a5d889e143
Two unrelated breakages surfaced after merging the PR into this branch; neither was caused by the appliances/cooking work. test_appendix_u.py (9 failures) — signature drift + wrong methodology label. The climate lookups were renamed `external_temperature_c(region=…)` → `(region_or_climate, month)` when PostcodeClimate support landed for the demand cascade, but the tests still passed `region=`. The expected values match our SAP 10.2 _TABLE_U1/U2/U3 exactly (UK-avg Jan 4.3 °C, Thames Jul 17.9 °C, solar Jul 189 W/m², Shetland Jan wind 9.5 m/s), so these are valid 10.2 coverage — fixed the call signature to positional and corrected the mislabelled "SAP 10.3" docstrings to SAP 10.2 (we track 10.2 deliberately). Also converted pytest.approx → abs(x-y)<=tol per the repo convention; pyright on the file drops 48 → 0. test_table_32.py (2 failures) — the parametrised "match PDF p.95" test pinned heating oil (code 4) = 7.64 and FAME (code 73) = 5.44, but the table deliberately diverges from the PDF for these two carriers: oil = 5.44 (Slice S0380.131, two independent lodging engines agree the PDF 7.64 is the outlier) and FAME = 7.64 (Slice S0380.168). Updated the two expected values to the worksheet-canonical figures the table actually uses, with inline citations + a docstring note on the divergence. Full calculator + property_baseline + heating-corpus suites: 1748 pass, 0 fail. pyright net-improving on both files. 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 | ||
| 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