👀 Views: 74 💬 Answers: 1 📅 Created: 2025-06-08

algorithm graph bfs Python

I'm building a feature where I tried several approaches but none seem to work. I am currently working on implementing a Breadth-First Search (BFS) algorithm in Python to traverse a graph. However, I'm experiencing an scenario where the algorithm does not visit all nodes when the graph contains cycles. My current implementation is not handling the cyclic nature of the graph correctly, leading to missed nodes. Here is the code I have so far: ```python from collections import deque def bfs(graph, start): visited = set() queue = deque([start]) while queue: vertex = queue.popleft() if vertex not in visited: print(vertex) # Process the node as needed visited.add(vertex) queue.extend(neighbor for neighbor in graph[vertex] if neighbor not in visited) # Example graph with a cycle graph = { 0: [1, 2], 1: [0, 3], 2: [0, 3], 3: [1, 2] } bfs(graph, 0) ``` When I run the provided example, I expect it to visit all nodes (0, 1, 2, 3), but it stops after visiting 0 and 1. I've tried adding print statements to debug which nodes are being visited and found that the queue gets exploring after processing node 1. I believe the scenario lies in how I'm checking for visited nodes when extending the queue. I also tried to implement a different approach by using a separate list for the queue, but that led to additional complications, and I still encountered the same scenario. Can someone guide to identify why my BFS implementation might not be traversing all the nodes, especially in the presence of cycles? Any advice or insights would be greatly appreciated! I'm working on a web app that needs to handle this. Thanks in advance! The stack includes Python and several other technologies. What would be the recommended way to handle this?