Go: package main

import (
	"fmt"
	"os"
	"bufio"
	"strings"
	"strconv"
)
var MAX = 1000000
type Vertex struct{
	Value int
	Routes map[int]int
	Done bool
}
func NewVertex(value int) *Vertex{
	routes := make(map[int]int)
	// for i, _ := range routes {
	// 	routes[i] = MAX
	// }
	return &Vertex{ value, routes, false }
}

func (v *Vertex) SetRoute(key, weight int) {
	v.Routes[key] = weight
}

type Path struct {
	Key int
	Weight int
}

var count = 0
func ShortestRoutes(list []*Vertex) []int {
	// create result table
	result  := make([]int, len(list))
	// fmt.Println(result)
	for i, _ := range result {
		result[i] = MAX
	}

	queue := make([]Path, 0)
	queue = append(queue, Path{0, 0})
	result[0] = 0

	for len(queue) != 0 {
		count++
		path := queue[0]
		queue = queue[1:]
		for key, weight := range list[path.Key].Routes {
			// fmt.Println(list[path.Key].Routes)
			// set to result
			// fmt.Printf("Path(%d, %d) ? result[%d] => %d, wieght: %d\n", path.Key, path.Weight, key, result[key], weight)
			if path.Weight + weight < result[key] {
				result[key] = path.Weight + weight 
				queue = append(queue, Path{key, result[key]})
			// } else if !list[key].Done {
			// 	queue = append(queue, Path{key, result[key]})
			}
		}
		list[path.Key].Done = true
	}
	return result
}
func main() {
	var n int
	fmt.Scanf("%d", &n)
	list := make([]*Vertex, n)
	scanner := bufio.NewScanner(os.Stdin)
	for i := 0; i < n; i++ {
		scanner.Scan()
		elements := strings.Split(scanner.Text(), " ")
		value, _ := strconv.Atoi(elements[0])
		list[i] = NewVertex(value)
		for j := 2; j < len(elements); j += 2 {
			key, _    := strconv.Atoi(elements[j])
			weight, _ := strconv.Atoi(elements[j + 1])
			list[i].SetRoute(key, weight)
		}
	}

	result := ShortestRoutes(list)
	for i := 0; i < len(result); i++ {
		fmt.Printf("%d %d\n", i, result[i]);
	}
	// fmt.Printf("count: %d\n", count)
}

Python: import sys, os, math, bisect, itertools, collections, heapq, queue, copy, array

# from scipy.sparse.csgraph import csgraph_from_dense, floyd_warshall
# from decimal import Decimal
# from collections import defaultdict, deque

sys.setrecursionlimit(10000000)

ii = lambda: int(sys.stdin.buffer.readline().rstrip())
il = lambda: list(map(int, sys.stdin.buffer.readline().split()))
fl = lambda: list(map(float, sys.stdin.buffer.readline().split()))
iln = lambda n: [int(sys.stdin.buffer.readline().rstrip()) for _ in range(n)]

iss = lambda: sys.stdin.buffer.readline().decode().rstrip()
sl = lambda: list(map(str, sys.stdin.buffer.readline().decode().split()))
isn = lambda n: [sys.stdin.buffer.readline().decode().rstrip() for _ in range(n)]

lcm = lambda x, y: (x * y) // math.gcd(x, y)

MOD = 10 ** 9 + 7
INF = float('inf')


def main():
    if os.getenv("LOCAL"):
        sys.stdin = open("input.txt", "r")

    N = ii()

    # (距離, 接する頂点)の情報を持つ有向グラフのデータを生成
    graph = [[] for _ in range(N)]
    for _ in range(N):
        v1, k, *vertices = il()
        for idx in range(0, k * 2, 2):
            v2, c = vertices[idx:idx + 2]
            graph[v1].append((c, v2))

    # ダイクストラ法
    dist = [INF] * N    # 各頂点までの距離を保持する配列
    dist[0] = 0         # 開始始点の頂点は距離をゼロとする
    visited = [0] * N   # 各頂点の訪問状態を保持する配列[0: 未訪問, 1: 訪問済み]
    heap = [(0, 0)]     # 距離と始点頂点（自分自身への移動距離はゼロ）
    heapq.heapify(heap) # 距離と頂点の情報を距離で優先度付きキューとする
    while heap:
        # 頂点uとuに到達するまでの距離
        min_cost, u = heapq.heappop(heap)

        # さらに小さい距離で既に到達済みの場合はcontinue
        if dist[u] < min_cost: continue
        visited[u] = 1  # 頂点uを訪問済みにする

        # グラフの情報から接する頂点と移動距離を順に処理
        for cost, v in graph[u]:
            if visited[v] != 1:
                if dist[u] + cost < dist[v]:
                    # 未到達かつ小さい距離で移動できる場合には
                    # 距離の更新と優先度付きキューに(距離, 頂点)の情報を追加
                    dist[v] = dist[u] + cost
                    heapq.heappush(heap, (dist[v], v))
    # 回答
    for n in range(N):
        print(n, dist[n])


if __name__ == '__main__':
    main()

Python: from collections import defaultdict
import heapq
n = int(input())
global S, Q, l
S = [0]
Q = [(0, 0)]
l = [1000000 for _ in range(n)]
l[0] = 0
w_graph = [defaultdict(int) for _ in range(n)]
graph = [[] for _ in range(n)]
G = [None] * n
def input_graph(n):
  for i in range(n):
    node_id, k, *v_list = list(map(int, input().split()))
    G[i] = [(v, c) for v, c in zip(v_list[::2], v_list[1::2])]

heapq.heapify(Q)
def dijkstra():
  c = 0
  while Q and c < 10:
    u_c, u = heapq.heappop(Q)
    for v, v_c in G[u]:
      """if v not in S:
        S.append(v)
        l[v] = l[u] + v_c
        heapq.heappush(Q, (l[v], v))"""
      if  (l[v] > l[u] + v_c):
        l[v] = l[u] + v_c
        heapq.heappush(Q, (l[v], v))


if __name__ == "__main__":
  input_graph(n)
  dijkstra()
  for i, c in enumerate(l):
    print(i, c)

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_detail = map(int, each)
        v_index, v_adj_length, *v_adj_list = v_detail
        # assert len(v_adj_list) == v_adj_length * 2
        for j in range(0, v_adj_length * 2, 2):
            init_adj_matrix[v_index][v_adj_list[j]] = v_adj_list[j + 1]

    return init_adj_matrix


def dijkstra_path():
    # path search init
    start_vertex_index = 0
    path_list[start_vertex_index] = 0
    path_heap = []
    # heapq: rank by tuple[0], here ranked by d[u]
    hp.heappush(path_heap, (path_list[start_vertex_index], start_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_matrix[current_vertex_index].get(adj_vertex_index, -1)
            if current_adj_weight < 0:
                continue
            elif color[adj_vertex_index] is not BLACK:
                # 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))
    adj_matrix = generate_adj_matrix(init_vertices_table)
    ans = dijkstra_path()
    for i, v in enumerate(ans):
        print(i, v)