This document discusses different tools for integrating Python into a Scala stack to enable building real-time predictive models. It covers Jython, Jepp, Thrift, and REST APIs. Jepp is identified as allowing access to high-quality Python extensions with CPython speed while avoiding the overhead of separate runtimes like Jython. Thrift and REST are also presented as language-independent options that introduce communication overhead. The document concludes by detailing Fliptop's architecture that uses multiple Python servers communicating via Bottle to handle over 4,500 requests per second for predictive modeling.