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Mastering Embedded Linux Programming

You're reading from   Mastering Embedded Linux Programming Create fast and reliable embedded solutions with Linux 5.4 and the Yocto Project 3.1 (Dunfell)

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Product type Paperback
Published in May 2021
Publisher Packt
ISBN-13 9781789530384
Length 758 pages
Edition 3rd Edition
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Authors (2):
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Frank Vasquez Frank Vasquez
Author Profile Icon Frank Vasquez
Frank Vasquez
Mr. Chris Simmonds Mr. Chris Simmonds
Author Profile Icon Mr. Chris Simmonds
Mr. Chris Simmonds
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Table of Contents (27) Chapters Close

Preface 1. Section 1: Elements of Embedded Linux
2. Chapter 1: Starting Out FREE CHAPTER 3. Chapter 2: Learning about Toolchains 4. Chapter 3: All about Bootloaders 5. Chapter 4: Configuring and Building the Kernel 6. Chapter 5: Building a Root Filesystem 7. Chapter 6: Selecting a Build System 8. Chapter 7: Developing with Yocto 9. Chapter 8: Yocto Under the Hood 10. Section 2: System Architecture and Design Decisions
11. Chapter 9: Creating a Storage Strategy 12. Chapter 10: Updating Software in the Field 13. Chapter 11: Interfacing with Device Drivers 14. Chapter 12: Prototyping with Breakout Boards 15. Chapter 13: Starting Up – The init Program 16. Chapter 14: Starting with BusyBox runit 17. Chapter 15: Managing Power 18. Section 3: Writing Embedded Applications
19. Chapter 16: Packaging Python 20. Chapter 17: Learning about Processes and Threads 21. Chapter 18: Managing Memory 22. Section 4: Debugging and Optimizing Performance
23. Chapter 19: Debugging with GDB 24. Chapter 20: Profiling and Tracing 25. Chapter 21: Real-Time Programming 26. Other Books You May Enjoy

Chapter 16: Packaging Python

Python is the most popular programming language for machine learning. Combine that with the proliferation of machine learning in our day-to-day lives and it is no surprise that the desire to run Python on edge devices is intensifying. Even in this era of transpilers and WebAssembly, packaging Python applications for deployment remains an unsolved problem. In this chapter, you will learn what choices are out there for bundling Python modules together and when to use one method over another.

We start with a look back at the origins of today's Python packaging solutions, from the built-in standard distutils to its successor, setuptools. Next, we examine the pip package manager, before moving on to venv for Python virtual environments, followed by conda, the reigning general-purpose cross-platform solution. Lastly, I will show you how to use Docker to bundle Python applications along with their user space environment for rapid deployment to the cloud...

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