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 heapq
N=int(input())
rinsetu=[[] for j in range(N)]
d=[1000000]*(N)

color=["white"]*N
for i in range(N):
    a=list(map(int,input().split()))
    for j in range(a[1]):
        j1=j*2+2
        j2=j*2+3
        rinsetu[i].append([a[j1],a[j2]])
def hunterhunter():
    d[0]=0
    heap=[]
    heapq.heapify(heap)
    heapq.heappush(heap,[0,0])
    while(heap):
        mincost=heapq.heappop(heap)
        u=mincost[1]
        color[u]="black"
        for  i in rinsetu[u]:
            if color[i[0]]=="white":
                if i[1]+d[u]<d[i[0]]:
                    d[i[0]]=i[1]+d[u]
                    heapq.heappush(heap,[d[i[0]],i[0]])
hunterhunter()
for i,cost in enumerate(d):
    print(i,cost)

Python: n = int(input())

adj = [[100001 for j in range(n)] for i in range(n)]

for u in range(n):
    x = list(map(int, input().split()))
    for v, c in zip(x[2::2], x[3::2]):
        adj[u][v] = c

unvisited = [v for v in range(n)]

distance = [9900001] * n


def dijkstra(s):
    distance[s] = 0

    while True:
        mincost = 9900001
        for i in unvisited:
            if distance[i] < mincost:
                mincost = distance[i]
                u = i

        if mincost == 9900001:
            break

        unvisited.remove(u)

        for v in unvisited:
            weight_uv = adj[u][v]
            if weight_uv != 100001:
                t_d = distance[u] + weight_uv
                if t_d < distance[v]:
                    distance[v] = t_d



dijkstra(0)

for v, d in enumerate(distance):
    print(v, d)

Python: import sys

f_i = sys.stdin

n = int(f_i.readline())

adj = [list(map(int, x.split()[2:])) for x in f_i]

unvisited = [v for v in range(n)]

distance = [999900001] * n
distance[0] = 0

class VCost:
    def __init__(self, v, cost):
        self.v = v
        self.cost = cost
    def __lt__(self, other):
        return self.cost < other.cost

import heapq

vcost = [VCost(0, 0)]

def dijkstra():
    while vcost:
        uc = heapq.heappop(vcost)

        if uc.cost > distance[uc.v]:
            continue
        
        unvisited.remove(uc.v)
        
        for v, c in zip(adj[uc.v][::2], adj[uc.v][1::2]):
            if v in unvisited:
                t_cost = uc.cost + c
                if t_cost < distance[v]:
                    distance[v] = t_cost
                    heapq.heappush(vcost, VCost(v, t_cost))



dijkstra()

for v, d in enumerate(distance):
    print(v, d)

Python: import sys

f_i = sys.stdin

n = int(f_i.readline())

adj = [[]] * n
for x in f_i:
    x = list(map(int, x.split()))
    adj[x[0]] = [c_v for c_v in zip(x[3::2], x[2::2])]

import heapq

def dijkstra():
    PQ = [(0, 0)]
    isVisited = [False] * n
    distance = [999900001] * n

    distance[0] = 0
    
    while PQ:
        uc, u = heapq.heappop(PQ)

        if uc > distance[u]:
            isVisited[u] = True
        
            for vc, v in adj[u]:
                if isVisited[v] == False:
                    t_cost = distance[u] + vc
                    if t_cost < distance[v]:
                        distance[v] = t_cost
                        heapq.heappush(PQ, (t_cost, v))

    for v, d in enumerate(distance):
        print(v, d)


dijkstra()

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

class Graph:
    def __init__(self,V,E):
        self.V = V
        self.E = E

    def dijkstra(self,st):
        INF = 10**9+1
        D = [INF for i in range(len(self.V))]
        #D[i]:頂点iまでの距離
        D[st] = 0
        Q = [[0,st]]
        Used = set()
        #既に最短距離が確定した頂点の集合
        
        while len(Used) < len(self.V):
            p = heappop(Q)
            p_dist,p_ind = p[0],p[1]
            for e in self.E[p_ind]:
                to,cost = e[0],e[1]
                if to not in Used:
                    if D[to] > D[p_ind] + cost:
                        D[to] = D[p_ind] + cost
                        heappush(Q,[D[to],to])
            Used.add(p_ind)

        return D

def main():
    n = int(input())
    V = [i for i in range(n)]
    E = [set() for _ in range(n)]
    #E[i]:頂点iからの向かう先と重みの組
    #(to,cost) in E[i]は辺(i,to)の重みがcostであることを意味する
    for i in range(n):
        I = list(map(int,input().split()))
        for j in range(2,len(I)):
            if j % 2 == 0:
                E[i].add((I[j],I[j+1]))

    G = Graph(V,E)

    ans = G.dijkstra(0)
    for i in range(n):
        print(i,ans[i])

if __name__ == "__main__":
    main()