4d14607e7e
SAP-Schema-16.2 (datatypes/epc/domain/mapper.py): - 16.2 is structurally an RdSAP-17.1 cert under a different name; add _normalize_sap_schema_16_2 (field renames + defaults) and dispatch to the tested from_rdsap_schema_17_1 mapper. uprn_100020933699 maps → SAP 71. - Honour a "Single glazed" windows description when multiple_glazing_type="ND" (was defaulting to double) → RdSAP-21 code 5; eng 72→71 (lodged 70). - 4 regression tests + sap_16_2.json fixture; 0 new pyright errors. Flat party-wall fix (domain/sap10_calculator/worksheet/heat_transmission.py): - Full-SAP flats carry flatness in dwelling_type, not property_type, so the party-wall default fell through to the 0.25 house value instead of the RdSAP Table-15 flat 0.0. Add _is_flat_or_maisonette_dwelling fallback + regression test. uprn_10093116529 80→81 (matches the cert's lodged party u_value 0). Accuracy corpus pins (tests/domain/sap10_calculator/test_real_cert_sap_accuracy.py): - uprn_10093116543 (SAP-17.1 gas-combi semi): engine 81 (Elmhurst 77; documented full-SAP→RdSAP residual — measured wall/floor U + PCDB boiler vs RdSAP defaults). - uprn_10093116529 (SAP-17.1 g/f flat): engine 81 (Elmhurst 78). devcontainer: add poppler-utils (pdfinfo) for the documents-parser PDF fixtures. Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com> |
||
|---|---|---|
| .claude | ||
| .devcontainer | ||
| .github/workflows | ||
| .idea | ||
| .vscode | ||
| applications | ||
| asset_list | ||
| backend | ||
| backlog | ||
| datatypes | ||
| deployment/terraform | ||
| docs | ||
| domain | ||
| epr_data_exports | ||
| etl | ||
| harness | ||
| infrastructure | ||
| model_data/requirements | ||
| orchestration | ||
| recommendations | ||
| repositories | ||
| sap worksheets | ||
| 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 | ||
| next_claude_prompt.txt | ||
| P960-0001-001431-2.pdf | ||
| package-lock.json | ||
| package.json | ||
| playground.py.local-backup | ||
| pyproject.toml | ||
| pyrightconfig.json | ||
| pytest.ini | ||
| README.md | ||
| run_lambda_local.sh | ||
| serverless.yml | ||
| Summary_001431-3.pdf | ||
| 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