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Speed Up Your Python with Rust

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

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Product type Paperback
Published in Jan 2022
Publisher Packt
ISBN-13 9781801811446
Length 384 pages
Edition 1st Edition
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Author (1):
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Maxwell Flitton Maxwell Flitton
Author Profile Icon Maxwell Flitton
Maxwell Flitton
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Toc

Table of Contents (16) Chapters Close

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

Summary

In this chapter, we have managed to build a fully fledged pip Python module that has continuous integration. We initially set up a GitHub repository and created a virtual environment. This is an essential skill for most Python projects, and you should be using GitHub repositories and virtual environments even if your project is not a pip module. You will be able to share your project and work with other team members. We then defined our setup.py file so our code could be installed via pip. Even if our GitHub repository is private, people who have access to the GitHub repository could freely install our code. This gives us even more power when it comes to distributing our code.

When we have an interface defined, our users do not need to know much about our code, just how to use the interface. This also enables us to prevent repeated code. For instance, if we build a user data model with a database driver, we can package it as a pip module and use this in multiple web applications...

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