Go: package main

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

type Node struct {
	Id int
	Dis int
}

type PriorityQueue []*Node

func (pq PriorityQueue) Len() int { return len(pq) }

func (pq PriorityQueue) Less(i, j int) bool {
	return pq[i].Dis < pq[j].Dis
}

func (pq PriorityQueue) Swap(i, j int) {
	pq[i], pq[j] = pq[j], pq[i]
}

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

func (pq *PriorityQueue) Pop() interface{} {
	n := len(*pq)
	pop := (*pq)[n-1]
	*pq = (*pq)[0:n-1]
	return pop
}

func main() {
	var n int
	fmt.Scan(&n)

	sc := bufio.NewScanner(os.Stdin)
	sc.Split(bufio.ScanWords)

	g := make([][]int, n)
	c := make([][]int, n)
	pq := make(PriorityQueue, 0, n)
	d := make([]int, n)
	for i := 0; i < n; i++ {
		sc.Scan()
		u, _ := strconv.Atoi(sc.Text())
		sc.Scan()
		k, _ := strconv.Atoi(sc.Text())
		g[u] = make([]int, k)
		c[u] = make([]int, k)
		for j := 0; j < k; j++ {
			sc.Scan()
			g[u][j], _ = strconv.Atoi(sc.Text())
			sc.Scan()
			c[u][j], _ = strconv.Atoi(sc.Text())
		}

		if u == 0 {
			d[u] = 0
		} else {
			d[u] = 1 << 30
		}
		pq.Push(&Node{u, d[u]})
	}
	heap.Init(&pq)

	for pq.Len() > 0 {
		node := heap.Pop(&pq).(*Node)
		for i := 0; i < len(g[node.Id]); i++ {
			nextId := g[node.Id][i]
			nextDis := node.Dis + c[node.Id][i]
			if nextDis < d[nextId] {
				d[nextId] = nextDis
				heap.Push(&pq, &Node{nextId, nextDis})
			}
		}
	}

	wr := bufio.NewWriter(os.Stdout)
	for i := 0; i < n; i++ {
		wr.WriteString(strconv.Itoa(i))
		wr.WriteString(" ")
		wr.WriteString(strconv.Itoa(d[i]))
		wr.WriteString("\n")
	}
	wr.Flush()
}

Python: import sys
readline = sys.stdin.readline
from heapq import heapify, heappush, heappop
INF = float("inf")
def MAIN():
    n = int(input())
    G = [[i, INF] for i in range(n)]
    G[0][1] = 0
    m = {}
    for _ in range(n):
        A = list(map(int, readline().split()))
        m[A[0]] = {}
        for i in range(2, len(A), 2):
            m[A[0]][A[i]] = A[i + 1]
    dp = [(0, 0)]
    while dp:
        cost, u = heappop(dp)
        for v, c in m[u].items():
            if G[v][1] > G[u][1] + c:
                G[v][1] = G[u][1] + c
                heappush(dp, (G[v][1], v))
    print("\n".join(" ".join(map(str, a)) for a in G))
MAIN()

Python: from heapq import*
def m():
 n=int(input())
 A=[]
 for _ in[0]*n:
  e=list(map(int,input().split()))
  A+=[zip(e[2::2],e[3::2])]
 d=[0]+[float('inf')]*n
 H=[(0,0)]
 while H:
  u=heappop(H)[1]
  for v,c in A[u]:
   t=d[u]+c
   if d[v]>t:
    d[v]=t
    heappush(H,(t,v))
 print('\n'.join(f'{i} {d[i]}'for i in range(n)))
m()

Python: from heapq import*
I=float("inf")
def m():
 n=int(input())
 A=[]
 for _ in[0]*n:
  e=list(map(int,input().split()))
  A+=[zip(e[2::2],e[3::2])]
 d=[0]+[I]*n
 H=[(0,0)]
 while H:
  u=heappop(H)[1]
  for v,c in A[u]:
   t=d[u]+c
   if d[v]>t:
    d[v]=t
    heappush(H,(t,v))
 print('\n'.join(f'{i} {d[i]}'for i in range(n)))
m()

