92fc4f4f16
Hands off the next workstream: the 38 cert subdirs at
`sap worksheets/additional with api 2/`. Each subdir is named after
the 20-digit EPC cert reference and contains a Summary PDF + dr87
worksheet PDF. API JSONs are NOT in the dataset but ARE fetchable
via the existing `EpcClientService` (token in `backend/.env` as
`OPEN_EPC_API_TOKEN`).
User's stated ordering: Elmhurst Summary mapping FIRST, API path
SECOND. Folder names = cert refs; need to verify the matching before
bulk-pinning (any mis-filed PDF would silently invalidate slice
work).
Handover ships with verified dataset and first-attempt baselines:
- Folder-vs-cert sweep: **38/38 match** at handover (postcode
parity check between Summary PDF and Open EPC API).
- First-attempt Summary-path probe across 38 certs:
24 ✅ closed at ±0.07 (first-try, zero new slices needed)
9 ~ small gap (<1 SAP) — likely 1 slice each
3 ✗ big gap (>1 SAP) — multi-slice investigation
2 RAISES UnmappedElmhurstLabel: cylinder_size='Normal'
The two `Normal` cylinder raises are the immediate Phase 1 slice —
Slice S0380.15's strict-enum pattern paid off on its first new
cohort by surfacing the gap at extraction time instead of as a
downstream SAP delta.
Workstream phases documented in the handover:
Phase 0: folder-vs-cert sweep (already done — 38/38)
Phase 1: fix 'Normal' cylinder unmapped-label raise
Phase 2: bulk-pin the 24 first-try-closures as chain tests
Phase 3: close the 9 small-gap certs one slice each
Phase 4: investigate the 3 big-gap certs (likely HP-routing)
Phase 5: fetch + persist API JSON for all 38, run API path tests
Phase 6: cross-mapper EPC parity (Summary EPC ≡ API EPC) — the
user's stated north-star
Includes:
- Paste-able diagnostic probe scripts (Summary path + folder-vs-
cert sweep + .env loader + EpcClientService usage example).
- Full table of first-attempt deltas per cert with classifications.
- All 15 prior-session slice commits indexed.
- Memory references to the slicing / methodology conventions.
- Per-cert diagnostic recipe template.
Co-Authored-By: Claude Opus 4.7 <noreply@anthropic.com>
|
||
|---|---|---|
| .devcontainer | ||
| .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