Go: package main

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

//make priority queue
type Item struct {
	id       int
	priority int // this state is priority and distans from start
	index    int
}

type PriorityQueue []*Item

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

// we want the ascending-priority-queue.
// So we use less than here.
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 = j
	pq[j].index = i
}

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
}

func (pq *PriorityQueue) update(dist int, id int) {
	for _, i := range *pq {
		if i.id == id {
			if i.priority > dist {
				i.priority = dist
			}
		}
	}
}

// the main code
func nextInt(sc *bufio.Scanner) int {
	sc.Scan()
	n, _ := strconv.Atoi(sc.Text())
	return n
}

func dikstra(dist [][]int, n int) []int {
	// preparate priority queue
	inf := 1 << 30
	pq := make(PriorityQueue, n)
	shortests := make([]int, n)
	for i := 0; i < n; i++ {
		pq[i] = &Item{
			id:       i,
			priority: inf,
			index:    i,
		}

		shortests[i] = inf
	}
	pq[0].priority = 0
	shortests[0] = 0
	heap.Init(&pq)

	for pq.Len() > 0 {
		item := heap.Pop(&pq).(*Item)
		shortests[item.id] = item.priority
		for id, d := range dist[item.id] {
			if d != -1 {
				pq.update(item.priority+d, id)
			}
		}
		heap.Init(&pq)
	}
	return shortests
}

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

	// init
	n := nextInt(sc)
	dist := make([][]int, n)
	for i := 0; i < n; i++ {
		dist[i] = make([]int, n)
		for j := 0; j < n; j++ {
			dist[i][j] = -1
		}
	}

	// std Input
	for i := 0; i < n; i++ {
		u := nextInt(sc)
		k := nextInt(sc)
		for j := 0; j < k; j++ {
			v, c := nextInt(sc), nextInt(sc)
			dist[u][v] = c
		}
	}

	shortests := dikstra(dist, n)
	for i, d := range shortests {
		fmt.Printf("%d %d\n", i, d)
	}
}

Python: n = int(input())

INF = 2147483647
M = [[INF for j in range(n)] for i in range(n)]
check, dist = [0 for i in range(n)], [INF for i in range(n)]


def dijkstra(s):
    p = [-1 for i in range(n)]
    dist[s] = 0

    while True:
        min_cost = INF
        for i in range(n):
            if check[i] != 2 and dist[i] < min_cost:
                min_cost = dist[i]
                u = i

        if min_cost == INF:
            break

        check[u] = 2

        for v in range(n):
            if check[v] != 2 and M[u][v] != INF:
                if dist[u] + M[u][v] < dist[v]:
                    dist[v], p[v] = dist[u] + M[u][v], u
                    check[v] = 1


def main():
    for i in range(n):
        data = list(map(int, input().split()))
        for j in range(data[1]):
            M[data[0]][data[2*(j+1)]] = data[2*(j+1)+1]

    dijkstra(0)

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


if __name__ == '__main__':
    main()

Python: def createMatrix():
    matrix = [[INFTY] * n for i in range(n)]
    for i in range(n):
        u, k, *v = map(int, input().split())
        for j in range(0, k*2, 2):
            matrix[i][v[j]] = v[j+1]
    return matrix

def dijkstra():
    d[0] = 0
    p[0] = -1

    while True:
        mincost = INFTY
        # cost が最小の node を選択
        for i in range(n):
            if status[i] != VISITED and d[i] < mincost:
                mincost = d[i]
                u = i

        if mincost == INFTY:
            break

        status[u] = VISITED

        # u と v をつなぐ edge のうち最小の経路のコストの合計に更新
        for v in range(n):
            if status[v] != VISITED and matrix[u][v] != INFTY:
                if d[u] + matrix[u][v] < d[v]:
                    d[v] = d[u] + matrix[u][v]
                    p[v] = u
                    status[v] = VISITING

import sys
# sys.stdin = open('input.txt')

n = int(input())
NOT_VISITED = 0 # WHITE
VISITING = 1 # GRAY
VISITED = 2 # BLACK
INFTY = 10**21

matrix = createMatrix()
status =  [NOT_VISITED] * n
d = [INFTY] * n
p = [-1] * n

dijkstra()

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

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
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 search init
    start_vertex_index = 0
    path_list[start_vertex_index] = 0
    path_heap = []
    # heapq: compare by tuple[0]
    hp.heappush(path_heap, (path_list[start_vertex_index], start_vertex_index))
    while len(path_heap) >= 1:
        current_vertex = hp.heappop(path_heap)[1]

        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:
                # d[u] + w[u,v]
                alt_path = path_list[current_vertex] + current_adj_weight
                if alt_path < path_list[adj_vertex]:
                    # update path_list
                    path_list[adj_vertex] = alt_path
                    # update heap
                    hp.heappush(path_heap, (alt_path, adj_vertex))
                    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 i, v in enumerate(ans):
        print(i, v)

Python: n = int(input())

adj = [[False for j in range(n)] for i in range(n)]

for u in range(n):
    x = list(map(int, input().split()))
    for v, c in zip(x[2::2], x[3::2]):
        adj[u][v] = c

weights = [9900000] * n


def search(goal, path, weight):
    e = path[-1]
    if (e == goal) and (weight < weights[goal]):
        weights[goal] = weight
    elif weight < weights[goal]:
        for v, c in enumerate(adj[e]):
            if (v not in path) and (c is not False):
                path.append(v)
                weight += c
                search(goal, path, weight)
                weight -= c
                path.pop()


for i in range(n):
    search(i, [0], 0)

for v, w in enumerate(weights):
    print(v, w)