"
+
+    # Unknown descriptions which may get mapped later or handled via fallback
+    flat_as_built_unknown: str = "Flat, as built, unknown insulation"
+    loft_as_built_unknown: str = "Loft, as built, unknown insulation"
+    thatched_as_built_unknown: str = "Thatched, as built, unknown insulation"
+    sloping_pitched_as_built_unknown: str = "Pitched, as built, unknown insulation"
+
+    @property
+    def unknown_descriptions(self) -> List["EpcRoofDescriptions"]:
+        return [
+            EpcRoofDescriptions.flat_as_built_unknown,
+            EpcRoofDescriptions.loft_as_built_unknown,
+            EpcRoofDescriptions.thatched_as_built_unknown,
+            EpcRoofDescriptions.sloping_pitched_as_built_unknown,
+        ]

datatypes/epc/walls.py

@@ -0,0 +1,74 @@
+from enum import Enum
+from typing import List
+
+
+class EpcWallDescriptions(Enum):
+    # Cavity wall descriptions
+    cavity_insulated_assumed: str = "Cavity wall, as built, insulated (assumed)"
+    cavity_partial_insulated_assumed: str = "Cavity wall, as built, partial insulation (assumed)"
+    cavity_no_insulation_assumed: str = "Cavity wall, as built, no insulation (assumed)"
+    cavity_filled_cavity: str = "Cavity wall, filled cavity"
+    cavity_internal_insulation: str = "Cavity wall, with internal insulation"
+    cavity_external_insulation: str = "Cavity wall, with external insulation"
+    cavity_filled_plus_internal: str = "Cavity wall, filled cavity and internal insulation"
+    cavity_filled_plus_external: str = "Cavity wall, filled cavity and external insulation"
+
+    # Solid wall descriptions
+    solid_brick_internal_insulation: str = "Solid brick, with internal insulation"
+    solid_brick_external_insulation: str = "Solid brick, with external insulation"
+    solid_brick_no_insulation_assumed: str = 'Solid brick, as built, no insulation (assumed)'
+    solid_brick_partial_insulated_assumed: str = 'Solid brick, as built, partial insulation (assumed)'
+    solid_brick_insulated_assumed: str = 'Solid brick, as built, insulated (assumed)'
+
+    # System
+    system_external_insulation: str = "System built, with external insulation"
+    system_internal_insulation: str = "System built, with internal insulation"
+    system_no_insulation_assumed: str = "System built, as built, no insulation (assumed)"
+    system_partial_insulated_assumed: str = "System built, as built, partial insulation (assumed)"
+    system_insulated_assumed: str = "System built, as built, insulated (assumed)"
+
+    # Timber
+    timber_frame_internal_insulation: str = "Timber frame, with internal insulation"
+    timber_frame_external_insulation: str = "Timber frame, with external insulation"
+    timber_frame_no_insulation_assumed: str = "Timber frame, as built, no insulation (assumed)"
+    timber_frame_partial_insulated_assumed: str = "Timber frame, as built, partial insulation (assumed)"
+    timber_frame_insulated_assumed: str = "Timber frame, as built, insulated (assumed)"
+
+    # Granite/whinstone
+    granite_whinstone_external_insulation: str = "Granite or whin, with external insulation"
+    granite_whinstone_internal_insulation: str = "Granite or whin, with internal insulation"
+    granite_whinstone_no_insulation_assumed: str = "Granite or whin, as built, no insulation (assumed)"
+    granite_whinstone_partial_insulated_assumed: str = "Granite or whin, as built, partial insulation (assumed)"
+    granite_whinestone_insulated_assumed: str = "Granite or whin, as built, insulated (assumed)"
+
+    # Sandstone/limestone
+    sandstone_limestone_internal_insulation: str = "Sandstone, with internal insulation"
+    sandstone_limestone_external_insulation: str = "Sandstone, with external insulation"
+    sandstone_limestone_no_insulation_assumed: str = "Sandstone, as built, no insulation (assumed)"
+    sandstone_limestone_partial_insulated_assumed: str = "Sandstone, as built, partial insulation (assumed)"
+    sandstone_limestone_insulated_assumed: str = "Sandstone, as built, insulated (assumed)"
+
+    # Cob
+    cob_as_built_average: str = "Cob, as built"
+    cob_as_built_good: str = "Cob, as built"
+
+    # unknown descriptions which may get mapped later or handled via fallback
+    cavity_as_built_unknown: str = "Cavity wall, as built, unknown insulation"
+    solid_brick_as_built_unknown: str = "Solid brick, as built, unknown insulation"
+    system_as_built_unknown: str = "System built, as built, unknown insulation"
+    timber_frame_as_built_unknown: str = "Timber frame, as built, unknown insulation"
+    granite_as_built_unknown: str = "Granite or whin, as built, unknown insulation"
+    sandstone_as_built_unknown: str = "Sandstone, as built, unknown insulation"
+    cob_as_built_unknown: str = "Cob, as built, unknown insulation"
+
+    @property
+    def unknown_descriptions(self) -> List["EpcWallDescriptions"]:
+        return [
+            EpcWallDescriptions.cavity_as_built_unknown,
+            EpcWallDescriptions.solid_brick_as_built_unknown,
+            EpcWallDescriptions.system_as_built_unknown,
+            EpcWallDescriptions.timber_frame_as_built_unknown,
+            EpcWallDescriptions.granite_as_built_unknown,
+            EpcWallDescriptions.sandstone_as_built_unknown,
+            EpcWallDescriptions.cob_as_built_unknown,
+        ]

