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

Comparing speed with Python, Rust, and Numba

We have now built a pip module in Rust with command-line tools, Python interfaces, and unit tests. This is a shiny new tool that we have. Let's put it to the test. We know that Rust by itself is faster than Python. However, do we know that the pyo3 bindings slow us down? Also, there is another way to speed up our Python code and this is with Numba, a Python package that compiles Python code to speed it up. Should we go through all of the haste of creating the Rust package if we can achieve the same speed with Numba? In this section, we will run our Fibonacci function several times, in Python, Numba, and our Rust module. It has to be noted that Numba can be a headache to install. For instance, I could not install it on my MacBook Pro M1. I had to install Numba on a Linux laptop to run this section. You don't have to run the code in this section; it is more for demonstrative purposes. If you do want to try and run the test script...