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: from heapq import*
def m():
 n=int(input())
 A=[[]for _ in[0]*n]
 for _ in[0]*n:
  e=list(map(int,input().split()))
  for i in range(e[1]):k=2*-~i;A[e[0]]+=[(e[k],e[k+1])]
 H=[[0,0]]
 d=[0]+[1e6]*n
 c=[1]*n
 while H:
  f=heappop(H)
  u=f[1]
  c[u]=0
  if d[u]>=f[0]:
   for s in A[u]:
    v=s[0]
    if c[v]and d[v]>d[u]+s[1]:
     d[v]=d[u]+s[1]
     heappush(H,[d[v],v])
 for i in range(n):print(i,d[i])
m()

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
D_MAX = int(5e10 + 1)


def generate_adj_matrix(v_info):
    for each in v_info:
        v_index, v_adj_length, *v_adj_list = map(int, each)
        # assert len(v_adj_list) == v_adj_length * 2
        for pair in zip(v_adj_list[::2], v_adj_list[1::2]):
            init_adj_matrix[v_index][pair[0]] = pair[1]

    return init_adj_matrix


def dijkstra_path():
    # path search init
    path_list[init_vertex_index] = 0
    path_heap = []
    # heapq: rank by tuple[0], here ranked by d[u]
    hp.heappush(path_heap, (0, init_vertex_index))
    while len(path_heap) >= 1:
        current_vertex_index = hp.heappop(path_heap)[1]

        color[current_vertex_index] = BLACK

        current_vertex_index_info = adj_table[current_vertex_index]
        for adj_vertex_index in current_vertex_index_info.keys():
            current_adj_weight = current_vertex_index_info.get(adj_vertex_index)
            if color[adj_vertex_index] is not BLACK:
                # alt: d[u] + w[u,v]
                alt_path = path_list[current_vertex_index] + current_adj_weight
                if alt_path < path_list[adj_vertex_index]:
                    # update path_list
                    path_list[adj_vertex_index] = alt_path
                    # update heap
                    hp.heappush(path_heap, (alt_path, adj_vertex_index))
                    parent_list[adj_vertex_index] = current_vertex_index
                    color[adj_vertex_index] = GRAY

    return path_list


if __name__ == '__main__':
    _input = sys.stdin.readlines()
    vertices_num = int(_input[0])
    init_vertices_table = map(lambda x: x.split(), _input[1:])
    # assert len(init_vertices_table) == vertices_num

    parent_list, path_list = [-1] * vertices_num, [D_MAX] * vertices_num
    color = [WHITE] * vertices_num
    init_adj_matrix = tuple(dict() for _ in range(vertices_num))
    init_vertex_index = 0

    adj_table = generate_adj_matrix(init_vertices_table)
    ans = dijkstra_path()
    for i, v in enumerate(ans):
        print(i, v)

Python: import sys
from heapq import*
e=sys.stdin.readline
n=int(e())
A=[[]for _ in[0]*n]
for _ in[0]*n:
 b=list(map(int,e().split()))
 for i in range(b[1]):k=2*-~i;A[b[0]]+=[(b[k],b[k+1])]
H=[[0,0]]
d=[0]+[1e6]*n
c=[1]*n
while H:
 f=heappop(H)
 u=f[1]
 c[u]=0
 if d[u]>=f[0]:
  for s in A[u]:
   v=s[0]
   if c[v]and d[v]>d[u]+s[1]:
    d[v]=d[u]+s[1]
    heappush(H,[d[v],v])
for i in range(n):print(i,d[i])

Python: import heapq
from collections import defaultdict

n = int(input())
graph = defaultdict(list)
for _ in range(n):
    u, k, *edges = map(int, input().split())
    for i in range(0, len(edges), 2):
        graph[u].append((edges[i], edges[i+1]))

q = [(0, 0)]
d = {}

# O(V^2)
while q:
    d_min, u = heapq.heappop(q)
    if u in d:
        continue
    d[u] = d_min
    for v, w in graph[u]:
        if v not in d:
            heapq.heappush(q, (d_min+w, v))

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

Python: import heapq as pq
inf = float("inf")
n = int(input())
M = [None] * n

for i in range(n):
    L = list(map(int, input().split()))
    M[L[0]] = []
    for j in range(L[1]):
        M[L[0]].append([L[2 * j + 2], L[2 * j + 3]])

def dijkstra(s):
    color = [0] * n
    d = [inf] * n
    d[s] = 0
    H =[]
    pq.heappush(H, [0, s])

    while len(H) != 0:
        u2,u1 = pq.heappop(H)
        color[u1] = 1
        if d[u1] < u2:
            continue
        for v1,v2 in M[u1]:
            if color[v1] == 1: continue
            if d[u1] + v2 < d[v1]:
                d[v1] = d[u1] + v2
                pq.heappush(H, [d[v1], v1])
    return d

d = dijkstra(0)
for i,v in enumerate(d):
 print("{} {}".format(i,v))

Python: import heapq as hq

def relax(u, v, w):
    if D[u] + w < D[v]:
        D[v] = D[u] + w
        P[v] = u
        for h in H:
            if h[1] == v:
                h[0] = D[v]
        hq.heapify(H)

INF = float('inf')
N = int(input())
D = [INF for i in range(N)]
P = [None for i in range(N)]
D[0] = 0

G = [{} for i in range(N)]
for i in range(N):
    x = list(map(int, input().split()))
    g = x[2:]
    for j, n in enumerate(g):
        if j % 2 == 0:
            G[i][n] = g[j + 1]

H = [[D[i], i] for i in range(N)]
hq.heapify(H)
S = set()

while 0 < len(H):
    d_u, u = hq.heappop(H)
    S.add(u)
    for v, w in G[u].items():
        if not (v in S):
            relax(u, v, w)

for i, d in enumerate(D):
    print('{0} {1}'.format(i, d))