TL;DR 🌳 We'll implement a Binary Tree together. 🧑‍🌾 We'll discuss a couple of ways to insert a node in a Binary Tree. 🧑‍🔬 We'll discuss Rust's ownership in action. ✨ We'll touch on more features and syntax in Rust. I was struggling hard with Rust's ownership when implementing a Binary Tree, so I pivoted and re-read about it. After taking my time understanding it and refactoring my code, I finally made a breakthrough😎 I'm very excited to share with you the awesome features in Rust I came across. You'll see interesting concepts like smart pointers and ownership. Let's get it! Data Structure A data structure look like this: Binary Tree Each node has no more than two child nodes. We refer to them as child and child. We can translate the description into Rust code like this: left right pub struct BinaryTree<T> {
    pub value: T,
    pub left: Option<Box<BinaryTree<T>>>,
    pub right: Option<Box<BinaryTree<T>>>,
} The struct holds a value with the generic type . We use enum to represent that the and child are both optional. BinaryTree T Option left right A is either a that contains a value of the type , or a that represents it doesn't. Because we are using to express whether a value is either something or nothing, the Rust compiler can check if we handle all the cases . Compared to JavaScript, where we use value to express the same concept, encourages me to handle use cases upfront, and it saves me a lot of trouble in runtime. Option<T> Some T None Option to prevent bugs null Option The is one of the smart pointers. It saves an address that points to data in memory. helps us to create a struct with an unknown size so that we can grow the Binary Tree by inserting nodes without thinking ahead how many nodes we'll have when creating the tree. Box Box BinaryTree is one of the reasons Rust is so performing and interesting to learn. Memory management Insertion Before inserting a new Binary Tree node, we need to create a root. Let's implement it: impl<T> BinaryTree<T> {
    pub fn new(value: T) -> Self {
        BinaryTree {
            value,
            left: None,
            right: None,
        }
    }
} The takes the value of and return a that holds the value and no child nodes. new associated function T BinaryTree Now that we can use to create a root node, we can think about how to insert child nodes. Intuitively, it would be great if we could insert the left or right child node by calling methods on the root node instance. Like this: BinaryTree::new BinaryTree::new(1)
  .left(BinaryTree::new(2))
  .right(BinaryTree::new(3)) Luckily, I found a from my friend at trivago, , explaining exactly how to implement it. great article Matthias impl<T> BinaryTree<T> {
    pub fn new(value: T) -> Self {
        BinaryTree {
            value,
            left: None,
            right: None,
        }
    }

    pub fn left(mut self, node: BinaryTree<T>) -> Self {
        self.left = Some(Box::new(node));
        self
    }

    pub fn right(mut self, node: BinaryTree<T>) -> Self {
        self.right = Some(Box::new(node));
        self
    }
} Now let's write some tests to make sure the associated functions work: #[cfg(test)]
mod tests {
    use super::*;

    #[test]
    fn create_new_tree() {
        let tree = BinaryTree::new(1);

        assert_eq!(tree.value, 1);
    }

    #[test]
    fn insert_left() {
        let tree = BinaryTree::new(1).left(BinaryTree::new(2));

        if let Some(node) = tree.left {
            assert_eq!(node.value, 2);
        }

        assert_eq!(tree.right, None);
    }

    #[test]
    fn insert_right() {
        let tree = BinaryTree::new(1).right(BinaryTree::new(2));

        if let Some(node) = tree.right {
            assert_eq!(node.value, 2);
        }

        assert_eq!(tree.left, None);
    }
} 🥳 Breadth-First Insertion The insertion methods are very flexible, and we can easily create a tree in just a few lines: BinaryTree::new(1)
    .left(
        BinaryTree::new(2)
            .left(BinaryTree::new(4))
            .right(BinaryTree::new(5))
    )
    .right(BinaryTree::new(3)) The code creates a Binary Tree like this: It got me thinking. If I just want to create a without any other requirements, can I insert a node and the tree finds the next available spot for me? balanced Binary Tree Something like this: let mut root = BinaryTree::new(1);
root.insert(2);
root.insert(3);
root.insert(4);
root.insert(5); And it creates the same tree structure as we saw above. We can achieve it by traversing the tree in the fashion and inserting a node as soon as we find an absent child node. breadth-first The easiest way to implement a breath-first traversal is with a . Rust has a in the standard library we can use. Queue VecDequeue pub fn insert(&mut self, new_value: T) {
    let mut queue: VecDeque<&mut BinaryTree<T>> = VecDeque::new();
    queue.push_front(self);

