Binary Tree 🌳

What's this?

This is a Python implementation of a binary tree data structure. Binary trees are efficient for search operations and widely used in ordered datasets due to their high efficiency, typically represented by the logarithmic Big O notation.

About Binary Trees

Binary trees consist of nodes where each node has at most two children, commonly referred to as the left and right child. The tree starts from a root node and branches out, forming a hierarchical structure. The properties of binary trees make them suitable for various applications, including search operations, sorting, and data organization.

How can I use this?

To utilize this binary tree implementation, follow these steps:

1. Run the Python Code: Copy the provided Python code into a Python environment (Python 3.8 or above) or save it to a .py file. Then run the code to initiate the binary tree program.

2. Interact with the Program:

   • Start by entering the root value for your binary tree.
   • Choose from the available options to perform various operations on the binary tree, including inserting values, viewing different traversal orders, visualizing the tree structure, searching for values, resetting the tree, and inserting random numbers.
   • Follow the on-screen prompts to input values and make selections.

3. Perform Operations:

   • Insert Values: Add new values to the binary tree.
   • View Traversal Orders: Display the tree values in pre-order, in-order, or post-order traversal.
   • Visualize Binary Tree: View the binary tree structure in a hierarchical format.
   • Search for Values: Search for specific values within the binary tree.
   • Reset Tree: Reset the binary tree with a new root value.
   • Insert Random Numbers: Insert a specified number of random values into the tree.

4. Explore and Modify: Feel free to explore the provided code, understand how binary trees work, and modify the code to suit your specific needs. You can customize the functionalities, enhance error handling, or add additional features as required.

5. Learn and Experiment: Use this implementation as a learning tool to understand binary trees better and experiment with different scenarios to observe how the tree behaves with various operations and inputs.

More about

• Developed by Nycolas Galdino
• My profile on GitHub

Enjoy exploring and experimenting with binary trees using this Python implementation! If you have any questions or encounter any issues, don't hesitate to ask for assistance.