Go: #include <bits/stdc++.h>
using namespace std;
static const int WHITE = 0;
static const int GRAY  = 1;
static const int BLACK = 2;
static const int N     = 100;

int n, tt;
vector<vector<int>> M(N, vector<int>(N));
vector<int> color(N), d(N), f(N);

void dfs_visit(int u) {
  color[u] = GRAY;
  d[u]     = ++tt;
  for (int v = 0; v < n; v++) {
    if (M[u][v] == 0) continue;
    if (color[v] == WHITE) { dfs_visit(v); }
  }
  color[u] = BLACK;
  f[u]     = ++tt;
}

void dfs() {
  tt = 0;

  for (int u = 0; u < n; u++) {
    if (color[u] == WHITE) dfs_visit(u);
  }
  for (int u = 0; u < n; u++) {
    printf("%d %d %d\n", u + 1, d[u], f[u]);
  }
}

int main() {
  int u, v, k;
  cin >> n;
  for (int i = 0; i < n; i++) {
    cin >> u >> k;
    u--;
    for (int j = 0; j < k; j++) {
      cin >> v;
      v--;
      M[u][v] = 1;
    }
  }

  dfs();
}

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])