Book Image

Speed Up Your Python with Rust

By : Maxwell Flitton
5 (2)
Book Image

Speed Up Your Python with Rust

5 (2)
By: Maxwell Flitton

Overview of this book

Python has made software development easier, but it falls short in several areas including memory management that lead to poor performance and security. Rust, on the other hand, provides memory safety without using a garbage collector, which means that with its low memory footprint, you can build high-performant and secure apps relatively easily. However, rewriting everything in Rust can be expensive and risky as there might not be package support in Rust for the problem being solved. This is where Python bindings and pip come in. This book will help you, as a Python developer, to start using Rust in your Python projects without having to manage a separate Rust server or application. Seeing as you'll already understand concepts like functions and loops, this book covers the quirks of Rust such as memory management to code Rust in a productive and structured manner. You'll explore the PyO3 crate to fuse Rust code with Python, learn how to package your fused Rust code in a pip package, and then deploy a Python Flask application in Docker that uses a private Rust pip module. Finally, you'll get to grips with advanced Rust binding topics such as inspecting Python objects and modules in Rust. By the end of this Rust book, you'll be able to develop safe and high-performant applications with better concurrency support.
Table of Contents (16 chapters)
1
Section 1: Getting to Understand Rust
5
Section 2: Fusing Rust with Python
11
Section 3: Infusing Rust into a Web Application

Introducing concurrency

As we explored in the introduction of Chapter 1, An Introduction to Rust from a Python Perspective, Moore's law is now failing, and therefore we have to consider other ways in which we can speed up our processing. This is where concurrency comes in. Concurrency is essentially running multiple computations at the same time. Concurrency is everywhere, and to give the concept full justice, we would have to write a whole book on it.

However, for the scope of this book, understanding the basics of concurrency (and when to use it) can add an extra tool to our belt that enables us to speed up computations. Furthermore, threads and processes are how we can break up our program into computations that run at the same time. To start our concurrency tour, we will cover threads.

Threads

Threads are the smallest unit of computation that we can process and manage independently. Threads are used to break a program into computational parts that can be run at...