Graph Traversal Algorithms: BFS & DFS

This repository contains Python implementations of two fundamental graph traversal algorithms: Breadth-First Search (BFS) and Depth-First Search (DFS). The code was originally written in Google Colab and demonstrates how to traverse a graph structure using iterative (queue-based) and recursive approaches.

Files

• bfs_&_dfs_py.py – Contains both BFS and DFS implementations with sample graphs.

Algorithms Overview

Breadth-First Search (BFS)

BFS explores a graph level by level, starting from a given root node. It uses a queue (via collections.deque) to manage the traversal order and a visited set to prevent revisiting nodes.

Key Features:

• Iterative approach
• Uses deque for efficient popleft operations
• Visits neighbors in FIFO order

Depth-First Search (DFS)

DFS explores as far as possible along each branch before backtracking. This implementation uses recursion and a visited set.

Key Features:

• Recursive approach
• Simple and compact code
• Uses system call stack implicitly

Example Graphs

BFS Example (Graph 1)

python graph = { 0: [1, 2, 3], 1: [0, 2, 4], 2: [0, 1], 3: [0], 4: [1] }

DFS Example (Graph 2)

python graph = { 'A': ['B', 'C', 'D'], 'B': ['E'], 'C': ['D', 'E'], 'D': [], 'E': [] }