Go: package main

import (
	"bufio"
	"fmt"
	"os"
	"strconv"
)

const (
	MAX_N      = 10000
	MAX_WEIGHT = 100000
)

type Edge struct {
	start  int
	end    int
	weight int
}

type ShortestInfo struct {
	edges    []Edge
	shortest int
}

type Neighbor struct {
	node   int
	weight int
}

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

	n, err := nextInt(sc)
	if err != nil {
		panic(err)
	}

	shortestList := make([]ShortestInfo, n)
	for i := 1; i < n; i++ {
		shortestList[i] = ShortestInfo{edges: []Edge{}, shortest: MAX_N*MAX_WEIGHT + 1}
	}

	adjacentMatrix, err := createAdjacentMatrix(n, sc)
	if err != nil {
		panic(err)
	}

	sssp([]int{0}, shortestList, adjacentMatrix)
	for _, v := range shortestList {
		fmt.Printf("%d %d\n", v.getEnd(), v.shortest)
	}
}

func (si ShortestInfo) getEnd() int {
	if len(si.edges) == 0 {
		return 0
	} else {
		return si.edges[len(si.edges)-1].end
	}
}

func createAdjacentMatrix(n int, sc *bufio.Scanner) ([][]Neighbor, error) {
	adjacentMatrix := make([][]Neighbor, n)
	for i := 0; i < n; i++ {
		id, err := nextInt(sc)
		if err != nil {
			return nil, err
		}
		adjacentMatrix[id] = []Neighbor{}
		vertexNum, err := nextInt(sc)
		if err != nil {
			return nil, err
		}
		for j := 0; j < vertexNum; j++ {
			v, err := nextInt(sc)
			if err != nil {
				return nil, err
			}
			c, err := nextInt(sc)
			if err != nil {
				return nil, err
			}
			adjacentMatrix[id] = append(adjacentMatrix[id], Neighbor{v, c})
		}
	}
	return adjacentMatrix, nil
}

func sssp(nodeStack []int, shortestList []ShortestInfo, adjacentMatrix [][]Neighbor) {
	for len(nodeStack) > 0 {
		currentNode := nodeStack[0]
		nodeStack = nodeStack[1:]
		currentShortest := getShortest(currentNode, shortestList)
		adjacents := findAdjacents(currentNode, adjacentMatrix)
		for i := 0; i < len(adjacents); i++ {
			adj := adjacents[i]
			if currentShortest.shortest+adj.weight < getShortest(adj.end, shortestList).shortest {
				setShortest(adj.end, adj, currentShortest, shortestList)
				nodeStack = append(nodeStack, adj.end)
			}
		}
	}
}

func getShortest(node int, shortestList []ShortestInfo) ShortestInfo {
	return shortestList[node]
}

func setShortest(node int, edge Edge, currentShortest ShortestInfo, shortestList []ShortestInfo) {
	newEdges := make([]Edge, len(currentShortest.edges)+1)
	for i := 0; i < len(newEdges)-1; i++ {
		newEdges[i] = currentShortest.edges[i]
	}
	newEdges[len(newEdges)-1] = edge
	shortestInfo := ShortestInfo{edges: newEdges, shortest: currentShortest.shortest + edge.weight}
	shortestList[node] = shortestInfo
}

func findAdjacents(currentNode int, adjacentMatrix [][]Neighbor) []Edge {
	adjacents := adjacentMatrix[currentNode]
	edges := []Edge{}
	for _, neighbor := range adjacents {
		edges = append(edges, Edge{start: currentNode, end: neighbor.node, weight: neighbor.weight})
	}
	return edges
}

func nextInt(sc *bufio.Scanner) (int, error) {
	sc.Scan()
	return strconv.Atoi(sc.Text())
}

Python: import sys
from heapq import *

MAX_INT= 10 ** 10

n = int(input())
adj_list = []

for _ in range(n):
  commands = sys.stdin.readline().split()
  lst = [ commands[i:i+2] for i in range(2, len(commands), 2)]
  adj_list.append(lst)

def dijkstra():
  # initialization
  visited = [False] * n
  dist_arr = [MAX_INT] * n
  pq = []
  prev = [None] * n

  # append 0 to pqs
  pq = [(0, 0)]
  dist_arr[0] = 0

  while len(pq) > 0:
    dist, idx = heappop(pq)
    visited[idx] = True

    # updating current values in dist
    for edge in adj_list[idx]:
      cur_idx, cur_dist = [ int(e) for e in edge]
      if visited[cur_idx]: continue

      new_dist = dist + cur_dist

      if new_dist < dist_arr[cur_idx]:
        dist_arr[cur_idx] = new_dist
        heappush(pq, (dist_arr[cur_idx], cur_idx))

  return dist_arr

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

Python: from heapq import heappop, heappush
from collections import defaultdict


class Dijkstra:
    """Graph input:
    {
    node:{node:cost,node:cost...},
    node:{node:cost,node:cost...},
    ...
    }
    """

    def __init__(self, graph: dict, N: int):
        self.graph = graph
        self.costs = [float("inf")] * N

    def calculate(self, start):
        queue = list()

        # step1: push the start point into the priority queue
        self.costs[start] = 0
        heappush(queue, (0, start))  # (cost,node)

        while queue:
            # step2: get the minimum cost node from unfixed node and fix the cost
            cost_from_start, min_node = heappop(queue)

            # step3: update the direct connected nodes
            for link, cost in self.graph[min_node].items():
                if cost_from_start + cost < self.costs[link]:
                    self.costs[link] = cost_from_start + cost
                    heappush(queue, (self.costs[link], link))

        return self.costs


n = int(input())
graph = defaultdict(dict)

for _ in range(n):
    data = [int(i) for i in input().split()]
    u = data[0]
    count = data[1]
    for j in range(1, count + 1):
        v = data[2 * j]
        w = data[2 * j + 1]
        graph[u][v] = w

dijkstra = Dijkstra(graph, n)
costs = dijkstra.calculate(0)

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