Go: package main

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

type Item struct {
	value    int // The value of the item; arbitrary.
	priority int // The priority of the item in the queue.
	// The index is needed by update and is maintained by the heap.Interface methods.
	index int // The index of the item in the heap.
}
type PriorityQueue []*Item

func (pq PriorityQueue) Len() int { return len(pq) }
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 = i
	pq[j].index = j
}
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
}

type Q struct {
	pq *PriorityQueue
	ds map[int]int // It has always same value as pq. For random access.
}

func newQ() *Q {
	pq := new(PriorityQueue)
	heap.Init(pq)
	return &Q{
		pq: pq,
		ds: make(map[int]int),
	}
}
func (q *Q) pop() (u, d int) {
	item := heap.Pop(q.pq).(*Item)
	delete(q.ds, item.value)
	return item.value, item.priority
}
func (q *Q) get(u int) (int, bool) { // returns d
	d, ok := q.ds[u]
	return d, ok
}
func (q *Q) set(u, d int) {
	q.ds[u] = d
	for _, item := range *q.pq {
		if item.value != u {
			continue
		}

		item.priority = d
		heap.Fix(q.pq, item.index)
		return
	}
	heap.Push(q.pq, &Item{
		priority: d,
		value:    u,
	})
}
func (q *Q) len() int {
	return len(q.ds)
}

func main() {
	r := bufio.NewReader(os.Stdin)

	var n int
	fmt.Fscan(r, &n)
	cs := make([]map[int]int, n) // []v_i -> c_i
	for h := 0; h < n; h++ {
		var u, k int
		fmt.Fscan(r, &u, &k)
		m := make(map[int]int)
		for i := 0; i < k; i++ {
			var v, c int
			fmt.Fscan(r, &v, &c)
			m[v] = c
		}

		cs[u] = m
	}

	q := newQ()
	q.set(0, 0)
	visited := make(map[int]struct{})
	out := make([]int, n)

	for q.len() > 0 {
		u, d := q.pop()
		for uu, c := range cs[u] {
			// Consider the connection between u and uu.
			if _, ok := visited[uu]; ok {
				continue
			}
			dd := d + c
			if d, ok := q.get(uu); !ok || d > dd {
				q.set(uu, dd)
			}
		}

		out[u] = d
		visited[u] = struct{}{}
	}

	for u, d := range out {
		fmt.Println(u, d)
	}
}

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)