0aa40b63cd
The cascade's `_main_fuel_code` previously returned None when
`MainHeatingDetail.main_fuel_type` was anything other than an int
(empty string, None, or an unmapped string label). The downstream
`table_32.unit_price_p_per_kwh(None)` then silently defaulted to mains
gas (3.48 p/kWh / CO2 0.21 kg/kWh / η 0.45 / PE 1.22) — a misleading
fallback where cost may happen to be close but CO2 / PE / efficiency
are completely wrong for the actual heating system.
Probe of the heating-systems corpus surfaced 26 of 41 controlled-
variable variants with `main_fuel_type=''`:
Community heating 1/2/3/4/6 (Table 4a 301-304) 5
Electric 11/12/13/14 (Table 4a 5xx/6xx/7xx) 4
No system (SAP code 699) 1
Oil 2 (HVO) / oil 3 (FAME) / oil 4 (FAME) /
oil 5 (bioethanol) / oil 6 (B30K) (Table 4b) 5
Solid fuel 2..11 (Table 4a 150-160 + 600-636) 10
pcdb 3 (lodges 'Bulk LPG' string — mapper dict gap) 1
Each pre-slice carried a residual pin in `_EXPECTATIONS` encoding the
broken mains-gas-default state. Solid fuel 8's +0.87 ΔSAP — the
"smallest open residual" the user asked to investigate next — turned
out to be the net of compensating cost/efficiency errors; the CO2
delta was +3525 kg/yr and PE +4103 kWh/yr because the cascade was
costing wood chips as mains gas.
Two changes land together:
1. Add `MissingMainFuelType(ValueError)` to
`domain/sap10_calculator/exceptions.py`. Semantics distinct from
the sibling `UnmappedSapCode` (which is for unmapped int dispatch
codes; this is for "value not resolvable to a SAP fuel code at
all"). The error message names the lodged value + the
`sap_main_heating_code` hint so the upstream mapper fix is
obvious.
2. `_main_fuel_code` in `cert_to_inputs.py` now raises
`MissingMainFuelType` when `main_fuel_type` is not an int.
`main is None` still returns None (genuinely no main heating).
The 26 blocked corpus variants are lifted out of the
`_EXPECTATIONS` residual-pin grid into a new tuple
`_BLOCKED_BY_MISSING_MAIN_FUEL_TYPE` driving a new parametrised test
`test_heating_systems_corpus_blocked_variant_raises_missing_main_fuel_type`
that asserts the raise for each blocked variant. As mapper-side fixes
land (deriving fuel from `sap_main_heating_code` via SAP 10.2 Table
4a/4b/4f, or extending `_ELMHURST_MAIN_FUEL_TO_SAP10`), variants move
back onto the residual-pin grid.
Mirrors the [[reference-unmapped-sap-code]] / [[reference-unmapped-
api-code]] strict-raise pattern: forcing function for spec/mapper
completion at the cascade boundary instead of silently producing
wrong outputs.
Extended handover suite at HEAD post-slice: 875 pass / 0 fail (was
874; +1 from the new `_main_fuel_code` strict-raise unit test;
26 blocked corpus pins replaced 1:1 by 26 assert-on-raise tests).
Pyright net-zero (43 → 43 — all pre-existing `pytest.approx` flags).
No golden fixture impact — every golden cert carries an int
`main_fuel_type`.
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