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

Generics


From the dawn of high-level programming languages, the pursuit of better abstraction is something that language designers have always strived for. As such, many ideas concerning code reuse emerged. The very first of them was functions. Functions allow you to chunk away a sequence of instructions within a named entity that can be called later many times, optionally accepting any arguments for each invocation. They reduce code complexity and amplify readability. However, functions can only get you so far. If you have a function, say avg, that calculates the average of a given list of integer values and later you have a use case where you need to calculate the average for a list of float values too, then the usual solution is to create a new function that can average float values from the list of floats. What if you wanted to accept a list of double values too? We probably need to write another function again. Writing the same function over and over again that differs only by its arguments...