Go: package main

import "fmt"

type node struct {
	id, d, v int
	adj      []node
}

var n int
var seen []bool
var graph []node

func max(a, b int) int {
	if a > b {
		return a
	}
	return b
}

func dfs(v, t int) int {
	// fmt.Printf("dfs(v %d, t %d) en:\n", v, t)
	seen[v] = true
	graph[v].v = t
	tt := t
	for _, vv := range graph[v].adj {
		if !seen[vv.id] {
			tt = max(tt, dfs(vv.id, tt+1))
		}
	}
	graph[v].d = tt + 1
	// fmt.Printf("dfs(v %d, t %d) ex: d %d\n", v, t, graph[v].d)
	return graph[v].d
}

func main() {
	fmt.Scan(&n)
	graph = make([]node, n+1)
	for i := 1; i <= n; i++ {
		var u, k, v int
		fmt.Scan(&u, &k)
		graph[u].id = u
		// 頂点uはk個の隣接頂点を持っている
		for j := 0; j < k; j++ {
			fmt.Scan(&v)
			var t node
			t.id = v
			graph[u].adj = append(graph[u].adj, t)
		}
	}
	// fmt.Println("n", n, "graph", graph)
	seen = make([]bool, n+1)
	// t := dfs(1, 1)
	v, t := 1, 1
	done := false
	for !done {
		tt := dfs(v, t)
		done = true
		for i := range seen {
			if !seen[i] {
				done = false
				v = graph[i].id
				t = tt
				break
			}
		}
	}
	for i := 1; i <= n; i++ {
		fmt.Printf("%d %d %d\n", i, graph[i].v, graph[i].d)
	}
}

Python: 
# ??±???????????¢?´¢(Depth First Search)

def DFS(n = 1, i = 0, time = 1):
    for j in range(n):
        if A[i][j] == 1 and d[j] == 0:
            time = time + 1
            d[j] = time
            time = DFS(n, j, time)
    time = time + 1
    f[i] = time
    return time

n = int(raw_input())
A = [0] * n
for i in range(n):
    A[i] = [0] * n

for i in range(n):
    value = map(int, raw_input().split())
    u = value[0] - 1
    k = value[1]
    nodes = value[2:]
    for j in range(k):
        v = nodes[j] - 1
        A[u][v] = 1

d = [0] * n
f = [0] * n

time = 0
for i in range(n):
    if d[i] == 0:
        time = time + 1
        d[i] = time
        time = DFS(n, i, time)

for i in range(n):
    print(str(i + 1) + " " + str(d[i]) + " " + str(f[i]))

Python: def depth(s, time):
    time += 1
    f[s] = 1
    d[s] = t
    for i in range(1, n+1):
        if G[s][i] == 1:
            if f[i] == 0:
                depth(i, time)
                t = f[i]
    f[s] = time + 1
 
n = int(raw_input())
G = [[0 for i in range(n+1)] for j in range(n+1)]
d = [0 for i in range(n+1)]
f = [0 for i in range(n+1)]
 
for i in range(n):
    v = map(int, raw_input().split())
    for j in range(v[1]):
        G[v[0]][v[2+j]] = 1
 
flag = [0 for i in range(n+1)]
for i in range(1, n+1):
    if flag[i] == 0:
        depth(i, max(f))
 
for i in range(1, n+1):
    print(str(i) + " " + str(d[i]) + " " + str(f[i]))

Python: import abc


class AdjacentGraph:
    """Implementation adjacency-list Graph.
    Beware ids are between 1 and size.
    """
    def __init__(self, size):
        self.size = size
        self._nodes = [[0] * (size+1) for _ in range(size+1)]

    def set_adj_node(self, id_, adj_id):
        self._nodes[id_][adj_id] = 1

    def __iter__(self):
        self._id = 0
        return self

    def __next__(self):
        if self._id < self.size:
            self._id += 1
            return (self._id, self._nodes[self._id][1:])

        raise StopIteration()

    def dfs(self, handler=None):

        visited = []
        while len(visited) < self.size:
            for id_ in range(1, self.size+1):
                if id_ not in visited:
                    stack = [(id_, 0)]
                    break
            while len(stack) > 0:
                i, j = stack.pop()
                if j == 0:
                    if handler:
                        handler.visit(i)
                    visited.append(i)
                    yield i
                try:
                    j = self._nodes[i].index(1, j+1)
                    stack.append((i, j))
                    if j not in visited:
                        stack.append((j, 0))
                except ValueError:
                    if handler:
                        handler.leave(i)


class EventHandler(abc.ABC):
    @abc.abstractmethod
    def visit(self, i):
        pass

