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 the work across multi-processing to escape the limitations of the

gill right on your local machine?

That's what Dask was built to do.

On this episode, you'll meet Matthew Rockland to talk about its origins, use cases, and a whole

bunch of other interesting topics.

This is Talk Python to Me, episode 207, recorded February 20th, 2019.

Welcome to Talk Python to Me, a weekly podcast on Python, the language, the libraries, the ecosystem, and the personalities. This is your host, Michael Kennedy. Follow me on Twitter where I'm at M Kennedy. Keep up with a show and listen to past episodes at TalkPython.fm, and follow the show on Twitter via at Talk Python. Hey folks, a quick announcement before we get to our conversation with Matthew.

People have been enjoying the courses over at Talk Python training for years now. But one

shortcoming we've been looking to address is to give you offline access to your content

while you're traveling or if you're

just in a location with spotty internet speeds. We also want to make taking our courses on your

mobile devices the best they can be. That's why I'm thrilled to tell you about our new apps,

which solve both of these problems at once. Just visit training.tokpython.fm slash apps and download

the Android version right now.

The iOS version is just around the corner. Should be out in a week or so. You'll have access to all

of your existing courses. But we've also added a single tap feature to allow you to join our two

free courses, the Responder Web Framework mini course and the MongoDB quick start course. So log in,

tap the free course,

and you'll be right in there. Please check out the apps and try one of the free courses today.

Now, let's talk Dask with Matthew. Matthew, welcome to talk Python to me. Thanks, Michael. I've listened to the show a lot. It's really an honor to be here. Thank you for having me. It's an honor to have

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