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Khalim Conn-Kowlessar 8dbe873daf ADR-0009: pivot to deterministic SAP 10.3 calculator (Accepted)
Promotes ADR-0009 from Proposed to Accepted after the grill-with-docs
session resolved all seven open questions. Bundles the SAP 10.3 and
RdSAP 10 specifications under docs/sap-spec/ plus a calculator design
sketch (module layout, monthly-loop pseudo-code, status table).

CONTEXT.md adds three new domain terms parallel to existing performance
language:
  - Calculated SAP10 Performance (parallel to Effective / Lodged)
  - SAP10 Calculation (process; implemented by Sap10Calculator)
  - Measure Application (process; implemented by MeasureApplicator)

ML pipeline is NOT retired — it stays as the residual head once the
calculator reaches parity in Session B. ADR-0009 §"Grill outcomes" carries
the seven binding scope decisions plus three Session-A-scope changes
discovered during the grill (RdSAP §19 EER formula, SAP 10.2 Appendix A
cross-reference, RdSAP Table 29 cascade defaults).
2026-05-17 21:27:21 +00:00
.devcontainer added env variables for boto 2026-05-12 12:34:17 +00:00
.github/workflows resolve merge conflict 2026-05-13 14:22:04 +00:00
.idea scaffolding for ml pipeline 2026-05-16 14:15:56 +00:00
.vscode added utils to allow easier subtask management 2026-03-02 15:15:39 +00:00
asset_list save 2026-05-07 15:55:44 +00:00
backend slice 15a: add wall/floor/roof + demand scalar features for retrofit simulation 2026-05-16 22:08:27 +00:00
backlog implemented onboarding 2026-04-21 20:23:33 +00:00
datatypes slice 15d: +50 features (gap fill + secondary building part); drop 2 derived 2026-05-17 10:13:03 +00:00
docs ADR-0009: pivot to deterministic SAP 10.3 calculator (Accepted) 2026-05-17 21:27:21 +00:00
epr_data_exports allowing carbon and energy otimisation by removing slack 2025-07-31 19:13:16 +01:00
etl scaffolding for ml pipeline 2026-05-16 14:15:56 +00:00
infrastructure/terraform correct tfstate bucket name 2026-05-12 13:03:04 +00:00
model_data/requirements its working the way khalim wanted wiht postcode and then search that 2026-01-22 15:17:13 +00:00
packages slice 20a.1: route ventilation through predicted_space_heating_kwh (v2.7.1) 2026-05-17 18:48:57 +00:00
recommendations save 2026-05-07 15:55:44 +00:00
scripts added type hinting to uprn 2026-05-12 09:40:12 +00:00
services slice 16i: MAE + RMSE in metrics; sample_weight_fn + low_sap_tail_weight 2026-05-17 14:48:00 +00:00
sfr/principal_pitch added added historic epc data class with shape 2026-05-08 12:03:35 +00:00
survey_report quidos site notes extraction 2025-02-18 19:49:29 +00:00
utils changed to utils 2026-05-11 08:37:44 +00:00
.coveragerc fixed unit tests 2023-10-05 16:04:12 +01:00
.dockerignore make sure all test files are ignored when docker images are built 2026-04-23 11:29:07 +00:00
.gitignore slice 14a: ml_training_data pkg + sample.py (CSV filter + random sample) 2026-05-16 17:39:43 +00:00
__init__.py added checking for directory before creation and made some minor style changes 2023-08-25 15:21:17 +01:00
AGENTS.md added bulk address uprn route 2026-04-20 13:06:31 +00:00
ara_backend_design.md second grill session updating prd + context 2026-05-15 10:41:47 +00:00
BaseUtility.py fixed missing task and subtask for single remote assessments 2025-11-27 17:50:26 +00:00
CLAUDE.md note kwh service not needing predictions 2026-05-13 21:52:02 +00:00
conftest.py working on integrating new EPC api into address2UPRN 2026-04-27 11:32:44 +00:00
CONTEXT.md ADR-0009: pivot to deterministic SAP 10.3 calculator (Accepted) 2026-05-17 21:27:21 +00:00
devcontainer.sh add dev container 2026-04-17 14:50:57 +00:00
Dockerfile.test post gres can't be ran as root 2026-03-13 15:56:13 +00:00
Dockerfile.test.dockerignore run tests 2026-03-13 15:44:16 +00:00
Makefile adding to dev container to create shared network on start up 2026-04-25 15:03:07 +00:00
MEMORY.md memory 2026-04-02 10:24:31 +00:00
package-lock.json restructuring openUrpn code 2023-07-20 11:41:43 +01:00
package.json restructuring openUrpn code 2023-07-20 11:41:43 +01:00
pyproject.toml slice 14a: ml_training_data pkg + sample.py (CSV filter + random sample) 2026-05-16 17:39:43 +00:00
pyrightconfig.json slice 14d: build_features wires bulk reader -> mapper -> EpcMlTransform 2026-05-16 18:38:41 +00:00
pytest.ini slice 14a: ml_training_data pkg + sample.py (CSV filter + random sample) 2026-05-16 17:39:43 +00:00
README.md adding to dev container to create shared network on start up 2026-04-25 15:03:07 +00:00
run_backlog.sh added bulk address uprn route 2026-04-20 13:06:31 +00:00
run_lambda_local.sh debugging local lambda run and updating the sap point checking condition 2023-09-13 18:47:12 +01:00
serverless.yml added logic to add to serverless 2026-04-22 12:39:44 +00:00
test.requirements.txt fixing missing deps for tests 2026-04-30 20:03:57 +00:00
tox.ini removing playright install for integration test 2026-04-30 20:08:13 +00:00
UBIQUITOUS_LANGUAGE.md note kwh service not needing predictions 2026-05-13 21:52:02 +00:00

Model Repository

This repository contains the code pertaining to the development of the data science and machine learning products being utilised by Hestia.

The different folders in this repository relate to services that can be used independently, or can be imported and used as part of a larger application

Getting Started

Prerequisites

Dev Container Setup

This repo uses a Docker Compose-based dev container. The model-backend service joins a shared-dev Docker network so it can communicate with other local services (e.g. a frontend container) running on your machine.

VS Code users: The initializeCommand in devcontainer.json creates the shared-dev network automatically before the container starts. No manual step required — just open the repo and select Reopen in Container.

Non-VS Code / CI workflows: Run the following once before starting the container:

make dev-setup

This is idempotent and safe to re-run if the network already exists.

Folders

backend/

This folder contains the code for the fastapi backend service, which provides an interface to much of the functionality in this repository, for the frontend

model_data/

This folder contains related to the reading and preparation of assessment model data, including pulling out epc attributes

Testing

All tests can be run, against the configuration in pytest.ini running

pytest

This will run the complete panel of tests and report on coverage in the locations specified by the pytest.ini file.

To run tests in a specific service, e.g. inside of model_data, simply run

pytest --cov-config=model_data/.coveragerc --cov=model_data

This will produce the test results and coverage reports