• numpy (>=1.23)

  • scipy (>=1.5.0)

  • scikit-learn (>=1.3)

  • joblib (>=1.0.0)

  • matplotlib (optional)

scikit-tree supports Python >= 3.9.

Installing with pip#

scikit-tree is available on PyPI. Just run

pip install sktree

Installing from source with Meson#

To install scikit-tree from source, first clone the repository:

git clone
cd scikit-tree

# ideally, you should always start within a virtual environment
conda create -n sklearn-dev python=3.9
conda activate sklearn-dev

Then run installation of build packages

pip install -r build_requirements.txt
pip install spin

# use spin CLI to run Meson build locally
./spin build -j 2

# you can now run tests
./spin test

via pip, you will be able to install in editable mode (pending Meson-Python support).

pip install -e .

# if editing Cython files
pip install --verbose --no-build-isolation --editable .
pip install --user -U