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

Passing complex Python objects into Rust

A key skill that enables us to take our Rust pip module development to the next level is taking in complex Python data structures/objects and using them. In Chapter 5, Creating a Rust Interface for Our pip Module, we accepted integers. We noticed that these raw integers were just directly transferred to our Rust function. However, with Python objects, it is more complex than this.

To explore this, we will create a new command-line function that reads a .yml file and passes a Python dictionary into our Rust function. The data in this dictionary will have the parameters needed for firing our fibonacci_numbers and fibonacci_number Rust functions, adding the results of those functions to the Python dictionary and passing it back to the Python system.

To achieve this, we must carry out the following steps:

  1. Update our setup.py file to support .yml loading and a command-line function that reads it.
  2. Define a command-line function...