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: 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))

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()