Speed Up Your Python with Rust: Optimize Python performance by creating Python pip modules in Rust with PyO3

Maxwell Flitton

ISBN 10: 180181144X / ISBN 13: 9781801811446

Verlag: Packt Publishing, 2022

Beschreibung

Bestandsnummer des Verkäufers I-9781801811446

Bibliografische Details

• Titel: Speed Up Your Python with Rust: Optimize Python performance by creating Python pip modules in Rust with PyO3
• Verlag: Packt Publishing
• Erscheinungsjahr: 2022
• Sprache: Englisch
• ISBN-10: 180181144X
• ISBN-13: 9781801811446
• Einband: Softcover
• Zustand: New

Über diesen Titel

Inhaltsangabe

Discover how to inject your code with highly performant Rust features to develop fast and memory-safe applications

Key Features

• Learn to implement Rust in a Python system without altering the entire system
• Write safe and efficient Rust code as a Python developer by understanding the essential features of Rust
• Build Python extensions in Rust by using Python NumPy modules in your Rust code

Book Description

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.

What you will learn

• Explore the quirks of the Rust programming language that a Python developer needs to understand to code in Rust
• Understand the trade-offs for multiprocessing and thread safety to write concurrent code
• Build and manage a software project with cargo and crates
• Fuse Rust code with Python so that Python can import and run Rust code
• Deploy a Python Flask application in Docker that utilizes a private Rust pip module
• Inspect and create your own Python objects in Rust

Who this book is for

This book is for Python developers who want to speed up their Python code with Rust and implement Rust in a Python system without altering the entire system. You'll be able to learn about all topics relating to Rust programming. Basic knowledge of Python is required to get the most out of this book.

Table of Contents

1. An Introduction to Rust
2. Structuring Code in Rust
3. Concurrency in Rust
4. Building Private pip Modules in Python
5. Creating a Rust Interface for Your pip Module
6. Working with Python Objects in Rust
7. Using Python Modules in Rust
8. Structuring an End-to-End Python Module in Rust
9. Structuring a Python Flask App for Rust
10. Injecting Rust into a Python Flask App
11. Best Practices

Über die Autorin bzw. den Autor

Maxwell Flitton is a software engineer who works for the open source financial loss modeling foundation OasisLMF. In 2011, Maxwell achieved his Bachelor of Science degree in nursing from the University of Lincoln, UK. While working 12-hour shift s in the A&E departments of hospitals, Maxwell obtained another degree in physics from the Open University in the UK and then moved on to another milestone, with a postgraduate diploma in physics and engineering in medicine from UCL in London. He's worked on numerous projects such as medical simulation soft ware for the German government and supervising computational medicine students at Imperial College London. He also has experience in financial tech and Monolith AI.