May 28, 2017

Cauldron with Scott Ernst

37 minutes

Summary

The notebook format that has been exemplified by the IPython/Jupyter project has gained in popularity among data scientists. While the existing formats have proven their value, they are still susceptible with difficulties in collaboration and maintainability. Scott Ernst created the Cauldron notebook to be testable, production ready, and friendly to version control. This week we explore the capabilities, use cases, and architecture of Cauldron and how you can start using it today!

Preface

Hello and welcome to Podcast.__init__, the podcast about Python and the people who make it great.

I would like to thank everyone who supports us on Patreon. Your contributions help to make the show sustainable.

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Visit the site to subscribe to the show, sign up for the newsletter, read the show notes, and get in touch.

To help other people find the show please leave a review on iTunes, or Google Play Music, tell your friends and co-workers, and share it on social media.

Your host as usual is Tobias Macey and today I’m interviewing Scott Ernst about Cauldron, a new notebook format built with software engineering best practices in mind.

Interview

Introductions

How did you get introduced to Python?

Can you start by explaining what Cauldron is and what problem you were trying to solve when you created it?

In the documentation it mentions that you can use any editor for creating the content of the notebook. Can you describe a typical workflow of authoring the various files and cells and viewing the output?

How does Cauldron compare to the Jupyter notebook format and what factors would lead someone to choose one over the other?

Does Cauldron support running languages other than Python? If not then what would be involved in adding that capability?

Cauldron notebooks support unit tests of individual cells. How does that process work and what are the limitations?

The option for running the notebook in the context of a task workflow tool appears to be a powerful capability. What are some of the considerations that are necessary when writing a notebook to be run in that manner?

What are some of the most interesting or unexpected projects that you have seen people using Cauldron for?

What do you have planned for the future of Cauldron?

Keep In Touch

@swernst on Twitter

Website

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The intro and outro music is from Requiem for a Fish The Freak Fandango Orchestra / CC BY-SA

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By Tobias Macey

4.4

100100 ratings

May 28, 2017

Cauldron with Scott Ernst

37 minutes

Summary

Preface

Hello and welcome to Podcast.__init__, the podcast about Python and the people who make it great.

I would like to thank everyone who supports us on Patreon. Your contributions help to make the show sustainable.

Visit the site to subscribe to the show, sign up for the newsletter, read the show notes, and get in touch.

To help other people find the show please leave a review on iTunes, or Google Play Music, tell your friends and co-workers, and share it on social media.

Your host as usual is Tobias Macey and today I’m interviewing Scott Ernst about Cauldron, a new notebook format built with software engineering best practices in mind.

Interview

Introductions

How did you get introduced to Python?

Can you start by explaining what Cauldron is and what problem you were trying to solve when you created it?

How does Cauldron compare to the Jupyter notebook format and what factors would lead someone to choose one over the other?

Does Cauldron support running languages other than Python? If not then what would be involved in adding that capability?

Cauldron notebooks support unit tests of individual cells. How does that process work and what are the limitations?

What are some of the most interesting or unexpected projects that you have seen people using Cauldron for?

What do you have planned for the future of Cauldron?

Keep In Touch

@swernst on Twitter

Website