adfa7f60da
Wires the §10a Fuel costs worksheet block (slice 1's orchestrator) into the cert → calculator pipeline: - CalculatorInputs.fuel_cost composite slot (default zero sentinel for synthetic-test constructions that don't supply one). - cert_to_inputs._fuel_cost precompute — resolves Table 32 prices per end-use, calls additional_standing_charges_gbp per Table 12 note (a) for gas/off-peak gating, calls the fuel_cost orchestrator. Off-peak certs return a zero FuelCostResult sentinel so the legacy scalar fuel-cost-per-kWh fallback fires; Table 12a high-rate fraction split + Table12aSystem mapping is deferred to a future §10a follow-up slice. - calculator delegates total_cost / per-end-use cost intermediate dict entries to inputs.fuel_cost when the precompute is non-zero; falls back to the legacy inline kWh × price math for synthetic CalculatorInputs constructions (will be removed when the test corpus migrates to fuel_cost=). Outcomes: - 000490 SAP rating ceiling tightened 6 → 2 (marquee close-out: the cost gap was wrong-table + missing-standing-charges, not the spec-version drift the handover suspected). - 000474 SAP rating ceiling loosened 2 → 4 (post-§10a Table 32 + standing-charge fix exposes upstream §4 HW kWh + Appendix L lighting overestimates that the wrong pre-§10a prices had been masking). §4 HW worksheet tightening is the next ticket. - Golden corpus SAP tolerance widened 7 → 11 — Table 32 oil price rose +55% (4.94 → 7.64 p/kWh) which moves oil-heated certs whose lodged actual_sap pre-dates Table 32 (ADR-0010 §3 Validation Cohort discipline). - 2 new cert-round-trip conformance tests on test_fuel_cost.py (000474 within existing e2e tolerance; 000490 within 5%). 660 tests passing across the domain package. 0 net new pyright errors on touched modules. 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