# Python program to find articulation points in an undirected graph
  
from collections import defaultdict
  
# This class represents an undirected graph
# using adjacency list representation
class Graph:
  
    def __init__(self, vertices):
        self.V = vertices # No. of vertices
        self.graph = defaultdict(list) # default dictionary to store graph
        self.Time = 0
  
    # function to add an edge to graph
    def addEdge(self, u, v):
        self.graph[u].append(v)
        self.graph[v].append(u)
  
    '''A recursive function that find articulation points
    using DFS traversal
    u --> The vertex to be visited next
    visited[] --> keeps track of visited vertices
    disc[] --> Stores discovery times of visited vertices
    parent[] --> Stores parent vertices in DFS tree
    ap[] --> Store articulation points'''
    def APUtil(self, u, visited, ap, parent, low, disc):
 
        # Count of children in current node
        children = 0
 
        # Mark the current node as visited and print it
        visited[u]= True
 
        # Initialize discovery time and low value
        disc[u] = self.Time
        low[u] = self.Time
        self.Time += 1
 
        # Recur for all the vertices adjacent to this vertex
        for v in self.graph[u]:
            # If v is not visited yet, then make it a child of u
            # in DFS tree and recur for it
            if visited[v] == False :
                parent[v] = u
                children += 1
                self.APUtil(v, visited, ap, parent, low, disc)
 
                # Check if the subtree rooted with v has a connection to
                # one of the ancestors of u
                low[u] = min(low[u], low[v])
 
                # u is an articulation point in following cases
                # (1) u is root of DFS tree and has two or more children.
                if parent[u] == -1 and children > 1:
                    ap[u] = True
 
                #(2) If u is not root and low value of one of its child is more
                # than discovery value of u.
                if parent[u] != -1 and low[v] >= disc[u]:
                    ap[u] = True   
                     
                # Update low value of u for parent function calls   
            elif v != parent[u]:
                low[u] = min(low[u], disc[v])
 
 
    # The function to do DFS traversal. It uses recursive APUtil()
    def AP(self):
  
        # Mark all the vertices as not visited
        # and Initialize parent and visited,
        # and ap(articulation point) arrays
        visited = [False] * (self.V)
        disc = [float("Inf")] * (self.V)
        low = [float("Inf")] * (self.V)
        parent = [-1] * (self.V)
        ap = [False] * (self.V) # To store articulation points
 
        # Call the recursive helper function
        # to find articulation points
        # in DFS tree rooted with vertex 'i'
        for i in range(self.V):
            if visited[i] == False:
                self.APUtil(i, visited, ap, parent, low, disc)
 
        for index, value in enumerate (ap):
            if value == True: print (index,end=" ")
 
 # Create a graph given in the above diagram
g1 = Graph(5)
g1.addEdge(1, 0)
g1.addEdge(0, 2)
g1.addEdge(2, 1)
g1.addEdge(0, 3)
g1.addEdge(3, 4)
  
print ("\nArticulation points in first graph ")
g1.AP()
 
g2 = Graph(4)
g2.addEdge(0, 1)
g2.addEdge(1, 2)
g2.addEdge(2, 3)
print ("\nArticulation points in second graph ")
g2.AP()
 
  
g3 = Graph (7)
g3.addEdge(0, 1)
g3.addEdge(1, 2)
g3.addEdge(2, 0)
g3.addEdge(1, 3)
g3.addEdge(1, 4)
g3.addEdge(1, 6)
g3.addEdge(3, 5)
g3.addEdge(4, 5)
print ("\nArticulation points in third graph ")
g3.AP()
 
# This code is contributed by Neelam Yadav

Time complexity: linear
Space complexity: linear