// Author: CCS
// I follow literally code in C, done many years ago
fn main() {
    // Adjacency matrix as a map
    graph := {
        'A': ['B', 'C']
        'B': ['A', 'D', 'E']
        'C': ['A', 'F']
        'D': ['B']
        'E': ['B', 'F']
        'F': ['C', 'E']
    }
    println('Graph: ${graph}')
    path := breadth_first_search_path(graph, 'A', 'F')
    println('\n The shortest path from node A to node F is: ${path.reverse()}')
}

// Breadth-First Search (BFS) allows you to find the shortest distance between two nodes in the graph.
fn breadth_first_search_path(graph map[string][]string, start string, target string) []string {
    mut path := []string{} // ONE PATH with SUCCESS = array
    mut queue := []string{} // a queue ... many paths
    // all_nodes := graph.keys() // get a key of this map
    // a map to store all the nodes visited to avoid cycles
    // start all them with False, not visited yet
    mut visited := visited_init(graph) // a map fully
    // false ==> not visited yet: {'A': false, 'B': false, 'C': false, 'D': false, 'E': false}
    queue << start // first arrival
    for queue.len != 0 {
        mut node := departure(mut queue) // get the front node and remove it
        if visited[node] == false { // check if this node is already visited
            // if no ... test it searchinf for a final node
            visited[node] = true // means: visit this node
            if node == target {
                path = build_path_reverse(graph, start, node, visited)
                return path
            }
            // Expansion of node removed from  queue
            print('\n Expansion of node ${node} (true/false): ${graph[node]}')
            // take  all nodes from the node
            for vertex in graph[node] { // println("\n ...${vertex}")
                // not explored yet
                if visited[vertex] == false {
                    queue << vertex
                }
            }
            print('\n QUEUE: ${queue} (only not visited) \n Visited: ${visited}')
        }
    }
    path = ['Path not found, problem in the Graph, start or end nodes! ']
    return path
}

// classical removing of a node from the start of a queue
fn departure(mut queue []string) string {
    mut x := queue[0]
    queue.delete(0)
    return x
}

// Creating aa map to initialize with of visited nodes .... all with false in the init
// so these nodes are NOT VISITED YET
fn visited_init(a_graph map[string][]string) map[string]bool {
    mut temp := map[string]bool{} // attention in these initializations with maps
    for i, _ in a_graph {
        temp[i] = false
    }
    return temp
}

// Based in the current node that is final, search for its parent, already visited, up to the root or start node
fn build_path_reverse(graph map[string][]string, start string, final string, visited map[string]bool) []string {
    print('\n\n Nodes visited (true) or no (false): ${visited}')
    array_of_nodes := graph.keys()
    mut current := final
    mut path := []string{}
    path << current

    for (current != start) {
        for i in array_of_nodes {
            if current in graph[i] && visited[i] == true {
                current = i
                break // the first occurrence is enough
            }
        }
        path << current // update the path tracked
    }
    return path
}

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