Managing Large Python Data Science Projects With Dask – The Real Python Podcast

Real Python Podcast Episode #112 Title Artwork

Jun 03, 2022 46m

Christopher Bailey
Guido Imperiale

What do you do when your data science project doesn’t fit within your computer’s memory? One solution is to distribute it across multiple worker machines. This week on the show, Guido Imperiale from Coiled talks about Dask and managing large data science projects through distributed computing.

We talk about projects where an orchestration system like Dask will help. Dask is designed to take advantage of parallel computing, spreading the work and data across multiple machines. Many familiar techniques for working with pandas and NumPy data are supported with Dask equivalents.

We also discuss the differences between managed and unmanaged memory. Guido shares advice on how to tackle memory issues while working with Dask.

This week we also talk briefly with Jodie Burchell, who will be a guest host on upcoming episodes. As a data scientist, Jodie will be bringing new topics, projects, and discussions to the show.


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