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

Summary

In this chapter, we have managed to build a fully fledged pip Python module that has continuous integration. We initially set up a GitHub repository and created a virtual environment. This is an essential skill for most Python projects, and you should be using GitHub repositories and virtual environments even if your project is not a pip module. You will be able to share your project and work with other team members. We then defined our setup.py file so our code could be installed via pip. Even if our GitHub repository is private, people who have access to the GitHub repository could freely install our code. This gives us even more power when it comes to distributing our code.

When we have an interface defined, our users do not need to know much about our code, just how to use the interface. This also enables us to prevent repeated code. For instance, if we build a user data model with a database driver, we can package it as a pip module and use this in multiple web applications...