tomas1861/lkpy

Python recommendation toolkit

Python recommendation tools

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

Developing

To contribute to LensKit, clone or fork the repository, get to work, and submit a pull request. We welcome contributions from anyone; if you are looking for a place to get started, see the issue tracker.

We recommend using an Anaconda environment for developing LensKit. To set this up, run:

conda env create -f dev-environment.yml

This will create a Conda environment called lkpy-dev with the packages required to develop and test LensKit.

Resources

• Documentation
• Mailing list, etc.

Acknowledgements

This material is based upon work supported by the National Science Foundation under Grant No. IIS 17-51278. Any opinions, findings, and conclusions or recommendations expressed in this material are those of the author(s) and do not necessarily reflect the views of the National Science Foundation.