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
}

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{1}, shortestList, adjacentMatrix)
	for _, v := range shortestList {
		fmt.Printf("%d %d\n", v.getEnd()-1, v.shortest)
	}
}

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

func createAdjacentMatrix(n int, sc *bufio.Scanner) ([][]int, error) {
	adjacentMatrix := make([][]int, n)
	for i := 0; i < n; i++ {
		id, err := nextInt(sc)
		if err != nil {
			return nil, err
		}
		adjacentMatrix[id] = make([]int, n)
		for j := 0; j < n; j++ {
			adjacentMatrix[id][j] = -1
		}
		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][v] = c
		}
	}
	return adjacentMatrix, nil
}

func sssp(nodeStack []int, shortestList []ShortestInfo, adjacentMatrix [][]int) {
	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-1]
}

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-1] = shortestInfo
}

func findAdjacents(currentNode int, adjacentMatrix [][]int) []Edge {
	adjacents := adjacentMatrix[currentNode-1]
	edges := []Edge{}
	for i, v := range adjacents {
		if v > 0 {
			edges = append(edges, Edge{start: currentNode, end: i + 1, weight: v})
		}
	}
	return edges
}

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

Python: 
n=int(input())
graph=[[0]*n for i in range(n)]


#graph[i][j]は、頂点iから頂点jへの枝の重みを表す(0は枝なし)
for loop in range(n):
    tmp_ope=list(map(int,input().split()))
    for j in range(1,tmp_ope[1]+1):
        graph[tmp_ope[0]][tmp_ope[2*j]]=tmp_ope[2*j+1]

#S[i]＝１の時、頂点iは走査済み
S=[0]*n
#d[i]はSに含まれる点のみを使って、頂点iにたどり着くときの最短パス
d=[999999]*n
d[0]=0

for loop in range(n):
    tmp_vertex=-1

    #tmp_vertexは走査済みでない点の中で、d[i]が最小となるインデックス
    for j in range(n):
        if(S[j]==0):
            if(tmp_vertex!=-1):
                if(d[j] < d[tmp_vertex]):
                    tmp_vertex=j
            else:
                tmp_vertex=j
    
    
    S[tmp_vertex]=1

    #dを更新
    for j in range(n):
        if(graph[tmp_vertex][j]!=0 and S[j]==0):
            d[j]=min([ d[j], d[tmp_vertex] + graph[tmp_vertex][j] ])

for i in range(n):
    print(f"{i} {d[i]}")

Python: from heapq import*
I=float("inf")
def m():
 n=int(input())
 A=[[]]*n
 for _ in range(n):
  e=list(map(int,input().split()))
  A[e[0]]=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))
 for i in range(n):print(i,d[i])
m()

Python: import sys, itertools
f = sys.stdin

def take2(iterable):
    i = iter(iterable)
    while True:
        yield next(i), next(i)

n = int(f.readline())
adj =[[(v, c) for v, c in take2(map(int, f.readline().split()[2:]))] for _ in range(n)]
d = [100000 * 100 + 1] * n

d[0] = 0
queue =[0]
while len(queue):
    parent = queue.pop()
    for v, c in adj[parent]:
        if d[v] > d[parent] + c:
            d[v] = d[parent] + c
            queue.append(v)

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

Python: import queue


class Edge:
    def __init__(self, from_v, to_v, cost):
        self.from_v = from_v
        self.to_v = to_v
        self.cost = cost

    def __lt__(self, other):
        return self.cost < other.cost

    def get_from_v(self):
        return self.from_v

    def get_to_v(self):
        return self.to_v

    def get_cost(self):
        return self.cost


class Vertex:
    def __init__(self, cost, id):
        self.cost = cost
        self.id = id

    def __lt__(self, other):
        return self.cost < other.cost

    def get_cost(self):
        return self.cost

    def get_id(self):
        return self.id


class Dijkstra:
    def __init__(self, number_of_vertex):
        # self.edges = []
        self.graf = [[] for _ in range(number_of_vertex)]
        self.number_of_vertex = number_of_vertex
        self.distance = []  # 最短距離
        self.INF = 1145141919810

    def add_edge(self, from_v, to_v, cost):
        # self.edges.append(Edge(from_v, to_v, cost))
        self.graf[from_v].append(Edge(from_v, to_v, cost))

    def compute_shortest_distance(self, start):
        self.distance = [self.INF] * self.number_of_vertex
        self.distance[start] = 0
        que = queue.PriorityQueue()

        que.put(Vertex(0, start))

        while not que.empty():
            top = que.get()
            cost = top.get_cost()
            id = top.get_id()
            if self.distance[id] < cost: continue
            for a_edge in self.graf[id]:
                to_v = a_edge.get_to_v()
                from_v = a_edge.get_from_v()
                prev_cost = self.distance[from_v]
                next_cost = self.distance[to_v]
                if next_cost > prev_cost + a_edge.get_cost():
                    next_cost = prev_cost + a_edge.get_cost()
                    self.distance[to_v] = next_cost
                    que.put(Vertex(next_cost, to_v))


n = int(input())
dij = Dijkstra(n)

for i in range(n):
    tmp = list(map(int, input().split()))
    u = tmp[0]
    k = tmp[1]
    vc = tmp[2:]
    for j in range(k):
        dij.add_edge(u, vc[2 * j], vc[2 * j + 1])

dij.compute_shortest_distance(0)

for i in range(n):
    print(str(i) + " " + str(dij.distance[i]))

Python: import sys
import heapq

n = int(sys.stdin.readline())

Q = []
adj = [[] for _ in range(n)]
for _ in range(n):
    cols = list(map(int, sys.stdin.readline().split()))
    for j in range(cols[1]):
        adj[cols[0]].append([cols[2+2*j], cols[2+2*j+1]])

d = [0] + [1e10] * (n-1)
color = [1] + [0] * (n-1)
heapq.heappush(Q, [0, 0])

while len(Q)>0:
    t, u = heapq.heappop(Q)
    color[u] = 2
    if d[u] < t: continue
    for v, w in adj[u]:
        if color[v] == 2: continue
        if d[v] > d[u] + w:
            d[v] = d[u] + w
            heapq.heappush(Q, [d[v], v])
            color[v] = 1

i=0
for e in d:
    print(i, e)
    i += 1