Go: package main

import (
	"bufio"
	"fmt"
	"os"
	"strconv"
)

const (
	MAX_N      = 10000
	MAX_WEIGHT = 100000
)

type Edge struct {
	start  int
	end    int
	weight int
}

type ShortestInfo struct {
	edges    []Edge
	shortest int
}

type Neighbor struct {
	node   int
	weight int
}

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

	n, err := nextInt(sc)
	if err != nil {
		panic(err)
	}

	shortestList := make([]ShortestInfo, n)
	for i := 1; i < n; i++ {
		shortestList[i] = ShortestInfo{edges: []Edge{}, shortest: MAX_N*MAX_WEIGHT + 1}
	}

	adjacentMatrix, err := createAdjacentMatrix(n, sc)
	if err != nil {
		panic(err)
	}

	sssp([]int{0}, shortestList, adjacentMatrix)
	for _, v := range shortestList {
		fmt.Printf("%d %d\n", v.getEnd(), v.shortest)
	}
}

func (si ShortestInfo) getEnd() int {
	if len(si.edges) == 0 {
		return 0
	} else {
		return si.edges[len(si.edges)-1].end
	}
}

func createAdjacentMatrix(n int, sc *bufio.Scanner) ([][]Neighbor, error) {
	adjacentMatrix := make([][]Neighbor, n)
	for i := 0; i < n; i++ {
		id, err := nextInt(sc)
		if err != nil {
			return nil, err
		}
		adjacentMatrix[id] = []Neighbor{}
		vertexNum, err := nextInt(sc)
		if err != nil {
			return nil, err
		}
		for j := 0; j < vertexNum; j++ {
			v, err := nextInt(sc)
			if err != nil {
				return nil, err
			}
			c, err := nextInt(sc)
			if err != nil {
				return nil, err
			}
			adjacentMatrix[id] = append(adjacentMatrix[id], Neighbor{v, c})
		}
	}
	return adjacentMatrix, nil
}

func sssp(nodeStack []int, shortestList []ShortestInfo, adjacentMatrix [][]Neighbor) {
	for len(nodeStack) > 0 {
		currentNode := nodeStack[0]
		nodeStack = nodeStack[1:]
		currentShortest := getShortest(currentNode, shortestList)
		adjacents := findAdjacents(currentNode, adjacentMatrix)
		for i := 0; i < len(adjacents); i++ {
			adj := adjacents[i]
			if currentShortest.shortest+adj.weight < getShortest(adj.end, shortestList).shortest {
				setShortest(adj.end, adj, currentShortest, shortestList)
				nodeStack = append(nodeStack, adj.end)
			}
		}
	}
}

func getShortest(node int, shortestList []ShortestInfo) ShortestInfo {
	return shortestList[node]
}

func setShortest(node int, edge Edge, currentShortest ShortestInfo, shortestList []ShortestInfo) {
	newEdges := make([]Edge, len(currentShortest.edges)+1)
	for i := 0; i < len(newEdges)-1; i++ {
		newEdges[i] = currentShortest.edges[i]
	}
	newEdges[len(newEdges)-1] = edge
	shortestInfo := ShortestInfo{edges: newEdges, shortest: currentShortest.shortest + edge.weight}
	shortestList[node] = shortestInfo
}

func findAdjacents(currentNode int, adjacentMatrix [][]Neighbor) []Edge {
	adjacents := adjacentMatrix[currentNode]
	edges := []Edge{}
	for _, neighbor := range adjacents {
		edges = append(edges, Edge{start: currentNode, end: neighbor.node, weight: neighbor.weight})
	}
	return edges
}

func nextInt(sc *bufio.Scanner) (int, error) {
	sc.Scan()
	return strconv.Atoi(sc.Text())
}

