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 sys, itertools
f = sys.stdin

def take2(iterable):
    i = iter(iterable)
    while True:
        yield next(i), next(i)

n = int(f.readline())
adj =[[(v, c) for v, c in take2(map(int, f.readline().split()[2:]))] for _ in range(n)]
d = [100000 * 100 + 1] * n

d[0] = 0
queue ={0}
while len(queue):
    parent = queue.pop()
    for v, c in adj[parent]:
        if d[v] > d[parent] + c:
            d[v] = d[parent] + c
            queue.update([v])

for i in range(n):
    print(i, d[i])

Python: n = int(input())

adj = [[]] * n
for i in range(n):
    x = list(map(int, input().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]:
            continue

        isVisited[u] = True
        
        for vc, v in adj[u]:
            if isVisited[v] == True:
                continue
            
            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: # -*- coding: utf-8 -*-
from heapq import heapify, heappop, heappush

N = int(input())
INF = float("inf")
d = {n: INF for n in range(N)}
d[0] = 0
adj = [[] for _ in range(N)]

searched = [False for _ in range(N)]
searched[0] = True

for n in range(N):
    inp = tuple(map(int, input().split()))
    assert n == inp[0]
    for i in range(inp[1]):
        adj[n] = list(zip(inp[2::2], inp[3::2]))

heap = [[0, 0]]

while len(heap):
    pcost, p = heappop(heap)
    searched[p] = True
    
    if d[p] < pcost:
        continue
    
    for v in adj[p]:
        if not searched[v[0]]:
            new_cost = pcost + v[1]
            if new_cost < d[v[0]]:
                d[v[0]] = new_cost
                heappush(heap, [d[v[0]], v[0]])

for n in range(N):
    print("{} {}".format(n, d[n]))

Python: import sys
from heapq import*
e=sys.stdin.readline
I=float("inf")
def m():
 n=int(e())
 A=[]
 for _ in[0]*n:
  b=list(map(int,e().split()))
  A+=[zip(b[2::2],b[3::2])]
 d=[0]+[I]*n
 H=[(0,0)]
 while H:
  u=heappop(H)[1]
  for v,c in A[u]:
   t=d[u]+c
   if d[v]>t:
    d[v]=t
    heappush(H,(t,v))
 print('\n'.join(f'{i} {d[i]}'for i in range(n)))
m()

Python: # Single Source Shortest Path 2
from heapq import heappush, heappop

INF = 10**15
N = int(input())
W = [tuple(zip(*[map(int, input().split()[2:])]*2)) for _ in [0]*N]

H = []
checked = [False]*N
D = [INF]*N
D[0] = 0


heappush(H, (D[0], 0))

while H:
    d, v = heappop(H)
    checked[v] = True

    if D[v] < d:
        continue

    for u, w in W[v]:
        if not checked[u]:
            if D[v] + w < D[u]:
                D[u] = D[v] + w
                heappush(H, (D[u], u))


[print(i, d) for i, d in enumerate(D)]

Python: import heapq
N=int(input())
rinsetu=[[] for j in range(N)]
d=[1000000]*(N)

color=["white"]*N
for i in range(N):
    a=list(map(int,input().split()))
    for j in range(a[1]):
        j1=j*2+2
        j2=j*2+3
        rinsetu[i].append([a[j1],a[j2]])
def hunterhunter():
    d[0]=0
    heap=[]
    heapq.heapify(heap)
    heapq.heappush(heap,[0,0])
    while(heap):
        mincost=heapq.heappop(heap)
        u=mincost[1]
        color[u]="black"
        for  i in rinsetu[u]:
            if color[i[0]]=="white":
                if i[1]+d[u]<d[i[0]]:
                    d[i[0]]=i[1]+d[u]
                    heapq.heappush(heap,[d[i[0]],i[0]])
hunterhunter()
for i,cost in enumerate(d):
    print(i,cost)

Python: n = int(input())

adj = [[100001 for j in range(n)] for i in range(n)]

for u in range(n):
    x = list(map(int, input().split()))
    for v, c in zip(x[2::2], x[3::2]):
        adj[u][v] = c

unvisited = [v for v in range(n)]

distance = [9900001] * n


def dijkstra(s):
    distance[s] = 0

    while True:
        mincost = 9900001
        for i in unvisited:
            if distance[i] < mincost:
                mincost = distance[i]
                u = i

        if mincost == 9900001:
            break

        unvisited.remove(u)

        for v in unvisited:
            weight_uv = adj[u][v]
            if weight_uv != 100001:
                t_d = distance[u] + weight_uv
                if t_d < distance[v]:
                    distance[v] = t_d



dijkstra(0)

for v, d in enumerate(distance):
    print(v, d)

Python: import sys

f_i = sys.stdin

n = int(f_i.readline())

adj = [list(map(int, x.split()[2:])) for x in f_i]

unvisited = [v for v in range(n)]

distance = [999900001] * n
distance[0] = 0

class VCost:
    def __init__(self, v, cost):
        self.v = v
        self.cost = cost
    def __lt__(self, other):
        return self.cost < other.cost

import heapq

vcost = [VCost(0, 0)]

def dijkstra():
    while vcost:
        uc = heapq.heappop(vcost)

        if uc.cost > distance[uc.v]:
            continue
        
        unvisited.remove(uc.v)
        
        for v, c in zip(adj[uc.v][::2], adj[uc.v][1::2]):
            if v in unvisited:
                t_cost = uc.cost + c
                if t_cost < distance[v]:
                    distance[v] = t_cost
                    heapq.heappush(vcost, VCost(v, t_cost))



dijkstra()

for v, d in enumerate(distance):
    print(v, d)