# Python Program for Breadth First Search or BFS for a Graph

• Difficulty Level : Basic
• Last Updated : 20 Dec, 2021

Breadth First Traversal (or Search) for a graph is similar to Breadth First Traversal of a tree (See method 2 of this post). The only catch here is, unlike trees, graphs may contain cycles, so we may come to the same node again. To avoid processing a node more than once, we use a boolean visited array. For simplicity, it is assumed that all vertices are reachable from the starting vertex.
For example, in the following graph, we start traversal from vertex 2. When we come to vertex 0, we look for all adjacent vertices of it. 2 is also an adjacent vertex of 0. If we don’t mark visited vertices, then 2 will be processed again and it will become a non-terminating process. A Breadth First Traversal of the following graph is 2, 0, 3, 1.

## Recommended: Please solve it on “PRACTICE ” first, before moving on to the solution.

Following are the implementations of simple Breadth First Traversal from a given source.

The implementation uses adjacency list representation of graphs. STL\’s list container is used to store lists of adjacent nodes and queue of nodes needed for BFS traversal.

## Python3

 `# Python3 Program to print BFS traversal``# from a given source vertex. BFS(int s)``# traverses vertices reachable from s.``from` `collections ``import` `defaultdict`` ` `# This class represents a directed graph``# using adjacency list representation``class` `Graph:`` ` `    ``# Constructor``    ``def` `__init__(``self``):`` ` `        ``# default dictionary to store graph``        ``self``.graph ``=` `defaultdict(``list``)`` ` `    ``# function to add an edge to graph``    ``def` `addEdge(``self``,u,v):``        ``self``.graph[u].append(v)`` ` `    ``# Function to print a BFS of graph``    ``def` `BFS(``self``, s):`` ` `        ``# Mark all the vertices as not visited``        ``visited ``=` `[``False``] ``*` `(``len``(``self``.graph))`` ` `        ``# Create a queue for BFS``        ``queue ``=` `[]`` ` `        ``# Mark the source node as ``        ``# visited and enqueue it``        ``queue.append(s)``        ``visited[s] ``=` `True`` ` `        ``while` `queue:`` ` `            ``# Dequeue a vertex from ``            ``# queue and print it``            ``s ``=` `queue.pop(``0``)``            ``print` `(s, end ``=` `" "``)`` ` `            ``# Get all adjacent vertices of the``            ``# dequeued vertex s. If a adjacent``            ``# has not been visited, then mark it``            ``# visited and enqueue it``            ``for` `i ``in` `self``.graph[s]:``                ``if` `visited[i] ``=``=` `False``:``                    ``queue.append(i)``                    ``visited[i] ``=` `True`` ` `# Driver code`` ` `# Create a graph given in``# the above diagram``g ``=` `Graph()``g.addEdge(``0``, ``1``)``g.addEdge(``0``, ``2``)``g.addEdge(``1``, ``2``)``g.addEdge(``2``, ``0``)``g.addEdge(``2``, ``3``)``g.addEdge(``3``, ``3``)`` ` `print` `(``"Following is Breadth First Traversal"``                  ``" (starting from vertex 2)"``)``g.BFS(``2``)`` ` `# This code is contributed by Neelam Yadav`

Please refer complete article on Breadth First Search or BFS for a Graph for more details!

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