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: #coding:utf-8
dic = {}
nil = -1

class Doubly:
    def __init__(self,key,l=nil,r=nil):
        self.l = l
        self.r = r
        self.key = key

    def Insert(self,key):
        obj = Doubly(key)
        obj.l = fake
        fakeR = fake.r
        fake.r = obj
        obj.r = fakeR
        fakeR.l = obj
        if key in dic.keys():
            dic[key].append(obj)
        else:
            dic[key] = [obj]
    def deleteFirst(self):
        fakeR = fake.r
        fake.r = fakeR.r
        fakeR.r.l = fake
        key = fakeR.key
        if dic != {}:
            dic[key].pop(0)
            if dic[key] == []:
                del dic[key]

    def deleteLast(self):
        fakeL = fake.l
        fake.l = fakeL.l
        fakeL.l.r = fake
        key = fakeL.key
        if dic != {}:
            dic[key].pop(0)
            if dic[key] == []:
                del dic[key]
        

    def Delete(self,target):
        if target in dic.keys():
            obj = dic[target].pop(0)
            objL = obj.l
            objR = obj.r
            objL.r = objR
            objR.l = objL
            if dic[target] == []:
                del dic[target]
        


n = int(input())

fake = Doubly(nil)
fake.l = fake
fake.r = fake


for i in range(n):
    data = list(input().split())
    order = data[0]
    if order == "insert":
        Doubly.Insert(Doubly, int(data[1]))
    elif order == "delete":
        Doubly.Delete(Doubly, int(data[1]))
    elif order == "deleteFirst":
        Doubly.deleteFirst(Doubly)
    else:
        Doubly.deleteLast(Doubly)

obj = fake.r
List = []
while obj.key != -1:
    List.append(str(obj.key))
    obj = obj.r

print(" ".join(List))

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


def generate_adj_table(v_table):
    for each in v_table:
        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_table[v_index][pair[0]] = pair[1]

    return init_adj_table


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

    while path_heap:
        current = hp.heappop(path_heap)[1]

        color[current] = BLACK

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

    return distance


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

    distance = [float('inf')] * vertices
    parents = [-1] * vertices
    color = [WHITE] * vertices
    init_adj_table = tuple(dict() for _ in range(vertices))
    init_vertex = 0

    adj_table = generate_adj_table(v_info)
    ans = dijkstra_path_heap()
    for i, v in enumerate(ans):
        print(i, v)

Python: import sys

f_i = sys.stdin

n = int(f_i.readline())

class VCost:
    def __init__(self, v, cost):
        self.v_n = v
        self.cost = cost
    def __lt__(self, other):
        return self.cost < other.cost
    def __gt__(self, other):
        return self.cost > other.cost

adj = [[VCost(int(v), int(c)) for v, c in zip(x.split()[2::2], x.split()[3::2])] for x in f_i]

import heapq

def dijkstra():
    PQ = []
    isVisited = [False] * n
    distance = [999900001] * n

    distance[0] = 0
    heapq.heappush(PQ, VCost(0, 0))
    
    while PQ:
        uc = heapq.heappop(PQ)
        u = uc.v_n

        if uc.cost > distance[uc.v_n]:
            continue

        isVisited[u] = True
        
        for vc in adj[u]:
            v = vc.v_n
            if isVisited[v] == True:
                continue
            t_cost = distance[u] + vc.cost
            if t_cost < distance[v]:
                distance[v] = t_cost
                heapq.heappush(PQ, VCost(v, t_cost))

    for v, d in enumerate(distance):
        print(v, d)


dijkstra()

Python: import heapq


n = int(input())
M = {}
for _ in range(n):
    u, k, *line = map(int, input().split())
    tmp = []
    for i in range(k):
        v, w = line[2*i:2*i+2]
        tmp.append((v, w))
    M[u] = tmp

INF = 10**10
WHITE = 0
GREY = 1
BLACK = 2
d = [INF for i in range(n)]
d_heap = []
color = [WHITE]*n
p = [-1]*n


def dijkstra():
    d[0] = 0
    p[0] = -1
    heapq.heappush(d_heap, (0, 0))

    while len(d_heap):
        # 最も小さいnodeを持ってくる、これもheapで処理したい。
        _, u = heapq.heappop(d_heap)
        color[u] = BLACK

        # heapで距離更新
        for v, w in M[u]:
            if color[v] != BLACK:
                if d[u]+w < d[v]:
                    d[v] = d[u]+w
                    p[v] = u
                    heapq.heappush(d_heap, (d[v], v))


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