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.

LensKit for Python (LKPY) is the successor to the Java-based LensKit project.

If you use LensKit for Python in published research, please cite:

Michael D. Ekstrand. 2020. LensKit for Python: Next-Generation Software for Recommender Systems Experiments. In Proceedings of the 29th ACM International Conference on Information and Knowledge Management (CIKM '20). DOI:10.1145/3340531.3412778. arXiv:1809.03125 [cs.IR].

Installing

To install the current release with Anaconda (recommended):

conda install -c conda-forge 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][].

Our development workflow is documented in the wiki; the wiki also contains other information on developing LensKit. User-facing documentation is at https://lkpy.lenskit.org.

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

pip install flit_core packaging
python build-tools/flit-conda.py --create-env --python-version 3.8

This will create a Conda environment called

lkpy

We don't maintain the Conda environment specification directly - instead, we maintain information in

setup.toml

flit-conda

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.