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

"""
input:
5
0 3 2 3 3 1 1 2
1 2 0 2 3 4
2 3 0 3 3 1 4 1
3 4 2 1 0 1 1 4 4 3
4 2 2 1 3 3

output:
0 0
1 2
2 2
3 1
4 3
"""

import sys
import heapq as hp

WHITE, GRAY, BLACK = 0, 1, 2


class SingleSourceShortestPath(object):
    __slots__ = ('adj_table', 'distance', 'parent', 'visited')

    def __init__(self, in_data):
        v_num = int(in_data[0])
        vertices = map(lambda x: x.split(), in_data[1:])
        adj_table = tuple(dict() for _ in range(v_num))

        for v_info in vertices:
            source, v_adj_length, *v_adj_list = map(int, v_info)
            # assert len(v_adj_list) == v_adj_length * 2
            for target, cost in zip(v_adj_list[::2], v_adj_list[1::2]):
                adj_table[source][target] = cost

        self.adj_table = adj_table
        self.distance = [float('inf')] * v_num
        self.parent = [-1] * v_num
        self.visited = [WHITE] * v_num

    def path_heap_dijkstra(self, root):
        # path search init
        self.distance[root] = 0
        path_heap = list()
        # heapq: rank by tuple[0], at here it's d[u]
        hp.heappush(path_heap, (0, root))

        while path_heap:
            csp, current = hp.heappop(path_heap)
            self.visited[current] = BLACK

            for adj, cost in self.adj_table[current].items():
                if self.visited[adj] is not BLACK:
                    # alt: d[u] + w[u,v]
                    alt_path = self.distance[current] + cost
                    if alt_path < self.distance[adj]:
                        # update path_list
                        self.distance[adj] = alt_path
                        # update heap
                        hp.heappush(path_heap, (alt_path, adj))
                        self.visited[adj] = GRAY
                        self.parent[adj] = current

        return self.distance


if __name__ == '__main__':
    _input = sys.stdin.readlines()
    case = SingleSourceShortestPath(in_data=_input)
    ans = case.path_heap_dijkstra(root=0)
    for i, v in enumerate(ans):
        print(i, v)

Python: # -*- coding: utf-8 -*-
from heapq import heappop, heappush

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

for n in range(N):
    inp = tuple(map(int, input().split()))
    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)
    
    for v, c in adj[p]:
        new_cost = pcost + c
        if new_cost < d[v]:
            d[v] = new_cost
            heappush(heap, [new_cost, v])

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

Python: from heapq import heappush, heappop
import sys
INFTY=sys.maxsize

def readinput():
    n=int(input())
    nList=[]
    for _ in range(n):
        nList.append([])
    for _ in range(n):
        l=list(map(int,input().split()))
        i=l[0]
        k=l[1]
        for j in range(k):
            v=l[2+j*2]
            c=l[2+j*2+1]
            nList[i].append([v,c])
    return n,nList

def dijkstra(s,n,nList):
    WHITE=0
    GRAY=1
    BLACK=2
    color=[WHITE]*n
    d=[INFTY]*n

    HQ=[]

    d[s]=0
    heappush(HQ,(d[s],s))

    while(len(HQ)>0):
        du,u=heappop(HQ)
        color[u]=BLACK

        if d[u]<du:
            continue

        for (v,vw) in nList[u]:
            if color[v]!=BLACK:
                if d[u] + vw < d[v]:
                    d[v] = d[u] + vw
                    color[v]=GRAY
                    heappush(HQ, (d[v], v))
    return d


def main(n,nList):
    d=dijkstra(0,n,nList)    
    for i in range(n):
        print('{} {}'.format(i,d[i]))

    return

if __name__=='__main__':
    n,nList=readinput()
    main(n,nList)

Python: import heapq

n = int(input())
d = [float("inf") for i in range(n)]
d[0] = 0
g = []
q = []

for i in range(n):
    heapq.heappush(q, (d[i], i))
    inp = list(map(int, input().split()))
    tmp = []
    for j in range(inp[1]):
        tmp.append(inp[2*j+2:2*j+4])
    g.append(tmp)

while q:
    q_pop = heapq.heappop(q)
    i = q_pop[1]
    if q_pop[0] > 100000*100000:
        continue
    for node in g[i]:
        d_tmp = d[i] + node[1]
        if d_tmp < d[node[0]]:
            d[node[0]] = d_tmp
            heapq.heappush(q, (d_tmp, node[0]))

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

Python: n=int(input())
inf=10**15;d=[inf]*n;d[0]=0
node=[[]for _ in range(n)]
for i in range(n):
	x=list(map(int,input().split()))
	for j in range(x[1]):
		node[i].append((x[j*2+2],x[j*2+3]))
from heapq import heappush,heappop
pq=[]
visited=[False]*n
heappush(pq,(0,0))#dis,num
while pq:
	u=heappop(pq)#1回あたりO(log|V|)がO(|V|)回ある
	u_dis=u[0];u_num=u[1]
	visited[u_num]=True
	for x in node[u_num]:
		x_dis=x[1];x_num=x[0]
		if visited[x_num]==False:
			if d[u_num]+x_dis<d[x_num]:
				d[x_num]=d[u_num]+x_dis
				heappush(pq,(d[x_num],x_num))
				#1回あたりO(log|V|)がO(|E|)回ある
for i in range(n):
	print(i,d[i])