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: n = int(input())
adjc_list = [[] for _ in range(n)]
INF = 99999999999999999999
V = [ele for ele in range(n)]
S = []
d = [INF] * n
p = [ele for ele in range(n)]

for i in range(n):
    tmp = [int(ele) for ele in input().split()]
    for j in range(1, tmp[1]*2, 2):
        v = tmp[j+1]
        w = tmp[j+2]
        adjc_list[i].append([w, v])
    adjc_list[i].sort()


def my_dijkstra_solver():
    root = 0  # given
    # 1. 初期化
    d = [INF] * n
    d[root] = 0
    VS = V

    # 2. 以下の処理を、S = Vになるまで繰り返す
    while VS:
        # 2.1. V-S の中から、 d[u] が最小である頂点 u を選択する。
        u = VS[0]
        for i in VS:
            if d[i] < d[u]:
                u = i

        S.append(u)  # 2.2. u を S に追加する.

        # 2.3. u に隣接し, かつ V-S に属するすべての頂点 v に対する以下の値を更新する
        VS.remove(u)
        for w, v in adjc_list[u]:
            if v in VS:
                if d[u] + w < d[v]:
                    d[v] = d[u] + w
                    p[v] = u  # 親をどこかで使うのはわかるが一旦忘れよう

    for i, cost in enumerate(d):
        print(i, cost)


if __name__ == "__main__":
    my_dijkstra_solver()

Python: from sys import stdin
input = stdin.readline

infty = 100_000_00

def dijkstra(N):
    d[0] = 0
    p[0] = -1
    u = 0

    while True:
        mincost = infty
        for i in range(N):
            if color[i] != 2 and d[i] < mincost:
                mincost = d[i]
                u = i
        color[u] = 2
        if mincost == infty:
            break

        for v in range(N):
            if M[u][v] != infty and color[v] != 2 :
                if M[u][v] + d[u] < d[v]:
                    d[v] = M[u][v] + d[u]
                    p[v] = u
                    color[v] = 1

N = int(input())
M = [[infty] * N for i in range(N)]
d = [infty] * N #V-T間の重み最小辺の記録
p = [-1] * (N)
color = [0] * N

for i in range(N):
    a = list(map(int, input().split()))
    for k in range(1, len(a)//2):
        M[i][a[2*k]] = a[2*k+1]


dijkstra(N)

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

Python: import heapq

n = int(input())
d = [float("inf") for i in range(n)]
d[0] = 0
g = []
q = []

for i in range(n):
    heapq.heappush(q, (d[i], i))
    inp = list(map(int, input().split()))
    tmp = []
    for j in range(inp[1]):
        tmp.append(inp[2*j+2:2*j+4])
    g.append(tmp)

while q:
    q_pop = heapq.heappop(q)
    i = q_pop[1]
    if q_pop[0] > 100*100000:
        continue
    for node in g[i]:
        d_tmp = d[i] + node[1]
        if d_tmp < d[node[0]]:
            d[node[0]] = d_tmp
            heapq.heappush(q, (d_tmp, node[0]))

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

Python: from sys import stdin
from collections import deque

def read_graph(n):
    A = [ [-1]*(n+1) for _ in range(n+1) ]
    for _ in range(n):
        line = deque(stdin.readline().strip().split())
        u = line.popleft()
        line.popleft()
        for l, k in enumerate(line):
            if l % 2 == 0:
                v = k
            else:
                A[int(u)][int(v)] = int(k)
    return A

def dijkstra(n, A, s):
    color = [ 'WHITE' for i in range(n) ]
    d = [ float('inf') for i in range(n) ]
    d[s] = 0
    p = [-1] * n

    while True:
        mincost = float('inf')
        for i in range(n):
            if color[i] != 'BLACK' and d[i] < mincost:
                mincost = d[i]
                u = i

        if mincost == float('inf'):
            break

        color[u] = 'BLACK'

        for v in range(n):
            if color[v] != 'BLACK' and A[u][v] != -1:
                if d[u] + A[u][v] < d[v]:
                    d[v] = d[u] + A[u][v]
                    p[v] = u
                    color[v] = 'GRAY'

    return d

n = int(input())
A = read_graph(n)
for i, k in enumerate(dijkstra(n, A, 0)):
    print(i, k)

Python: import sys
import heapq
input=sys.stdin.readline
INF=2<<28

def dijkstra(G,start,n):#グラフ,初期頂点,頂点数

    dist=[INF]*n;dist[start]=0
    used=[False]*n;used[0]=True
    q=[]

    for v in G[start]:
        heapq.heappush(q,v)
    
    while len(q)>0:
        now=heapq.heappop(q)
        if used[now[1]]:
            continue
        v=now[1]
        dist[v]=now[0]
        used[v]=True

        for e in G[v]:
            if not used[e[1]]:
                heapq.heappush(q,(e[0]+dist[v],e[1]))

    return dist

N=int(input().rstrip())
g=[[] for _ in range(N)]
for _ in range(N):
    u,k,*c=map(int,input().split())
    for j in range(0,k*2,2):
        g[u].append((c[j+1],c[j]))

ans=dijkstra(g,0,N)
for i,x in enumerate(ans):
    print(i,x)

Python: import sys
input = sys.stdin.buffer.readline

import heapq

#点の数が10**5のオーダー以下で使える
#頂点sからの各頂点への最短距離を出力
def dijkstra(s, n, edge): #s:始点、n:頂点の数、edge:重み付き辺の配列（edge[i]:iから出る[重み、行き先]の配列)
    INF = 10**20
    d = [INF]*n # d[i]: sと点iとの距離
    used = [True]*n #Trueは未確定
    d[s] = 0 #初期条件
    used[s] = False # 初期条件
    edge_list = []
    for a, b in edge[s]:
        heapq.heappush(edge_list, a*(10**6)+b) #heapqの中に重みと辺の抱き合わせた情報を入れる
    while len(edge_list):
        min_edge = heapq.heappop(edge_list) #まだ使われていない頂点の中から最小の重みのものを取りだす
        if not used[min_edge%(10**6)]: # 確定していたらcontinue、確定していない時のみ以下の処理を行う
            continue
        v = min_edge%(10**6) #行き先の情報を復元
        d[v] = min_edge // (10**6) #重みの情報を復元し、sとvの最短距離d[v]を更新する
        used[v] = False
        for e in edge[v]:
            if used[e[1]]: #その行き先がまだ未確定の場合
                heapq.heappush(edge_list, (e[0]+d[v])*(10**6) + e[1])
        
    return d


n = int(input())

edge = [[] for _ in range(n)] # edge:重み付き辺の配列（edge[i]:iから出るtuple(重み、行き先)の配列)
for _ in range(n):
    x, y, *li = list(map(int, input().split()))
    for i in range(y):
        edge[x].append((li[2*i+1], li[2*i]))
        #edge[li[2*i]].append([li[2*i+1], x]) # 無向グラフのとき

d = dijkstra(0, n, edge)

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