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