etl/bill_savings/KwhData.py

@@ -196,6 +196,10 @@ class KwhData:
         if save and self.bucket is None:
             raise Exception("bucket not set, cannot save data")
 
+        if data.empty:
+            # If we have no data
+            return data
+
         # TODO: New is a temporary parameter, which will transform the epc descriptions to their transformed features
         #       in anticipation of the new model
 

infrastructure/terraform/lambda/condition-etl/main.tf

@@ -0,0 +1,43 @@
+data "aws_secretsmanager_secret_version" "db_credentials" {
+  secret_id = "${var.stage}/assessment_model/db_credentials"
+}
+
+data "terraform_remote_state" "shared" {
+  backend = "s3"
+  config = {
+    bucket = "assessment-model-terraform-state"
+    key = "env:/${var.stage}/terraform.tfstate" # TODO: dont hardcode this
+    region = "eu-west-2"
+  }
+}
+
+locals {
+  db_credentials = jsondecode(data.aws_secretsmanager_secret_version.db_credentials.secret_string)
+}
+
+
+module "lambda" {
+  source = "../modules/lambda_with_sqs"
+
+  name  = "condition-etl"
+  stage = var.stage
+
+  image_uri = local.image_uri
+  timeout = 180
+
+
+  environment = merge(
+    {
+      STAGE     = var.stage
+      LOG_LEVEL = "info"
+      DB_USERNAME = local.db_credentials.db_assessment_model_username
+      DB_PASSWORD = local.db_credentials.db_assessment_model_password
+    },
+  )
+
+}
+
+resource "aws_iam_role_policy_attachment" "attach_condition_etl_s3_read" {
+  role       = module.lambda.role_name
+  policy_arn = data.terraform_remote_state.shared.outputs.condition_etl_s3_read_arn
+}

infrastructure/terraform/lambda/condition-etl/provider.tf

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

infrastructure/terraform/lambda/condition-etl/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

@@ -6,6 +6,10 @@ module "role" {
   name   = "${var.name}-lambda-${var.stage}"
 }
 
+output "role_name" {
+  value = module.role.role_name
+}
+
 ############################################
 # SQS queue + DLQ
 ############################################

infrastructure/terraform/lambda/postcodeSplitter/main.tf

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

infrastructure/terraform/lambda/postcodeSplitter/provider.tf

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

infrastructure/terraform/lambda/postcodeSplitter/variables.tf

@@ -0,0 +1,26 @@
+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/shared/main.tf

@@ -84,7 +84,7 @@ resource "aws_db_instance" "default" {
   # Temporary to enfore immediate change
   apply_immediately = true
   # Set up storage type to gp3 for better performance
-  storage_type      = "gp3"
+  storage_type = "gp3"
 }
 
 # Set up the bucket that recieve the csv uploads of epc to be retrofit
@@ -298,10 +298,6 @@ module "address2uprn_state_bucket" {
 
 }
 
-output "address2uprn_state_bucket_name" {
-  value = module.address2uprn_state_bucket.bucket_name
-}
-
 module "address2uprn_registry" {
   source = "../modules/container_registry"
   name   = "address2uprn"
@@ -309,6 +305,62 @@ module "address2uprn_registry" {
 
