AVL Tree Implementation in Python

This is an implementation of the AVL tree data structure in Python.

Overview

AVL tree is a self-balancing binary search tree, and it is named after its two inventors, Adelson-Velsky and Landis. In an AVL tree, the heights of the two child subtrees of any node differ by at most one. In other words, it is a binary tree with height-balancing property.

This implementation contains the following methods:

• insert(element): inserts a new node into the tree
• remove(element): removes a node from the tree
• find(element): finds an element in the tree
• pre_order_walk(): returns a list of the nodes traversed in pre-order
• in_order_walk(): returns a list of the nodes traversed in in-order
• post_order_walk(): returns a list of the nodes traversed in post-order
• get_tree_height(): returns the height of the tree
• get_min(): returns the smallest node in the tree
• get_max() returns the largest node in the tree
• to_graphviz(): returns a code the can be used to visualize the tree

Usage

To use the AVL tree, simply import the AVL class from the module and create an instance of it:

from AVL import AVL

tree = AVL()

You can then use the methods listed above to insert, remove, and find elements in the tree.

tree.insert(5)
tree.insert(3)
tree.insert(8)

print(tree.find(3)) # True
print(tree.find(10)) # False

print(tree.pre_order_walk()) # [5, 3, 8]
print(tree.in_order_walk()) # [3, 5, 8]

You can also use https://dreampuf.github.io/GraphvizOnline/ to visulize the tree. To do this you need to call the to_graphviz() function:

print(tree.to_graphviz())

The function prints the code you need to copy and paste in the website above.

Contributing

Contributions to this project are welcome. If you find a bug or want to suggest an improvement, please open an issue or submit a pull request. Or email me here: f.asadi2002@gmail.com

License

This code is released under the MIT License.