Go: package main

import (
	"bufio"
	"container/heap"
	"fmt"
	"os"
	"strconv"
)

//make priority queue
type Item struct {
	id       int
	priority int // this state is priority and distans from start
	index    int
}

type PriorityQueue []*Item

func (pq PriorityQueue) Len() int { return len(pq) }

// we want the ascending-priority-queue.
// So we use less than here.
func (pq PriorityQueue) Less(i, j int) bool {
	return pq[i].priority < pq[j].priority
}

func (pq PriorityQueue) Swap(i, j int) {
	pq[i], pq[j] = pq[j], pq[i]
	pq[i].index = j
	pq[j].index = i
}

func (pq *PriorityQueue) Push(x interface{}) {
	n := len(*pq)
	item := x.(*Item)
	item.index = n
	*pq = append(*pq, item)
}

func (pq *PriorityQueue) Pop() interface{} {
	old := *pq
	n := len(old)
	item := old[n-1]
	item.index = -1 //for safety
	*pq = old[0 : n-1]
	return item
}

func (pq *PriorityQueue) update(dist int, id int) {
	for _, i := range *pq {
		if i.id == id {
			if i.priority > dist {
				i.priority = dist
			}
		}
	}
}

// the main code
func nextInt(sc *bufio.Scanner) int {
	sc.Scan()
	n, _ := strconv.Atoi(sc.Text())
	return n
}

func dikstra(dist [][]int, n int) []int {
	// preparate priority queue
	inf := 1 << 30
	pq := make(PriorityQueue, n)
	shortests := make([]int, n)
	for i := 0; i < n; i++ {
		pq[i] = &Item{
			id:       i,
			priority: inf,
			index:    i,
		}

		shortests[i] = inf
	}
	pq[0].priority = 0
	shortests[0] = 0

	for pq.Len() > 0 {
		item := heap.Pop(&pq).(*Item)
		shortests[item.id] = item.priority
		for id, d := range dist[item.id] {
			if d != -1 {
				pq.update(item.priority+d, id)
			}
		}
		heap.Init(&pq)
	}
	return shortests
}

func main() {
	sc := bufio.NewScanner(os.Stdin)
	sc.Split(bufio.ScanWords)

	// init
	n := nextInt(sc)
	dist := make([][]int, n)
	for i := 0; i < n; i++ {
		dist[i] = make([]int, n)
		for j := 0; j < n; j++ {
			dist[i][j] = -1
		}
	}

	// std Input
	for i := 0; i < n; i++ {
		u := nextInt(sc)
		k := nextInt(sc)
		for j := 0; j < k; j++ {
			v, c := nextInt(sc), nextInt(sc)
			dist[u][v] = c
		}
	}

	shortests := dikstra(dist, n)
	for i, d := range shortests {
		fmt.Printf("%d %d\n", i, d)
	}
}

Python: from collections import defaultdict
import heapq
v_num = int(input())
connect = defaultdict(list)

for _ in range(v_num):
    que = [int(n) for n in input().split(" ")]
    connect[que[0]] = [[v, w] for v, w in zip(que[2:len(que):2], que[3:len(que):2])]
    # weight_edge[que[0]] = {k:v for k, v in zip(que[2:len(que):2], que[3:len(que):2])}
queue = []
heapq.heapify(queue)
heapq.heappush(queue, [0, 0])
distance = [-1 for n in range(v_num)]
went = 0
visited = set()
while went < v_num:
    q = heapq.heappop(queue)
    weight, here = q
    if here in visited:
        continue
    visited |= {here}
    went += 1
    distance[here] = weight
    for conn in connect[here]:
        if conn[0] not in visited:
            heapq.heappush(queue, [weight + conn[1], conn[0]])
for i in range(v_num):
    print(i, distance[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(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_index] = 0
    path_heap = []
    # heapq: rank by tuple[0], at here it's d[u]
    hp.heappush(path_heap, (0, init_vertex_index))

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

        color[current_vertex] = BLACK

        current_vertex_adjs = adj_table[current_vertex]
        for adj_vertex, adj_weight in current_vertex_adjs.items():
            # adj_weight = current_vertex_adjs.get(adj_vertex)
            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_index = 0

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

Python: import heapq as hq

n=int(input())
da=[[] for i in range(n)]
for i in range(n):
    li=list(map(int,input().split()))
    for i in range(li[1]):
        da[li[0]].append([li[i*2+3],li[i*2+2]])
q=[]
ans=[-1 for i in range(n)]
ans[0]=0
for i in da[0]:
    hq.heappush(q,i)
while len(q)!=0:
    no=hq.heappop(q)
    if ans[no[1]] < 0:
        ans[no[1]]=no[0]
        for i in da[no[1]]:
            hq.heappush(q,[no[0]+i[0],i[1]])
for i in range(n):
    print("{} {}".format(i,ans[i]))

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()

Python: import sys
import heapq
n = int(input())
V = [[int(i) for i in input().split()] for _ in range(n)]
dis = [sys.maxsize for _ in range(n)]
dis[0] = 0
h = []
for i in range(n):
    heapq.heappush(h,(dis[i],i))
while(len(h)>0):
    node = heapq.heappop(h)
    tmp = node[1]
    for i in range(V[tmp][1]):
        ind = V[tmp][2*i+2]
        cos = V[tmp][2*i+3]
        if cos + dis[tmp] < dis[ind]:
            dis[ind] = cos + dis[tmp]
            heapq.heappush(h,(dis[ind],ind))
for i,j in enumerate(dis):
    print(i,j)