Problem:
Rooted Trees

A graph G = (V, E) is a data structure where V is a finite set of vertices and E is a binary relation on V represented by a set of edges. Fig. 1 illustrates an example of a graph (or graphs).

Fig. 1

A free tree is a connnected, acyclic, undirected graph. A rooted tree is a free tree in which one of the vertices is distinguished from the others. A vertex of a rooted tree is called "node."

Your task is to write a program which reports the following information for each node u of a given rooted tree T:

node ID of u

parent of u

depth of u

node type (root, internal node or leaf)

a list of chidlren of u

If the last edge on the path from the root r of a tree T to a node x is (p, x), then p is the parent of x, and x is a child of p. The root is the only node in T with no parent.

A node with no children is an external node or leaf. A nonleaf node is an internal node

The number of children of a node x in a rooted tree T is called the degree of x.

The length of the path from the root r to a node x is the depth of x in T.

Here, the given tree consists of n nodes and evey node has a unique ID from 0 to n-1.

Fig. 2 shows an example of rooted trees where ID of each node is indicated by a number in a circle (node). The example corresponds to the first sample input.

Fig. 2

Input

The first line of the input includes an integer n, the number of nodes of the tree.

In the next n lines, the information of each node u is given in the following format:

id k c1 c2 ... ck

where id is the node ID of u, k is the degree of u, c1 ... ck are node IDs of 1st, ... kth child of u. If the node does not have a child, the k is 0.

Output

Print the information of each node in the following format ordered by IDs:

node id: parent = p, depth = d, type, [c1...ck]

p is ID of its parent. If the node does not have a parent, print -1.

d is depth of the node.

type is a type of nodes represented by a string (root, internal node or leaf). If the root can be considered as a leaf or an internal node, print root.

c1...ck is the list of children as a ordered tree.

Please follow the format presented in a sample output below.

Constraints

1 ≤ n ≤ 100000

Sample Input 1

13
0 3 1 4 10
1 2 2 3
2 0
3 0
4 3 5 6 7
5 0
6 0
7 2 8 9
8 0
9 0
10 2 11 12
11 0
12 0

Sample Output 1

node 0: parent = -1, depth = 0, root, [1, 4, 10]
node 1: parent = 0, depth = 1, internal node, [2, 3]
node 2: parent = 1, depth = 2, leaf, []
node 3: parent = 1, depth = 2, leaf, []
node 4: parent = 0, depth = 1, internal node, [5, 6, 7]
node 5: parent = 4, depth = 2, leaf, []
node 6: parent = 4, depth = 2, leaf, []
node 7: parent = 4, depth = 2, internal node, [8, 9]
node 8: parent = 7, depth = 3, leaf, []
node 9: parent = 7, depth = 3, leaf, []
node 10: parent = 0, depth = 1, internal node, [11, 12]
node 11: parent = 10, depth = 2, leaf, []
node 12: parent = 10, depth = 2, leaf, []

Sample Input 2

4
1 3 3 2 0
0 0
3 0
2 0

Sample Output 2

node 0: parent = 1, depth = 1, leaf, []
node 1: parent = -1, depth = 0, root, [3, 2, 0]
node 2: parent = 1, depth = 1, leaf, []
node 3: parent = 1, depth = 1, leaf, []

Note

You can use a left-child, right-sibling representation to implement a tree which has the following data:

the parent of u

the leftmost child of u

the immediate right sibling of u

Reference

Introduction to Algorithms, Thomas H. Cormen, Charles E. Leiserson, Ronald L. Rivest, and Clifford Stein. The MIT Press.

Solution in Python3 (judge verdict: Accepted)

# -*- coding: utf-8 -*-
#import sys
#sys.setrecursionlimit(1145141919)


N = int(input())
tree = {n:{"parent":-1, "left": -1, "right": -1} for n in range(N)} # left-child right-sibing
parent = set([n for n in range(N)])
for n in range(N):
    inp = [int(n) for n in input().split()]
    tree[inp[0]]["children"] = inp[2:]

    tree[inp[0]]["left"] = inp[2] if len(inp) > 2 else -1
    
    for ip in inp[2:]:
        tree[ip]["parent"] = inp[0]
    
    for i, ip in enumerate(inp[2:-1]):
        tree[inp[2+i]]["right"] = inp[3+i]
    parent = parent.difference(inp[2:])    

def set_depth(n, depth):
    print(depth)
    tree[n]["depth"] = depth
    if tree[n]["left"] != -1:
        set_depth(tree[n]["left"], depth+1)
    if tree[n]["right"] != -1:
        set_depth(tree[n]["right"], depth)

def get_depth(n):
    d = 0
    while tree[n]["parent"] != -1:
        d += 1
        n = tree[n]["parent"]
    return d

#set_depth(parent.pop(), 0)
        
for n in range(N):
    tree[n]["depth"] = get_depth(n)
    if tree[n]["parent"] == -1:
        tree[n]["type"] = "root"
    elif tree[n]["children"] != []:
        tree[n]["type"] = "internal node"
    else:
        tree[n]["type"] = "leaf"
        
    print("node {}: parent = {}, depth = {}, {}, {}"\
          .format(n, tree[n]["parent"], tree[n]["depth"], tree[n]["type"], tree[n]["children"]))