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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
Languages
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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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Toc

Table of Contents (15) Chapters Close

Preface 1. Hello Rust! FREE CHAPTER 2. Cargo and Crates 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

An IoT database

As in the previous implementation, this tree builds on the numerical_id property of IoTDevice as keys, and the device object as value. In code, a node looks very similar to the previous example:

type Tree = Box<Node>;
type KeyType = u64;

type Data = (Option<IoTDevice>, Option<Tree>);

#[derive(Clone, PartialEq, Debug)]
enum NodeType {
Leaf,
Regular,
}

#[derive(Clone, PartialEq)]
enum Direction {
Left,
Right(usize),
}

#[derive(Clone)]
struct Node {
devices: Vec<Option<IoTDevice>>,
children: Vec<Option<Tree>>,
left_child: Option<Tree>,
pub node_type: NodeType,
}

Instead of triples, this node type uses a synchronized index to find the children associated with a specified key-value pair. These pairs are also created ad hoc by evaluating the numerical_id property of the contained device, thereby also simplifying the code and eventual updates to the keys. Something that is missing from the node is a parent pointer,...

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