e312aae95d
Per review (Khalim): lift the full-SAP detection out of the SAP-Schema-16.x branch into a single top-level gate in from_api_response, and key it on the gov-API's own assessment_type declaration rather than the structural sap_opening_types proxy. - _is_full_sap_assessment(data): assessment_type == "SAP" — the authoritative SAP-vs-RdSAP classification. Verified to separate the entire fixture corpus: every full-SAP schema (SAP-Schema-17.x/18.x + the broken LIG 16.x) is "SAP"; every reduced cert (RdSAP-Schema-* and reduced SAP-Schema-16.x, incl. sap_16_0.json) is "RdSAP". data_type / sap_opening_types agree but are derived shape artifacts; assessment_type is the meaning. - A cert that is full-SAP by assessment_type but whose schema_type LABEL is not a recognised full-SAP schema is a *broken schema type* (label disagrees with the assessment). _record_broken_schema_type logs it — visible, not silently rerouted — so unreliable labels surface and coverage grows as new mislabels appear. Generalises beyond 16.x to any future mislabel. - _from_full_sap maps it via the full-SAP 17.1 mapper (real measured openings, no defaulting; only `tenure` defaulted). Correctly-labelled full-SAP certs keep their dedicated branches (one-mapper-per-schema convention); reduced certs are unchanged. Tests: broken cert routed AND recorded; correctly-labelled full-SAP not recorded. 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