.. rbartpackages/docs/guide/installation.rst
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Installation
============

``rbartpackages`` drives R packages through `rpy2 <https://rpy2.github.io>`_, so
you need both a Python and an R installation.

Python package
--------------

.. code-block:: sh

    pip install rbartpackages

(Or the equivalent for your package manager, e.g. :code:`uv add rbartpackages`.)
To install the latest development version:

.. code-block:: sh

    pip install git+https://github.com/bartz-org/rbartpackages.git

Optional extras enable the corresponding input-conversion paths: ``pandas`` and
``polars`` let you pass data frames, ``jax`` lets you pass jax arrays.

.. code-block:: sh

    pip install rbartpackages[pandas,polars,jax]

R packages
----------

Install `R <https://cran.r-project.org>`_, then install the wrapped packages you
intend to use. ``BART``, ``dbarts`` and ``bartMachine`` are on CRAN; ``BART3``
and ``missBART`` live on GitHub:

.. code-block:: r

    install.packages(c("BART", "dbarts", "bartMachine"))
    # BART3 and missBART:
    install.packages("remotes")
    remotes::install_github("rsparapa/bnptools/BART3")
    remotes::install_github("yongchengoh/missBART")

``bartMachine`` is a Java package and additionally requires a working Java
toolchain and ``rJava`` (run ``R CMD javareconf`` after installing a JDK).

Importing a wrapper (e.g. ``from rbartpackages import BART3``) requires the
matching R package to be installed, because the class docstrings are pulled from
the R documentation at import time.