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: def E_dijkstra(V,AL,S):
    from heapq import heappush,heappop
    INF=float('inf')
    ans=[INF]*V
    ans[S]=0
    used=[0]*V # 0:未確定
    used[S]=1
    que=[]
    for i in range(V):
        heappush(que,(ans[i],i))
    while que:
        x,u=heappop(que)
        used[u]=1
        for v,w in AL[u]:
            if not used[v] and ans[v]>x+w:
                ans[v]=x+w
                heappush(que,(ans[v],v))
    return ans

# verified: https://onlinejudge.u-aizu.ac.jp/courses/library/5/GRL/1/GRL_1_A
# import sys
# input = sys.stdin.readline
# V,E,R=map(int,input().split())
# AL=[[] for i in range(V)]
# for _ in range(E):
#     S,T,D=map(int,input().split())
#     AL[S].append((T,D))
# for ans in E_dijkstra(V,AL,R):
#     print('INF' if ans==float('inf') else ans)

import sys
input = sys.stdin.readline

N=int(input())
AL=[[] for _ in range(N)]
for _ in range(N):
    for i,x in enumerate(input().split()):
        x=int(x)
        if i==0:
            j=x
        elif i==1:
            pass
        else:
            if i%2==0:
                tmp=[x]
            else:
                tmp.append(x)
                AL[j].append(tmp)
for ans in enumerate(E_dijkstra(N,AL,0)):
    print(*ans)

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_matrix():
    for each in init_vertices_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_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

        current_vertex_index_info = adj_table[current_vertex_index]
        for adj_vertex_index in current_vertex_index_info.keys():
            current_adj_weight = current_vertex_index_info.get(adj_vertex_index)
            if 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()
    ans = dijkstra_path()
    for i, v in enumerate(ans):
        print(i, v)

Python: import heapq

n = int(input())
C = [[] for _ in range(n)]
for _ in range(n):
    tmp = list(map(int,input().split()))
    for i in range(1,tmp[1]+1):
        C[tmp[0]].append(tuple(tmp[2*i:2*i+2]))

q = []

def heap_dijkstra(start = 0):
    visited = [False]*n
    INF = 10000000000
    d = [INF]*n

    d[start] = 0
    visited[start] = True
    add_node = start

    for i in range(n-1):
        for adj_weight in C[add_node]:
            if visited[adj_weight[0]] == False:
                heapq.heappush(q,(d[add_node]+adj_weight[1],adj_weight[0]))

        while 1:
            tmp = heapq.heappop(q)
            if visited[tmp[1]] == False:
                min_weight = tmp[0]
                min_node = tmp[1]
                break
        
        add_node = min_node
        visited[min_node] = True
        d[min_node] = min_weight
    
    return d

D = heap_dijkstra()

for i in range(n):
    print("{} {}".format(i,D[i]))

Python: n = int(input())
adjacents = []
inf =  999999999999999
distances = [inf] * n
colors  = ["white"] * n
from heapq import heappush, heappop

for i in range(n):
  u, k, *a = map(int, input().split())
  adjacents.append([])
  for l in range(k):
    v = a[(l * 2)]
    c = a[(l * 2 + 1)]
    adjacents[u].append([v, c])

def dijkstra(u):
  distances[u] = 0
  queue = []
  heappush(queue, [0, u])

  while queue:
    w, u = heappop(queue)
    
    if distances[u] < w:
      continue
    
    colors[u] = "black"
    distances[u] = w

    for edge, weight in adjacents[u]:
      if colors[edge] != "black" and distances[edge] > weight + w:
        heappush(queue, [weight + w, edge])

dijkstra(0)

for index, edge in enumerate(distances):
  print(index, edge)