Podcast.init

Solving Python Package Creation For End User Applications With PyOxidizer - Episode 282

Sep 29 '20

Summary

Python is a powerful and expressive programming language with a vast ecosystem of incredible applications. Unfortunately, it has always been challenging to share those applications with non-technical end users. Gregory Szorc set out to solve the problem of how to put your code on someone else’s computer and have it run without having to rely on extra systems such as virtualenvs or Docker. In this episode he shares his work on PyOxidizer and how it allows you to build a self-contained Python runtime along with statically linked dependencies and the software that you want to run. He also digs into some of the edge cases in the Python language and its ecosystem that make this a challenging problem to solve, and some of the lessons that he has learned in the process. PyOxidizer is an exciting step forward in the evolution of packaging and distribution for the Python language and community.

Announcements

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Your host as usual is Tobias Macey and today I’m interviewing Gregory Szorc about his work on PyOxidizer, a revolutionary new approach to building and distributing self-contained Python applications

Interview

Introductions
How did you get introduced to Python?
Can you start by giving an overview on the shortcomings of the current state of the art for distributing Python projects, both for deployment and end-user consumption?
What is PyOxidizer and what motivated you to create it?
How does PyOxidizer differ from projects such as CxFreeze, Py2Exe, or Shiv?
What are the characteristics of CPython and the packaging ecosystem that make it so challenging to easily distribute self-contained applications?
For someone using PyOxidizer, what is their workflow for building an executable that they can share with end users?
- What are some of the edge cases or special considerations that they need to be aware of?
How is PyOxidizer implemented?
- How has the design or direction evolved since you first began working on it?
From your experience in working on PyOxidizer, what changes would you like to see in the Python language or the CPython reference implementation?
What are some of the most interesting, unexpected, or challenging lessons that you have learned while working on PyOxidizer?
What do you have planned for the future of PyOxidizer?
What are the ways that listeners can contribute to PyOxidizer?

Keep In Touch

Website
indygreg on GitHub

Picks

Tobias
- Carlos Santana
Gregory
- Home Air Quality Monitor

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.
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