Packaging Your Python Application: Wheels, Docker + More | Real Python Podcast #24

Have you wondered, how should I package my Python code? You've written the application, but now you need to distribute it to the machines it's intended to run on. It depends on what the code is, the libraries it depends on, and with whom do you want to share it. This week on the show we have Itamar Turner-Trauring, creator of the website pythonspeed.com. We discuss his article "Options for Packaging Your Python Code: Wheels, Conda, Docker, and More," covering the how of sharing your code.

Topics:

- 00:00:00 -- Introduction
- 00:01:36 -- About the naming of pythonspeed.com
- 00:03:47 -- Fil - Python Memory Profiler
- 00:06:44 -- Small Big Data: What to do when your data doesn't fit in memory - PyCon 2020
- 00:12:17 -- Options for packaging your Python code: Wheels, Conda, Docker, and more
- 00:15:13 -- Python Wheels
- 00:19:22 -- pipx: Install and Run Python Applications in Isolated Environments
- 00:20:52 -- PEX, and friends
- 00:24:51 -- System Package, RPM or DEB
- 00:29:42 -- Conda Packaging and conda-forge
- 00:36:09 -- Video Course Spotlight
- 00:37:23 -- Self-contained executable: PyInstaller, PyOxidizer, Briefcase
- 00:43:45 -- Container image (Docker, Singularity)
- 00:54:55 -- Why alpine may not be the best choice
- 01:05:28 -- Singularity
- 01:07:50 -- What are you excited about in the world of Python?
- 01:10:40 -- What do you want to learn next?
- 01:13:54 -- Thanks and Goodbye

? Links from the show: https://realpython.com/podcasts/rpp/24/