712cc6f3f8
pdftotext dumps of hand-entered Elmhurst worksheets wrap the §11 glazing-
GAP column ("16 mm or more") onto the glazing-TYPE token, yielding labels
like "Double between 2002 and 2021 16 mm or [1st]" that
`_elmhurst_glazing_type_code` didn't recognise → UnmappedElmhurstLabel,
blocking the whole Summary from parsing.
Added a fallback: when the lightly-cleaned label isn't a known key, strip a
trailing wrapped gap descriptor (`\s+\d+\s*mm\b.*$`) and retry. Applied
AFTER the direct lookup so explicitly-mapped interleaved variants (e.g.
"Double with unknown 16 mm or install date more", where the gap splits into
the middle) are unaffected. The gap drives the API-path U-value lookup, not
the site-notes glazing-type enum, so dropping it is loss-free for the
cascade.
Unblocks running our cascade on hand-entered worksheet Summaries — used to
validate the PV β-split against simulated case 18 (our split matches the
P960 worksheet exactly: gen 2684.17, onsite 970.77, export 1713.40).
Suite: 2391 passed, 1 skipped. Zero new pyright errors (mapper 32=32).
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