Go: package main

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

type Item struct {
	value    int // The value of the item; arbitrary.
	priority int // The priority of the item in the queue.
	// The index is needed by update and is maintained by the heap.Interface methods.
	index int // The index of the item in the heap.
}
type PriorityQueue []*Item

func (pq PriorityQueue) Len() int { return len(pq) }
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 = i
	pq[j].index = j
}
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
}

type Q struct {
	pq *PriorityQueue
	ds map[int]int // It has always same value as pq. For random access.
}

func newQ() *Q {
	pq := new(PriorityQueue)
	heap.Init(pq)
	return &Q{
		pq: pq,
		ds: make(map[int]int),
	}
}
func (q *Q) pop() (u, d int) {
	item := heap.Pop(q.pq).(*Item)
	delete(q.ds, item.value)
	return item.value, item.priority
}
func (q *Q) get(u int) (int, bool) { // returns d
	d, ok := q.ds[u]
	return d, ok
}
func (q *Q) set(u, d int) {
	q.ds[u] = d
	for _, item := range *q.pq {
		if item.value != u {
			continue
		}

		item.priority = d
		heap.Fix(q.pq, item.index)
		return
	}
	heap.Push(q.pq, &Item{
		priority: d,
		value:    u,
	})
}
func (q *Q) len() int {
	return len(q.ds)
}

func main() {
	r := bufio.NewReader(os.Stdin)

	var n int
	fmt.Fscan(r, &n)
	cs := make([]map[int]int, n) // []v_i -> c_i
	for h := 0; h < n; h++ {
		var u, k int
		fmt.Fscan(r, &u, &k)
		m := make(map[int]int)
		for i := 0; i < k; i++ {
			var v, c int
			fmt.Fscan(r, &v, &c)
			m[v] = c
		}

		cs[u] = m
	}

	q := newQ()
	q.set(0, 0)
	visited := make(map[int]struct{})
	out := make([]int, n)

	for q.len() > 0 {
		u, d := q.pop()
		for uu, c := range cs[u] {
			// Consider the connection between u and uu.
			if _, ok := visited[uu]; ok {
				continue
			}
			dd := d + c
			if d, ok := q.get(uu); !ok || d > dd {
				q.set(uu, dd)
			}
		}

		out[u] = d
		visited[u] = struct{}{}
	}

	for u, d := range out {
		fmt.Println(u, 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)