You're reading from Speed Up Your Python with Rust Optimize Python performance by creating Python pip modules in Rust with PyO3

Product type Paperback

Published in Jan 2022

Publisher Packt

ISBN-13 9781801811446

Length 384 pages

Edition 1st Edition

Languages

Python

Tools

Docker

Concepts

Software Architecture

Author (1):

Maxwell Flitton

View More author details

Table of Contents (16) Chapters

Preface

1. Section 1: Getting to Understand Rust

2. Chapter 1: An Introduction to Rust from a Python Perspective FREE CHAPTER

3. Chapter 2: Structuring Code in Rust

4. Chapter 3: Understanding Concurrency

5. Section 2: Fusing Rust with Python

6. Chapter 4: Building pip Modules in Python

7. Chapter 5: Creating a Rust Interface for Our pip Module

8. Chapter 6: Working with Python Objects in Rust

9. Chapter 7: Using Python Modules with Rust

10. Chapter 8: Structuring an End-to-End Python Package in Rust

11. Section 3: Infusing Rust into a Web Application

12. Chapter 9: Structuring a Python Flask App for Rust

13. Chapter 10: Injecting Rust into a Python Flask App

14. Chapter 11: Best Practices for Integrating Rust

15. Other Books You May Enjoy

Using NumPy and other Python modules in Rust

In this section, we are going to understand the basics of importing a Python module such as NumPy in our Rust program and return the result to our Python function. We will build our functionality in our Fibonacci number package that we have been coding so far in this book. We will also briefly explore importing a Python module in a generic sense so that you experience how to use a Python module that has the functionality you are relying on. We will build a more comprehensive approach to using Python modules in our Rust code in the next section. For this section, we will write all our code in the src/lib.rs file. Here are the steps we need to take:

First, we need to acknowledge that we pass in a dictionary and return the results in it. Because of this, we must import the PyDict struct by running the following code:
```
use pyo3::types::PyDict;
```
Now that this is imported, we can define our function by running the following code:
```
#[pyfunction...
```