d9aee9b9c4
Adds the (API JSON + Summary PDF) fixtures for cert
0380-2471-3250-2596-8761 — the Air Source Heat Pump pilot
identified in the handover. Property: 16 Beech Lea, WIGTON CA7 5JY
(semi-detached bungalow, ASHP PCDB idx 104568).
Source: API JSON fetched via EpcClientService. Summary PDF copied
from `sap worksheets/Additional data with api/
0380-2471-3250-2596-8761/Summary_000899.pdf`.
Worksheet target: SAP 88.5104 (continuous), from `dr87-0001-000899
.pdf`.
**This is the HP pilot, intentionally deferred.** Initial probe on
these fixtures (uncommitted before this slice):
- Summary mapper cascade SAP: 18.08 (Δ -70.43 vs worksheet)
- API mapper cascade SAP: 70.14 (Δ -18.37 vs worksheet)
Both paths are catastrophically RED. The mapper has never been
validated against an ASHP cert and there's substantial cascade
plumbing required:
- API mapper correctly identifies the HP (COP 2.3) but fabric HLC
is 104 W/K vs the ~50 W/K needed for SAP 88.51.
- Summary mapper misreads the HP as an 80%-efficient boiler
(catastrophic).
- 7 of 9 newly-staged certs are ASHPs (6 share PCDB idx 104568,
cert 9418 uses 102421), so a shared HP-cascade fix will likely
close most of them at once.
Stashed here so the next agent can pick up the HP workstream
without needing to refetch from the EPB API. Recommend not
attempting these slices until the boiler workflow (cert 0330) is
proven; the boiler cascade is the reference shape and HP work
should build on a known-good baseline. Handover §"Heat-pump
workstream sketch" outlines the likely 15-30 slice queue.
Co-Authored-By: Claude Opus 4.7 <noreply@anthropic.com>
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| .devcontainer | ||
| .github/workflows | ||
| .idea | ||
| .vscode | ||
| applications | ||
| asset_list | ||
| backend | ||
| backlog | ||
| datatypes | ||
| deployment/terraform | ||
| docs/adr | ||
| domain | ||
| epr_data_exports | ||
| etl | ||
| infrastructure | ||
| model_data/requirements | ||
| orchestration | ||
| recommendations | ||
| repositories | ||
| scripts | ||
| sfr/principal_pitch | ||
| survey_report | ||
| tests | ||
| utilities | ||
| utils | ||
| .coveragerc | ||
| .dockerignore | ||
| .gitignore | ||
| __init__.py | ||
| ara_backend_design.md | ||
| BaseUtility.py | ||
| CLAUDE.md | ||
| conftest.py | ||
| CONTEXT.md | ||
| devcontainer.sh | ||
| Dockerfile.test | ||
| Dockerfile.test.dockerignore | ||
| Makefile | ||
| MEMORY.md | ||
| package-lock.json | ||
| package.json | ||
| pyproject.toml | ||
| pyrightconfig.json | ||
| pytest.ini | ||
| README.md | ||
| run_lambda_local.sh | ||
| serverless.yml | ||
| test.requirements.txt | ||
| tox.ini | ||
| UBIQUITOUS_LANGUAGE.md | ||
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