Go: package main

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

var scanner = bufio.NewScanner(os.Stdin)

func nextString() string {
	scanner.Scan()
	return scanner.Text()
}

func nextInt() int {
	n, err := strconv.Atoi(nextString())
	if err != nil {
		fmt.Printf("strconv.Atoi failed: %v\n", err)
	}
	return n
}

var infty = 1000000000

type DirectedGraphNodeID int

type DirectedGraphNode struct {
	key         DirectedGraphNodeID
	adjacents   []*DirectedGraphNode
	costs       []int
	distance    int
	predecessor *DirectedGraphNode
}

func newDirectedGraph(nNodes int) *DirectedGraph {
	graph := DirectedGraph{}
	graph.nodes = make([]*DirectedGraphNode, nNodes)
	for i := 0; i < nNodes; i++ {
		node := DirectedGraphNode{}
		node.key = DirectedGraphNodeID(i)
		node.distance = infty
		graph.nodes[i] = &node
	}
	return &graph
}

type DirectedGraph struct {
	nodes []*DirectedGraphNode
}

func (g *DirectedGraph) setAdjacency(i, j DirectedGraphNodeID, cost int) {
	g.nodes[i].adjacents = append(g.nodes[i].adjacents, g.nodes[j])
	g.nodes[i].costs = append(g.nodes[i].costs, cost)
}

func (g *DirectedGraph) print() {
	for i := 0; i < len(g.nodes); i++ {
		node := g.nodes[i]
		key := node.key
		strings := []string{strconv.Itoa(int(key)), strconv.Itoa(node.distance)}
		for j := 0; j < len(node.adjacents); j++ {
			nodeJ := fmt.Sprintf("(%v, %v)", node.adjacents[j].key, node.costs[j])
			strings = append(strings, nodeJ)
		}
		fmt.Printf("%v\n", strings)
	}
}

func (g *DirectedGraph) relaxEdge(l, r *DirectedGraphNode, w int) {
	if r.distance > l.distance+w {
		// fmt.Printf("%v -> %v, %v\n", l.key, r.key, l.distance+w)
		r.distance = l.distance + w
		r.predecessor = l
	}
}

func main() {
	scanner.Split(bufio.ScanWords)

	nNodes := nextInt()
	graph := newDirectedGraph(nNodes)

	for i := 0; i < nNodes; i++ {
		iNode := DirectedGraphNodeID(nextInt())
		nAdjacent := nextInt()
		for j := 0; j < nAdjacent; j++ {
			jNode := DirectedGraphNodeID(nextInt())
			cost := nextInt()
			graph.setAdjacency(iNode, jNode, cost)
		}
	}

	graph.nodes[0].distance = 0
	for iNode := 0; iNode < nNodes; iNode++ {
		for iLeft := 0; iLeft < len(graph.nodes); iLeft++ {
			nodeLeft := graph.nodes[iLeft]
			for iRight := 0; iRight < len(nodeLeft.adjacents); iRight++ {
				nodeRight := nodeLeft.adjacents[iRight]
				cost := nodeLeft.costs[iRight]
				graph.relaxEdge(nodeLeft, nodeRight, cost)
			}
		}
	}

	// graph.print()

	for iNode := 0; iNode < len(graph.nodes); iNode++ {
		node := graph.nodes[iNode]
		fmt.Println(node.key, node.distance)
	}
}

