56f41ca4a2
Closes 31 of 32 mapper-vs-hand-built load-bearing divergences by populating fields the Elmhurst mapper extracts from Summary_000480. pdf but the original cohort hand-built left at their `make_minimal_ sap10_epc` / dataclass-default values. Every change is cascade- equivalent — none alter `_FIXTURE_PINS["000480"]` SapResult fields (all 11 1e-4 pins remain GREEN against worksheet `SAP value 61.2986`). Mirrors the Slice 64 / 72 pattern. 000480-specific deltas vs 000477: - Two SapBuildingParts (Main + Ext1) → Cat A descriptive fields applied per-bp; Ext1 floor is "Above unheated space" (not "Ground floor") because the extension hangs over an open passageway (the cert's `is_exposed_floor=True` for the lowest Ext1 floor). - `roof_insulation_thickness=300` on Main — cascade-inert because the RR (19.83 m²) is larger than the Main storey footprint (15.28 m²), so Main has no external roof line; set for field parity with the mapper, which extracts the §8 Main row's 300 mm regardless. - `extensions_count=1` — was 0 by default; the mapper extracts it from `len(survey.extensions)` (Slice 54 fix). Standard Cat A additions (per Slice 72 pattern): floor descriptive fields, roof_insulation_location, 6 ventilation zero counts, draught_lobby=True, pressure_test="Not available", top-level descriptive strings + booleans + number_of_storeys=3, shower_outlets, central_heating_pump_age_str. Diff count: 32 → **1**. Remaining diff is structural: - `sap_windows: LEN 7 vs 2` — closed via the next-slice 1:1 expansion. 11 cohort 000480 cascade pins still GREEN; pyright net-zero on the touched fixture. Co-Authored-By: Claude Opus 4.7 <noreply@anthropic.com> |
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| .devcontainer | ||
| .github/workflows | ||
| .idea | ||
| .vscode | ||
| asset_list | ||
| backend | ||
| backlog | ||
| datatypes | ||
| docs | ||
| epr_data_exports | ||
| etl | ||
| infrastructure/terraform | ||
| model_data/requirements | ||
| packages | ||
| recommendations | ||
| scripts | ||
| services | ||
| sfr/principal_pitch | ||
| survey_report | ||
| utils | ||
| .coveragerc | ||
| .dockerignore | ||
| .gitignore | ||
| __init__.py | ||
| AGENTS.md | ||
| 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_backlog.sh | ||
| 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