    loop {
        let BinaryTree {
            ref mut left,
            ref mut right,
            ..
        } = queue.pop_back().unwrap();

        match left {
            Some(node) => {
                queue.push_front(node);
            }
            None => {
                *left = Some(Box::new(BinaryTree::new(new_value)));
                return;
            }
        }

        match right {
            Some(node) => {
                queue.push_front(node);
            }
            None => {
                *right = Some(Box::new(BinaryTree::new(new_value)));
                return;
            }
        }
    }
} The algorithm is to force the loop to visit sibling nodes first, from left to right, before visiting the next layer of child nodes. In each iteration, we'll check if either the or child is absent. If we find one, that's the next available spot for the new node. left right It's a rather straightforward algorithm, but . The problem was that I didn't understand . I struggled to get it right ownership in Rust Let's go through the method together. insert First thing we want to decide is how do we want to use the first argument . is referring to the instance the method is called on. What we need from is to be able to mutate the and child node so that we can insert a new node. Simply passing in a mutable reference will do the job because the method doesn't need to take ownership of . self self BinaryTree self left right &mut self self For the item data type, we can use the same data type as to store mutable references of . VecDeque self BinaryTree When popping the queue inside the loop, we want to use a mutable reference to and because we want to insert the new node. left right When inserting the new node, we the and to allow the new node assignment, like this: . dereference left right *left = Some(Box::new(BinaryTree::new(new_value))) It took me some time to figure out how to borrow or move the data in the method. Once I got it, it made so much sense! Let's write some tests for it🧑‍🔬 #[test]
fn insert() {
    let mut tree = BinaryTree::new(1);
    tree.insert(2);
    tree.insert(3);
    tree.insert(4);
    tree.insert(5);

    assert_eq!(
        tree,
        BinaryTree::new(1)
            .left(
                BinaryTree::new(2)
                    .left(BinaryTree::new(4))
                    .right(BinaryTree::new(5))
            )
            .right(BinaryTree::new(3))
    );

    tree.insert(6);

    assert_eq!(
        tree,
        BinaryTree::new(1)
            .left(
                BinaryTree::new(2)
                    .left(BinaryTree::new(4))
                    .right(BinaryTree::new(5))
            )
            .right(BinaryTree::new(3).left(BinaryTree::new(6)))
    )
} If we run the tests, you'll see an error message like this: It's because the trees couldn't compare with each other. We can fix it by adding trait to the struct. PartialEq BinaryTree + #[derive(PartialEq)]
pub struct BinaryTree<T> {
    pub value: T,
    pub left: Option<Box<BinaryTree<T>>>,
    pub right: Option<Box<BinaryTree<T>>>,
} 🥳 Converting Array into Binary Tree Now that we have an automatic insertion with the method, we can consider creating a balanced tree more conveniently. For example, I want to have something similar to : an associated function that takes in an array and returns a balanced . insert Vec::from BinaryTree::from BinaryTree Let's write a test to visualize the use case better: #[test]
fn create_new_tree_with_from() {
    // `BinaryTree::from` takes in a reference of an array because borrowing is sufficient
    let tree = BinaryTree::from(&[1, 2, 3, 4, 5, 6]);

    assert_eq!(
        tree,
        BinaryTree::new(1)
            .left(
                BinaryTree::new(2)
                    .left(BinaryTree::new(4))
                    .right(BinaryTree::new(5))
            )
            .right(BinaryTree::new(3).left(BinaryTree::new(6)))
    )
} To implement , we can iterate through the array and use the method to create the tree structure. BinaryTree::from insert impl<T> BinaryTree<T> {
    pub fn from(new_values: &[T]) -> Self {
        let (first, rest) = new_values.split_first().unwrap();
        let mut root: BinaryTree<T> = BinaryTree::new(*first);

        for value in rest {
            root.insert(*value)
        }
        root
    }
} In the function, we created a root node from the first array element and then inserted the rest element in the tree one by one. If you try to test it, you'll see an error message like this: We can fix it by specifying the type implements the trait. T Copy - impl<T> BinaryTree<T> {
+ impl<T> BinaryTree<T>
+ where
+     T: Copy,
+ { The reason is that the method actually take ownership over . In order to keep the program memory saved, the compiler didn't allow us to "move" the array elements into the method because the array might be referenced in other parts of the program. So what we can do is to pass in a copy (duplicate) of an array element. insert new_value insert Now it should work! Final Thoughts That's it! The full implementation of our Binary Tree assertion is here⬇️ #[derive(Debug, PartialEq)]
pub struct BinaryTree<T> {
    pub value: T,
    pub left: Option<Box<BinaryTree<T>>>,
    pub right: Option<Box<BinaryTree<T>>>,
}

impl<T> BinaryTree<T>
where
    T: Copy,
{
    ///
    /// Create a new Binary Tree node.
    ///
    pub fn new(value: T) -> Self {
        BinaryTree {
            value,
            left: None,
            right: None,
        }
    }