    @abc.abstractmethod
    def leave(self, i):
        pass


class Logger(EventHandler):
    def __init__(self, n):
        self.log = [(0, 0)] * n
        self.step = 0

    def visit(self, i):
        self.step += 1
        self.log[i-1] = (self.step, 0)

    def leave(self, i):
        self.step += 1
        (n, m) = self.log[i-1]
        self.log[i-1] = (n, self.step)

    def by_node(self):
        i = 1
        for discover, finish in self.log:
            yield (i, discover, finish)
            i += 1


def run():
    n = int(input())
    g = AdjacentGraph(n)
    log = Logger(n)

    for i in range(n):
        id_, c, *links = [int(x) for x in input().split()]
        for n in links:
            g.set_adj_node(id_, n)

    for i in g.dfs(log):
        pass

    for node in log.by_node():
        print(" ".join([str(i) for i in node]))


if __name__ == '__main__':
    run()

Python: N = int(input())
DG = {}
node_ls = []
is_visited = {}
#有効グラフをdictで管理することにする
for _ in range(N):
    tmp = input().split()
    node_id = tmp[0]
    node_ls.append(node_id)
    is_visited[node_id] = False
    adj_num = int(tmp[1])#各頂点の次元が入っている
    if adj_num != 0:
        DG[node_id] = tmp[2:]
    else:
        DG[node_id] = []


d = {}#最初に発見したときの時刻を記録
f = {}#隣接リストを調べ終えたときの完了時刻を記録
t = 1

def dfs(node):
    global t
    #終了条件
    if is_visited[node]:
        return

    is_visited[node] = True
    d[node] = t
    t += 1
    for no in DG[node]:
        dfs(no)
    f[node] = t
    t += 1

for node in node_ls:
    dfs(node)

#print(d,f)
for node in node_ls:
    print(node, d[node], f[node])

Python: n = int(input())

class Node:
    def __init__(self, idd, neighbors):
        self.idd = idd
        self.neighbors = neighbors
        self.foundAt = 0
        self.completeAt = 0
        
    def __repr__(self):
        return "{0} {1} {2}".format(self.idd, self.foundAt, self.completeAt)

Nodes = [None] * n
for i in range(n):
    row = [int(tt) for tt in input().split()]
    Nodes[row[0]-1] = Node(row[0], [ row[j + 2] for j in range(row[1])])
        
def depthSearch(Nodes):
    stack = [Nodes[0]]
    
    time = 2
    current = stack[-1]
    current.foundAt = 1
    while len(stack) > 0 or any([node.foundAt==0 for node in Nodes]):
        if(len(stack)==0):
            newStart = [node for node in Nodes if node.foundAt==0][0]
            newStart.foundAt = time
            stack.append(newStart)
            time += 1
        current = stack[-1]
        if(len(current.neighbors) > 0):
            next_n = Nodes[current.neighbors.pop(0)-1]
            if(next_n.foundAt != 0):
                continue
            next_n.foundAt = time
            stack.append(next_n)
        else:
            current.completeAt = time
            stack.pop(-1)
        time += 1
    return Nodes
Nodes = depthSearch(Nodes)
for node in Nodes:
    print(node)

Python: 
n=int(input())
used=[False for i in range(n)]
d=[0 for i in range(n)]
f=[0 for i in range(n)]
mat=[]
for i in range(n):
    tmp=list(map(int,input().split()))
    mat.append(tmp[2:])

t=1
def dfs(now):
    global t
    if used[now]:
        return
    else:
        used[now]=True
    d[now]=t
    t+=1
    for i in range(len(mat[now])):
        dfs(mat[now][i]-1)
    f[now]=t
    t+=1

for i in range(n):
    if used[i]==False:
        dfs(i)
for i in range(n):
    print(i+1,d[i],f[i])