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PyCon

Notes and notebooks from pycon.

Down the Rabbit Hole

Reproducible data flows in Python

This will be extremely useful for all our work.

Epiphanies

Python's Quirks

Not that useful, but kind of interestings

Network Analysis 101

NetworkX + NXVis

Extremely useful. With many practical examples. I think we need a graph database. Bonus notebook three could be a lifesaver in Alex's project.

  • NOTEBOOK 5!!!! BONUS NOTEBOOK 3 *

Using Pandas For Better (Or Worse)

You already know all of this. If you don't somebody else in the group does. Probably not worth your time.

Thinking outside the GIL with AsyncIO and Multiprocessing

Facebook exascale storage people made a module that combines asyncio and multiprocessing for 8x performance gains against single threaded code and 5x gains against multiprocessed code. It implements map -> multiprocessing -> async.io --> reduce to fully saturate a box. Repo is here https://github.com/jreese/aiomultiprocess.

Performance Python: Seven Strategies for Optimizing your Numerical Code

Useful ways to improve performance on numerical and data frame structured code.

"WHAT IS THIS MESS?" - Writing tests for pre-existing code bases

Testing code. This guy is a bit militant, but it is useful. He describes how to integrate CI/CD into code bases. FrateMatcher comes to mind.

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