Growing Dask To Make Scaling Python Data Science Easier At Coiled

The Python Podcast.__init__ - Podcast autorstwa Tobias Macey

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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 Hello and welcome to Podcast.__init__, the podcast about Python and the people who make it great. 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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. Visit the site to subscribe to the show, sign up for the mailing list, and read the show notes. If you’ve learned something or tried out a project from the show then tell us about it! Email [email protected]) with your story. To help other people find the show please leave a review on iTunes and tell your friends and co-workers Join the community in the new Zulip chat workspace at pythonpodcast.com/chat Links Sign up for the Coiled Beta! Coiled Dask Data Engineering Podcast Interview About Dask PyData NumPy SciPy Cell Biology Datacamp Dataframed Matthew Rocklin on Podcast.__init__ about functional programming with Toolz IPython Notebook PyTorch Podcast Episode Airflow Prefect XGBoost Tornado Coiled Blog Post About The Goals of Dask Spark AsyncIO Concurrent.futures Pangeo Xarray RAPIDS Nvidia Cuda Prefect Data Engineering Podcast Episode Celery Life Sciences Tensorflow Snorkel Data Engineering Podcast Episode Dagster Data Engineering Podcast Episode DevOps Docker Kubernetes Metaflow Podcast Episode Ray Podcast Episode Anyscale Yarn Gartner Hype Cycle Travis Oliphant Postgres Amazon ECS Django Django Allauth Quansight Wes McKinney Podcast Interview Ursa Labs The intro and outro music is from Requiem for a Fish The Freak Fandango Orchestra / CC BY-SA

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