BFS can be implemented using Queue. Remember that stack is use to create a DFS. The steps for BFS using Queue are: 1. Create empty queue and enqueue root node to it. 2. Do the following when queue is...

Solve the code using python language

Extracted text: BFS can be implemented using Queue. Remember that stack is use to create a DFS. The steps for BFS using Queue are: 1. Create empty queue and enqueue root node to it. 2. Do the following when queue is not empty a. Dequeue a node from queue and print it b. Enqueue left child of popped node to queue if not null c. Enqueue right child of popped node to queue if not nul" Implement the code shown in Figure shown below: Show the outcome ! #bfs implementation visited={} 12 13 level={} #distance dictionary parent={} bfs_traversal_output3[] 14 15 16 17 queue=Queue () 18 v for node in adj_list.keys(): visited[node]=False parent[node]=None level[node]= -1 #inf print(visited) 19 20 21 22 print(parent) print(level) #define source node 23 24 25 26 S="A" visited[s]=True level[s]=0 27 28 29 queue.put(s) #add source node to the queue 30 v while not queue.empty(): 31 u=queue.get() #pop first element of queue #add vertex 'u' to our bfs_traversal bfs_traversal_output.append(u) #append it for v in adj_list[u]: if not visited[v]: visited[v]=True parent[v]=u level[v]=level[u]+1 queue.put(v) 32 33 34 v 35 v 36 37 38 39 40 print(bfs_traversal_output)