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 collections import namedtuple
import heapq

Edge = namedtuple('Edge', ('fr', 'to', 'cost'))
inf = int(1e9)


def bellman_ford(n, start, edges):
    dists = [inf for _ in range(n)]
    dists[start] = 0
    while True:
        updated = False
        for e in edges:
            if dists[e.fr] != inf and dists[e.fr] + e.cost < dists[e.to]:
                updated = True
                dists[e.to] = dists[e.fr] + e.cost

        if not updated:
            break

    return dists


def dijkstra(n, costs):
    dists = [inf for _ in range(n)]
    dists[0] = 0

    queue = []
    for (i, d) in enumerate(dists):
        heapq.heappush(queue, (d, i))

    while len(queue) > 0:
        d, i = heapq.heappop(queue)
        if d > dists[i]:
            continue

        for v in range(n):
            if v == i or costs[i][v] == inf:
                continue

            if dists[i] + costs[i][v] < dists[v]:
                dists[v] = dists[i] + costs[i][v]
                heapq.heappush(queue, (dists[v], v))

    return dists


def warshall_floyd(n, costs):
    dists = [[costs[i][j] for j in range(n)] for i in range(n)]

    for k in range(n):
        for i in range(n):
            for j in range(n):
                dists[i][j] = min(dists[i][j], dists[i][k] + dists[k][j])

    return dists


n = int(input())

m = [[inf if i != j else 0 for i in range(n)] for j in range(n)]
es = []
for i in range(n):
    fs = list(map(int, input().split()))
    ne = fs[1]
    for j in range(ne):
        v = fs[2+2*j]
        c = fs[2+2*j+1]
        m[i][v] = c
        es.append(Edge(i, v, c))


# d = bellman_ford(n, 0, es)
# d = dijkstra(n, m)
d = warshall_floyd(n, m)
for (i, di) in enumerate(d[0]):
    print(i, di)

Python: rootList = [-1 for i in range(n)]
parent = [0 for i in range(n)]
lenList = [0 for i in range(n)]

def getRoot(x):
    r = rootList[x]
    if r < 0:
        rootList[x] = x
    elif r != x:
        rootList[x] = getRoot(r)
    return rootList[x]


edgeList.sort(key=lambda x: x[0])
flag = True
while flag:
    flag = False
    for e in edgeList:    # weight:e[0], e[1]->e[2]
        if e[2] == 0:
            continue
        x = getRoot(e[1])
        y = getRoot(e[2])
        if x == 0 != y:
            parent[e[2]] = e[1]
            lenList[e[2]] += lenList[e[1]] + e[0]
            rootList[y] = 0
            flag = True
            break

for i, j in zip(range(n), lenList):
    print(i, j)

Python: n = int(input())
from collections import defaultdict
G = defaultdict(list)
for i in range(n):
    i = [int(i) for i in input().split()]
    k = i[1]
    G[i[0]] = list(zip(i[2::2],i[3::2]))

def mind(Q, d):
    c = float('inf')
    ret = 0
    for i, j in enumerate(d):
        if c > j and i in Q:
            c = j
            ret = i
    return ret

def dijkstra(G):
    d = [0] + [float('inf')] * (n - 1)
    Q = set(range(n))
    while len(Q) != 0:
        u = mind(Q, d)
        Q = Q - set([u])
        for v, c in G[u]:
            if d[v] > d[u] + c:
                d[v] = d[u] + c
    return d

for i,j in enumerate(dijkstra(G)):
    print(i, j)

Python: from collections import namedtuple

Edge = namedtuple('Edge', ('fr', 'to', 'cost'))
inf = 1e9


def bellman_ford(n, start, edges):
    dists = [inf for _ in range(n)]
    dists[start] = 0
    while True:
        updated = False
        for e in edges:
            if dists[e.fr] != inf and dists[e.fr] + e.cost < dists[e.to]:
                updated = True
                dists[e.to] = dists[e.fr] + e.cost

        if not updated:
            break

    return dists


def dijkstra(n, costs):
    dists = [inf for _ in range(n)]
    dists[0] = 0
    determined = [False for _ in range(n)]

    while True:
        v, min_d = -1, inf
        for i in range(n):
            if determined[i]:
                continue
            if dists[i] < min_d:
                v, min_d = i, dists[i]

        if v == -1:
            break

        determined[v] = True

        for i in range(n):
            if determined[i] or costs[v][i] == -1:
                continue

            dists[i] = min(dists[i], dists[v] + costs[v][i])

    return dists


n = int(input())

m = [[-1 for _ in range(n)] for _ in range(n)]
es = []
for i in range(n):
    fs = list(map(int, input().split()))
    ne = fs[1]
    for j in range(ne):
        v = fs[2+2*j]
        c = fs[2+2*j+1]
        m[i][v] = c
        es.append(Edge(i, v, c))


# d = bellman_ford(n, 0, es)
d = dijkstra(n, m)
for (i, di) in enumerate(d):
    print(i, di)