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

Chapter 7: Using Python Modules with Rust

We have now become comfortable with writing Python packages in Rust that can be installed using pip. However, a large advantage of Python is that it has a lot of mature Python libraries that help us write productive code with minimal errors. This seems a legitimate observation that could halt us from adopting Rust in our Python system. However, in this chapter, we counter this observation by importing Python modules into our Rust code and running Python code in our Rust code. To achieve an understanding of this, we are going to use the NumPy Python package to implement a basic mathematical model. Once this is done, we are going to use the NumPy package in our Rust code to simplify the implementation of our mathematical model. Finally, we will evaluate the speed of both implementations.

In this chapter, we will cover the following topics:

  • Exploring NumPy
  • Building a model in NumPy
  • Using NumPy and other Python modules in Rust...