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Compiling Python through PyLLVM and MongoDB for Data Scientists

Episode #103, published Thu, Mar 16, 2017, recorded Mon, Mar 6, 2017.

This episode is carbon neutral.
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:

Anna on Twitter: @annaisworking

PyLLVM: github.com/aherlihy/PythonLLVM
Wrestling Python into LLVM Intermediate Representation: youtube.com/watch?v=knL-c9WIru8

BSON-NumPy Docs: readthedocs.org/projects/bson-numpy
BSON-NumPy Package: pypi.org/project/BSON-NumPy
BSON-NumPy on GitHub: github.com/aherlihy/bson-numpy

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Anna Herlihy
Anna Herlihy
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