5f4a78e4c9
The existing golden test compares calc PE/CO2 against the integer-rounded
lodged register values (energy_consumption_current / co2_emissions_current),
which conflates real calculator gaps with register rounding. This adds a
parallel pin against each cert's Elmhurst dr87 worksheet (286)/(272) at full
precision — a clean calculator-vs-Elmhurst signal for the 47 worksheet-backed
certs (9 ASHP + 38 cohort-2).
Findings at capture (calc − worksheet, on the worksheet's own decimal TFA):
- 37/47 exact on both PE (<0.05 kWh/m²) and CO2 (<0.02 kg).
- 10 higher-consumption gas certs carry PE +0.5..+1.5 kWh/m² AND
CO2 -0.5..-1.1 kg simultaneously. PE-over + CO2-under on the same
certs is the fingerprint of a small gas→electricity fuel-split
difference (elec PE 1.51 > gas 1.13, but elec CO2 0.136 < gas 0.21),
not a factor-value error — next slice candidate.
An earlier "41/47 PE gaps" reading was a JSON-integer-TFA division artifact;
comparing on the worksheet's decimal TFA (which the calculator also uses)
collapses it to the real 10. Worksheet values frozen as literals (the dr87
PDFs are untracked, so not parsed at test time) per the worksheet_unrounded_sap
convention. Also replaced a pre-existing pytest.approx with abs-diff to keep
the file at zero pyright errors (feedback_abs_diff_over_pytest_approx).
106 passed (was 59); pyright 0 errors.
Co-Authored-By: Claude Opus 4.8 <noreply@anthropic.com>
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| .devcontainer | ||
| .github/workflows | ||
| .idea | ||
| .vscode | ||
| applications | ||
| asset_list | ||
| backend | ||
| backlog | ||
| datatypes | ||
| deployment/terraform | ||
| docs | ||
| domain | ||
| epr_data_exports | ||
| etl | ||
| infrastructure | ||
| model_data/requirements | ||
| orchestration | ||
| recommendations | ||
| repositories | ||
| sap worksheets/heating systems examples | ||
| 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