Go: package main

import (
	"fmt"
	"bufio"
	"os"
	"strconv"
	"container/heap"
)

type Node struct {
	Id int
	Dis int
}

type PriorityQueue []*Node

func (pq PriorityQueue) Len() int { return len(pq) }

func (pq PriorityQueue) Less(i, j int) bool {
	return pq[i].Dis < pq[j].Dis
}

func (pq PriorityQueue) Swap(i, j int) {
	pq[i], pq[j] = pq[j], pq[i]
}

func (pq *PriorityQueue) Push(x interface{}) {
	*pq = append(*pq, x.(*Node))
}

func (pq *PriorityQueue) Pop() interface{} {
	n := len(*pq)
	pop := (*pq)[n-1]
	*pq = (*pq)[0:n-1]
	return pop
}

func main() {
	var n int
	fmt.Scan(&n)

	sc := bufio.NewScanner(os.Stdin)
	sc.Split(bufio.ScanWords)

	g := make([][]int, n)
	c := make([][]int, n)
	pq := make(PriorityQueue, 0, n)
	d := make([]int, n)
	for i := 0; i < n; i++ {
		sc.Scan()
		u, _ := strconv.Atoi(sc.Text())
		sc.Scan()
		k, _ := strconv.Atoi(sc.Text())
		g[u] = make([]int, k)
		c[u] = make([]int, k)
		for j := 0; j < k; j++ {
			sc.Scan()
			g[u][j], _ = strconv.Atoi(sc.Text())
			sc.Scan()
			c[u][j], _ = strconv.Atoi(sc.Text())
		}

		if u == 0 {
			d[u] = 0
		} else {
			d[u] = 1 << 30
		}
		pq.Push(&Node{u, d[u]})
	}
	heap.Init(&pq)

	for pq.Len() > 0 {
		node := heap.Pop(&pq).(*Node)
		for i := 0; i < len(g[node.Id]); i++ {
			nextId := g[node.Id][i]
			nextDis := node.Dis + c[node.Id][i]
			if nextDis < d[nextId] {
				d[nextId] = nextDis
				heap.Push(&pq, &Node{nextId, nextDis})
			}
		}
	}

	wr := bufio.NewWriter(os.Stdout)
	for i := 0; i < n; i++ {
		wr.WriteString(strconv.Itoa(i))
		wr.WriteString(" ")
		wr.WriteString(strconv.Itoa(d[i]))
		wr.WriteString("\n")
	}
	wr.Flush()
}

Python: from sys import maxsize
from heapq import heappop, heappush


class Node:
    WHITE = 0
    GRAY = 1
    BLACK = 2

    def __init__(self):
        self.adjs = []
        self.color = Node.WHITE
        self.dist = maxsize

    def __lt__(self, other):
        return self.dist < other.dist

    def __repr__(self):
        return "Node({},{},{})".format(self.adjs, self.color, self.dist)


def read_adj():
    n = int(input())
    nodes = [Node() for _ in range(n)]

    for i in range(n):
        u, _, *rest = [int(x) for x in input().split()]
        for i in range(0, len(rest) - 1, 2):
            nodes[u].adjs.append((rest[i], rest[i+1]))

    return nodes


def shortest_path(nodes):
    h = []

    nodes[0].dist = 0
    nodes[0].color = Node.GRAY
    heappush(h, (0, 0))

    while len(h) > 0:
        min_node, min_dist = heappop(h)
        if nodes[min_node].dist < min_dist:
            continue

        nodes[min_node].color = Node.BLACK

        for adj, c in nodes[min_node].adjs:
            if nodes[min_node].color == Node.BLACK:
                continue
            if nodes[min_node].dist + c < nodes[adj].dist:
                nodes[adj].dist = nodes[min_node].dist + c
                nodes[adj].color = Node.GRAY
                heappush(h, (adj, nodes[adj].dist))


def print_dist(nodes):
    for u, n in enumerate(nodes):
        print(u, n.dist)


def main():
    nodes = read_adj()
    shortest_path(nodes)
    print_dist(nodes)


if __name__ == '__main__':
    main()

