Learn Algorithm Design by Building a Shortest Path Algorithm - Step 54

Tell us what’s happening:

I suggest updating step 54 of the curriculum. Currently, when inputting a string of nodes as the target, only one path is processed at a time, which i don’t think is the intended behavior. If ‘BD’ is entered as the target, it should show paths to both ‘B’ and ‘D’, but the code breaks. A possible improvement is changing [target] to list(target), allowing the string to split into individual nodes correctly.

Your code so far


my_graph = {
    'A': [('B', 3), ('D', 1)],
    'B': [('A', 3), ('C', 4)],
    'C': [('B', 4), ('D', 7)],
    'D': [('A', 1), ('C', 7)]
}

def shortest_path(graph, start, target = ''):
    unvisited = list(graph)
    distances = {node: 0 if node == start else float('inf') for node in graph}
    paths = {node: [] for node in graph}
    paths[start].append(start)
    
    while unvisited:
        current = min(unvisited, key=distances.get)
        for node, distance in graph[current]:
            if distance + distances[current] < distances[node]:
                distances[node] = distance + distances[current]
                if paths[node] and paths[node][-1] == node:
                    paths[node] = paths[current][:]
                else:
                    paths[node].extend(paths[current])
                paths[node].append(node)
        unvisited.remove(current)

# User Editable Region

    targets_to_print = [target] if target else graph


shortest_path(my_graph, 'A')

# User Editable Region

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Challenge Information:

Learn Algorithm Design by Building a Shortest Path Algorithm - Step 55

the function was not designed to take in multiple targets
I don’t know if it’s an improvement worth adding, but if you feel strongly about it you can open a github issue and it can be discussed