Go: package main

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

const (
	MAX_N      = 100
	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: # coding: utf-8

import heapq


class Dijkstra:

    """
    Dijkstra's algorithm: find the shortest path from a vertex
    Complexity: O(E + log(V))
    used in GRL1A(AOJ)
    """

    def __init__(self, V, G, INF=float("inf")):

        """
        V: the number of vertexes
        E: adjacency list (all edge in G must be 0 or positive)
        INF: Infinity distance
        """
        self.V = V
        self.G = G
        self.INF = INF
        self.distance, self.prev = list(), list()


    def dijkstra(self, start):

        Q = list()
        self.distance = [self.INF for _ in range(self.V)]
        self.prev = [-1 for _ in range(self.V)]

        self.distance[start] = 0
        heapq.heappush(Q, (0, start))

        while len(Q) > 0:
            dist, from_v = heapq.heappop(Q)
            if self.distance[from_v] < dist:
                continue
            for to_v, nxt_dist in self.G[from_v]:
                if self.distance[from_v] + nxt_dist >= self.distance[to_v]:
                    continue
                self.distance[to_v] = self.distance[from_v] + nxt_dist
                heapq.heappush(Q, (self.distance[to_v], to_v))
                self.prev[to_v] = from_v
        
        return self.distance


    def get_path(self, goal):

        path = [goal]
        while self.prev[goal] != -1:
            path.append(prev[goal])
            goal = self.prev[end]

        return path[::-1]


if __name__ == "__main__":
    
    n = int(input())
    g = [[] for _ in range(n)]
    for _ in range(n):
        v, _, *e = map(int, input().split())
        for u, d in zip(e[::2], e[1::2]):
            g[v].append((u, d))

    dist = Dijkstra(n, g).dijkstra(0)
    for i, d in enumerate(dist):
        print(i, d)

Python: from enum import Enum


class Sssp(object):
    """ single source shortest path """
    INFINITY = 999999999
    class Status(Enum):
        """ ?????????????¨??????¶??? """
        white = 1  # ????¨????
        gray = 2  # ?¨???????
        black = 3  #?¨???????

    def __init__(self, data):
        num_of_nodes = len(data)
        self.color = [Sssp.Status.white] * num_of_nodes  # ????????????????¨??????¶???
        self.M = [[Sssp.INFINITY] * num_of_nodes for _ in range(num_of_nodes)]
        self._make_matrix(data)  # data????????????????????£??\??????(?????\?¶???¨???????????????????????§????????????)
        self.d = [Sssp.INFINITY] * num_of_nodes
        self.p = [-1] * num_of_nodes  # ????????????????????????????¨??????????

    def _make_matrix(self, data):
        for d in data:
            my_id = d[0]
            d = d[2:]
            while len(d) > 1:
                to_node, cost = d[0], d[1]
                self.M[my_id][to_node] = cost
                d = d[2:]

    def dijkstra(self, start):
        self.d[start] = 0
        self.p[start] = -1

        while True:
            mincost = Sssp.INFINITY
            for i in range(len(self.d)):
                if self.color[i] != Sssp.Status.black and self.d[i] < mincost:
                    mincost = self.d[i]
                    u = i

            if mincost == Sssp.INFINITY:
                break

            self.color[u] = Sssp.Status.black

            for v in range(len(self.d)):
                if self.color[v] != Sssp.Status.black and self.M[u][v] != Sssp.INFINITY:
                    if self.d[u] + self.M[u][v] < self.d[v]:
                        self.d[v] = self.d[u] + self.M[u][v]
                        self.p[v] = u
                        self.color[v] = Sssp.Status.gray


if __name__ == '__main__':
    # ??????????????\???
    num = int(input())
    data = []
    for i in range(num):
        data.append(list(map(int, input().split(' '))))

    # ???????????¢?´¢
    s = Sssp(data)
    s.dijkstra(0)

    # ???????????¨???
    for i in range(num):
        print('{0} {1}'.format(i, s.d[i]))

Python: n=int(input())
inf=10**15;d=[inf]*n;d[0]=0
node=[[]for _ in range(n)]
for i in range(n):
	x=list(map(int,input().split()))
	for j in range(x[1]):
		node[i].append((x[j*2+2],x[j*2+3]))
dis=[[inf]*n for _ in range(n)]
for i in range(n):
	dis[i][i]=0
for i in range(n):
	for x in node[i]:
		dis[i][x[0]]=x[1]
s=[False]*n
while True:
	min_cost=inf
	for i in range(n):
		if s[i]==0 and d[i]<min_cost:
			min_cost=d[i]
			u=i
	if min_cost==inf:
		break
	s[u]=True
	for i in range(n):
		if s[i]==False and dis[u][i]!=inf:
			if d[u]+dis[u][i]<d[i]:
				d[i]=d[u]+dis[u][i]		
for i in range(n):
	print(i,d[i])