Online python to c++ compiler

s = input()
op = ''
for i in range(len(s)-1):
    if s[i]==s[i+1]:
        op += s[i]
        op += '*'
     else:
        op += s[i]
op += s[-1]
print(op)

Online python to c++ compiler

s = input()
op = ''
for i in range(len(s)-1):
    if s[i]==s[i+1]:
        op += s[i]
        op += '*'
    else:
        op += s[i]
op += s[-1]
print(op)

Online python to c++ compiler

val = input().split(' ')
nums = input().split(' ')
levels = []
for _ in range(int(val[1])):
    levels.append(int(input()))
nums = [int(x) for x in nums]
for idx in range(int(val[1])):
    r = [x for x in nums if x >= levels[int(idx)]]
    print(min(r))

Online python to c++ compiler

graph = {'S':{'A':1, 'C':2}, 'A':{'B':6}, 'B':{'D':1, 'E':2}, 'C':{'A':4, 'D':3}, 'D':{'E':1}, 'E':{}} #we illustrate the dijkstra graph

def dijkstra(graph,start,target):
    # we set all the default value first for all variable
    shortest_distance = {}
    previous = {}
    unvisitNodes = graph
    infinity = 999999999
    pathway = []

    # for loop to check wether node have visit or not
    # if the node in unvisit nodes, set the shortest distance for the node to infinity
    # Set the shortest distance for start node to 0
    for node in unvisitNodes:
        shortest_distance[node] = infinity
    shortest_distance[start] = 0

    # while loop to decide the next node will be visit
    # for first time around, it start with start node (itself)
    #
    while unvisitNodes:
        minNode = None
        for node in unvisitNodes:
            if minNode is None:
                minNode = node
            elif shortest_distance[node] < shortest_distance[minNode]:
                minNode = node
                            
        # for loop to calculate shortest distance target node form start node
        # update the short distance target node from start node if calculate distance is less than known distance
        # initialize the previous node for each calculate node
        # decide the next node will be visit by the smallest known distance from start vertex
        # add the node into visited node
        for neighbourNode, weight in graph[minNode].items():
            if weight + shortest_distance[minNode] < shortest_distance[neighbourNode]:
                shortest_distance[neighbourNode] = weight + shortest_distance[minNode]
                previous[neighbourNode] = minNode
        unvisitNodes.pop(minNode)

    #set currentNode into target
    currentNode = target
    #while loop to list all the path way for the calculate nodes
    while currentNode !=start:
        try:
            pathway.insert(0,currentNode)
            currentNode = previous[currentNode]
        except KeyError:
            print('Path not reach')
            break
    #add start node into the path way for each calculate nodes    
    pathway.insert(0,start)
    #display the shortest distance and the path way for each target nodes
    if shortest_distance[target] != infinity:
        print('You are required shortest distance and path:- ')
        print('From: ' + str(start))
        print('To: ' + str(target))
        print('Shortest distance for ' + str(target) + ' from ' + str(start) + ' is ' + str(shortest_distance[target]))
        print('The path is ' + str(pathway))


# call the dijkstra function by assign the start and target nodes as the parameter
dijkstra(graph,'S','S')

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