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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

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A B-Tree's search works just the way binary tree searches do: recursively checking each node for the path to follow. In B-Trees, this becomes very convenient since it can be done in a loop, in this case, by the get_device() function:

pub fn get_device(&self, key: KeyType) -> Option<&IoTDevice> {
let mut result = None;
for d in self.devices.iter() {
if let Some(device) = d {
if device.numerical_id == key {
result = Some(device);
break;
}
}
}
result
}

This function is implemented at the node structure and does a regular linear search for the key itself. If it is unable to find that key, the find_r() function has to decide whether to continue, which it does by evaluating the node type. Since leaf nodes don't have any children, not finding the desired key will end the search, returning None. Regular nodes allow the search to continue on a deeper level of the tree:

pub...
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