Modified Python implementation of Dijkstra's Algorithm (https://gist.github.com/econchick/4666413)

dijkstra.py

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']) 

Amazing Graph class! Thanks a lot!

@mdsrosa
Hi!
Thanks Alot for this implementation!
Q:
If I will remove line 15: self.edges[to_node].append(from_node)
Will it make the graph DIRECTED instead of undirected? Will it work?
I did not fully understand how line 16:
self.distances[(from_node, to_node)] = distance
works for both edges.

Just want to tell you, THANK YOU!!!! I have spent weeks on this, my assignment was like super late but thank you, I was able to bend my data structure to your classes will! Appreciate it

THIS IS NEAT!

BUT WHAT IF THERE EXIST TWO shortest paths, HOW CAN I GET BOTH? THANKS.

Thank you so, so, very much! I spent hours banging my head against a wall working with recursive functions before I found this Gist, which works like a charm!

Works like a charm. Thanks a bunch.

EdgeList can contain duplicate items in current scenario. It would be great if it is a defautdict(set) . Would there be any improvement in performance?

this is o(mn) naive implementation correct?

Hello,
In this code, Why I should revise the add_edge definition in Graph class like this:

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
    self.distances[(to_node, from_node)] = distance     #I added this line

It doesn't work when the destination is the same as the origin.

I added few modifications for when I need to calculate the distance for same node:
` def are_these_nodes_adjacents(from_node, to_node):
return to_node in graph.edges[from_node]

    def shortest_path_same_node(graph, origin, visited):
        min_distance = None
        min_node = None
        for node, distance in visited.items():
            if(are_these_nodes_adjacents(node, origin)):
                if(min_node is None):
                    min_node = node
                    min_distance = distance + graph.distances[(min_node, origin)]
                else:
                    if(min_distance > distance):
                        min_node = node
                        min_distance = distance + graph.distances[(min_node, origin)]
        return min_distance

    def shortest_path2(graph, origin, destination):
        visited, paths = dijkstra(graph, origin)
        result = 0
        if(origin == destination):
            result = shortest_path_same_node(graph, origin, visited)
        else:
            result = visited[destination]

        return result`

Thanks this is great.

Hi can I get a quest? How can I replace first line? I just started my way with python so don't judge me ;)

I want replace that because I don't know how it works but I want to implement this algorithm