Complete Your Hardware "Weekend Projects" In An Actual Weekend With Belay

Summary

Working on hardware projects often has significant friction involved when compared to pure software. Brian Pugh enjoys tinkering with microcontrollers, but his "weekend projects" often took longer than a weekend to complete, so he created Belay. In this episode he explains how Belay simplifies the interactions involved in developing for MicroPython boards and how you can use it to speed up your own experimentation.

Announcements

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Your host as usual is Tobias Macey and today I’m interviewing Brian Pugh about Belay, a python library that enables the rapid development of projects that interact with hardware via a micropython-compatible board.

Interview

Introductions
How did you get introduced to Python?
Can you describe what Belay is and the story behind it?
Who are the target users for Belay?
What are some of the points of friction involved in developing for hardware projects?
- What are some of the features of Belay that make that a smoother process?
What are some of the ways that simplifying the develop/debug cycles can improve the overall experience of developing for hardware platforms?
- What are some of the inherent limitations of constrained hardware that Belay is unable to paper over?
Can you describe how Belay is implemented?
What does the workflow look like when using Belay as compared to using MicroPython directly?
What are some of the ways that you are using Belay in your own projects?
What are the most interesting, innovative, or unexpected ways that you have seen Belay used?
What are the most interesting, unexpected, or challenging lessons that you have learned while working on Belay?
When is Belay the wrong choice?
What do you have planned for the future of Belay?

Keep In Touch

BrianPugh on GitHub
LinkedIn

Picks

Tobias
- Gunnar Computer Glasses

Closing Announcements

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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