1bfce431d2
Cert 9501 (Summary_000784.pdf) is a flat. The Elmhurst Summary's
§1.0 "Property type" section lodges the built-form descriptor
("M Mid-Terrace", "D Detached", ...) only for houses — flats have no
attachment line, and the §2.0 "Number of Storeys" header follows
immediately after the "F Flat" property-type value.
The extractor's prior `_extract_attachment` regex captured the line
right after the property-type value unconditionally, so cert 9501
ended up with `attachment="2.0 Number of Storeys:"` — section-header
noise that the mapper surfaced on `EpcPropertyData.built_form`.
Downstream, this broke the cascade's `_dwelling_exposure` routing
(no prefix match → defaulted to fully-exposed houses) and so the
cert 9501 Summary path was Δ -5.25 SAP vs worksheet 68.5252.
Detect section-header noise via the leading `<digit>.<digit> `
pattern and the "Number of Storeys" substring; return "" in that
case so flats produce empty `built_form`. Houses still pick up their
real attachment (cohort 0330's "M Mid-Terrace" remains correct).
Co-Authored-By: Claude Opus 4.7 <noreply@anthropic.com>
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| .github/workflows | ||
| .idea | ||
| .vscode | ||
| applications | ||
| asset_list | ||
| backend | ||
| backlog | ||
| datatypes | ||
| deployment/terraform | ||
| docs/adr | ||
| 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