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

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]:
            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: from heapq import*
I=float("inf")
def m():
 n=int(input())
 A=[]
 for _ in[0]*n:
  e=list(map(int,input().split()))
  A+=[zip(e[2::2],e[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: from heapq import heapify,heappop,heappush

class Graph:
    def __init__(self,V,E):
        self.V = V
        self.E = E

    def dijkstra(self,st):
        INF = 10**9+1
        D = [INF for i in range(len(self.V))]
        #D[i]:頂点iまでの距離
        D[st] = 0
        Q = [[0,st]]
        Used = set()
        #既に最短距離が確定した頂点の集合
        
        while len(Used) < len(self.V):
            p = heappop(Q)
            p_dist,p_ind = p[0],p[1]
            for e in self.E[p_ind]:
                to,cost = e[0],e[1]
                if to not in Used:
                    if D[to] > D[p_ind] + cost:
                        D[to] = D[p_ind] + cost
                        heappush(Q,[D[to],to])
            Used.add(p_ind)

        return D

def main():
    n = int(input())
    V = [i for i in range(n)]
    E = [set() for _ in range(n)]
    #E[i]:頂点iからの向かう先と重みの組
    #(to,cost) in E[i]は辺(i,to)の重みがcostであることを意味する
    for i in range(n):
        I = list(map(int,input().split()))
        for j in range(2,len(I)):
            if j % 2 == 0:
                E[i].add((I[j],I[j+1]))

    G = Graph(V,E)

    ans = G.dijkstra(0)
    for i in range(n):
        print(i,ans[i])

if __name__ == "__main__":
    main()

Python: #!/usr/bin/env python
from __future__ import division, print_function
from sys import stdin, maxint
import heapq


def main():
    num = int(stdin.readline())

    L = []
    for _ in xrange(num):
        it = iter(int(s) for s in stdin.readline().split()[1:])
        L.append([(next(it), next(it)) for _ in xrange(next(it))])

    weight = [[maxint, i] for i in xrange(num)]
    weight[0][0] = 0
    V = set(xrange(1, num))
    W = weight[:]
    heapq.heappop(W)
    index = 0

    while V:
        for v, cost in L[index]:
            if v not in V:
                continue
            weight[v][0] = min(weight[v][0], cost + weight[index][0])

        heapq.heapify(W)
        index = heapq.heappop(W)[1]
        V.remove(index)

    for d, i in weight:
        print(i, d)


main()

Python: 
n=int(input())
graph=[[0]*n for i in range(n)]


#graph[i][j]は、頂点iから頂点jへの枝の重みを表す(0は枝なし)
for loop in range(n):
    tmp_ope=list(map(int,input().split()))
    for j in range(1,tmp_ope[1]+1):
        graph[tmp_ope[0]][tmp_ope[2*j]]=tmp_ope[2*j+1]

#S[i]＝１の時、頂点iは走査済み
S=[0]*n
#d[i]はSに含まれる点のみを使って、頂点iにたどり着くときの最短パス
d=[999999]*n
d[0]=0

for loop in range(n):
    tmp_vertex=-1

    #tmp_vertexは走査済みでない点の中で、d[i]が最小となるインデックス
    for j in range(n):
        if(S[j]==0):
            if(tmp_vertex!=-1):
                if(d[j] < d[tmp_vertex]):
                    tmp_vertex=j
            else:
                tmp_vertex=j
    
    
    S[tmp_vertex]=1

    #dを更新
    for j in range(n):
        if(graph[tmp_vertex][j]!=0 and S[j]==0):
            d[j]=min([ d[j], d[tmp_vertex] + graph[tmp_vertex][j] ])

for i in range(n):
    print(f"{i} {d[i]}")

Python: import sys
readline = sys.stdin.readline
from heapq import heapify, heappush, heappop
INF = float("inf")
def MAIN():
    n = int(input())
    adj = [[]] * n
    for _ in range(0, n):
        U = list(map(int, input().split()))
        adj[U[0]] = zip(U[2::2], U[3::2])
    def dijkstra():
        d = [0] + [INF] * (n - 1)
        hq = [(0, 0)]
        while hq:
            u = heappop(hq)[1]
            for v, c in adj[u]:
                alt = d[u] + c
                if d[v] > alt:
                    d[v] = alt
                    heappush(hq, (alt, v))
        print("\n".join(str(i) + " " + str(c) for i, c in enumerate(d)))
    dijkstra()
MAIN()

Python: import heapq


def dijkstra(n):
    inf = 10 ** 6 + 1
    dist = [0] + [inf] * (n - 1)
    q = [(0, 0)]
    while q:
        u = heapq.heappop(q)[1]
        for (v, c) in edge[u]:
            alt = dist[u] + c
            if dist[v] > alt:
                dist[v] = alt
                heapq.heappush(q, (alt, v))
    return dist

n = int(input())
edge = [[]] * n
for _ in range(n):
    l = list(map(int, input().split()))
    edge[l[0]] = (e for e in zip(l[2::2], l[3::2]))
for i, c in enumerate(dijkstra(n)):
    print(i, c)

Python: N = int(input())
G = [[] for i in range(N)]
for nod in range(N):
    U = list(map(int, input().split()))[2:]
    G[nod] = zip(U[0::2], U[1::2])



import heapq


def dijkstra(x):
    d = [float('inf')] * N
    d[x] = 0
    visited = {x}

    # d, u
    hq = [(0, x)]

    while hq:
        u = heapq.heappop(hq)[1]
        visited.add(u)

        for node, cost in G[u]:
            if (node not in visited) and d[node] > d[u] + cost:
                d[node] = d[u] + cost
                heapq.heappush(hq, (d[u]+cost, node))
    return d


distance = dijkstra(0)
#print(distance)
for i in range(N):
    print(i, distance[i])