Go: package main

import (
	"bufio"
	"container/heap"
	"fmt"
	"os"
	"strconv"
)

// I/O
type Scanner struct {
	sc *bufio.Scanner
}

func NewScanner() *Scanner {
	sc := bufio.NewScanner(os.Stdin)
	sc.Split(bufio.ScanWords)
	sc.Buffer(make([]byte, 1024), int(1e+9))
	return &Scanner{sc}
}

func (s *Scanner) nextStr() string {
	s.sc.Scan()
	return s.sc.Text()
}

func (s *Scanner) nextInt() int {
	i, e := strconv.Atoi(s.nextStr())
	if e != nil {
		panic(e)
	}
	return i
}

func (s *Scanner) nextFloat() float64 {
	f, e := strconv.ParseFloat(s.nextStr(), 64)
	if e != nil {
		panic(e)
	}
	return f
}

func (s *Scanner) nextRuneSlice() []rune {
	return []rune(s.nextStr())
}

func (s *Scanner) nextIntSlice(n int) []int {
	res := make([]int, n)
	for i := 0; i < n; i++ {
		res[i] = s.nextInt()
	}
	return res
}

func (s *Scanner) nextFloatSlice(n int) []float64 {
	res := make([]float64, n)
	for i := 0; i < n; i++ {
		res[i] = s.nextFloat()
	}
	return res
}

// Arithmetic
func max(nums ...int) int {
	m := nums[0]
	for _, i := range nums {
		if m < i {
			m = i
		}
	}
	return m
}

func min(nums ...int) int {
	m := nums[0]
	for _, i := range nums {
		if m > i {
			m = i
		}
	}
	return m
}

func abs(x int) int {
	if x > 0 {
		return x
	}
	return -x
}

func pow(x, y int) int {
	res := 1
	for i := 0; i < y; i++ {
		res *= x
	}
	return res
}

func ceil(a, b int) int {
	if a%b == 0 {
		return a / b
	} else {
		return a/b + 1
	}
}

// Sort
type RuneSlice []rune

func (a RuneSlice) Len() int           { return len(a) }
func (a RuneSlice) Less(i, j int) bool { return a[i] < a[j] }
func (a RuneSlice) Swap(i, j int)      { a[i], a[j] = a[j], a[i] }

// Main
const INF = 1 << 60

type Edge struct {
	to, cost int
}

type Node struct {
	id, cost int
}

type PQ []Node

func (pq PQ) Len() int           { return len(pq) }
func (pq PQ) Less(i, j int) bool { return pq[i].cost < pq[j].cost }
func (pq PQ) Swap(i, j int)      { pq[i], pq[j] = pq[j], pq[i] }

func (pq *PQ) Push(x interface{}) {
	*pq = append(*pq, x.(Node))
}

func (pq *PQ) Pop() interface{} {
	old := *pq
	n := len(old)
	x := old[n-1]
	*pq = old[0 : n-1]
	return x
}

func main() {
	sc := NewScanner()
	wtr := bufio.NewWriter(os.Stdout)
	N := sc.nextInt()
	E := make([][]Edge, N)
	for i := 0; i < N; i++ {
		id, k := sc.nextInt(), sc.nextInt()
		E[id] = make([]Edge, k)
		for j := 0; j < k; j++ {
			to, cost := sc.nextInt(), sc.nextInt()
			E[id][j] = Edge{to, cost}
		}
	}

	d := make([]int, N)
	for i := 0; i < N; i++ {
		d[i] = INF
	}
	done := make([]bool, N)
	pq := &PQ{}
	heap.Init(pq)
	d[0] = 0
	heap.Push(pq, Node{0, 0})
	for pq.Len() > 0 {
		cur := heap.Pop(pq).(Node).id
		if done[cur] {
			continue
		}
		done[cur] = true
		for i := 0; i < len(E[cur]); i++ {
			to, cost := E[cur][i].to, E[cur][i].cost+d[cur]
			if !done[to] && cost < d[to] {
				d[to] = cost
				heap.Push(pq, Node{to, cost})
			}
		}
	}

	for i := 0; i < N; i++ {
		fmt.Fprintln(wtr, i, d[i])
	}
	wtr.Flush()
}

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])

