Go: package main

import (
	"bufio"
	"fmt"
	"io"
	"os"
	"strconv"
)

const (
	initialBufSize = 100000
	maxBufSize     = 1000000
)

var sc *bufio.Scanner

func initScanner(r io.Reader) *bufio.Scanner {
	buf := make([]byte, initialBufSize)

	sc := bufio.NewScanner(r)
	sc.Buffer(buf, maxBufSize)
	sc.Split(bufio.ScanWords) // bufio.ScanLines
	return sc
}

func main() {
	sc = initScanner(os.Stdin)
	resolve(parseProblem())
}

type graph struct {
	size  int
	edges [][]int
}

func parseProblem() *graph {
	n := scanInt(sc)
	g := &graph{
		size:  n,
		edges: make([][]int, n),
	}
	for i := 0; i < g.size; i++ {
		_ = scanInt(sc)
		k := scanInt(sc)
		g.edges[i] = make([]int, k)
		for j := 0; j < k; j++ {
			g.edges[i][j] = scanInt(sc) - 1
		}
	}
	return g
}

func resolve(g *graph) {
	ds := make([]int, g.size)
	fs := make([]int, g.size)
	time := 0
	for i := 0; i < len(ds); i++ {
		if ds[i] == 0 {
			time++
			time = _dfs(ds, fs, time, g, i)
		}
	}
	for i := 0; i < len(ds); i++ {
		fmt.Println(i+1, ds[i], fs[i])
	}
	return
}

func _dfs(ds, fs []int, time int, g *graph, idx int) int {
	ds[idx] = time
	for _, next := range g.edges[idx] {
		if ds[next] > 0 {
			continue
		}
		time++
		time = _dfs(ds, fs, time, g, next)
	}
	time++
	fs[idx] = time
	return time
}

// snip-scan-funcs
func scanInt(sc *bufio.Scanner) int {
	sc.Scan()
	i, _ := strconv.Atoi(sc.Text())
	return int(i)
}
func scanString(sc *bufio.Scanner) string {
	sc.Scan()
	return sc.Text()
}

Python: def d(u):
 global t
 C[u]=1;t+=1;D[u]=t
 for v in range(N):
  if M[u][v]and C[v]==0:d(v)
 C[u]=2;t+=1;F[u]=t
N=int(input())
M=[[0]*N for _ in[0]*N]
for e in[list(map(int,input().split()))for _ in[0]*N]:
 for v in e[2:]:M[e[0]-1][v-1]=1
C,D,F=[0]*N,[0]*N,[0]*N
t=0
for i in range(N):
 if C[i]==0:d(i)
for i in range(N):print(i+1,D[i],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):
        stack = [(1, 0)]
        visited = []
        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: #!/usr/bin/env python
# -*- coding: utf-8 -*-

import sys

UNVISITED, VISITED_IN_STACK, POPPED_OUT = 0, 1, 2


def generate_adj_matrix(v_info):
    for v_detail in v_info:
        v_adj_list = v_detail[2:]
        assert len(v_adj_list) == int(v_detail[1])
        for each in v_adj_list:
            init_adj_matrix[int(v_detail[0]) - 1][int(each) - 1] = 1
    return init_adj_matrix


def graph_dfs(v_init):
    global time

    # init the first node of overall graph iterations(times >= 1)
    vertex_visit_stack.append(v_init)
    vertex_status_list[v_init] = VISITED_IN_STACK
    vertex_d_time[v_init] += time
    # init end

    while len(vertex_visit_stack) > 1:
        current_vertex = vertex_visit_stack[-1]
        next_vertex = get_adj_vertices(vertex=current_vertex)

        if next_vertex:
            if vertex_status_list[next_vertex] is UNVISITED:
                vertex_status_list[next_vertex] = VISITED_IN_STACK
                time += 1
                vertex_d_time[next_vertex] += time
                vertex_visit_stack.append(next_vertex)
        else:
            vertex_visit_stack.pop()
            vertex_status_list[current_vertex] = POPPED_OUT
            time += 1
            vertex_f_time[current_vertex] += time

    return None


def get_adj_vertices(vertex):
    index = int(vertex) - 1
    for j in range(vertex_num):
        if adj_matrix[index][j]:
            adj_matrix[index][j] = 0
            return j + 1
    return None


def dfs_start():
    global time
    for i in range(vertex_num):
        if vertex_status_list[i + 1] == UNVISITED:
            # print('round', i + 1)
            graph_dfs(v_init=i + 1)
            time += 1


if __name__ == '__main__':
    _input = sys.stdin.readlines()
    vertex_num = int(_input[0])
    vertex_info = list(map(lambda x: x.split(), _input[1:]))
    init_adj_matrix = [[0] * vertex_num for _ in range(vertex_num)]
    # assert len(vertex_info) == vertex_num

    # config length = (vertex_num + 1)
    vertex_visit_stack = [-1]
    vertex_status_list = [UNVISITED] * vertex_num
    vertex_status_list.insert(0, -1)
    vertex_d_time, vertex_f_time = ([0] * (vertex_num + 1) for _ in range(2))

    adj_matrix = generate_adj_matrix(vertex_info)
    # timing start from 1
    time = 1
    dfs_start()
    for k in range(vertex_num):
        print(k + 1, vertex_d_time[k + 1], vertex_f_time[k + 1])

Python: def dfs(i,a,d,f,t):
    if d[i-1]:
        return t
    d[i-1] = t
    t += 1
    for j in a[i-1]:
        t = dfs(j,a,d,f,t)
    f[i-1] = t
    t += 1
    return t
 
if __name__ == "__main__":
    n = int(input())
    a = []
    for i in range(n):
        a.append(list(map(int,input().split()))[2:])
    d = [0]*n
    f = [0]*n
    t = 1
    for i in range(n):
        if d[i] == 0:
            t = dfs(i+1,a,d,f,t)
    for i in range(n):
        print(i+1,d[i],f[i])

Python: """Depth First Search."""

n = int(input())

adj = [None]
for i in range(n):
    adj_i = list(map(int, input().split()[2:]))
    adj.append(adj_i)

# searched or not, number of vertex, discovery time and finishing time
sndf = [None]
for i in range(1, n + 1):
    sndf.append([False, i])

path = []

def dfs(u):
    time = 0
    path.append(u)
    time += 1
    sndf[u].append(time)

    while path:
        u = path[-1]
        if adj[u]:
            v = adj[u].pop(0)
            if not sndf[v][0]:
                time += 1
                sndf[v].append(time)
                path.append(v)
        else:
            path.pop()
            sndf[u][0] = True
            time += 1
            sndf[u].append(time)


dfs(1)

for x in sndf[1:]:
    print(*x[1:])