Compiling Python through PyLLVM and MongoDB for Data Scientists

This episode we have an optimization 2fer.

We begin looking at optimizing a subset of Python code for machine learning using the LLVM compiler with a project called PyLLVM which takes plain python code, compiles it to optimized machine instructions and distributes it across a cluster.

In the second half, we look at a fabulous new way to work with MongoDB for Python writing data scientists. The project is called bson-numpy and provides a direct connection between MongoDB and NumPy and is 10x faster than standard pymongo.

Links from the show: