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Hands-On Data Structures and Algorithms with Rust

You're reading from   Hands-On Data Structures and Algorithms with Rust Learn programming techniques to build effective, maintainable, and readable code in Rust 2018

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Product type Paperback
Published in Jan 2019
Publisher Packt
ISBN-13 9781788995528
Length 316 pages
Edition 1st Edition
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Author (1):
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Claus Matzinger Claus Matzinger
Author Profile Icon Claus Matzinger
Claus Matzinger
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Table of Contents (15) Chapters Close

Preface 1. Hello Rust! 2. Cargo and Crates FREE CHAPTER 3. Storing Efficiently 4. Lists, Lists, and More Lists 5. Robust Trees 6. Exploring Maps and Sets 7. Collections in Rust 8. Algorithm Evaluation 9. Ordering Things 10. Finding Stuff 11. Random and Combinatorial 12. Algorithms of the Standard Library 13. Assessments 14. Other Books You May Enjoy

A location cache

Caching values is a typical use case for maps because even a large number of items won't affect the performance much, since the keys are always distinct. These keys can even carry information themselves!

For the use case defined in the last section, each customer uses postcodes within a country to identify locations; they typically cover an area that only holds a single office. Postal codes are stored as strings to cover the real world's wide variety of systems, and they are unique per country.

Thanks to a previous generic implementation, the entire LocationCache type can be an alias to a specialized HashMap, only requiring the hash function to be supplied on creation, shown as follows:

pub type LocationCache = HashMap<String, LocationInformation>;

The HashMap itself is a custom implementation that contains a key of type K, which has to also implement PartialEq (for comparing key instances directly), and Clone (for practical reasons).

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