Have you wondered about graph theory and how to start exploring it in Python? What resources and Python libraries can you use to experiment and learn more? This week on the show, former co-host David Amos returns to talk about what he’s been up to and share his knowledge about graph theory in Python.

David started a Ph.D. program studying mathematics, with a focus on graph theory. Though life interrupted his pursuit after three years, he is still passionate about the subject. He’s been using these skills to create documentation and teach users as part of RelationalAI’s education team.

David has also been exploring the Julia programming language. He wrote about it on his blog, created videos, and started a podcast on the topic. He shares his excitement about learning new techniques from different languages and how these ideas can enhance your coding in Python.

This episode is sponsored by Sentry.

Course Spotlight: Defining Python Constants for Code Maintainability

In this video course, you’ll learn how to properly define constants in Python. By coding a bunch of practical example, you’ll also learn how Python constants can improve your code’s readability, reusability, and maintainability.

Topics:

  • 00:00:00 – Introduction
  • 00:02:09 – What have you been up to?
  • 00:03:31 – Exploring the Julia language
  • 00:07:24 – Where do you see Julia being used?
  • 00:10:17 – Cross pollination of languages
  • 00:12:45 – Connecting with RelationalAI
  • 00:16:33 – Sponsor: Sentry
  • 00:17:42 – Digging into graph theory
  • 00:21:54 – Edges as connections
  • 00:24:55 – Defining terms
  • 00:31:30 – Storing graph information
  • 00:41:55 – Applications once the graph is built
  • 00:49:07 – Video Course Spotlight
  • 00:50:40 – Additional resources to learn more
  • 00:53:59 – What are you excited about in the world of Python?
  • 00:58:05 – What do you want to learn next?
  • 01:00:25 – How can people follow your work online?
  • 01:02:55 – Thanks and goodbye

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