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
	heap.Init(&pq)

	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: import heapq


class SSST:
    """Given weighted graph, find minimum spanning tree.

    >>> st = SSST([[(2, 3), (3, 1), (1, 2)], \
                   [(0, 2), (3, 4)], \
                   [(0, 3), (3, 1), (4, 1)], \
                   [(2, 1), (0, 1), (1, 4), (4, 3)], \
                   [(2, 1), (3, 3)]])
    >>> [st.weight(n) for n in range(5)]
    [0, 2, 2, 1, 3]
    """
    def __init__(self, graph):
        self.size = len(graph)
        self.tree = []
        self.weights = [0] * self.size
        self._search(graph)

    def weight(self, n):
        return self.weights[n]

    def _search(self, graph):
        visited = [0]

        while len(visited) < self.size:
            h = []
            for node in visited:
                for i, w in graph[node]:
                    if i not in visited:
                        heapq.heappush(h, (w+self.weights[node], node, i))

            weight, src, dst = heapq.heappop(h)
            visited.append(dst)
            self.weights[dst] = weight
            self.tree.append((src, dst))


def run():
    n = int(input())

    nodes = [None] * n
    for _ in range(n):
        id_, deg, *edges = [int(i) for i in input().split()]
        nodes[id_] = []
        for _ in range(deg):
            tgt, wgt, *edges = edges
            nodes[id_].append((tgt, wgt))

    st = SSST(nodes)
    for node in range(n):
        print('{} {}'.format(node, st.weight(node)))


if __name__ == '__main__':
    run()

Python: # -*- coding: utf-8 -*-
"""
Created on Tue May 21 23:08:18 2019

@author: Yamazaki Kenichi
"""

n = int(input())
A = [list(map(int,input().split())) for i in range(n)]
INFTY = 10**6
M = [[INFTY for i in range(n)] for i in range(n)]
for a in A:
    u, k = a[0], a[1]
    for i in range(k):
        M[u][a[i*2+2]] = a[i*2+3]

class Dijkstra(object):
    
    def __init__(self, size, INFTY=10**6):
        self.color = [-1 for i in range(size)]
        self.d = [INFTY for i in range(size)]
        self.p = [-1 for i in range(size)]
        self.d[0] = 0 
        self.p[0] = -1
    
    def add(self, M, INFTY=10**6):
        while True:
            mincost = INFTY
            for i in range(len(M)):
                if self.color[i] != 1 and self.d[i] < mincost:
                    mincost = self.d[i]
                    u = i
            if mincost == INFTY:
                break
            self.color[u] = 1            
            for v in range(len(M)):
                if self.color[v] != 1 and M[u][v] != INFTY:
                    if self.d[v] > self.d[u] + M[u][v]:
                        self.d[v] = self.d[u] + M[u][v]
                        self.p[v] = u
                        self.color[v] = 0
        return self.d

dij = Dijkstra(n)
ans = dij.add(M)
for i in range(n):
    print(i,ans[i])

Python: #!/usr/bin/env python
# -*- coding: utf-8 -*-

import sys

WHITE, GRAY, BLACK = 0, 1, 2
D_MAX = int(1e7 + 1)


def generate_adj_matrix(v_info):
    for v_detail in v_info:
        v_index = int(v_detail[0])
        v_adj_length = int(v_detail[1])
        v_adj_list = v_detail[2:]
        # 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]] = int(v_adj_list[j + 1])

    return init_adj_matrix


def dijkstra_path():
    path_list[0] = 0

    while True:
        min_cost = D_MAX
        current_vertex = None
        for i in range(vertices_num):
            if color[i] is not BLACK and path_list[i] < min_cost:
                min_cost = path_list[i]
                current_vertex = i

        if min_cost == D_MAX:
            break

        color[current_vertex] = BLACK

        for v in range(vertices_num):
            current_v_weight = adj_matrix[current_vertex].get(str(v), -1)
            if current_v_weight < 0:
                continue
            elif color[v] is not BLACK:
                if path_list[current_vertex] + current_v_weight < path_list[v]:
                    path_list[v] = path_list[current_vertex] + current_v_weight
                    parent_list[v] = current_vertex
                    color[v] = GRAY

    return path_list


if __name__ == '__main__':
    _input = sys.stdin.readlines()
    vertices_num = int(_input[0])
    init_vertices_table = list(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 = [{} for _ in range(vertices_num)]
    adj_matrix = generate_adj_matrix(init_vertices_table)
    ans = dijkstra_path()
    for j in range(vertices_num):
        print(j, ans[j])