depth first search in graph code example

Example 1: python depth first search

# left to right, pre-order depth first tree search, iterative. O(n) time/space
def depthFirstSearch(root):
    st = [root]
    while st:
        current = st.pop()
        print(current)
        if current.right is not None: st.append(current.right) 
        if current.left is not None: st.append(current.left)

Example 2: DFS in c++

#include <bits/stdc++.h>
using namespace std;
 

class Graph {
    int V; 
 
 
    list<int>* adj;
 
  
    void DFSUtil(int v, bool visited[]);
 
public:
    Graph(int V);
 
    void addEdge(int v, int w);
 
  
    void DFS(int v);
};
 
Graph::Graph(int V)
{
    this->V = V;
    adj = new list<int>[V];
}
 
void Graph::addEdge(int v, int w)
{
    adj[v].push_back(w); 
}
 
void Graph::DFSUtil(int v, bool visited[])
{
   
    visited[v] = true;
    cout << v << " ";
 
   
    list<int>::iterator i;
    for (i = adj[v].begin(); i != adj[v].end(); ++i)
        if (!visited[*i])
            DFSUtil(*i, visited);
}
 

void Graph::DFS(int v)
{
   
    bool* visited = new bool[V];
    for (int i = 0; i < V; i++)
        visited[i] = false;
 
 
    DFSUtil(v, visited);
}
 

int main()
{
  
    Graph g(4);
    g.addEdge(0, 1);
    g.addEdge(0, 2);
    g.addEdge(1, 2);
    g.addEdge(2, 0);
    g.addEdge(2, 3);
    g.addEdge(3, 3);
 
    cout << "Following is Depth First Traversal"
            " (starting from vertex 2) \n";
    g.DFS(2);
 
    return 0;
}

Example 3: dfs python

###############
#The Algorithm (In English):

# 1) Pick any node. 
# 2) If it is unvisited, mark it as visited and recur on all its 
#    adjacent nodes. 
# 3) Repeat until all the nodes are visited, or the node to be 
#    searched is found.


# The graph below (declared as a Python dictionary)
# is from the linked website and is used for the sake of
# testing the algorithm. Obviously, you will have your own
# graph to iterate through.
graph = {
    'A' : ['B','C'],
    'B' : ['D', 'E'],
    'C' : ['F'],
    'D' : [],
    'E' : ['F'],
    'F' : []
}

visited = set() # Set to keep track of visited nodes.


##################
# The Algorithm (In Code)

def dfs(visited, graph, node):
    if node not in visited:
        print (node)
        visited.add(node)
        for neighbour in graph[node]:
            dfs(visited, graph, neighbour)
            
# Driver Code to test in python yourself.
# Note that when calling this, you need to
# call the starting node. In this case it is 'A'.
dfs(visited, graph, 'A')

# NOTE: There are a few ways to do DFS, depending on what your
# variables are and/or what you want returned. This specific
# example is the most fleshed-out, yet still understandable,
# explanation I could find.

Example 4: depth first search

// performs a depth first search (DFS)
// nodes are number from 1 to n, inclusive
#include <bits/stdc++.h>
using namespace std;


vector<vector<int>> adj;  // adjacency list
// visited[v] = true if v has been visited by dfs
vector<bool> visited;

bool all_edges_are_directed = true;

void dfs(int v) {
    // determines if dfs has been done on v
    if(visited[v])
        return;
    visited[v] = true;

    // write code here to do stuff with node v

    // traverse nodes that are adjacent to v
    for (int u: adj[v]){
        dfs(u);
    }
}

int main() {
    int n;  // number of vertices
    int m;  // number of edges
    cin >> n >> m;
    adj = vector<vector<int>>(n+1, vector<int>());
    visited = vector<bool>(n+1, false);

    for(int i = 0; i < m; ++i) {
        // nodes a and b have an edge between them
        int a, b;
        cin >> a >> b;

        if(all_edges_are_directed)
            adj[a].push_back(b);
        else {
            adj[a].push_back(b);
            adj[b].push_back(a);
        }
    }
    
    // do depth first search on all nodes
    for(int i = 1; i <= n; ++i){
        dfs(i);
    }
}

Example 5: depth first search

# HAVE USED ADJACENY LIST
class Graph:
    def __init__(self,lst=None):
        self.lst=dict()
        if lst is None:
            pass
        else:
            self.lst=lst
    def find_path(self,start,end):
        self.checklist={}
        for i in self.lst.keys():
            self.checklist[i]=False
        self.checklist[start]=True
        store,extra=(self.explore(start,end))
        if store==False:
            print('No Path Found')
        else:
            print(extra)
    def explore(self,start,end):
        while True:
            q=[]        
            #print(self.checklist,q)
            q.append(start)
            flag=False            
            for i in self.lst[start]:
                if i==end:
                    q.append(i)
                    return True,q
                if self.checklist[i]:
                    pass
                else:
                    flag=True
                    self.checklist[i]=True
                    q.append(i)
                    break   
            if flag:
                store,extra=self.explore(q[-1],end) 
                if store==False:
                    q.pop()
                    if len(q)==0:return False
                    return self.explore(q[-1],end)
                elif store==None:
                    pass
                elif store==True:
                    q.pop()
                    q.extend(extra)
                    return True,q
            else:
                return False,None
    def __str__(self):return str(self.lst)
if __name__=='__main__':
    store={1: [2, 3, 4], 2: [3, 1], 3: [2, 1], 4: [5, 8, 1], 5: [4, 6, 7], 6: [5, 7, 9, 8], 7: [5, 6], 8: [4, 6, 9], 9: [6, 8, 10], 10: [9],11:[12,13]}
    a=Graph(store)
    a.find_path(1,11) # No Path Found 
    a.find_path(1,6)# [1, 4, 5, 6]    
    a.find_path(3,10)   # [3, 2, 1, 4, 5, 6, 9, 10] 
    a.find_path(4,10)# [4, 5, 6, 9, 10]
    print(a) #