f326e4eb53
The gov-EPC API mapper sets BOTH roof_construction (int) and roof_construction_type (str, derived via _API_ROOF_CONSTRUCTION_TO_STR), but the Elmhurst mapper set only the string — leaving roof_construction None on every site-notes cert. The SAP cascade reads the STRING (so SAP cross-mapper parity always held), but consumers of the int (e.g. domain/sap10_ml/transform.py ML aggregates `main_dwelling_roof_ construction`) silently saw None on the Elmhurst path. New `_elmhurst_roof_construction_int` maps the Elmhurst roof-type code to the same SAP10 int the API lodges (F→1, PN→3, PA→4, PS→8, S/A→7), harvested from the committed Summary fixtures. Unlike the wall map it returns None (not a strict-raise) for unmapped codes: the int is not cascade-load-bearing, so an unknown roof must not block the cert (vaulted 5 / thatched 6 / NR omitted until a fixture surfaces them). The 6 hand-built U985 reference fixtures gain the matching roof_construction int (4/4/3 etc.) so test_from_elmhurst_site_notes_ matches_hand_built_* still asserts structural parity. SAP output is unchanged (cascade reads the string). §4 suite green (2407 passed); the two pre-existing stone-§5.6 sap10_ml failures are unrelated/out of scope. 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 | ||
| 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