Python: from heapq import heapify, heappop, heappush, heappushpop


class PriorityQueue:
    def __init__(self, heap):
        '''
        heap ... list
        '''
        self.heap = heap
        heapify(self.heap)

    def push(self, item):
        heappush(self.heap, item)

    def pop(self):
        return heappop(self.heap)

    def pushpop(self, item):
        return heappushpop(self.heap, item)

    def __call__(self):
        return self.heap

    def __len__(self):
        return len(self.heap)


def dijkstra(graph, s, N):
    '''
    graph...隣接リスト形式 リスト内要素は(ノード, エッジ長)
    s...始点ノード
    N...頂点数

    return
    ----------
    D ... 各点までの最短距離
    P ... 最短経路木における親
    '''
    pq = PriorityQueue([])
    P = [None] * N
    D = [float('inf')] * N
    D[s] = 0
    pq.push((D[s], s))  # (最短距離, 次のノード)
    while pq:
        d, v = pq.pop()
        if D[v] < d:  # この辺を扱っても最短距離にならない
            continue  # is_visitedなくてもこれを使うことで最小のものを再び探索するのを防げる
        for to, cost in graph[v]:
            if D[to] > D[v] + cost:  # v周りにおける最短経路の候補の更新
                D[to] = D[v] + cost
                pq.push((D[to], to))
                P[to] = v
    return D, P

# load datas
N = int(input())
adj = [[] for _ in range(N)]  # (node_id, 隣接要素, 隣接nodeidとコスト)の順で格納する
'''
例
[
(0について) [(1,1235), (4,65)]
(1について) [(20,6000)]
...
]
'''
for _ in range(N):
    tmp = list(map(int, input().split()))
    if tmp[1] != 0:
        node = tmp[0]
        for i in range(2, 2 + tmp[1] * 2, 2):
            adj[node].append((tmp[i], tmp[i + 1]))

D, P = dijkstra(adj, 0,N)

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

Python: # coding: utf-8

import heapq

def dj(adjm, start):
    n = len(adjm)
    d = [float("inf")] * n
    d[start] = 0
    q = []
    heapq.heappush(q, (0, start))

    while(q):
        td, v = heapq.heappop(q)
        for k in adjm[v].keys():
            nd = td + adjm[v][k]
            if d[k] > nd:
                d[k] = nd
                heapq.heappush(q, (nd, k))
    return d


def main():
    n = int(input())
    # 隣接行列
    adjm = [{} for _ in range(n)]
    for i in range(n):
        vdata = list(map(int, input().split()))
        for j in range(vdata[1]):
            v, c = vdata[j * 2 + 2], vdata[j * 2 + 3]
            adjm[i][v] = c
    ans = dj(adjm, 0)
    for i, d in enumerate(ans):
        print(i, d)


if __name__ == "__main__":
    main()

Python: from collections import defaultdict
import heapq
v_num = int(input())
connect = defaultdict(list)

for _ in range(v_num):
    que = [int(n) for n in input().split(" ")]
    connect[que[0]] = [[v, w] for v, w in zip(que[2:len(que):2], que[3:len(que):2])]
    # weight_edge[que[0]] = {k:v for k, v in zip(que[2:len(que):2], que[3:len(que):2])}
queue = []
heapq.heapify(queue)
heapq.heappush(queue, [0, 0])
distance = [-1 for n in range(v_num)]
went = 0
visited = set()
while went < v_num:
    q = heapq.heappop(queue)
    weight, here = q
    if here in visited:
        continue
    visited |= {here}
    went += 1
    distance[here] = weight
    for conn in connect[here]:
        if conn[0] not in visited:
            heapq.heappush(queue, [weight + conn[1], conn[0]])
for i in range(v_num):
    print(i, distance[i])