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curriculum/challenges/english/blocks/learn-tree-traversal-by-building-a-binary-search-tree/65ca2a52d579b22feb89177f.md

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--description--

As a last step, print the whole tree.

Call print() by passing the string 'Inorder traversal after deleting 40:' as the first argument and an inorder_traversal() call as the second argument.

With this, you have finished the implementation of the binary search tree. Great work!

--hints--

You should call print passing the string 'Inorder traversal after deleting 40:' as the first argument and an inorder_traversal() call as the second argument.

js
({ test: () => assert.match(code, /^print\s*\(\s*("|')Inorder traversal after deleting 40:\1\s*,\s*bst\.inorder_traversal\s*\(\s*\)\s*\)/m) })

--seed--

--seed-contents--

py

class TreeNode:

    def __init__(self, key):
        self.key = key
        self.left = None
        self.right = None

    def __str__(self):
        return str(self.key)

class BinarySearchTree:

    def __init__(self):
        self.root = None

    def _insert(self, node, key):
        if node is None:
            return TreeNode(key)

        if key < node.key:
            node.left = self._insert(node.left, key)
        elif key > node.key:

            node.right = self._insert(node.right, key)
        return node

    def insert(self, key):
        self.root = self._insert(self.root, key)
        
    def _search(self, node, key):
        if node is None or node.key == key:
            return node
        if key < node.key:
            return self._search(node.left, key)
        return self._search(node.right, key)
    
    def search(self, key):
        return self._search(self.root, key)

    def _delete(self, node, key):
        if node is None:
            return node
        if key < node.key:
            node.left = self._delete(node.left, key)
        elif key > node.key:
            node.right = self._delete(node.right, key) 
        else:
            if node.left is None:
                return node.right
            elif node.right is None:
                return node.left   
            
            node.key = self._min_value(node.right)
            node.right = self._delete(node.right, node.key)   
        
        return node

    def delete(self, key):
        self.root = self._delete(self.root, key)

    def _min_value(self, node):
        while node.left is not None:
            node = node.left
        return node.key

    def _inorder_traversal(self, node, result):
        if node:
            self._inorder_traversal(node.left, result)
            result.append(node.key)
            self._inorder_traversal(node.right, result)

    def inorder_traversal(self):
        result = []
        self._inorder_traversal(self.root, result)
        return result

--fcc-editable-region--
bst = BinarySearchTree()
nodes = [50, 30, 20, 40, 70, 60, 80]

for node in nodes:
    bst.insert(node)

print('Search for 80:', bst.search(80))

print("Inorder traversal:", bst.inorder_traversal())

bst.delete(40)

print("Search for 40:", bst.search(40))

--fcc-editable-region--

--solutions--

py
class TreeNode:
    def __init__(self, key):
        self.key = key
        self.left = None
        self.right = None

    def __str__(self):
        return str(self.key)


class BinarySearchTree:
    def __init__(self):
        self.root = None

    def insert(self,key):
        self.root = self._insert(self.root, key)

    def _insert(self, node, key):
        if node is None:
            return TreeNode(key)
        if key < node.key:
            node.left = self._insert(node.left, key)
        elif key > node.key:
            node.right = self._insert(node.right, key)
        return node

    def search(self, key):
        return self._search(self.root, key)

    def _search(self, node, key):
        if node is None or node.key == key:
            return node
        if key < node.key:
            return self._search(node.left, key)
        return self._search(node.right, key)

    def delete(self, key):
        self.root = self._delete(self.root, key)

    def _delete(self, node, key):
        if node is None:
            return node
        if key < node.key:
            node.left = self._delete(node.left, key)
        elif key > node.key:
            node.right = self._delete(node.right, key)
        else:
            if node.left is None:
                return node.right
            elif node.right is None:
                return node.left

            node.key = self._min_value(node.right)
            node.right = self._delete(node.right, node.key)
        return node

    def _min_value(self, node):
        while node.left is not None:
            node = node.left
        return node.key

    def inorder_traversal(self):
        result = []
        self._inorder_traversal(self.root, result)
        return result

    def _inorder_traversal(self, node, result):
        if node:
            self._inorder_traversal(node.left, result)
            result.append(node.key)
            self._inorder_traversal(node.right, result)


bst = BinarySearchTree()
nodes = [50, 30, 20, 40, 70, 60, 80]

for node in nodes:
    bst.insert(node)

print("Inorder traversal:", bst.inorder_traversal())

print("Search for 40:", bst.search(40))

bst.delete(40)

print("Search for 40:", bst.search(40))

print("Inorder traversal after deleting 40:", bst.inorder_traversal())