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Dijkstra's algorithm can find for you the shortest path between two nodes on a graph. It's a must-know f...

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This next could be written little bit shorter:

path, current_vertex = deque(), dest

while previous_vertices[current_vertex] is not None:

path.appendleft(current_vertex)

current_vertex = previous_vertices[current_vertex]

if path:

path.appendleft(current_vertex)

----->>>

path, current_vertex = deque(), dest

while current_vertex:

path.appendleft(current_vertex)

current_vertex = previous_vertices[current_vertex]

Nicely done!

If you are only trying to get from A to B in a graph... then the A* algorithm usually performs slightly better: en.wikipedia.org/wiki/A*_search_al... That's what many SatNav packages use :)

Yep! I will write about it soon. Thanks for reading :)

Hello Maria,

First of all, thank you for taking the time to share your knowledge with all of us! I am sure that your code will be of much use to many people, me amongst them!

I actually have two questions.

First: do you know -or do you have heard of- how to change the weights of your graph after each movement?

In my case, I would like to impede my graph to move through certain edges setting them to 'Inf' in each iteration (later, I would remove these 'Inf' values and set them to other ones.

Second: Do you know how to include restrictions to Dijkstra, so that the path between certain vertices goes through a fixed number of edges?

Many thanks in advance, and best regards!

Hello back,

I was finally able to find a solution to change the weights dynamically during the search process, however, I am still not sure about how to impose the condition of having a path of length >= N, being N the number of traversed edges. The only idea I have come up with would consist on turning to infinity the last edge towards my destination vertex if the overall distance lies below N. However, this would make this edge no longer available for use for the other paths that would arrive to destination vertex. Any ideas from your side folks? Many thanks in advance, and best regards!

If we want to know the shortest path and total length at the same time

how to change the code?

Using Python object-oriented knowledge, I made the following modification to the dijkstra method:

## return the distance between the nodes

I'd like to know that too.

The algotithm says

## 6 Stop, if the destination node has been visited.

in the code

## 6. Stop, if the smallest distance

## among the unvisited nodes is infinity.

if distances[current_vertex] == inf:

break

The code visits all nodes even after the destination has been visited.

What changes should i do if i dont want to use the deque() data structure?

Also how to read the graph contents from a file with the below structure

a / b / 3

a / c / 5

...

Source node: a

Destination node: j

Using Python object-oriented knowledge, I made the following modification to the dijkstra method to make it return the distance instead of the path as a deque object.

return the distance between the nodes

distance_between_nodes = 0

for index in range(1, len(path)):

for thing in self.edges:

if thing.start == path[index - 1] and thing.end == path[index]:

distance_between_nodes += thing.cost

return distance_between_nodes

# return path

What changes should i do if i dont want to use the deque() data structure?

Also how to read the graph contents from a file with the below structure

a / b / 3

a / c / 5

...

Source node: a

Destination node: j

This algorithm is working correctly only if the graph is directed,but if the graph is undireted it will not.

To make the algorithm work as directed graph you will have to edit neighbour function as

for beginners? sure it's packed with 'advanced' py features. @submit, namedtuple, list comprehentions, you name it!

Can you please tell us what the asymptote is in this algorithm and why?

Thank you Maria, this is exactly was I looking for... a good code with a good explanation to understand better this algorithm.

A similar approach here:

rebrained.com/?p=392