Discover, Locate, Learn: Python's Breadth First Search Demystified.

Breadth First Search use case.


Breadth First search is also called a level order traversal. BFS is an algorithm to traverse the graph level by level. While traversing the algorithm visits all vertices and edges, any node is taken as a root node during traversal starting. For BF search a queue data structure would be used that follows FIFO(First In First Out) principle.

Breadth First Search algorithm.

Coding: The Silent Symphony. - Updated: 2024-05-18 by Andrey BRATUS, Senior Data Analyst.




The process organised in such a way that we visit nodes level wise, i e first we complete the top level and then move on to lower levels. The practical example of BFS use case is a chess game engine where we build the game tree from the current position and apply all possible moves to find a win position. Breadth-first search finds a solution node if one exists.


Breadth First Search Python code:



import collections

# BFS function
def bfs(graph, root):

    visited, queue = set(), collections.deque([root])
    visited.add(root)

    while queue:

        # Dequeue a vertex from queue
        vertex = queue.popleft()
        print(str(vertex) + " ", end="")

        # If not visited, mark it as visited, and
        # enqueue it
        for neighbour in graph[vertex]:
            if neighbour not in visited:
                visited.add(neighbour)
                queue.append(neighbour)



graph = {'0': set(['1', '2']),
          '1': set(['0', '3', '4']),
          '2': set(['0']),
          '3': set(['1']),
          '4': set(['2', '3'])}
         
print("BFS Traversal: ")
bfs(graph, '3')

OUT: BFS Traversal:
3 1 0 4 2





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