BFS Implementation in Python 3 def bfs(graph, root):
    visited, queue = [], [root]
    while queue:
        vertex = queue.pop(0)
        for w in graph[vertex]:
            if w not in visited:
                visited.append(w)
                queue.append(w)

graph = {0: [1, 2], 1: [2], 2: []}
bfs(graph, 0)


Does this look like a correct implementation of BFS in Python 3?
sets perform containing checks (w in visited) \$O(1)\$ rather than \$O(n)\$ for lists.
collections.deque are better than lists for poping elements at the front (popleft).
you should put your example code under an if __name__ == '__main__' clause.
w as a variable name does not convey meaning, you should try to come up with something more explicit.




import collections


def breadth_first_search(graph, root): 
    visited, queue = set(), collections.deque([root])
    while queue: 
        vertex = queue.popleft()
        for neighbour in graph[vertex]: 
            if neighbour not in visited: 
                visited.add(neighbour) 
                queue.append(neighbour) 


if __name__ == '__main__':
    graph = {0: [1, 2], 1: [2], 2: []} 
    breadth_first_search(graph, 0)




Given a growing number of comments indicating that the code does not return anything, I’d like to add that, yes, this code does not process nodes: it only traverse the graph and you're likely to want to add your own custom logic to process each node. As your mileage may vary (building a traversal list, finding the first node that satisfies a condition, etc.), there is not a "one code fits all" approach, but a useful first approximation would be to yield each node as they are traversed:

import collections


def breadth_first_search(graph, root): 
    visited, queue = set(), collections.deque([root])
    while queue: 
        vertex = queue.popleft()
        yield vertex
        visited.add(vertex)
        queue.extend(n for n in graph[vertex] if n not in visited)


if __name__ == '__main__':
    graph = {1: [2, 4, 5], 2: [3, 6, 7], 3: [], 4: [], 5: [], 6: [], 7: []}
    list(breadth_first_search(graph, 1))  # [1, 2, 4, 5, 3, 6, 7]


Note that this alternative iteration also takes care of the bug mentioned in this answer