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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 built a fully fleshed-out Python pip module with command-line tools, interfaces, and Rust code. We managed gitignore for both Rust and Python development. We then defined our setup tools for packaging our Python code and module with the compilation of Rust code that has Python bindings. Once these were defined, we learned how to build Rust functions that spanned multiple Rust files that could be wrapped in pyo3 bindings.

Our development did not just stop at Rust. We also explored Python's singleton and adapter design patterns to build more advanced Python interfaces for our users. We then tested our code with unit tests and speed checking. It must be noted that we did not cover GitHub actions in this chapter. GitHub actions are defined in the same way as they were in the previous chapter. Instead of running tests using the Python unit test, we run our tests using Cargo and so on. However, uploading to PyPI is a little more complicated. To cover...

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