    ///
    /// Create a balanced tree from an array reference.
    ///
    pub fn from(new_values: &[T]) -> Self {
        let (first, rest) = new_values.split_first().unwrap();
        let mut root: BinaryTree<T> = BinaryTree::new(*first);

        for value in rest {
            root.insert(*value)
        }
        root
    }

    ///
    /// Insert a tree node in the next available branch with breadth first traversal.
    ///
    pub fn insert(&mut self, new_value: T) {
        let mut queue: VecDeque<&mut BinaryTree<T>> = VecDeque::new();
        queue.push_front(self);
        loop {
            let BinaryTree {
                ref mut left,
                ref mut right,
                ..
            } = queue.pop_back().unwrap();

            match left {
                Some(node) => {
                    queue.push_front(node);
                }
                None => {
                    *left = Some(Box::new(BinaryTree::new(new_value)));
                    return;
                }
            }

            match right {
                Some(node) => {
                    queue.push_front(node);
                }
                None => {
                    *right = Some(Box::new(BinaryTree::new(new_value)));
                    return;
                }
            }
        }
    }

    ///
    /// Insert a left child node.
    ///
    pub fn left(mut self, node: BinaryTree<T>) -> Self {
        self.left = Some(Box::new(node));
        self
    }

    ///
    /// Insert a right child node.
    ///
    pub fn right(mut self, node: BinaryTree<T>) -> Self {
        self.right = Some(Box::new(node));
        self
    }
}

#[cfg(test)]
mod tests {
    use super::*;

    #[test]
    fn create_new_tree() {
        let tree = BinaryTree::new(1);

        assert_eq!(tree.value, 1);
    }

    #[test]
    fn insert_left() {
        let tree = BinaryTree::new(1).left(BinaryTree::new(2));

        if let Some(node) = tree.left {
            assert_eq!(node.value, 2);
        }

        assert_eq!(tree.right, None);
    }

    #[test]
    fn insert_right() {
        let tree = BinaryTree::new(1).right(BinaryTree::new(2));

        if let Some(node) = tree.right {
            assert_eq!(node.value, 2);
        }

        assert_eq!(tree.left, None);
    }

    #[test]
    fn insert() {
        let mut tree = BinaryTree::new(1);
        tree.insert(2);
        tree.insert(3);
        tree.insert(4);
        tree.insert(5);

        assert_eq!(
            tree,
            BinaryTree::new(1)
                .left(
                    BinaryTree::new(2)
                        .left(BinaryTree::new(4))
                        .right(BinaryTree::new(5))
                )
                .right(BinaryTree::new(3))
        );

        tree.insert(6);

        assert_eq!(
            tree,
            BinaryTree::new(1)
                .left(
                    BinaryTree::new(2)
                        .left(BinaryTree::new(4))
                        .right(BinaryTree::new(5))
                )
                .right(BinaryTree::new(3).left(BinaryTree::new(6)))
        )
    }

    #[test]
    fn create_new_tree_from() {
        let tree = BinaryTree::from(&[1, 2, 3, 4, 5, 6]);

        assert_eq!(
            tree,
            BinaryTree::new(1)
                .left(
                    BinaryTree::new(2)
                        .left(BinaryTree::new(4))
                        .right(BinaryTree::new(5))
                )
                .right(BinaryTree::new(3).left(BinaryTree::new(6)))
        )
    }
} Reference Binary Tree Balanced Binary Tree Breadth-First Search Queue Type Rust Option Pointer Rust Box Rust VecDequeue Trait Rust PartialEq Trait Rust Copy Rust Vec::from Rust Associated Function Rust Ownership JavaSCript null The Stack and the Heap Of Boxes and Trees - Smart Pointers in Rust Problem with Implementing Binary Tree Insertion The Option Enum and Its Advantages Over Null Values Treating Smart Pointers Like Regular References with the Deref Trait This article is originally posted on . Daw-Chih’s website

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