Growing Dask To Make Scaling Python Data Science Easier At Coiled

Episode • Aug 10, 2020 • 52m

Summary

Python is a leading choice for data science due to the immense number of libraries and frameworks readily available to support it, but it is still difficult to scale. Dask is a framework designed to transparently run your data analysis across multiple CPU cores and multiple servers. Using Dask lifts a limitation for scaling your analytical workloads, but brings with it the complexity of server administration, deployment, and security. In this episode Matthew Rocklin and Hugo Bowne-Anderson discuss their recently formed company Coiled and how they are working to make use and maintenance of Dask in production. The share the goals for the business, their approach to building a profitable company based on open source, and the difficulties they face while growing a new team during a global pandemic.

Announcements

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Your host as usual is Tobias Macey and today I’m interviewing Matthew Rocklin and Hugo Bowne-Anderson about their work building a business around the Dask ecosystem at Coiled

Interview

Introductions
How did you get introduced to Python?
Can you give a quick overview of what Dask is and your motivations for creating it?
- How has Dask changed or evolved in the past 3 1/2 years since we last talked about it?
How has the rest of the ecosystem changed in that time?
After working on Dask for the past few years, what led you to the decision to build a business around it?
What are the sharp edges of programming for Dask that users are looking for help on solving?
What are the difficulties that users face in deploying and maintaining a production installation of Dask?
What are the limitations of Dask when scaling both up and down?
What are you building at Coiled to improve the user experience for users of Python and Dask?
- What are your thoughts on the pros and cons of orienting your messaging around the scalability of Python, as opposed to focusing on a specific industry or problem domain?
What are the challenges that you are facing in managing the tensions between the open source and proprietary work that you are doing?
How are you handling the ongoing governance of the Dask project?
What are some of the most interesting, unexpected, or challenging lessons that you have learned while building and launching a company based on an open source project?
What do you have planned for the future of both Coiled and Dask?

Keep In Touch

Matt
- Website
- @mrocklin on Twitter
- mrocklin on GitHub
Hugo
- LinkedIn
- @hugobowne on Twitter
- Website

Picks

Tobias
- The Hobbit
  - Audiobook
  - Audible Free Trial (affiliate link)
Matt
- Prefect
Hugo
- Race After Technology by Ruha Benjamin
- Ruha Benjamin on deep learning: Computational depth without sociological depth is ‘superficial learning’

Closing Announcements

Thank you for listening! Don’t forget to check out our other show, the Data Engineering Podcast for the latest on modern data management.
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