Metadata-Version: 2.1
Name: tabular-trees
Version: 0.3.0
Summary: Package to assist with analysis of tree-based models.
Home-page: https://github.com/richardangell/tabular-trees
License: BSD-3-Clause
Author: Richard Angell
Author-email: richardangell37@gmail.com
Requires-Python: >=3.9,<4.0
Classifier: License :: OSI Approved :: BSD License
Classifier: Programming Language :: Python :: 3
Classifier: Programming Language :: Python :: 3.9
Classifier: Programming Language :: Python :: 3.10
Classifier: Programming Language :: Python :: 3.11
Classifier: Programming Language :: Python :: 3.12
Provides-Extra: lightgbm
Provides-Extra: sklearn
Provides-Extra: xgboost
Requires-Dist: lightgbm (>=4.5.0,<5.0.0) ; extra == "lightgbm"
Requires-Dist: pandas (>=2.2.0,<3.0.0)
Requires-Dist: scikit-learn (>=1.5.0,<2.0.0) ; extra == "sklearn"
Requires-Dist: tqdm (==4.66.3)
Requires-Dist: typing-extensions (>=4.12.2,<5.0.0)
Requires-Dist: xgboost (>=2.1.0,<3.0.0) ; extra == "xgboost"
Project-URL: Documentation, https://tabular-trees.readthedocs.io/en/latest/
Project-URL: Repository, https://github.com/richardangell/tabular-trees
Description-Content-Type: text/markdown

# tabular-trees

![PyPI](https://img.shields.io/pypi/v/tabular-trees?color=success&style=flat)
![Read the Docs](https://img.shields.io/readthedocs/tabular-trees)
![GitHub](https://img.shields.io/github/license/richardangell/tabular-trees)
![GitHub last commit](https://img.shields.io/github/last-commit/richardangell/tabular-trees)
![Build](https://github.com/richardangell/tabular-trees/actions/workflows/coverage.yml/badge.svg?branch=main)

## Introduction

`tabular-trees` is a package for making analysis on tree-based models easier. 

Tree based models (specifically GBMs) from `xgboost`, `lightgbm` or `scikit-learn` can be exported to `TabularTrees` objects for further analysis.

The `explain` and `validate` modules contain functions that operate on `TabularTrees` objects.

See the [documentation](http://tabular-trees.readthedocs.io/) for more information.

## Install

The easiest way to get `tabular-trees` is to install directly from [pypi](https://pypi.org/project/tabular-trees/):

```
pip install tabular_trees
```

`tabular-trees` works with GBMs from `xgboost`, `lightgbm` or `scikit-learn`. These packages must be installed to use the relevant functionality from `tabular-trees`.

`[lightgbm, sklearn, xgboost]` are optional depedencies that can be specified for `tabular-trees`. They can be installed along with `tabular-trees` as follows:

```
pip install tabular_trees[lightgbm, sklearn]
```

## Build

`tabular-trees` uses [poetry](https://python-poetry.org/) as the environment management and package build tool. Follow the instructions [here](https://python-poetry.org/docs/#installation) to install.

To install the package locally, for development purposes along with the development dependencies run:

```
poetry install --with dev
```

`dev` is an optional dependency group, the other one is `docs` which is only required if building the documentation.

To install all the optional, development dependencies as well as all the extras for the package run:

```
poetry install --extras "lightgbm xgboost" --with dev,docs
```