Python: from queue import PriorityQueue
 
INF=1<<30
n=int(input())
adj=[[]for i in range(n+1)]
maxx = 10010

def dijkstra():
    global adj
    PQ=PriorityQueue()
      
    d=[INF for i in range(n)]
    #p=[-1 for i in range(n)]
    flag=[0 for i in range(n)]
 
    d[0] = 0;
    PQ.put((0, 0))
    while (not PQ.empty()):
        f = PQ.get()
        u = f[1]
        
        # 标记已经加入S
        flag[u] = 1

        #如果不是最小最短路径则忽略
        #if (d[u] >f[0] ):
            #continue
        lens = len(adj[u])
        for j in range(lens):
            v = adj[u][j][0]
            if (flag[v] == 0 and d[v] > d[u] + adj[u][j][1]):
                d[v] = d[u] + adj[u][j][1]
                PQ.put((d[v], v));
            

    for i in range(n):
        if d[i]==INF:
            print("%d %d"%(i, -1))
        else:
            print("%d %d"%(i, d[i]))
        

for i in range(n):
    s=[int(x) for x in input().split()]
    u=s[0]
    k=s[1]
    for j in range(k):
        adj[u].append((s[j*2+2],s[2*j+3]))
 
dijkstra()

Python: import sys
from collections import defaultdict
from typing import Dict


def find_shortest_distance(start_vertex: int, n: int,  relations: Dict[int, Dict]) -> Dict[int, int]:
    unreached_vertices = [x for x in range(1, n)]
    distance = {x: sys.maxsize for x in range(n)}
    distance[start_vertex] = 0
    vtx = None
    tmp_distance = [sys.maxsize for x in range(n)]
    for k, v in relations[start_vertex].items():
        tmp_distance[k] = v

    while True:
        min_dist = sys.maxsize
        for i in unreached_vertices:
            dist = tmp_distance[i]
            if dist < min_dist:
                min_dist = dist
                vtx = i
        if min_dist == sys.maxsize:
            break
        unreached_vertices.remove(vtx)
        distance[vtx] = min_dist
        neighbor_vertices = relations[vtx]
        for n_vtx, n_dist in neighbor_vertices.items():
            n_dist_from_start = distance[vtx] + n_dist
            tmp_dist = tmp_distance[n_vtx]
            if tmp_dist == sys.maxsize:
                tmp_distance[n_vtx] = n_dist_from_start
            else:
                if n_dist_from_start < tmp_dist:
                    tmp_distance[n_vtx] = n_dist_from_start
    return distance


def main():
    n = int(input())
    relations = defaultdict(dict)

    lines = sys.stdin.readlines()
    for i in range(n):
        u, k, *vtx_wght = map(int, lines[i].split())
        for v_i in range(k):
            relations[u][vtx_wght[2*v_i]] = vtx_wght[2*v_i+1]

    dist_from_0 = find_shortest_distance(0, n, relations)

    answers = [None] * n
    sorted_dist = sorted(dist_from_0.items(), key=lambda x: x[0])
    for i in range(n):
        answers[i] = f"{sorted_dist[i][0]} {sorted_dist[i][1]}"
    [print(ans) for ans in answers]
    return


main()

Python: #!/usr/bin/python3
from heapq import heappop, heappush
n = int(input())
inf = 100 * 100000

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

for i in range(n):
    L = list(map(int, input().split()))
    u = L[0]
    k = L[1]
    v = L[2::2]
    c = L[3::2]
    for j in range(k):
        M[u].append((v[j], c[j]))
result = [0] * n
S = set()
V = set(range(n))
S.add(0)
d = []
for m in M[0]:
    heappush(d, (m[1], m[0]))
T = V - S

while len(T) != 0:
    c, v = heappop(d)
    while v in S:
        c, v = heappop(d)
    result[v] = c
    S.add(v)
    T.remove(v)
    for m in M[v]:
        if m[0] in T:
            heappush(d, (result[v] + m[1], m[0]))

for i, v in enumerate(result):
    print(i, v)