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Installation

OpenBoost 1.0 is a release candidate. Install with --pre until 1.0.0.

Quick install

pip install --pre openboost

uv add --prerelease=allow openboost

pip install openboost without --pre still resolves the older stable release.

GPU support

Numba CUDA kernels for histogram trees. Requires an NVIDIA GPU.

pip install --pre "openboost[cuda]"

uv add --prerelease=allow "openboost[cuda]"

Then:

import openboost as ob
print(ob.get_backend(), ob.is_cuda())   # "cuda" True when a GPU is visible

See GPU setup for backend pinning, multi-GPU, and troubleshooting.

Optional extras

Extra What it includes Install
cuda numba-cuda + CuPy for GPU trees pip install --pre "openboost[cuda]"
sklearn scikit-learn wrappers pip install --pre "openboost[sklearn]"
jax autodiff for custom distributions / formulas pip install --pre "openboost[jax]"
distributed Ray for multi-GPU pip install --pre "openboost[distributed]"
all Everything pip install --pre "openboost[all]"

Finite-difference Jacobians work without JAX. Install jax when you want autodiff on a custom NLL.

Requirements

  • Python 3.10+
  • NumPy 1.24+
  • Numba 0.60+
  • SciPy 1.10+

For GPU

  • NVIDIA GPU, CUDA Compute Capability 3.5+
  • CUDA Toolkit 11 or 12
  • numba-cuda>=0.23, cupy-cuda12x>=13

Verify

import openboost as ob

print(f"OpenBoost {ob.__version__}")
print(f"Backend: {ob.get_backend()}")   # "cuda" or "cpu"
print(f"GPU:     {ob.is_cuda()}")

Development install

git clone https://github.com/jxucoder/openboost.git
cd openboost
uv sync --extra dev
# GPU kernels:
uv sync --extra cuda --extra dev