The output of the above code will be as follow:įollowing is the Breadth-First Search 5 3 7 2 4 8 Example Then we will run the while loop for the queue for visiting the nodes and then will remove the same node and print it as it is visited.Īt last, we will run the for loop to check the not visited nodes and then append the same from the visited and queue list.Īs the driver code, we will call the user to define the bfs function with the first node we wish to visit. And inside a function, we will keep appending the visited and queue lists. After creation, we will create two lists, one to store the visited node of the graph and another one for storing the nodes in the queue.Īfter the above process, we will declare a function with the parameters as visited nodes, the graph itself and the node respectively. In the above code, first, we will create the graph for which we will use the breadth-first search. # Driver Code print( "Following is the Breadth-First Search")īfs(visited, graph, '5') # function calling While queue: # Creating loop to visit each node Queue = #Initialize a queue def bfs(visited, graph, node): #function for BFS Now, we will see how the source code of the program for implementing breadth first search in python.Ĭonsider the following graph which is implemented in the code below: Mark and enqueue all (unvisited) neighbors of uīFS implementation in Python (Source Code) The pseudocode for BFS in python goes as below: Many times, a graph may contain two different disconnected parts and therefore to make sure that we have visited every vertex, we can also run the BFS algorithm at every node.
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