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

Building a Rust interface with the pyO3 crate

Building an interface does not just mean adding more functions to our module in Rust and wrapping them. In a sense, we do have to do some of this; however, exploring how to import them from other Rust files is important. We also must explore and understand the relationship that we can have between Rust and Python when we are building up our module. To achieve this, we will carry out these steps:

  1. Build our Fibonacci module in our Rust package.
  2. Create command-line tools for our package.
  3. Create adapters for our package.

With step one, we can just build out our module with Rust code. Steps two and three are more Python-focused, wrapping our Rust code in Python code to ease the interaction of our Rust module with external Python code. In Chapter 6, Working with Python Objects in Rust, we will interact directly with Python objects in our Rust code. With all this in mind, let's our Python interface by initially building...