0ba0575877
domain/building_geometry.gross_heat_loss_wall_area(epc, identifier) sums heat_loss_perimeter x room_height across a building part's storeys — the heat-loss wall area (party walls excluded by construction), not total wall area. Lives outside the calculator so Modelling cost quantities can reuse it; the calculator computes the same quantity inline today and should be DRY'd onto this later (coordinated with the calculator branch). Pinned at 45.93 m^2 against the 000490 MAIN part. Toward #1155 cost (behaviour 4). pyright strict clean. Co-Authored-By: Claude Opus 4.8 <noreply@anthropic.com> |
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| backend | ||
| backlog | ||
| datatypes | ||
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| domain | ||
| epr_data_exports | ||
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| ara_backend_design.md | ||
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| CONTEXT.md | ||
| devcontainer.sh | ||
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| README.md | ||
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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