Python: import sys
readline = sys.stdin.readline
from heapq import heapify, heappush, heappop
INF = float("inf")
def MAIN():
    n = int(input())
    adj = [[]] * n
    for _ in range(0, n):
        U = list(map(int, input().split()))
        adj[U[0]] = zip(U[2::2], U[3::2])
    def dijkstra():
        d = [0] + [INF] * (n - 1)
        hq = [(0, 0)]
        while hq:
            u = heappop(hq)[1]
            for v, c in adj[u]:
                alt = d[u] + c
                if d[v] > alt:
                    d[v] = alt
                    heappush(hq, (alt, v))
        print("\n".join(f"{i} {c}" for i, c in enumerate(d)))
    dijkstra()
MAIN()

Python: import heapq

class Pair:
    def __init__(self, num=None, wei=None):
        self.num = num
        self.wei = wei # weight
    def __str__(self):
        return str(self.num) + ' ' + str(self.wei)

def createAdjList():
    adjList = []
    for i in range(n):
        innerList = []
        u, k, *v = map(int, input().split())
        for j in range(0, k*2, 2):
            # [weight, num] (not [num, weigt])
            # Comparison of lists in Python is lexicographical -  the first non-equal pair determines the winner of the ordering
            newPair = [v[j+1],v[j]]
            innerList.append(newPair)
        adjList.append(innerList)
    return adjList

#TODO: write dijkstra
def dijkstra():
    d[0] = 0
    pq = []
    pq.append([0,0])
    heapq.heapify(pq)

    while len(pq) > 0:
        # cost が最小の node を選択
        uWei, uNum  = heapq.heappop(pq)

        status[uNum] = VISITED

        # uWei が最小コストでない場合は無視 (wight 更新前に push された、最短ではないルート)
        if d[uNum] < uWei:
            continue

        # u と v をつなぐ edge のうち最小の経路のコストの合計に更新
        for v in adjList[uNum]:
            vNum = v[1]
            vWei = v[0]
            if status[vNum] != VISITED and d[uNum] + vWei < d[vNum]:
                d[vNum] = d[uNum] + vWei
                status[vNum] = VISITING
                heapq.heappush(pq, [d[vNum], vNum])

import sys
# sys.stdin = open('input.txt')

n = int(input())
NOT_VISITED = 0 # WHITE
VISITING = 1 # GRAY
VISITED = 2 # BLACK
INFTY = 10**21

status = [NOT_VISITED] * n
d = [INFTY] * n
p = [-1] * n

adjList = createAdjList()
dijkstra()
for i in range(n):
    print(i, d[i])

Python: from heapq import*
I=float("inf")
def m():
 n=int(input())
 A=[]
 for _ in range(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: import queue

INFTY=1<<21

#ダイクストラ法
def dijkstra(n,EdgeMatrix,start):

    NodeList=queue.PriorityQueue() #探索対象の頂点
    Distance=[INFTY]*n #頂点0からの最短経路
    used=[False]*n #頂点の使用情報

    Distance[start]=0 #0から0までの距離は0
    used[start]=True #0から探索を始める
    LastNode=start #最新の頂点
    count=1 #つないだ頂点の数

    while count<n:
        for i in range(len(EdgeMatrix[LastNode])):
            #探索していない頂点へ距離の短い辺があればキューに追加
            Edge=EdgeMatrix[LastNode][i]
            if used[Edge[0]]==False and Distance[Edge[0]]>Distance[LastNode]+Edge[1]:
                    Distance[Edge[0]]=Distance[LastNode]+Edge[1]
                    NodeList.put([Distance[Edge[0]],Edge[0]])

        #最も近い探索していない頂点
        while True:
            minNode=NodeList.get()
            if used[minNode[1]]==False:
                break

        LastNode=minNode[1] #最新の頂点を更新
        used[minNode[1]]=True #頂点の使用情報を更新
        count+=1 #つないだ頂点の数を更新
    return Distance

#入力
n=int(input())

#辺の隣接行列
EdgeMatrix=[[] for i in range(n)]
for i in range(n):
    l=(list(map(int,input().split())))
    for j in range(l[1]):
        EdgeMatrix[l[0]].append([l[2*j+2],l[2*j+3]])

#頂点0からの最短経路
Distance=dijkstra(n,EdgeMatrix,0)

for node,distance in enumerate(Distance):
    print(node,distance)