Run recommender algorithms and experiments
Project description
# Python recommendation tools
[![Build Status](https://dev.azure.com/md0553/md/_apis/build/status/lenskit.lkpy)](https://dev.azure.com/md0553/md/_build/latest?definitionId=1) [![codecov](https://codecov.io/gh/lenskit/lkpy/branch/master/graph/badge.svg)](https://codecov.io/gh/lenskit/lkpy) [![Maintainability](https://api.codeclimate.com/v1/badges/c02098c161112e19c148/maintainability)](https://codeclimate.com/github/lenskit/lkpy/maintainability)
LensKit is a set of Python tools for experimenting with and studying recommender systems. It provides support for training, running, and evaluating recommender algorithms in a flexible fashion suitable for research and education.
Python LensKit (LKPY) is the successor to the Java-based LensKit project.
## Installing
To install the current release with Anaconda (recommended):
conda install -c lenskit lenskit
Or you can use pip:
pip install lenskit
To use the latest development version, install directly from GitHub:
pip install -U git+https://github.com/lenskit/lkpy
Then see [Getting Started](https://lkpy.lenskit.org/en/latest/GettingStarted.html)
## Resources
[Documentation](https://lkpy.lenskit.org)
[Mailing list, etc.](https://lenskit.org/connect)
Project details
Release history Release notifications | RSS feed
Download files
Download the file for your platform. If you're not sure which to choose, learn more about installing packages.