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: import heapq


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

    def __init__(self, V, E, start, INF=10**9):
        """ V: the number of vertexes
            E: adjacency list (all edge in E must be 0 or positive)
            start: start vertex
            INF: Infinity distance
        """
        self.V = V
        self.E = E
        self.dijkstra(start, INF)

    def dijkstra(self, start, INF):
        que = list()
        self.distance = [INF] * self.V  # distance from start
        self.prev = [-1] * self.V  # prev vertex of shortest path
        self.distance[start] = 0
        heapq.heappush(que, (0, start))

        while len(que) > 0:
            dist, fr = heapq.heappop(que)
            if self.distance[fr] < dist:
                continue
            for to, cost in self.E[fr]:
                if self.distance[fr] + cost < self.distance[to]:
                    self.distance[to] = self.distance[fr] + cost
                    heapq.heappush(que, (self.distance[to], to))
                    self.prev[to] = fr

    def getPath(self, end):
        path = [end]
        while self.prev[end] != -1:
            end = self.prev[end]
        return path[::-1]
V = int(input())
edge = [[] for _ in range(V)]
for _ in range(V):
    u, _, *e = map(int, input().split())
    for t, d in zip(e[::2], e[1::2]):
        edge[u].append((t, d))

sp = ShortestPath(V, edge, 0)
for i, d in enumerate(sp.distance):
    print(i, d)

Python: #!/usr/bin/env python
# -*- coding: utf-8 -*-

"""
input:
5
0 3 2 3 3 1 1 2
1 2 0 2 3 4
2 3 0 3 3 1 4 1
3 4 2 1 0 1 1 4 4 3
4 2 2 1 3 3

output:
0 0
1 2
2 2
3 1
4 3
"""

import sys
import heapq as hp

WHITE, GRAY, BLACK = 0, 1, 2
D_MAX = int(5e10 + 1)


def generate_adj_table(v_table):
    for each in v_table:
        v_index, v_adj_length, *v_adj_list = map(int, each)
        assert len(v_adj_list) == v_adj_length * 2
        for pair in zip(v_adj_list[::2], v_adj_list[1::2]):
            init_adj_table[v_index][pair[0]] = pair[1]

    return init_adj_table


def dijkstra_path_heap():
    # path search init
    path_list[init_vertex] = 0
    path_heap = []
    # heapq: rank by tuple[0], at here it's d[u]
    hp.heappush(path_heap, (0, init_vertex))

    while len(path_heap) >= 1:
        current_vertex = hp.heappop(path_heap)[1]

        color[current_vertex] = BLACK

        for adj_vertex, adj_weight in adj_table[current_vertex].items():
            if color[adj_vertex] is not BLACK:
                # alt: d[u] + w[u,v]
                alt_path = path_list[current_vertex] + adj_weight
                if alt_path < path_list[adj_vertex]:
                    # update path_list
                    path_list[adj_vertex] = alt_path
                    # update heap
                    hp.heappush(path_heap, (alt_path, adj_vertex))
                    parent_list[adj_vertex] = current_vertex
                    color[adj_vertex] = GRAY

    return path_list


if __name__ == '__main__':
    _input = sys.stdin.readlines()
    vertices_num = int(_input[0])
    init_vertices_table = map(lambda x: x.split(), _input[1:])
    # assert len(init_vertices_table) == vertices_num

    parent_list, path_list = [-1] * vertices_num, [D_MAX] * vertices_num
    color = [WHITE] * vertices_num
    init_adj_table = tuple(dict() for _ in range(vertices_num))
    init_vertex = 0

    adj_table = generate_adj_table(init_vertices_table)
    ans = dijkstra_path_heap()
    for i, v in enumerate(ans):
        print(i, v)

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()