Recommender systems or Collaborative filtering is the process of filtering for information using techniques involving collaboration among multiple agents. Applications of collaborative filtering typically involve very large data sets. Collaborative filtering methods have been applied to many different kinds of data including: sensing and monitoring data, such as in mineral exploration, environmental sensing over large areas or multiple sensors; financial data, such as financial service institutions that integrate many financial sources; or in electronic commerce and web applications where the focus is on user dataHere is the list of python libraries for building recommender systems.1. Crab Crab is a ﬂexible, fast recommender engine for Python that integrates classic information ﬁltering recom- mendation algorithms in the world of scientiﬁc Python packages (numpy, scipy, matplotlib). The engine aims to provide a rich set of components from which you can construct a customized recommender system from a set of algorithms. The tutorial is from official documentation of Crab.Python wrapper for the SUGGEST, which is a Top-N recommendation engine that implements a variety of recommendation algorithms for collaborative filtering. SUGGEST is a Top-N recommendation engine that implements a variety of recommendation algorithms. Top-N recommender systems, a personalized information filtering technology, are used to identify a set of N items that will be of interest to a certain user. In recent years, top-N recommender systems have been used in a number of different applications such to recommend products a customer will most likely buy; recommend movies, TV programs, or music a user will find enjoyable; identify web-pages that will be of interest; or even suggest alternate ways of searching for information.Unison is the recommendation system behind GroupStreamer, an Android application that recommends music for groups. You can also checkout the source code of the mobile application if you're interested.A python library for implementing a recommender system, for documentation and examples click The Spark Python API (PySpark) exposes the Spark programming model to Python.