niyamit-sphere 0.1.43

A modern Python implementation of HAZUS flood methodology for building vulnerability and loss estimation.

SPHERE: Spatial Platform for Hazard Evaluation and Risk Estimation

Click the link to run the sample in Google Colab!

A modern Python implementation of the HAZUS flood methodology for building vulnerability and loss estimation. This repository packages a set of libraries (sphere-core, sphere-data, sphere-flood) that implement flood vulnerability functions, lookup tables, and analysis scripts suitable for research and operational use.

This project is a newer reimplementation of HAZUS flood vulnerability logic with a focus on clarity, type annotations, and tested, modular code.

Key features

• Building vulnerability functions (HAZUS-derived)
• Flood damage cross-reference and interpolation utilities
• Example analysis scripts in examples/
• Test coverage under tests/

License This code is released under the MIT License — see LICENSE for details.

Quick start

1. Create a virtual environment (Python 3.10+).

uv sync --all-packages

2. Run tests

uv run pytest -q

3. Explore examples in the examples/ directory.

uv run examples\fast_analysis.py

Contributing Please see CONTRIBUTING.md for guidelines on reporting issues, proposing changes, running tests, and contributing patches. All contributors must agree to the project's MIT license by submitting pull requests.

Contact For questions and larger design discussions, please open an issue on the project GitHub repository.

Development

There are two convenient ways to work with the workspace packages locally:

• Lightweight dev environment using PYTHONPATH (recommended for quick development):

  • Linux/macOS:

     source scripts/dev.env
     uv run pytest -q
    

  • Windows PowerShell:

     .\scripts\dev.env.ps1
     uv run pytest -q
    

  This sets PYTHONPATH so imports like import sphere.core resolve against the in-repo sources without installing packages into your virtualenv.

-- Meta package (sphere-meta): a minimal aggregator distribution that depends on sphere-core, sphere-data, and sphere-flood. You can build and install libs/sphere-meta if you want a single installable package that pulls the three distributions from PyPI.

```powershell
cd libs/sphere-meta
uv run python -m build -w
python -m pip install dist\sphere_meta-0.1.0-py3-none-any.whl
```

CI notes

In CI, prefer one of these two approaches:

• Set PYTHONPATH (fast): add the paths to GITHUB_ENV so tests can import the in-repo packages.
• Build wheels for each package and install them (strict): build and install wheels in the job before running tests.