DFS

Dfs

# Depth First Search: DFS Algorithm

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

graph= {
    'A' : ['B','C'],
    'B' : ['D', 'E'],
    'C' : ['F'],
    'D' : [],
    'E' : ['F'],
    'F' : []
    }
visited = set() # Set to keep track of visited nodes of graph.

def dfs(visited, graph, node):  #function for dfs 
    if node not in visited:
        ''' 
        We start with A
        Then B
        Then D
        Then E
        Then F
        Then C
        A -> B -> D -> E -> F -> C
        '''
        print(node)
        # added to visited to avoid visit the node twice 
        visited.add(node)
        for neighbour in graph[node]:
            ''' 
            * Neighbour of A : B and C but first visit B
            * Then neighbour of B : D and E but first visit D 
            * Then neighbour of D : doesn't have neighbour then backtrack to the neighbour
                of the previous node (B) which is E
            * Then neighbour of E : F
            * Then neighbour of F : doesn't have neighbour then backtrack to the neighbour 
                of the previous node E but doesn't have other neighbour except F which is visited
                So backtracking again to B and B also doesn't have nodes not visited 
                So backtracking again to A: C not visited YAY!
            '''
            dfs(visited, graph, neighbour)
    
print(dfs(visited, graph, 'A'))

DFS explained

 def depth_first_search(graph):
    visited, stack = set(), [root]
    while stack:
        vertex = stack.pop()
        if vertex not in visited:
            visited.add(vertex)
            stack.extend(graph[vertex] - visited)
    return visited

Source: brilliant.org

DFS explained

Initialize an empty stack for storage of nodes, S.
For each vertex u, define u.visited to be false.
Push the root (first node to be visited) onto S.
While S is not empty:
    Pop the first element in S, u.
    If u.visited = false, then:
        U.visited = true
        for each unvisited neighbor w of u:
            Push w into S.
End process when all nodes have been visited.

Source: brilliant.org

DFS

print("found ans")

-3

Source: purdue.brightspace.com

Similar codes

2 votes218 views4 answers
Pandas difference between two dataframes
Python
-1 vote237 views1 answer
Parametric relu in keras convolution layer
Python
1 vote244 views2 answers
Run flask in background
Python Flask
0 vote223 views1 answer
Python docx extract image
Python
1 vote205 views1 answer
How to make a breakable loop in python
Python
9 votes238 views6 answers
Reaction role discord.py
Python
0 vote212 views1 answer
How to record pyttsx3 file using python
Python
0 vote212 views1 answer
Line continutation in r string python
Python
10 votes200 views3 answers
Discord.py custom status
Python
110 votes210 views6 answers
Read text file in python
Python