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@dingran
Last active November 30, 2023 22:43
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Python implementation of Dijkstra's algorithm, single source all desinations and single source single destination
from collections import defaultdict
def build_graph(edge_list):
graph = defaultdict(list)
seen_edges = defaultdict(int)
for src, dst, weight in edge_list:
seen_edges[(src, dst, weight)] += 1
if seen_edges[(src, dst, weight)] > 1: # checking for duplicated edge entries
continue
graph[src].append((dst, weight))
graph[dst].append((src, weight)) # remove this line of edge list is directed
return graph
def dijkstra(graph, src, dst=None):
nodes = []
for n in graph:
nodes.append(n)
nodes += [x[0] for x in graph[n]]
q = set(nodes)
nodes = list(q)
dist = dict()
prev = dict()
for n in nodes:
dist[n] = float('inf')
prev[n] = None
dist[src] = 0
while q:
u = min(q, key=dist.get)
q.remove(u)
if dst is not None and u == dst:
return dist[dst], prev
for v, w in graph.get(u, ()):
alt = dist[u] + w
if alt < dist[v]:
dist[v] = alt
prev[v] = u
return dist, prev
def find_path(pr, node): # generate path list based on parent points 'prev'
p = []
while node is not None:
p.append(node)
node = pr[node]
return p[::-1]
if __name__ == "__main__":
edges = [
("A", "B", 7),
("A", "D", 5),
("B", "C", 8),
("B", "D", 9),
("B", "E", 7),
("C", "E", 5),
("D", "E", 15),
("D", "F", 6),
("E", "F", 8),
("E", "G", 9),
("F", "G", 11)
]
g = build_graph(edges)
print("=== Dijkstra ===")
print("--- Single source, single destination ---")
d, prev = dijkstra(g, "A", "E")
path = find_path(prev, "E")
print("A -> E: distance = {}, path = {}".format(d, path))
d, prev = dijkstra(g, "F", "G")
path = find_path(prev, "G")
print("F -> G: distance = {}, path = {}".format(d, path))
print("--- Single source, all destinations ---")
ds, prev = dijkstra(g, "A")
for k in ds:
path = find_path(prev, k)
print("A -> {}: distance = {}, path = {}".format(k, ds[k], path))
@Tasen-pro
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finally found it

@Tasen-pro
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what is the work of that line 20?

@jjlizcano
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thank you so much

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