Metadata-Version: 2.4
Name: bartrs
Version: 0.3.0
Classifier: Programming Language :: Rust
Classifier: Programming Language :: Python :: Implementation :: CPython
Classifier: Programming Language :: Python :: Implementation :: PyPy
Requires-Dist: numba>=0.60.0
Requires-Dist: pymc>=6.0.1
Requires-Dist: arviz>=1.1.0
Requires-Dist: pymc-bart>=0.12.0
Requires-Dist: pre-commit>=4.0.1 ; extra == 'dev'
Requires-Dist: pytest-cov>=6.0.0 ; extra == 'dev'
Requires-Dist: pytest>=8.3.4 ; extra == 'dev'
Requires-Dist: ruff>=0.8.3 ; extra == 'dev'
Provides-Extra: dev
License-File: LICENSE
Summary: Rust implementation of Bayesian Additive Regression Trees for Probabilistic programming with PyMC
Author-email: Otto Vintola <hello@ottovintola.com>
License-Expression: Apache-2.0
Requires-Python: >=3.12, <3.14
Description-Content-Type: text/markdown
Project-URL: Homepage, https://github.com/pymc-devs/bartrs
Project-URL: Issues, https://github.com/pymc-devs/bartrs/issues

# bart-rs

A high-performance Rust implementation of an optimized Particle Gibbs BART (PGBART) sampler. This is the sampler used by ```pymc-bart```.

## Table of Contents

- [Installation](#installation)

## Installation

bart-rs is available on PyPI with a pre-built wheels for Linux, MacOS and Windows.

```bash
pip install bartrs
```

