6ee2f6257a
Closes the mapper-coverage gaps surfaced by the modelling_e2e prediction-cohort failures (portfolio 796): - built_form (SAP-16.0): derive from dwelling_type in _normalize_sap_schema_16_x (Mid-terrace->4, End-terrace->3, Semi-detached->2, Detached->1; flats->modal 4). ML-only field (SAP calc never reads it) so SAP- and gate-neutral. 5 flat certs that omitted built_form now map. - photovoltaic_supply as a measured-array LIST: routed all pre-21 RdSAP mappers (17.0/17.1/18.0/19.0/20.0.0) through _map_schema_21_pv, whose list branch is now dict-tolerant (_pv_array_field reads dict OR dataclass). They capture the PV arrays like 21.0.x instead of raising "'list' object has no attribute none_or_no_details" and sinking the whole cohort. - windows-as-dict (16.x): handled in the normalizer (not just windows-as-list). Genuinely-sparse certs (omit door_count/habitable/glazed_area) remain fail-loud; the gate-regressing multiple_glazed_proportion default and the recursive RdSAP-21.0.0 ADR-0028 alignment are left fail-loud + flagged for review (worklist). +5 regression tests; component-accuracy gate 26/26; 0 new pyright errors. Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com> |
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| .claude/skills | ||
| .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