Ybot is erlang bot software inspired by Github hubot. It supports IRC and XMPP transports and is extensible with plugins. Plugins can be written with Python, Ruby, or shell. It supports IRC chat, XMPP multi user chat, and 37 signals Campfire chat. It can simultaneously run any number of bots on different transports.
VoltDB is a blazingly fast relational database system. It is specifically designed to run on modern scale-out architectures: fast, inexpensive servers connected via high-speed data networks. It is aimed at a new generation of database applications - real-time feeds, sensor-driven data streams, micro-transactions, low-latency trading systems - requiring database throughput that can reach millions of operations per second. What’s more, the applications that use this data must scale on demand, provide flawless fault tolerance, and enable real-time visibility into the data that drives business value. It includes client application drivers for applications written in Java, C++, C#, PHP, and Python. VoltDB community members have also authored client libraries for Erlang, Ruby and Node.js. There are streaming export capabilities for leading analytic database environments, including Apache Hadoop.
Open Transactions is a solid, easy-to-use, financial crypto and digital cash library, including an API, server, and test client. It features anonymous numbered accounts, untraceable digital cash, triple-signed receipts, basket currencies, and signed XML contracts. It also supports cheques, invoices, payment plans, markets with trades, and other instruments. It uses OpenSSL and Lucre blinded tokens.
MyMediaLite is a lightweight, multi-purpose library of recommender system algorithms. It addresses the two most common scenarios in collaborative filtering: rating prediction (e.g. on a scale of 1 to 5 stars), and item prediction from implicit feedback (e.g. from clicks or purchase actions). It contains dozens of recommender engines, including state-of-the-art matrix factorization methods. It also supports real-time updates to the recommender engines, storing engines to disk and reloading them again, and several evaluation measures to compare the accuracy of different recommender system methods. Three command-line programs that offer most of the functionality contained in the library are included.