breadth search

Breadth First Search

graph = {
  '5' : ['3','7'],
  '3' : ['2', '4'],
  '7' : ['8'],
  '2' : [],
  '4' : ['8'],
  '8' : []
}

visited = [] # List for visited nodes.
queue = []     #Initialize a queue

def bfs(visited, graph, node): #function for BFS
  visited.append(node)
  queue.append(node)

  while queue:          # Creating loop to visit each node
    m = queue.pop(0) 
    print (m, end = " ") 

    for neighbour in graph[m]:
      if neighbour not in visited:
        visited.append(neighbour)
        queue.append(neighbour)

# Driver Code
print("Following is the Breadth-First Search")
bfs(visited, graph, '5')    # function calling

Posted by: Guest on March-07-2022

Source

BFS-> uses queue DFS-> uses stack or recursion (less code) NOTE: same idea algo wise for both IDEA: 1 declare the DS(if bfs-DS will be queue,if dfs-stack) 2 push the start node to DS 3 when you push you mark it as visited 4 until the DS is not empty run a loop 5 inside loop pop the DS(deque for queue or pop for stack) and save it in a new object actual 6 loop through the neighbors of actual 7 if the current neighbor n is not visited 8 then push n in DS 9 mark n as visited in the next line.

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