dae17a6d39
User clarified end-of-session: mapper is a thin enum-and-shape translation; when residuals remain after closing mapper coverage gaps, the gap is in the **calculator cascade**. This unlocks an Elmhurst-only fixture path that doesn't need API JSON at all. The fixture shape mirrors the 6 historical Elmhurst U985 fixtures (000474, 000477, 000480, 000487, 000490, 000516) at `domain/sap10_calculator/worksheet/tests/_elmhurst_worksheet_NNNNNN.py` + `test_e2e_elmhurst_sap_score.py`: build_epc() → cert_to_inputs → calculate_sap_from_inputs ↳ every SapResult field pinned at abs=1e-4 against U985 line refs Any failing pin is definitionally a calculator bug. The user generates certs in Elmhurst SAP and exports Summary + worksheet ZIPs — no gov.uk EPB lodgement required. Extended test case (000565) ready at `sap worksheets/extended test case/`: - Summary_000565.pdf (input) - U985-0001-000565.pdf (worksheet ground-truth) Cert 000565 is a wacky stress-test that exercises 3-4 zero-coverage cascade paths in one cert: Main + 4 extensions, age mix A through J, RR on every part with mixed ages, conservatory with fixed heaters, curtain-wall Ext2 post-2023, mixed wall types (solid brick + stone + curtain wall), mixed party walls (CU + CF + Unable to determine). After this cert lands, the user has agreed to generate single-feature certs (oil only, LPG only, solid fuel only, electric direct only, multi-main-heating, basement) to surface single-cause calculator gaps. Handover doc now has implementation outline (mirror _elmhurst_worksheet_000474.py shape) and a coverage-paths table showing which targets each fuel-type/config exercises. |
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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