Book Image

Mastering Embedded Linux Programming - Third Edition

By : Frank Vasquez, Chris Simmonds
5 (3)
Book Image

Mastering Embedded Linux Programming - Third Edition

5 (3)
By: Frank Vasquez, Chris Simmonds

Overview of this book

If you’re looking for a book that will demystify embedded Linux, then you’ve come to the right place. Mastering Embedded Linux Programming is a fully comprehensive guide that can serve both as means to learn new things or as a handy reference. The first few chapters of this book will break down the fundamental elements that underpin all embedded Linux projects: the toolchain, the bootloader, the kernel, and the root filesystem. After that, you will learn how to create each of these elements from scratch and automate the process using Buildroot and the Yocto Project. As you progress, the book will show you how to implement an effective storage strategy for flash memory chips and install updates to a device remotely once it’s deployed. You’ll also learn about the key aspects of writing code for embedded Linux, such as how to access hardware from apps, the implications of writing multi-threaded code, and techniques to manage memory in an efficient way. The final chapters demonstrate how to debug your code, whether it resides in apps or in the Linux kernel itself. You’ll also cover the different tracers and profilers that are available for Linux so that you can quickly pinpoint any performance bottlenecks in your system. By the end of this Linux book, you’ll be able to create efficient and secure embedded devices using Linux.
Table of Contents (27 chapters)
1
Section 1: Elements of Embedded Linux
10
Section 2: System Architecture and Design Decisions
18
Section 3: Writing Embedded Applications
22
Section 4: Debugging and Optimizing Performance

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...