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: import heapq
from collections import deque
from enum import Enum
import sys
import math
from _heapq import heappush, heappop

#------------------------------------------#

BIG_NUM = 2000000000
HUGE_NUM = 9999999999999999
MOD = 1000000007
EPS = 0.000000001

#------------------------------------------#

class Edge:
    def __init__(self,arg_to,arg_cost):
        self.to = arg_to
        self.cost = arg_cost

class Info:
    def __init__(self,arg_node_id,arg_sum_cost):
        self.node_id = arg_node_id
        self.sum_cost = arg_sum_cost

    def __lt__(self,arg):
        return self.sum_cost < arg.sum_cost


V = int(input())
min_dist = [BIG_NUM]*V
G = [[] for i in range(V)]

for loop in range(V):
    node_id,tmp_num,*table = list(map(int,input().split()))
    for i in range(0,len(table),2):
        G[node_id].append(Edge(table[i],table[i+1]))


min_dist[0] = 0
Q = []

heappush(Q, Info(0,0))

while len(Q) > 0:
    info = heappop(Q)
    if info.sum_cost > min_dist[info.node_id]:
        continue
    for edge in G[info.node_id]:
        if min_dist[edge.to] > info.sum_cost+edge.cost:
            min_dist[edge.to] = info.sum_cost+edge.cost
            heappush(Q, Info(edge.to,min_dist[edge.to]))


for i in range(V):
    print("%d %d"%(i,min_dist[i]))

Python: from heapq import heappush, heappop
from collections import deque

def main():
    V = int(input())
    q = []
    G = [deque() for i in range(V)]
    
    for i in range(V):
        tmp = list(map(int, input().split()))
        
        if tmp[0] == 0:
            for j in range(tmp[1]): heappush(q, (tmp[2+2*j:4+2*j][::-1]))
                
        else:
            for j in range(tmp[1]): G[tmp[0]].append(tmp[2+2*j:4+2*j])
            
    dist = [float('inf')] * V
    visited = [False] * V
    dist[0], visited[0] = 0, True
    
    while q:
        cost, v = heappop(q)
        
        if visited[v]: continue
    
        dist[v], visited[v] = cost, True
        for u, c in G[v]:
            if visited[u] or dist[u] < cost + c: continue
            heappush(q, [c+cost, u])
        
    for i in range(V): print(i, dist[i])
    
if __name__ == '__main__':
    main()

Python: import heapq

n = int(input())
edges = [None] * n
for _ in range(n):
    l = list(map(int, input().split()))
    edges[l[0]] = set((c, j) for j, c in (l[i:i + 2] for i in range(2, l[1] * 2 + 2, 2)))

min_costs = [0] * n
visited = [False] * n
visited[0] = True
queue = list(edges[0])
heapq.heapify(queue)
remains = n - 1

while True:
    total_cost, vertex = heapq.heappop(queue)
    if visited[vertex]:
        continue
    visited[vertex] = True
    min_costs[vertex] = total_cost
    remains -= 1
    if not remains:
        break
    for cost, vertex2 in edges[vertex]:
        if not visited[vertex2]:
            heapq.heappush(queue, (total_cost + cost, vertex2))

for r in enumerate(min_costs):
    print(*r)

Python: import heapq


class ShortestPath:
    """Dijkstra's algorithm : find the shortest path from a vertex
       Complexity: O(E + log(V))
       used in GRL1A(AOJ)
    """

    def __init__(self, V, E, start, INF=10**9):
        """ V: the number of vertexes
            E: adjacency list (all edge in E must be 0 or positive)
            start: start vertex
            INF: Infinity distance
        """
        self.V = V
        self.E = E
        self.dijkstra(start, INF)

    def dijkstra(self, start, INF):
        que = list()
        self.distance = [INF] * self.V  # distance from start
        self.prev = [-1] * self.V  # prev vertex of shortest path
        self.distance[start] = 0
        heapq.heappush(que, (0, start))

        while len(que) > 0:
            dist, fr = heapq.heappop(que)
            if self.distance[fr] < dist:
                continue
            for to, cost in self.E[fr]:
                if self.distance[fr] + cost < self.distance[to]:
                    self.distance[to] = self.distance[fr] + cost
                    heapq.heappush(que, (self.distance[to], to))
                    self.prev[to] = fr

    def getPath(self, end):
        path = [end]
        while self.prev[end] != -1:
            end = self.prev[end]
        return path[::-1]
V = int(input())
edge = [[] for _ in range(V)]
for _ in range(V):
    u, _, *e = map(int, input().split())
    for t, d in zip(e[::2], e[1::2]):
        edge[u].append((t, d))

sp = ShortestPath(V, edge, 0)
for i, d in enumerate(sp.distance):
    print(i, d)