Hello and welcome to Podcast.__init__, the podcast about Python’s role in data and science.
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Your host as usual is Tobias Macey and today I’m interviewing Sam Willis about Tetra, a full stack component framework for your Django applications
How did you get introduced to Python?
Can you describe what Tetra is and the story behind it?
What are the problems that you are aiming to solve with this project?
What are some of the other ways that you have addressed those problems?
What are the shortcomings that you encountered with those solutions?
What was missing in the existing landscape of full-stack application development patterns that prompted you to build a new meta-framework?
What are some of the sources of inspiration (positive and negative) that you looked to while deciding on the component selection and implementation strategy?
Can you describe how Tetra is implemented?
What are the core principles that you are relying on to drive your design of APIs and developer experience?
What is the process for building a full component in Tetra?
A perennial challenge with combining the syntax across multiple languages in a single file is editor support. How are you thinking about that with Tetra’s implementation?
What is your grand vision for Tetra and how are you working to make it sustainable?
What are the most interesting, innovative, or unexpected ways that you have seen Tetra used?
What are the most interesting, unexpected, or challenging lessons that you have learned while working on Tetra?
When is Tetra the wrong choice?
What do you have planned for the future of Tetra?
Keep In Touch
@samwillis on Twitter
samwillis on GitHub
The Machine Learning Podcast
Slow Horses TV Show
Thank you for listening! Don’t forget to check out our other shows. The Data Engineering Podcast covers the latest on modern data management. The Machine Learning Podcast helps you go from idea to production with machine learning.
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Ruby on Rails
Python Import Hooks
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