c783a15ff1
Rewrites the cert 001479 closure handover into a forward-looking
brief for the new workstream: validating the API EpcPropertyDataMapper
against 9 newly-staged (Summary + worksheet + API) cert triples.
Key contents:
- User's stated workflow (verbatim): Summary path proves itself
against the worksheet → becomes canonical reference for API parity.
- Folder-structure changes since the prior handover were written
(packages/domain/ removed; sap10_calculator + sap10_ml now at the
repo root under a PEP 420 namespace; docs/sap-spec/ moved into
domain/sap10_calculator/docs/; PCDB data into tables/pcdb/data/).
- New test data layout: `sap worksheets/Additional data with api/
<cert-ref>/{Summary_NNNNNN.pdf, dr87-0001-NNNNNN.pdf}`.
- Cert reference table with heating type, PCDB index, worksheet SAP,
TFA, bp count, dwelling type for all 9 triples.
- Major scope discovery: 7 of 9 are Air Source Heat Pumps (PCDB
104568 / 102421). The mapper has never been validated against HPs;
cert 0380 pilot showed catastrophic deltas (Summary -70 / API -18
SAP vs worksheet). Recommended deferring HP certs until boiler
workflow is proven.
- Cert 0330 (mid-terrace gas boiler) pilot status: fixtures staged
uncommitted; Summary path +0.47 SAP, API path +2.15 SAP vs
worksheet 61.5993. Cascade-component diff localises 2 specific
gaps (windows HLC +6.71 W/K likely from glazing_type=14 missing
from Slice 93's transmission map; HW kWh +1060 needs §4
subsystem probe).
- Tooling shortcut: use OPEN_EPC_API_TOKEN (not EPC_AUTH_TOKEN) in
backend/.env with EpcClientService._fetch_certificate(cert_ref)
to fetch raw JSON.
- First actions for next agent: confirm baseline, commit cert 0330
fixtures, add RED Layer 2 test, iterate.
Lesson preserved: cohort hand-builts encode non-spec quirks
(e.g. has_suspended_timber_floor=False to override §(12) spec
inference and match the non-spec worksheet). Cross-check against
spec-inferred mapper output before trusting hand-built fields.
Co-Authored-By: Claude Opus 4.7 <noreply@anthropic.com>
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|---|---|---|
| .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