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

Chapter 16. Exploring Maps and Sets

Up until this chapter, data structures have only become faster for searching, and this chapter is no different. What makes it different is why and how data can be found in two higher-level data structures: maps and sets. While the former is also known as dictionary, associative array, object, or hash table, the latter commonly crosses people's minds as a mathematical concept. Both can rely on hashing, a technique that allows for constant (or close to constant) time retrieval of items, checking whether they are contained in a set, or routing requests in distributed hash tables.

These data structures are also one level higher than the previous ones, since all of them build on existing structures, such as dynamic arrays or trees, and to top things off, the chapter starts with an algorithm. Understanding this chapter will be great preparation heading into the second part of the book, where algorithms are the main focus. Topics learned in this chapter include...