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
}

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{1}, shortestList, adjacentMatrix)
	for _, v := range shortestList {
		fmt.Printf("%d %d\n", v.getEnd()-1, v.shortest)
	}
}

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

func createAdjacentMatrix(n int, sc *bufio.Scanner) ([][]int, error) {
	adjacentMatrix := make([][]int, n)
	for i := 0; i < n; i++ {
		id, err := nextInt(sc)
		if err != nil {
			return nil, err
		}
		adjacentMatrix[id] = make([]int, n)
		for j := 0; j < n; j++ {
			adjacentMatrix[id][j] = -1
		}
		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][v] = c
		}
	}
	return adjacentMatrix, nil
}

func sssp(nodeStack []int, shortestList []ShortestInfo, adjacentMatrix [][]int) {
	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-1]
}

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-1] = shortestInfo
}

func findAdjacents(currentNode int, adjacentMatrix [][]int) []Edge {
	adjacents := adjacentMatrix[currentNode-1]
	edges := []Edge{}
	for i, v := range adjacents {
		if v > 0 {
			edges = append(edges, Edge{start: currentNode, end: i + 1, weight: v})
		}
	}
	return edges
}

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

Python: import heapq

n = int(input())
C = [[] for _ in range(n)]
for _ in range(n):
    tmp = list(map(int,input().split()))
    for i in range(1,tmp[1]+1):
        C[tmp[0]].append(tuple(tmp[2*i:2*i+2]))

q = []

def heap_dijkstra(start = 0):
    visited = [False]*n
    INF = 10000000000
    d = [INF]*n

    d[start] = 0
    visited[start] = True
    add_node = start

    for i in range(n-1):
        for adj_weight in C[add_node]:
            if visited[adj_weight[0]] == False:
                heapq.heappush(q,(d[add_node]+adj_weight[1],adj_weight[0]))

        while 1:
            tmp = heapq.heappop(q)
            if visited[tmp[1]] == False:
                min_weight = tmp[0]
                min_node = tmp[1]
                break
        
        add_node = min_node
        visited[min_node] = True
        d[min_node] = min_weight
    
    return d

D = heap_dijkstra()

for i in range(n):
    print("{} {}".format(i,D[i]))

Python: n = int(input())
adjacents = []
inf =  999999999999999
distances = [inf] * n
colors  = ["white"] * n
from heapq import heappush, heappop

for i in range(n):
  u, k, *a = map(int, input().split())
  adjacents.append([])
  for l in range(k):
    v = a[(l * 2)]
    c = a[(l * 2 + 1)]
    adjacents[u].append([v, c])

def dijkstra(u):
  distances[u] = 0
  queue = []
  heappush(queue, [0, u])

  while queue:
    w, u = heappop(queue)
    
    if distances[u] < w:
      continue
    
    colors[u] = "black"
    distances[u] = w

    for edge, weight in adjacents[u]:
      if colors[edge] != "black" and distances[edge] > weight + w:
        heappush(queue, [weight + w, edge])

dijkstra(0)

for index, edge in enumerate(distances):
  print(index, edge)

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_vertex = hp.heappop(path_heap)[1]

        color[current_vertex] = BLACK

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

    return distance


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

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

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

Python: def dijkstra(n):
    inf = 10 ** 6 + 1
    dist = [0] + [inf] * (n - 1)
    visited = [False] * n

    while not all(visited):
        dmin = inf
        for i, (d, v) in enumerate(zip(dist, visited)):
            if v:
                continue
            elif dmin > d:
                dmin, u = d, i
        visited[u] = True
        for (v, c) in edge[u]:
            if dist[v] > dist[u] + c:
                dist[v] = dist[u] + c
    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)