 }
 
-output "address2uprn_repository_url" {
+################################################
-  value = module.address2uprn_registry.repository_url
+# Condition ETL – Lambda ECR
+################################################
+module "condition_etl_state_bucket" {
+  source      = "../modules/tf_state_bucket"
+  bucket_name = "condition-etl-terraform-state"
+
+}
+
+module "condition_etl_registry" {
+  source = "../modules/container_registry"
+  name   = "condition-etl"
+  stage = var.stage
+
+}
+
+################################################
+# Postcode Splitter – Lambda ECR
+################################################
+module "postcode_splitter_state_bucket" {
+  source      = "../modules/tf_state_bucket"
+  bucket_name = "postcode-splitter-terraform-state"
+
+}
+
+module "postcode_splitter_registry" {
+  source = "../modules/container_registry"
+  name   = "postcode_splitter"
+  stage = var.stage
+
+}
+
+################################################
+# Conidition data – S3 bucket
+################################################
+module "condition_data_bucket" {
+  source      = "../modules/s3"
+  bucketname = "condition-data-${var.stage}"
+  allowed_origins = var.allowed_origins
+}
+
+resource "aws_iam_policy" "condition_etl_s3_read" {
+  name        = "ConditionETLReadS3"
+  description = "Allow Lambda to read objects from condition-data-${var.stage}"
+  policy      = jsonencode({
+    Version = "2012-10-17"
+    Statement = [
+      {
+        Effect = "Allow"
+        Action = ["s3:GetObject"]
+        Resource = "arn:aws:s3:::condition-data-${var.stage}/*"
+      }
+    ]
+  })
+}
+
+output "condition_etl_s3_read_arn" {
+  value = aws_iam_policy.condition_etl_s3_read.arn
 }

pytest.ini

@@ -1,4 +1,4 @@
 [pytest]
 pythonpath = .
 addopts = --cov-report term-missing --cov=etl/epc --cov=recommendations --cov=backend --cov=etl/epc_clean --cov=etl/spatial
-testpaths = recommendations/tests backend/tests etl/epc/tests etl/epc_clean/tests etl/spatial/tests backend/condition/tests backend/address2UPRN/tests
+testpaths = recommendations/tests backend/tests etl/epc/tests etl/epc_clean/tests etl/spatial/tests backend/condition/tests backend/address2UPRN/tests backend/onboarders/tests

recommendations/Recommendations.py

@@ -1090,6 +1090,7 @@ class Recommendations:
 
         ashp_cop = ashp_cop if ashp_cop else assumptions.AVERAGE_ASHP_EFFICIENCY
 
+        #
         kwh_impact_table = kwh_simulation_predictions["heating_kwh_predictions"][
             kwh_simulation_predictions["heating_kwh_predictions"]["property_id"] == str(property_instance.id)
             ].merge(

recommendations/RoofRecommendations.py

@@ -331,18 +331,18 @@ class RoofRecommendations:
         """
 
         # Can a non-primary part satisfy loft insulation?
-        primary_needs_loft = component_needs[1]["needs_loft_insulation"]
+        primary_needs_loft = component_needs[0]["needs_loft_insulation"]
         secondary_needs_loft = any(
-            p['needs_loft_insulation'] for idx, p in component_needs.items() if idx != 1
+            p['needs_loft_insulation'] for idx, p in component_needs.items() if idx != 0
         )
 
         if primary_needs_loft and not secondary_needs_loft:
             # Only option is loft
             return "loft"
 
-        primary_needs_sloping = component_needs[1]["needs_sloping_ceiling"]
+        primary_needs_sloping = component_needs[0]["needs_sloping_ceiling"]
         secondary_needs_sloping = any(
-            p['needs_sloping_ceiling'] for idx, p in component_needs.items() if idx != 1
+            p['needs_sloping_ceiling'] for idx, p in component_needs.items() if idx != 0
         )
 
         if primary_needs_sloping and not secondary_needs_sloping:
@@ -418,11 +418,13 @@ class RoofRecommendations:
             return needs_sloping, not needs_loft  # Indicates that the property needs sloping ceiling as we only run
             # this in that case
 
+        roof_components = [x for x in find_my_epc_components if x["component_name"] == "Roof"]
+
         extracted_roof_descriptions = {
             idx: {
                 "description": component["description"],
                 **RoofAttributes(component["description"]).process()
-            } for idx, component in enumerate(find_my_epc_components) if component["component_name"] == "Roof"
+            } for idx, component in enumerate(roof_components)
         }
 
         component_needs = {}

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 = 524
 SCENARIOS = [
-    986,
+    1009,
 ]
 scenario_names = {
-    986: "EPC C",
+    1009: "EPC C; Most Economic",
 }
 
 

utils/s3.py

@@ -264,6 +264,7 @@ def save_excel_to_s3(df, bucket_name, file_key):
 
 
 def read_csv_from_s3(bucket_name, filepath):
+    logger.info(f"Reading CSV file from S3 bucket '{bucket_name}' with key '{filepath}'")
     s3 = boto3.client('s3')
 
     # Get the object from s3