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: import heapq
from collections import deque
from enum import Enum
import sys
import math
from _heapq import heappush, heappop

#------------------------------------------#

BIG_NUM = 2000000000
HUGE_NUM = 9999999999999999
MOD = 1000000007
EPS = 0.000000001

#------------------------------------------#

class Edge:
    def __init__(self,arg_to,arg_cost):
        self.to = arg_to
        self.cost = arg_cost

class Info:
    def __init__(self,arg_node_id,arg_sum_cost):
        self.node_id = arg_node_id
        self.sum_cost = arg_sum_cost

    def __lt__(self,arg):
        return self.sum_cost < arg.sum_cost


V = int(input())
min_dist = [BIG_NUM]*V
G = [[] for i in range(V)]

for loop in range(V):
    node_id,tmp_num,*table = list(map(int,input().split()))
    for i in range(0,len(table),2):
        G[node_id].append(Edge(table[i],table[i+1]))


min_dist[0] = 0
Q = []

heappush(Q, Info(0,0))

while len(Q) > 0:
    info = heappop(Q)
    if info.sum_cost > min_dist[info.node_id]:
        continue
    for edge in G[info.node_id]:
        if min_dist[edge.to] > info.sum_cost+edge.cost:
            min_dist[edge.to] = info.sum_cost+edge.cost
            heappush(Q, Info(edge.to,min_dist[edge.to]))


for i in range(V):
    print("%d %d"%(i,min_dist[i]))

Python: import heapq
from collections import deque
from enum import Enum
import sys
import math
from _heapq import heappush, heappop

#------------------------------------------#

BIG_NUM = 2000000000
HUGE_NUM = 9999999999999999
MOD = 1000000007
EPS = 0.000000001

#------------------------------------------#

class Edge:
    def __init__(self,arg_to,arg_cost):
        self.to = arg_to
        self.cost = arg_cost

class Info:
    def __init__(self,arg_node_id,arg_sum_cost):
        self.node_id = arg_node_id
        self.sum_cost = arg_sum_cost

    def __lt__(self,arg):
        return self.sum_cost < arg.sum_cost


V = int(input())
min_dist = [BIG_NUM]*V
G = [[] for i in range(V)]

for loop in range(V):
    node_id,tmp_num,*table = list(map(int,input().split()))
    for i in range(0,len(table),2):
        G[node_id].append(Edge(table[i],table[i+1]))


min_dist[0] = 0
Q = []

heappush(Q, Info(0,0))

while len(Q) > 0:
    info = heappop(Q)
    if info.sum_cost > min_dist[info.node_id]:
        continue
    for edge in G[info.node_id]:
        if min_dist[edge.to] > info.sum_cost+edge.cost:
            min_dist[edge.to] = info.sum_cost+edge.cost
            heappush(Q, Info(edge.to,min_dist[edge.to]))


for i in range(V):
    print("%d %d"%(i,min_dist[i]))

Python: INFTY = 1 << 21
WHITE = 0
GRAY = 1
BLACK = 2
 
n = int(input())
M = [list(map(int, input().split())) for i in range(n)]
for u in range(0, n):
    U = list(map(int, input().split()[2:]))
    for j in range(0, len(U), 2):
        M[u][U[j]] = U[j + 1]
d = [INFTY for i in range(n)]
color = [WHITE for i in range(n)]

def dijkstra():
    global M, d, color, n
    d[0] = 0
    color[0] = GRAY
    while(1):
        minv = INFTY
        u = -1
        for i in range(n):
            if (minv > d[i] and color[i] != BLACK):
                u = i
                minv = d[i]
        if (u == -1):
            break
        color[u] = BLACK
        for v in range(n):
            if (color[v] != BLACK and M[u][v] != INFTY):
                if (d[v] > d[u] + M[u][v]):
                    d[v] = d[u] + M[u][v]
                    color[v] = GRAY
    for i in range(n):
        print(str(i), (-1 if d[i] == INFTY else str(d[i])))
dijkstra()

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] if i != j else 0 for i in range(n)] for j 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 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)
d = warshall_floyd(n, m)
for (i, di) in enumerate(d[0]):
    print(i, di)

Python: n = int(input())

graph = [[] for i in range(n)]

for i in range(n):
    a = list(map(int, input().split()))
    for j in range(a[1]):
        graph[a[0]].append(a[2+j*2:4+j*2])  #[頂点, cost]

memo = [10**10 for i in range(n)]
memo[0] = 0

import heapq
q = []
heapq.heappush(q, (0, 0))   #(それまでのcost, 頂点)
while len(q) != 0:
    top = heapq.heappop(q)
    for g in graph[top[1]]:
        cost = top[0] + g[1]
        if memo[g[0]] > cost:
            memo[g[0]] = cost
            heapq.heappush(q, (cost, g[0]))

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