bf6a7e04b3
Removes the legacy SAP-10.3-flavoured scalar internal_gains_w API (plus
its InternalGainsBreakdown dataclass, _default_occupancy_sap_j, and the
L5b/L8c fallback constants used only by the legacy path). Calculator
now indexes a CalculatorInputs.internal_gains_monthly_w 12-tuple per
month instead of recomputing inline.
cert_to_inputs:
- _hot_water_fuel_kwh_per_yr now also returns the §4 (65)m
heat_gains_monthly_kwh tuple (was discarded). Plumbed forward into
internal_gains_from_cert via water_heating_gains bridge.
- Calls §5 orchestrator with EpcPropertyData + dwelling_volume_m3 +
(65)m + AVERAGE overshading (Table 6d default per note 1).
- Falls back to (0.0,) * 12 internal gains when TFA missing.
CalculatorInputs gains a new required field `internal_gains_monthly_w`.
Synthetic-input tests (test_calculator, test_bre_worked_examples)
updated to pass a 450 W constant tuple.
All 283 §1-§7 tests pass. E2e SAP-score regression unaffected for
000490 (still within 1 point) and 000474 (still within 7) because the
legacy fixture build_epc()s don't carry §5-specific sap_windows /
bulbs / heating-details, so the orchestrator returns the L5b lighting
fallback + zero (65)m — matches the legacy scalar's behaviour.
Co-Authored-By: Claude Opus 4.7 <noreply@anthropic.com>
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| .devcontainer | ||
| .github/workflows | ||
| .idea | ||
| .vscode | ||
| asset_list | ||
| backend | ||
| backlog | ||
| datatypes | ||
| docs | ||
| epr_data_exports | ||
| etl | ||
| infrastructure/terraform | ||
| model_data/requirements | ||
| packages | ||
| recommendations | ||
| scripts | ||
| services | ||
| sfr/principal_pitch | ||
| survey_report | ||
| utils | ||
| .coveragerc | ||
| .dockerignore | ||
| .gitignore | ||
| __init__.py | ||
| AGENTS.md | ||
| 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_backlog.sh | ||
| 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