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: # -*- coding: utf-8 -*-
"""
Created on Sat Jul 14 19:11:44 2018

@author: maezawa
"""
infinity = 2*10**9

n = int(input())
adj = [[] for _ in range(n)]

for j in range(n):
    ain = list(map(int, input().split()))
    u = ain[0]
    k = ain[1]
    for i in range(2,2+2*k,2):
        adj[u].append([ain[i],ain[i+1]])
    #print(*adj[u])

color = [0]*n
d = [infinity for _ in range(n)]
p = [0]*n
p[0] = -1
d[0] = 0

def dyk(s):
    cnt = 1
    cur = s
    candidates = set() # remaining nodes
    while True:
        for i, w in adj[cur]:
            if color[i] == 2:
                continue
            if d[i] > d[cur] + w:
                d[i] = d[cur] + w
                color[i] = 1
            candidates.add(i)
        min_d = infinity
        for j in candidates:
            if min_d > d[j]:
                min_node = j
                min_d = d[j]
        candidates.remove(min_node)
        p[min_node] = cur
        color[cur] = 2
        cur = min_node
        cnt += 1
        #print(cur, d)
        #print(candidates)
        if cnt == n:
            break
    return

dyk(0)
for i in range(n):
    print(i, d[i])
    
#print(*p, sep = '\n')

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

        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 not current_adj_weight:
                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)

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(5e20 + 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

        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 not current_adj_weight:
                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)