Go: package main

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

const NIL = -1

type Node struct {
	id     int
	weight int
}

func init() {
	sc.Split(bufio.ScanWords)
}

type NodeHeap []Node

func (h NodeHeap) Len() int           { return len(h) }
func (h NodeHeap) Less(i, j int) bool { return h[i].weight < h[j].weight }
func (h NodeHeap) Swap(i, j int)      { h[i], h[j] = h[j], h[i] }

func (h *NodeHeap) Push(x interface{}) {
	*h = append(*h, x.(Node))
}

func (h *NodeHeap) Pop() interface{} {
	old := *h
	n := len(old)
	x := old[n-1]
	*h = old[0 : n-1]
	return x
}

var sc = bufio.NewScanner(os.Stdin)

func scanInt() int {
	num, _ := strconv.Atoi(scanString())
	return num
}

func scanString() string {
	sc.Scan()
	return sc.Text()
}

func init() {
	sc.Split(bufio.ScanWords)
}

func main() {
	n := scanInt()

	route := make([][]Node, n)
	weight := make([]int, n)
	for i := 0; i < n; i++ {
		weight[i] = NIL
	}

	for i := 0; i < n; i++ {
		u := scanInt()
		k := scanInt()
		route[i] = make([]Node, k)
		for j := 0; j < k; j++ {
			route[u][j] = Node{id: scanInt(), weight: scanInt()}
		}
	}

	start := Node{id: 0, weight: 0}
	h := &NodeHeap{start}
	heap.Init(h)

	for h.Len() > 0 {
		node := heap.Pop(h).(Node)
		if weight[node.id] != NIL {
			continue
		}
		weight[node.id] = node.weight

		for _, nextNode := range route[node.id] {
			if weight[nextNode.id] != NIL {
				continue
			}
			nextNode.weight += node.weight
			heap.Push(h, nextNode)
		}
	}

	for i, w := range weight {
		fmt.Println(i, w)
	}
}

Python: import sys
from collections import defaultdict
from typing import Dict


def find_shortest_distance(start_vertex: int, n: int,  relations: Dict[int, Dict]) -> Dict[int, int]:
    unreached_vertices = [x for x in range(1, n)]
    distance = {x: sys.maxsize for x in range(n)}
    distance[start_vertex] = 0
    vtx = None
    tmp_distance = [sys.maxsize for x in range(n)]
    for k, v in relations[start_vertex].items():
        tmp_distance[k] = v

    while True:
        min_dist = sys.maxsize
        for i in unreached_vertices:
            dist = tmp_distance[i]
            if dist < min_dist:
                min_dist = dist
                vtx = i
        if min_dist == sys.maxsize:
            break
        unreached_vertices.remove(vtx)
        distance[vtx] = min_dist
        neighbor_vertices = relations[vtx]
        for n_vtx, n_dist in neighbor_vertices.items():
            n_dist_from_start = distance[vtx] + n_dist
            tmp_dist = tmp_distance[n_vtx]
            if tmp_dist == sys.maxsize:
                tmp_distance[n_vtx] = n_dist_from_start
            else:
                if n_dist_from_start < tmp_dist:
                    tmp_distance[n_vtx] = n_dist_from_start
    return distance


def main():
    n = int(input())
    relations = defaultdict(dict)

    lines = sys.stdin.readlines()
    for i in range(n):
        u, k, *vtx_wght = map(int, lines[i].split())
        for v_i in range(k):
            relations[u][vtx_wght[2*v_i]] = vtx_wght[2*v_i+1]

    dist_from_0 = find_shortest_distance(0, n, relations)

    answers = [None] * n
    sorted_dist = sorted(dist_from_0.items(), key=lambda x: x[0])
    for i in range(n):
        answers[i] = f"{sorted_dist[i][0]} {sorted_dist[i][1]}"
    [print(ans) for ans in answers]
    return


main()

Python: #!/usr/bin/python3
from heapq import heappop, heappush
n = int(input())
inf = 100 * 100000

M = [[] for i in range(n)]

for i in range(n):
    L = list(map(int, input().split()))
    u = L[0]
    k = L[1]
    v = L[2::2]
    c = L[3::2]
    for j in range(k):
        M[u].append((v[j], c[j]))
result = [0] * n
S = set()
V = set(range(n))
S.add(0)
d = []
for m in M[0]:
    heappush(d, (m[1], m[0]))
T = V - S

while len(T) != 0:
    c, v = heappop(d)
    while v in S:
        c, v = heappop(d)
    result[v] = c
    S.add(v)
    T.remove(v)
    for m in M[v]:
        if m[0] in T:
            heappush(d, (result[v] + m[1], m[0]))

for i, v in enumerate(result):
    print(i, v)

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

WHITE, GRAY, BLACK = 0, 1, 2
D_MAX = int(1e7 + 1)


def generate_adj_matrix(v_info):
    for v_detail in v_info:
        v_index = int(v_detail[0])
        v_adj_length = int(v_detail[1])
        v_adj_list = v_detail[2:]
        # assert len(v_adj_list) == v_adj_length * 2
        for j in range(0, v_adj_length * 2, 2):
            init_adj_matrix[v_index][v_adj_list[j]] = int(v_adj_list[j + 1])

    return init_adj_matrix


def dijkstra_path():
    path_list[0] = 0

    while True:
        min_cost = D_MAX
        current_vertex = None
        for i in range(vertices_num):
            if color[i] is not BLACK and path_list[i] < min_cost:
                min_cost = path_list[i]
                current_vertex = i

        if min_cost == D_MAX:
            break

        color[current_vertex] = BLACK

        for adj_vertex in range(vertices_num):
            current_adj_weight = adj_matrix[current_vertex].get(str(adj_vertex), -1)
            if current_adj_weight < 0:
                continue
            elif color[adj_vertex] is not BLACK:
                if path_list[current_vertex] + current_adj_weight < path_list[adj_vertex]:
                    path_list[adj_vertex] = path_list[current_vertex] + current_adj_weight
                    parent_list[adj_vertex] = current_vertex
                    color[adj_vertex] = GRAY

    return path_list


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

    parent_list, path_list = [-1] * vertices_num, [D_MAX] * vertices_num
    color = [WHITE] * vertices_num
    init_adj_matrix = tuple(dict() for _ in range(vertices_num))
    adj_matrix = generate_adj_matrix(init_vertices_table)
    ans = dijkstra_path()
    for j in range(vertices_num):
        print(j, ans[j])