Parallelizing computation with Dask

Episode #207, published Sun, Apr 14, 2019, recorded Wed, Feb 20, 2019

What if you could write standard numpy and pandas code but have it run on a distributed computing grid for incredible parallel processing right from Python? How about just splitting it across multiprocessing to escape the limitations of the GIL on your local machine? That's what Dask was built to do.

On this episode, you'll meet Matthew Rocklin to talk about its origins, use-cases, and a whole bunch of other interesting topics.

Links from the show

Dask: dask.org
Matthew on Twitter: @mrocklin
Matthew's website: matthewrocklin.com
Dask examples: github.com
PyCon presentation: youtube.com
PyCon presentation slides: matthewrocklin.com/slides
Episode transcripts: talkpython.fm

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Matthew Rocklin

Matthew Rocklin works on Dask at Coiled to enable scalable computing for the Python community.

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