Let's consider an example of implementing Depth-First Search (DFS) and Breadth-First Search (BFS) algorithms in Python to traverse a graph represented using an adjacency list. ```py from collections import defaultdict class Graph: def __init__(self): self.graph = defaultdict(list) def add_edge(self, u, v): self.graph[u].append(v) def dfs_util(self, v, visited): visited.add(v) print(v, end=' ') for neighbor in self.graph[v]: if neighbor not in visited: self.dfs_util(neighbor, visited) def dfs(self, start): visited = set() self.dfs_util(start, visited) def bfs(self, start): visited = set() queue = [start] visited.add(start) while queue: v = queue.pop(0) print(v, end=' ') for neighbor in self.graph[v]: if neighbor not in visited: queue.append(neighbor) visited.add(neighbor) # Example usage g = Graph() g.add_edge(0, 1) g.add_edge(0, 2) g.add_edge(1, 2) g.add_edge(2, 0) g.add_edge(2, 3) g.add_edge(3, 3) print("DFS traversal:") g.dfs(2) print("\nBFS traversal:") g.bfs(2) ``` This code defines a simple graph class using an adjacency list representation. It includes methods to add edges, perform Depth-First Search (DFS), and Breadth-First Search (BFS) traversals. The **dfs_util** method is a recursive helper function for DFS traversal, while the **dfs** method initializes the visited set and starts DFS from a given node. Similarly, the **bfs** method performs BFS traversal using a queue. You can create a **Graph** object, add edges using the **add_edge** method, and then perform DFS or BFS traversal starting from any node using the respective methods.