Modified Python implementation of Dijkstra's Algorithm (https://gist.github.com/econchick/4666413)
from collections import defaultdict, deque
class Graph(object):
def __init__(self):
self.nodes = set()
self.edges = defaultdict(list)
self.distances = {}
def add_node(self, value):
self.nodes.add(value)
def add_edge(self, from_node, to_node, distance):
self.edges[from_node].append(to_node)
self.edges[to_node].append(from_node)
self.distances[(from_node, to_node)] = distance
def dijkstra(graph, initial):
visited = {initial: 0}
path = {}
nodes = set(graph.nodes)
while nodes:
min_node = None
for node in nodes:
if node in visited:
if min_node is None:
min_node = node
elif visited[node] < visited[min_node]:
min_node = node
if min_node is None:
break
nodes.remove(min_node)
current_weight = visited[min_node]
for edge in graph.edges[min_node]:
try:
weight = current_weight + graph.distances[(min_node, edge)]
except:
continue
if edge not in visited or weight < visited[edge]:
visited[edge] = weight
path[edge] = min_node
return visited, path
def shortest_path(graph, origin, destination):
visited, paths = dijkstra(graph, origin)
full_path = deque()
_destination = paths[destination]
while _destination != origin:
full_path.appendleft(_destination)
_destination = paths[_destination]
full_path.appendleft(origin)
full_path.append(destination)
return visited[destination], list(full_path)
if __name__ == '__main__':
graph = Graph()
for node in ['A', 'B', 'C', 'D', 'E', 'F', 'G']:
graph.add_node(node)
graph.add_edge('A', 'B', 10)
graph.add_edge('A', 'C', 20)
graph.add_edge('B', 'D', 15)
graph.add_edge('C', 'D', 30)
graph.add_edge('B', 'E', 50)
graph.add_edge('D', 'E', 30)
graph.add_edge('E', 'F', 5)
graph.add_edge('F', 'G', 2)
print(shortest_path(graph, 'A', 'D')) # output: (25, ['A', 'B', 'D'])