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
import heapq
n = int(input())
V = [[int(i) for i in input().split()] for _ in range(n)]
dis = [sys.maxsize for _ in range(n)]
dis[0] = 0
h = []
for i in range(n):
    heapq.heappush(h,(dis[i],i))
while(len(h)>0):
    node = heapq.heappop(h)
    tmp = node[1]
    for i in range(V[tmp][1]):
        ind = V[tmp][2*i+2]
        cos = V[tmp][2*i+3]
        if cos + dis[tmp] < dis[ind]:
            dis[ind] = cos + dis[tmp]
            heapq.heappush(h,(dis[ind],ind))
for i,j in enumerate(dis):
    print(i,j)

Python: from heapq import heappop, heappush
import sys


class SSSP:
    """Given weighted graph, find Single Sorce Shortest Path from node 0.

    >>> st = SSSP([[(2, 3), (3, 1), (1, 2)], \
                   [(0, 2), (3, 4)], \
                   [(0, 3), (3, 1), (4, 1)], \
                   [(2, 1), (0, 1), (1, 4), (4, 3)], \
                   [(2, 1), (3, 3)]])
    >>> [st.weight(n) for n in range(5)]
    [0, 2, 2, 1, 3]
    """
    def __init__(self, graph):
        self.size = len(graph)
        self.tree = []
        self.weights = [-1] * self.size
        self._search(graph)

    def weight(self, n):
        return self.weights[n]

    def _search(self, graph):
        h = []
        self.weights[0] = 0
        count = 1
        for i, w in graph[0]:
            heappush(h, (w, 0, i))

        while count < self.size:
            while len(h) > 0:
                weight, src, dst = heappop(h)
                if self.weights[dst] < 0:
                    self.weights[dst] = weight
                    count += 1
                    self.tree.append((src, dst))
                    for i, w in graph[dst]:
                        if self.weights[i] < 0:
                            heappush(h, (w+weight, dst, i))
                    break


def run():
    n = int(input())

    nodes = [None] * n
    for line in sys.stdin:
        id_, deg, *edges = [int(i) for i in line.split()]
        nodes[id_] = []
        for _ in range(deg):
            tgt, wgt, *edges = edges
            nodes[id_].append((tgt, wgt))

    st = SSSP(nodes)
    for node in range(n):
        print('{} {}'.format(node, st.weight(node)))


if __name__ == '__main__':
    run()

Python: from heapq import heappush, heappop

inf = float('inf')
n = int(input())
g = []
for i in range(n):
    line = list(map(int, input().split()[2:]))
    g.append(zip(line[0::2], line[1::2]))

dist = [inf] * n
dist[0] = 0
heap = [(0, 0)]

while heap:
    current = heappop(heap)[1]
    for v, c in g[current]:
        new_dist = dist[current] + c
        if new_dist < dist[v]:
            dist[v] = new_dist
            heappush(heap, (new_dist, v))

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

Python: n = int(input())
INF = float("inf")
edges = [[] for _ in range(n)]
visited = [False]*n
# edges = [[INF for _ in range(n)] for _ in range(n)]
# edges = [[] for _ in range(n) for _ in range(n)]
d = [INF]*n
d[0] = 0

for _ in range(n):
    ls = list(map(int, input().split()))
    u = ls[0]
    degrees = ls[1]
    data = ls[2:]
  
    for i in range(degrees):
        v = data[i*2]
        cost = data[i*2+1]
        edges[u].append((v, cost))
        # edges[u][v] = cost

#通常版
# for _ in range(n):
#     dmin = float("inf")
#     for i in range(n):
#         if not visited[i] and d[i] < dmin:
#             dmin = d[i]
#             u = i
#     visited[u] = True
#     for v, c in edges[u]:
#         d[v] = min(d[v], d[u] + c)

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

# exit()
#heap版
import heapq

heap = [(0, 0)]
d[0] = 0


while heap:
    du, u = heapq.heappop(heap)
    for v, cost in edges[u]:
        if du + cost < d[v]:
            d[v] = du +  cost
            # visited[u] = True
            heapq.heappush(heap, (d[v], v))

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

Python: n=int(input())
g=[[]for i in range(n)]
for i in range(n):
    d=list(map(int,input().split()))
    for j in range(d[1]):
        g[d[0]].append((d[2+j*2+1],d[2+j*2]))

def dijkstra(g,st,ed):
    from heapq import heappush, heappop, heapify
    inf=10**18
    dist=[inf for i in range(len(g))]
    visited=[False for i in range(len(g))]
    dist[st]=0
    que=[]
    heappush(que,(0,st))
    while que:
        c,v=heappop(que)
        if visited[v]:
            continue
        visited[v]=True
        for x in g[v]:
            tmp=x[0]+c
            if tmp<dist[x[1]] and not visited[x[1]]:
                dist[x[1]]=tmp
                heappush(que,(tmp,x[1]))
    return dist

dist=dijkstra(g,0,n-1)
for i in range(n):
    print(i,dist[i])