# pyRecLab: A Software Library for Quick Prototyping of Recommender Systems

## TL;DR

pyRecLab is a Python-compatible C++ library that enables rapid development and testing of recommender systems, offering a user-friendly alternative to existing Java and C# tools with comparable performance.

## Contribution

It introduces pyRecLab, a new library that simplifies quick prototyping of recommender systems in Python, filling a gap left by existing libraries in other languages.

## Key findings

- pyRecLab achieves similar error metrics to LibRec.
- It offers fast train/test times for recommender system development.
- The library is suitable for programmers with limited experience.

## Abstract

This paper introduces pyRecLab, a software library written in C++ with Python bindings which allows to quickly train, test and develop recommender systems. Although there are several software libraries for this purpose, only a few let developers to get quickly started with the most traditional methods, permitting them to try different parameters and approach several tasks without a significant loss of performance. Among the few libraries that have all these features, they are available in languages such as Java, Scala or C#, what is a disadvantage for less experienced programmers more used to the popular Python programming language. In this article we introduce details of pyRecLab, showing as well performance analysis in terms of error metrics (MAE and RMSE) and train/test time. We benchmark it against the popular Java-based library LibRec, showing similar results. We expect programmers with little experience and people interested in quickly prototyping recommender systems to be benefited from pyRecLab.