Python: import sys

def dijkstra(v_count: int, edges: list, start: int,
             *, adj_matrix: bool = False, unreachable=float("inf")) -> list:
    """ ダイクストラ法
    :param v_count: 頂点数
    :param edges: 辺のリスト(隣接リストor隣接行列)
    :param start: スタートする頂点
    :param adj_matrix: edgesに渡したリストが隣接行列ならTrue
    :param unreachable: 到達不能を表すコスト値
                        隣接行列の辺の有無の判定および返すリストの初期値に使用
    """
    from heapq import heappush, heappop

    vertices = [unreachable] * v_count
    vertices[start] = 0
    q, rem = [(0, start)], v_count - 1

    while q and rem:
        cost, v = heappop(q)
        if vertices[v] < cost:
            continue
        rem -= 1

        dests = (filter(lambda x: x[1] != unreachable, enumerate(edges[v]))
                 if adj_matrix else edges[v])

        for dest, _cost in dests:
            newcost = cost + _cost
            if vertices[dest] > newcost:
                vertices[dest] = newcost
                heappush(q, (newcost, dest))

    return vertices

n = int(input())
edges = [[] for _ in [0]*n]
for a in (tuple(map(int, l.split())) for l in sys.stdin):
    edges[a[0]] = tuple(zip(a[2::2], a[3::2]))
vertices = dijkstra(n, edges, 0)
for i, n in enumerate(vertices):
    print(i, n)

Python: n = int(input())
INF = float("inf")
M = [[INF for _ in range(n)] for _ in range(n)]
for _ in range(n):
    a,*b = map(int,input().split())
    if b[0] != 0:
        c = b[1:]
        for i in range(len(c)//2):
            k,w = c[2*i],c[2*i+1]
            M[a][k] = w
searched = [0]*n
d = [INF]*n
p = [None]*n
d[0] = 0
p[0] = -1
while 1:
    mc = INF
    for i in range(n):
        if not searched[i] and d[i] < mc:
            mc = d[i]
            u = i
    if mc == INF:
        break
    searched[u] = 1
    for v in range(n):
        if not searched[v] and M[u][v] != INF:
            if d[u]+M[u][v] < d[v]:
                d[v] = d[u]+M[u][v]
                p[v] = u
for i in range(n):
    print(i,d[i])

Python: n = int(input())
G = [[-1 for i in range(n)] for j in range(n)]
d = [999999 for i in range(n)]
  
for i in range(n):
    v = input().split()
    for j in range(int(v[1])):
        G[int(v[0])][int(v[2+2*j])] = int(v[3+2*j])

flag = [0] * n
tn = [0]
d[0] = 0
for k in range(n):
    for i in range(n):
        if i in tn:
            for j in range(n):
                if G[i][j] != -1:
                    if d[j] > d[i] + G[i][j]:
                        d[j] = d[i] + G[i][j]
                    if j not in tn:
                        tn.append(j)
  
for i in range(n):
    print(str(i) + " " + str(d[i]))

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(1e7 + 1)


def generate_adj_matrix(v_info):
    for each in v_info:
        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_matrix[v_index][pair[0]] = pair[1]

    return init_adj_matrix


def dijkstra_path():
    # path search init
    path_list[init_vertex_index] = 0
    path_heap = []
    # heapq: rank by tuple[0], here ranked by d[u]
    hp.heappush(path_heap, (0, init_vertex_index))
    while len(path_heap) >= 1:
        current_vertex_index = hp.heappop(path_heap)[1]

        color[current_vertex_index] = BLACK

        for adj_vertex_index in range(vertices_num):
            current_adj_weight = adj_table[current_vertex_index].get(adj_vertex_index, -1)
            if current_adj_weight < 0:
                continue
            elif color[adj_vertex_index] is not BLACK:
                # alt: d[u] + w[u,v]
                alt_path = path_list[current_vertex_index] + current_adj_weight
                if alt_path < path_list[adj_vertex_index]:
                    # update path_list
                    path_list[adj_vertex_index] = alt_path
                    # update heap
                    hp.heappush(path_heap, (alt_path, adj_vertex_index))
                    parent_list[adj_vertex_index] = current_vertex_index
                    color[adj_vertex_index] = 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_matrix = tuple(dict() for _ in range(vertices_num))
    init_vertex_index = 0

    adj_table = generate_adj_matrix(init_vertices_table)
    ans = dijkstra_path()
    for i, v in enumerate(ans):
        print(i, v)