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

46 votes172 views6 answers
Dataframe to CSV
Python
1 vote184 views1 answer
Upgrade pip wheel
Python
0 vote184 views2 answers
Python open excel application
Python
0 vote170 views1 answer
Higher-order functions and operations on callable objects in python
Python
3 votes172 views2 answers
Secondary y axis matplotlib
Python
1 vote170 views1 answer
If a number times a number is true python
Python
51 votes167 views6 answers
Pickle load
Python
5 votes168 views1 answer
Python test is nan
Python
0 vote162 views1 answer
éliminer le background image python
Python
0 vote237 views1 answer
How to draw a square pygame
Python