Installation¶

ZADU requires Python 3.10 or newer.

Base package¶

Install the default NumPy/SciPy execution path from PyPI:

python -m pip install zadu

The base package supports all 22 measures and installs NumPy, SciPy, scikit-learn, Numba, HDBSCAN, and threadpoolctl. Matplotlib, MLX, and PyTorch are optional.

Optional visualization¶

Install Matplotlib and ZADUVis helpers with:

python -m pip install "zadu[vis]"

See Visualization for an example.

Optional accelerator backends¶

Apple Silicon users can install MLX separately:

python -m pip install "zadu[mlx]"

Install PyTorch support with:

python -m pip install "zadu[torch]"

Installing an accelerator does not select it. Set backend, device, and dtype in ExecutionConfig; see Execution backends.

Development installation¶

Clone the repository and install an editable development environment:

git clone https://github.com/hj-n/zadu.git
cd zadu
python -m pip install -e ".[dev]"

Documentation dependencies are separate:

python -m pip install -e ".[docs]"
python -m mkdocs serve