Python/graphs/bfs_shortest_path.py

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graph = {'A': ['B', 'C', 'E'],
'B': ['A','D', 'E'],
'C': ['A', 'F', 'G'],
'D': ['B'],
'E': ['A', 'B','D'],
'F': ['C'],
'G': ['C']}
def bfs_shortest_path(graph, start, goal):
# keep track of explored nodes
explored = []
# keep track of all the paths to be checked
queue = [[start]]
# return path if start is goal
if start == goal:
return "That was easy! Start = goal"
# keeps looping until all possible paths have been checked
while queue:
# pop the first path from the queue
path = queue.pop(0)
# get the last node from the path
node = path[-1]
if node not in explored:
neighbours = graph[node]
# go through all neighbour nodes, construct a new path and
# push it into the queue
for neighbour in neighbours:
new_path = list(path)
new_path.append(neighbour)
queue.append(new_path)
# return path if neighbour is goal
if neighbour == goal:
return new_path
# mark node as explored
explored.append(node)
# in case there's no path between the 2 nodes
return "So sorry, but a connecting path doesn't exist :("
bfs_shortest_path(graph, 'G', 'D') # returns ['G', 'C', 'A', 'B', 'D']