Uber has been one of the most active companies trying to accelerate the implementation of real world machine learning solutions. Just this year, Uber has introduced technologies like Michelangelo, Pyro.ai and Horovod that focus on key building blocks of machine learning solutions in the real world. This week, Uber introduced another piece of its machine learning stack, this time aiming to short the cycle from experimentation to product. PyML, is a library to enable the rapid development of Python applications in a way that is compatible with their production runtime. The problem PyML attempts to address is one of those omnipresent challenges in large scale machine learning applications.