Book Image

The Complete Rust Programming Reference Guide

By : Rahul Sharma, Vesa Kaihlavirta, Claus Matzinger
Book Image

The Complete Rust Programming Reference Guide

By: Rahul Sharma, Vesa Kaihlavirta, Claus Matzinger

Overview of this book

Rust is a powerful language with a rare combination of safety, speed, and zero-cost abstractions. This Learning Path is filled with clear and simple explanations of its features along with real-world examples, demonstrating how you can build robust, scalable, and reliable programs. You’ll get started with an introduction to Rust data structures, algorithms, and essential language constructs. Next, you will understand how to store data using linked lists, arrays, stacks, and queues. You’ll also learn to implement sorting and searching algorithms, such as Brute Force algorithms, Greedy algorithms, Dynamic Programming, and Backtracking. As you progress, you’ll pick up on using Rust for systems programming, network programming, and the web. You’ll then move on to discover a variety of techniques, right from writing memory-safe code, to building idiomatic Rust libraries, and even advanced macros. By the end of this Learning Path, you’ll be able to implement Rust for enterprise projects, writing better tests and documentation, designing for performance, and creating idiomatic Rust code. This Learning Path includes content from the following Packt products: • Mastering Rust - Second Edition by Rahul Sharma and Vesa Kaihlavirta • Hands-On Data Structures and Algorithms with Rust by Claus Matzinger
Table of Contents (29 chapters)
Title Page
Copyright
About Packt
Contributors
Preface
Index

Web applications in Rust


"The most important property of a program is whether it accomplishes the intention of its user." 

C. A. R. Hoare

It's rare for a low-level language to enable developers to write web applications with it while providing thekind of high-level ergonomics that dynamic languages do. With Rust, it's quite the opposite. Developing web applications with Rust is a similar experience one might expect from dynamic languages such as Ruby or Python, due to its high-level abstractions.

 

Web applications developed in dynamic languages can only get you so far though. A lot of developers find to what, as their code base reaches about a 100,000 lines of code, they start seeing the brittle nature of dynamic languages. With every small change you make, you need to have tests in place to let you know what parts of the application are affected. As the application grows, it becomes a whack-a-mole situation in terms of testing and updating.

Building web applications in a statically typed...