d44af109a9
The SAP 10.2 / RdSAP 10 calculator is closed at 930/930 pin tests green.
Tidying the docs for hand-off to the API-integration agent.
New: docs/sap-spec/SAP_CALCULATOR.md
Canonical module overview — public API surface, two-cascade
architecture (Rating UK-avg, Demand postcode), simulator-use-case
example, file map, validation contract + hard rules, fixture cohort
notes, spec page references. Replaces the scattered "what's the
shape" knowledge that was previously only in commit messages.
Rewritten: docs/sap-spec/HANDOVER_NEXT.md
Old handover (work queue for slices 26-36) is obsolete. Replaced
with the next agent's brief: build an API → SAP scoring integration
test using the 6 Elmhurst fixtures. Includes a copy-paste reference
scoring path, expected outputs per fixture, list of files to read
on day 1, and scope guardrails.
Refreshed module docstrings:
- cert_to_inputs.py: now describes both cascades, the deferred-edge-
case list reflects current state (RR/secondary/§15 living-area
rounding all DONE; thermal-mass and control-temp adjustment still
deferred).
- calculator.py: per-end-use CO2/PE factor machinery documented;
stale "single-fuel approximation" claim removed (closed in slice 32).
- sap/README.md: validation paragraph now says "930/930 green" and
points to SAP_CALCULATOR.md instead of the obsolete HANDOVER_NEXT.
Verified the API examples in both docs produce the expected per-fixture
outputs (SAP=62, EI=60, Carbon=3104.1222, PE=16931.7227 for 000474).
Wider regression: 1585/1585 PASS, zero failures.
Co-Authored-By: Claude Opus 4.7 <noreply@anthropic.com>
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| .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