Go: package main

import (
	"bufio"
	"fmt"
	"os"
	"strconv"
)

const BIG_COST = 200000

type Path struct {
	node int
	cost int
}

func main() {
	sc := bufio.NewScanner(os.Stdin)
	sc.Split(bufio.ScanWords)

	nNodes := scanInt(sc)

	// 各頂点につながる頂点一覧を得るための隣接リスト
	graph := make([][]Path, nNodes)

	for i := 0; i < nNodes; i++ {
		u := scanInt(sc)
		k := scanInt(sc)
		graph[i] = make([]Path, k)
		for d := 0; d < k; d++ {
			graph[u][d] = Path{
				node: scanInt(sc),
				cost: scanInt(sc),
			}
		}
	}

	// 0 から各頂点への最小コストを保存する配列
	minCosts := make([]int, nNodes)

	minCosts[0] = 0
	for i := 1; i < nNodes; i++ {
		minCosts[i] = BIG_COST
	}

	// 各頂点が調査済みかどうかを保持する配列
	checked := make([]bool, nNodes)

	// 最小コストのパスを高速に取得するためのヒープ。
	// コストが小さいものほどルートに来るようにする。
	heap := NewHeap(func(a, b Path) bool {
		return a.cost < b.cost
	})

	heap.insert(Path{node: 0, cost: 0})
	for heap.size > 0 {
		u := heap.extractMax()

		// 隣接行列を使っていた時とは違い、ヒープには
		// 同じノードへのパスが複数含まれうる。そのため既によりコストの低い
		// パスが見つかっている場合は無視する。
		if minCosts[u.node] < u.cost {
			continue
		}

		checked[u.node] = true

		for _, v := range graph[u.node] {
			cost := v.cost + u.cost
			if !checked[v.node] && cost < minCosts[v.node] {
				minCosts[v.node] = cost
				heap.insert(Path{node: v.node, cost: cost})
			}
		}
	}

	w := bufio.NewWriter(os.Stdout)
	for i, cost := range minCosts {
		fmt.Fprintf(w, "%d %d\n", i, cost)
	}
	w.Flush()
}

func scanInt(sc *bufio.Scanner) int {
	sc.Scan()
	v, _ := strconv.Atoi(sc.Text())
	return v
}

// --- From ALDS1_9_C: Priority Queue

type Heap struct {
	size   int
	heap   []Path
	isHigh func(a, b Path) bool
}

func NewHeap(isHigh func(a, b Path) bool) Heap {
	heap := make([]Path, 1) // 先頭は不使用
	return Heap{size: 0, heap: heap, isHigh: isHigh}
}

func (h *Heap) insert(v Path) {
	h.size += 1
	if h.size > len(h.heap)-1 {
		h.heap = append(h.heap, v)
	} else {
		h.heap[h.size] = v
	}

	for i := h.size; i > 1; {
		parent := i / 2
		if h.isHigh(h.heap[parent], h.heap[i]) {
			break
		}
		h.heap[i], h.heap[parent] = h.heap[parent], h.heap[i]
		i = parent
	}
}

func (h *Heap) extractMax() Path {
	if h.size <= 0 {
		panic("cannot extract from empty heap")
	}

	max := h.heap[1]
	h.heap[1] = h.heap[h.size]
	h.size -= 1
	h.maxHeapify(1)

	return max
}

func (h *Heap) maxHeapify(idx int) {
	left := idx * 2
	right := left + 1
	largest := idx

	if left <= h.size {
		if h.isHigh(h.heap[left], h.heap[idx]) {
			largest = left
		}
		if right <= h.size && h.isHigh(h.heap[right], h.heap[largest]) {
			largest = right
		}
	}

	if largest != idx {
		h.heap[idx], h.heap[largest] = h.heap[largest], h.heap[idx]
		h.maxHeapify(largest)
	}
}

Python: import sys

f_i = sys.stdin

n = int(f_i.readline())

adj = [[]] * n
for x in f_i:
    x = list(map(int, x.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] == False:
                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: 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)