Book Image

Rust Standard Library Cookbook

By : Jan Hohenheim, Daniel Durante
Book Image

Rust Standard Library Cookbook

By: Jan Hohenheim, Daniel Durante

Overview of this book

Mozilla’s Rust is gaining much attention with amazing features and a powerful library. This book will take you through varied recipes to teach you how to leverage the Standard library to implement efficient solutions. The book begins with a brief look at the basic modules of the Standard library and collections. From here, the recipes will cover packages that support file/directory handling and interaction through parsing. You will learn about packages related to advanced data structures, error handling, and networking. You will also learn to work with futures and experimental nightly features. The book also covers the most relevant external crates in Rust. By the end of the book, you will be proficient at using the Rust Standard library.
Table of Contents (12 chapters)

How it works...

Before you can use rand, you have to tell Rust that you're using the crate by writing:

extern crate rand;

After that, rand will provide a random generator. We can access it by either calling rand::random(); [6] or by accessing it directly with rand::thread_rng(); [22].

If we go the first route, the generator will need to be told what type to generate. You can either explicitly state the type in the method call [6] or annotate the type of the resulting variable [8]. Both are equal and result in the exact same thing. Which one you use is up to you. In this book, we will use the first convention.

As you can see in lines [29 and 33], you need neither if the type is unambiguous in the called context.

The generated value will be between its type's MIN and MAX constants. In the case of i32, this would be std::i32::MIN and std::i32::MAX, or, in concrete numbers, -2147483648 and 2147483647. You can verify these numbers easily by calling the following:

println!("min: {}, max: {}", std::i32::MIN, std::i32::MAX);

As you can see, these are very big numbers. For most purposes, you will probably want to define custom limits. You can go the second route discussed earlier and use rand::Rng for that[22]. It has a gen method, which is actually implicitly called by rand::random(), but also a gen_range() that accepts a minimum and maximum value. Keep in mind that this range is non-inclusive, which means that the maximum value can never be reached. This is why in line [29], rng.gen_range(0, 10) will only generate the numbers 0, 1, 2, 3, 4, 5, 6, 7, 8, and 9, without the 10.

All of the described ways of generating random values use uniform distribution, which means that every number in the range has the same chance of being generated. In some contexts, it makes sense to use other distributions. You can specify a generator's distribution during its creation[40]. As of the time of publication, the rand crate supports the ChaCha and ISAAC distributions.