- Introduction
- 1. Depth-First Search (DFS) Overview
- 2. Python Implementation of DFS on a Binary Search Tree
- Conclusion

Depth-First Search (DFS) is a graph traversal algorithm that explores as far down a branch as possible before backtracking. When applied to a Binary Search Tree (BST), DFS can be implemented using three main traversal methods: in-order, pre-order, and post-order. Each method processes nodes in a different order, providing various ways to explore the tree.

**In-Order Traversal**:- Visits nodes in the following order: left subtree, root node, right subtree.
- For a BST, this results in nodes being visited in ascending order.

**Pre-Order Traversal**:- Visits nodes in the following order: root node, left subtree, right subtree.
- Useful for creating a copy of the tree or performing actions on the root before its subtrees.

**Post-Order Traversal**:- Visits nodes in the following order: left subtree, right subtree, root node.
- Ideal for tasks like deleting the tree where children are processed before the parent.

**In-Order Traversal**: Retrieve elements in sorted order.**Pre-Order Traversal**: Useful for tree serialization or copying.**Post-Order Traversal**: Useful for deleting nodes or processing the tree from bottom to top.

First, define the BST and implement the DFS traversal methods.

Here's how to use the `BinarySearchTree`

class and perform the different DFS traversals.

Performing Depth-First Search (DFS) on a Binary Search Tree (BST) involves using different traversal methods to explore nodes. In-order, pre-order, and post-order traversals each offer unique ways to process the tree's nodes. By implementing these traversals in Python, you can effectively navigate and manipulate BST structures for various applications, from sorting elements to managing hierarchical data.