a2bcc2c8af
The calculator tests lived under domain/sap10_calculator/{tests,worksheet/
tests,rdsap/tests,climate/tests,validation/tests}, none of which are in
pytest.ini testpaths — so CI (which collects tests/) never ran them. Relocate
all five dirs to tests/domain/sap10_calculator/{,worksheet,rdsap,climate,
validation}, mirroring the tests/domain/property_baseline/ convention, so the
cascade-pin / golden / e2e conformance suites run in CI.
Mechanics:
- git mv preserves history (110 files).
- Flattening the trailing /tests keeps each file's depth-to-repo-root
identical, so all 16 repo-root parents[4] fixture refs stay valid. Only
test_pcdb_etl.py's parents[1] (→ pcdb data) and one hardcoded absolute
golden-fixture path in test_cert_to_inputs.py needed rebasing.
- Cross-imports rewritten domain.sap10_calculator.worksheet.tests →
tests.domain.sap10_calculator.worksheet (21 files incl. the external
importer backend/documents_parser/tests/test_summary_pdf_mapper_chain.py).
- Golden-fixture path strings in test_summary_pdf_mapper_chain.py +
scripts/fetch_cohort2_api_jsons.py updated to the new location (the JSONs
moved with the rdsap tests).
load_cells / gitignored worksheet xlsx: the xlsx-pinned tests (test_dimensions
/ ventilation / water_heating) read 2026-05-19-17-18 RdSap10Worksheet.xlsx,
which is gitignored (.gitignore `*.xlsx`) and so absent in CI. _xlsx_loader.
load_cells now pytest.skip()s when the file is absent, so those tests run
locally and skip cleanly in CI instead of erroring — no new CI failures from
the move, and the gitignore policy is respected.
Verified: tests/domain/sap10_calculator + backend/documents_parser +
tests/domain/property_baseline = 2248 pass, 1 skipped; pyright resolves the
new import paths with zero import-resolution errors.
Co-Authored-By: Claude Opus 4.8 <noreply@anthropic.com>
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|---|---|---|
| .devcontainer | ||
| .github/workflows | ||
| .idea | ||
| .vscode | ||
| applications | ||
| asset_list | ||
| backend | ||
| backlog | ||
| datatypes | ||
| deployment/terraform | ||
| docs | ||
| domain | ||
| epr_data_exports | ||
| etl | ||
| infrastructure | ||
| model_data/requirements | ||
| orchestration | ||
| recommendations | ||
| repositories | ||
| sap worksheets/heating systems examples | ||
| 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