Welcome to our deep dive into the fascinating world of AVL Trees! This lesson is designed for beginners and intermediates, so let's take it slow and steady. By the end, you'll have a solid understanding of this self-balancing binary search tree.
An AVL Tree is a self-balancing binary search tree named after its inventors Adelson-Velsky and Landis. It's designed to maintain a balance, ensuring that the height of the two child subtrees of any node differ by at most one.
AVL Trees are useful when dealing with large datasets, as they provide faster search, insert, and delete operations compared to ordinary binary search trees, while still maintaining a balanced structure.
Balance is maintained in AVL Trees through four types of rotations:
class Node:
# ... (omitted for brevity)
def left_rotate(self):
passclass Node:
# ... (omitted for brevity)
def right_rotate(self):
passclass Node:
# ... (omitted for brevity)
def double_left_rotate(self):
passclass Node:
# ... (omitted for brevity)
def double_right_rotate(self):
passInserting a new node into an AVL Tree involves standard binary search tree insertion, followed by height updates and balance checks to ensure the tree remains balanced.
Deleting a node in an AVL Tree can lead to unbalanced trees, so special cases must be handled, such as the cases of a leaf node, a node with one child, and a node with two children.
What is an AVL Tree?
Stay tuned for the continuation of our AVL Tree adventure! In the next part, we'll dive deep into AVL Tree Insertion and Deletion. π―
Happy coding! π‘π‘π‘