Go: // ダイクストラのアルゴリズム
package main

import (
	"bufio"
	"fmt"
	"log"
	"math"
	"os"
	"strconv"
	"strings"
)

type color int

const (
	white color = iota // 未訪問
	mst                // MSTとして確定
)

// 頂点
type node struct {
	num     int         // 頂点の番号
	weights map[int]int // 重みMAP
	parent  *node       // MSTへの重み最小の親
	sum     int         // 始点からの距離
	color   color
}

func (p *node) getMinToMst() int {
	if p.parent == nil {
		return math.MaxInt32
	}
	return p.weights[p.parent.num]
}

func main() {
	scanner := bufio.NewScanner(os.Stdin)
	n := eGetInt(scanner)

	nodes := make([]*node, n)
	for i := 0; i < n; i++ {
		weights := eAtoi((strings.Fields(eGetline(scanner))))
		v := &node{weights[0], make(map[int]int, weights[1]), nil, 0, white}
		for j := 0; j < weights[1]; j++ {
			k := weights[j*2+2] // 相手の頂点名
			w := weights[j*2+3] // 重み
			v.weights[k] = w
		}
		nodes[i] = v
	}

	// 初回はnode[0]がMSTに入るように
	nodes[0].parent = nodes[0]

	for { // 全部チェックするまで

		// どの頂点を新たにMSTに取り込むか

		var minNode *node
		min := math.MaxInt32
		for _, v := range nodes {
			if v.color == mst {
				continue
			}
			if v.getMinToMst() < min {
				min = v.getMinToMst()
				minNode = v
			}
		}
		if minNode == nil {
			// すべて完了している.
			break
		}

		// MSTに追加する頂点決定
		minNode.color = mst
		// 自分の親の合計値と合算する
		minNode.sum = minNode.parent.sum + min

		// MSTに属していない頂点それぞれについて,MSTとの最小の重みの距離を加算
		for _, v := range nodes {
			if v.color == mst {
				continue
			}
			w, ok := v.weights[minNode.num]
			if !ok {
				// minNodeと接してない
				continue
			}

			if w < v.getMinToMst() {
				// minNodeへの距離がもっとも重みが少ないので親を変更
				v.parent = minNode
			}
		}
	}

	for i, v := range nodes {
		fmt.Printf("%d %d\n", i, v.sum)
	}
}

func eGetInt(scanner *bufio.Scanner) int {
	t := eAtoi(strings.Fields(eGetline(scanner)))
	return t[0]
}

func eGetline(p *bufio.Scanner) string {
	if !p.Scan() {
		if err := p.Err(); err != nil {
			log.Fatal(err.Error())
		}
		return ""
	}
	return p.Text()
}

func eAtoi(s []string) []int {
	ints := make([]int, len(s))
	var err error
	for i, e := range s {
		ints[i], err = strconv.Atoi(e)
		if err != nil {
			log.Fatal(err.Error())
		}
	}
	return ints
}

Python: from heapq import heappop, heappush

def dijkstra1(g, source):
    # O(ElogV)

    n = len(g)
    inf = float("inf") # 高速化のためにはfloat("inf")ではないほうがいい
    dist = [inf] * n
    dist[source] = 0
    q = [(0, source)]

    while q:
        cost, u = heappop(q)
        if dist[u] < cost:
            continue
        for c, v in V[u]:
            if dist[v] > dist[u] + c:
                dist[v] = dist[u] + c
                heappush(q, (dist[v], v))

    return dist

def dijkstra2(g, source):
    n = len(V)
    inf = float("inf") # 高速化のためにはfloat("inf")ではないほうがいい
    used = [False]*n
    dist = [inf]*n
    dist[0] = 0
    
    for _ in range(n):
        c1, u = min([(dist[i], i) for i in range(n) if not used[i]])
        used[u] = True
        for c2, v in V[u]:
            if v==u: continue
            dist[v] = min(dist[v], c1+c2)
    return dist


if __name__ == "__main__":
    n = int(input())
    V = [[] for _ in range(n)]

    for _ in range(n):
        u, k, *vc = map(int, input().split())
        for i in range(0, 2*k, 2):
            v, c = vc[i], vc[i+1]
            V[u].append((c, v))

    d = dijkstra2(V, 0)
    for i, j in enumerate(d):
        print(i, j)

Python: import heapq

def dijkstra(graph, weights, s):
    d = {u: float('inf') for u in graph}
    d[s] = 0
    queue = []
    heapq.heappush(queue, (0, s))
    while queue:
        w, u = heapq.heappop(queue)
        for v in graph[u]:
            d_temp = d[u] + weights[u, v]
            if d[v] > d_temp:
                d[v] = d_temp
                heapq.heappush(queue, (d_temp, v))
    return d

n = int(input())
graph, weights = {}, {}
for _ in range(n):
    line = input().split()
    neighbors = []
    for i in range(0, 2 * int(line[1]), 2):
        neighbors.append(line[2+i])
        weights[line[0], line[2+i]] = int(line[3+i])
    graph[line[0]] = neighbors

d = dijkstra(graph, weights, '0')

for i in range(n):
    print(i, d[str(i)])

Python: n=int(input())
M=[[-1]*n for _ in[0]*n]
for _ in[0]*n:
 e=list(map(int,input().split()))
 for i in range(e[1]):k=2*-~i;M[e[0]][e[k]]=e[k+1]
d=[0]+[1e6]*~-n
c=[1]*n
while 1:
 m,u=1e6,-1
 for i in range(n):
  if m>d[i]and c[i]:m,u=d[i],i
 if u<0:break
 c[u]=0
 for v in range(n):
  if c[v]and 1+M[u][v]and d[v]>d[u]+M[u][v]:
   d[v]=d[u]+M[u][v]
for i in range(n):print(i,d[i])

Python: import heapq

n=int(input())
u=[0]*n
k=[0]*n
v=[0]*n
z=[[] for _ in range(n) ]
for i in range(n):
  u[i],k[i],*v[i] = map(int,input().split())
  for j in range(0,len(v[i]),2):
    z[i].append([v[i][j],v[i][j+1]])
d=[float("inf")]*n 
e=[-1] *n #いったことなければ -1


def dijkstra(x):
  e[x]=0 #ブクマ
  d[x]=0
  q= [ (d[x],x) ] 
  
  while len(q)>0:
    #print(d)
    b,a = heapq.heappop(q)
    e[a]=0
    
    if d[a] < b:
      pass
    else:
      to_go = z[a]
      for s,t in to_go:
        if e[s]==0:
          pass
        else:
          if d[s] > d[a]+t :
            d[s] = d[a]+t
            heapq.heappush( q, (d[s],s) )

  
dijkstra(0)
for i in range(n):
  print(i,d[i])

Python: import queue
from sys import maxsize as INFTY
from collections import namedtuple
Q = namedtuple("Q", "u c")

n = int(input())
dic = {}

for _ in range(n):
    a = [int(x) for x in input().split()]
    a.reverse()

    u, k = a.pop(), a.pop()
    for _ in range(k):
        v, c = a.pop(), a.pop()
        dic[(u, v)] = c


def bfs(n, s):
    res = [INFTY] * n
    q = queue.Queue()
    q.put(Q(s, 0))

    while q.qsize() != 0:
        p = q.get()
        if res[p.u] <= p.c: continue
        res[p.u] = p.c

        for i in range(n):
            if i == p.u: continue
            v = (p.u, i)
            if v not in dic: continue
            q.put(Q(i, p.c + dic[v]))
    return res


ans = bfs(n, 0)
for i in range(n):
    print(i, ans[i])