Python: n = int(input())
from collections import defaultdict
G = defaultdict(list)
for i in range(n):
    i = [int(i) for i in input().split()]
    k = i[1]
    G[i[0]] = list(zip(i[2::2],i[3::2]))

def mind(Q, d):
    c = float('inf')
    ret = 0
    for i, j in enumerate(d):
        if c > j and i in Q:
            c = j
            ret = i
    return ret

def dijkstra(G):
    d = [0] + [float('inf')] * (n - 1)
    Q = set(range(n))
    while len(Q) != 0:
        u = mind(Q, d)
        Q = Q - set([u])
        for v, c in G[u]:
            if d[v] > d[u] + c:
                d[v] = d[u] + c
    return d

for i,j in enumerate(dijkstra(G)):
    print(i, j)

Python: # coding: utf-8

import heapq


class Dijkstra:

    """
    Dijkstra's algorithm: find the shortest path from a vertex
    O(E + log(V))
    verified:
        https://onlinejudge.u-aizu.ac.jp/#/courses/lesson/1/ALDS1/12/ALDS1_12_B
    """

    def __init__(self, V, G, INF=float("inf")):

        """
        V: the number of vertexes
        E: adjacency list (all edge in G must be 0 or positive)
        INF: Infinity distance
        """
        self.V = V
        self.G = G
        self.INF = INF
        self.distance, self.prev = list(), list()


    def dijkstra(self, start):

        Q = list()
        self.distance = [self.INF for _ in range(self.V)]
        self.prev = [-1 for _ in range(self.V)]

        self.distance[start] = 0
        heapq.heappush(Q, (0, start))

        while len(Q) > 0:
            dist, from_v = heapq.heappop(Q)
            if self.distance[from_v] < dist:
                continue
            for to_v, nxt_dist in self.G[from_v]:
                if self.distance[from_v] + nxt_dist >= self.distance[to_v]:
                    continue
                self.distance[to_v] = self.distance[from_v] + nxt_dist
                heapq.heappush(Q, (self.distance[to_v], to_v))
                self.prev[to_v] = from_v
        
        return self.distance


    def get_path(self, goal):

        path = [goal]
        while self.prev[goal] != -1:
            path.append(prev[goal])
            goal = self.prev[end]

        return path[::-1]


if __name__ == "__main__":
    
    """
    an example of use
    """

    n = int(input())
    g = [[] for _ in range(n)]
    for _ in range(n):
        v, _, *e = map(int, input().split())
        for u, d in zip(e[::2], e[1::2]):
            g[v].append((u, d))
            g[u].append((v, d))

    dist = Dijkstra(n, g).dijkstra(0)
    for i, d in enumerate(dist):
        print(i, d)

Python: #coding:utf-8
import numpy as np

n = int(input())
inf = 1000000000000000

def minHeapify(Q,i):
    H = len(Q)
    l = 2*i
    r = 2*i + 1
    if l < H and Q[l][1] < Q[i][1]:
        smallest = l
    else:
        smallest = i
    if r < H and Q[r][1] < Q[smallest][1]:
        smallest = r

    if smallest != i:
        Q[i], Q[smallest] = Q[smallest], Q[i]
        minHeapify(Q,smallest)

def buildMinHeap(Q):
    H = len(Q)
    for i in range(H // 2, -1, -1):
        minHeapify(Q,i)

def Insert(Q,key):
    v = key[0]
    Q.append([v,inf])
    lens = len(Q)
    heapIncreaseKey(Q,lens-1,key)

def heapIncreaseKey(Q,i,key):
    Q[i][1] = key[1]
    while i > 0 and Q[i // 2][1] > Q[i][1]:
        Q[i], Q[i // 2] = Q[i // 2], Q[i]
        i //= 2

def heapExtractMin(Q):
    H = len(Q)
    minv = Q[0][0]
    Q[0] = Q[H-1]
    Q.pop()
    minHeapify(Q,0)
    return minv




def dijkstra(s):
    color = ["white" for i in range(n)]
    d = [inf for i in range(n)]
    d[s] = 0
    Q = [[s,0]]
    while Q != []:
        u = heapExtractMin(Q)
        color[u] = "black"
        for vw in mtrx[u]:
            [v,w] = vw
            if color[v] != "black":
                if d[u] + w < d[v]:
                    d[v] = d[u] + w
                    color[v] = "gray"
                    Insert(Q,[v,d[v]])
    return d



mtrx = [[] for i in range(n)]
for i in range(n):
    col = list(map(int,input().split()))
    u,k = col[0], col[1]
    for j in range(k):
        [v,w] = col[2*j+2: 2*j+4]
        mtrx[u].append([v,w])



d = dijkstra(0)
for i,j in enumerate(d):
    print(i,j)