Go: package main

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

const (
	white int = iota
	gray
	black
)

type node struct {
	id     int
	parent int
	edge   []int
	weight []int
	color  int
}

type graph struct {
	nodes    []node
	distance []int
}

var infty = 1 << 32
var null = -1

func constructgraph() *graph {
	sc := bufio.NewScanner(os.Stdin)
	sc.Split(bufio.ScanWords)
	n := nextInt(sc)

	g := &graph{make([]node, n), make([]int, n)}

	for i := 0; i < n; i++ {
		id := nextInt(sc)
		edges := nextInt(sc)
		n := node{}
		n.id = id
		n.edge = make([]int, edges)
		n.weight = make([]int, edges)
		n.color = white
		for j := 0; j < edges; j++ {
			to := nextInt(sc)
			w := nextInt(sc)
			n.edge[j] = to
			n.weight[j] = w
		}
		g.nodes[id] = n
	}
	return g
}

func nextInt(sc *bufio.Scanner) int {
	sc.Scan()
	v, _ := strconv.Atoi(sc.Text())
	return v
}

func (g *graph) preparedijkstra(s int) {
	for i := 0; i < len(g.nodes); i++ {
		g.nodes[i].color = white
		g.nodes[i].parent = null
		g.distance[i] = infty
	}
	g.distance[s] = 0
}

func (g *graph) dijkstra(s int) []int {
	g.preparedijkstra(s)

	for {
		var u int
		mincost := infty
		for i, d := range g.distance {
			if g.nodes[i].color != black && mincost > d {
				mincost = d
				u = i
			}
		}

		if mincost == infty {
			break
		}

		g.nodes[u].color = black

		for i, e := range g.nodes[u].edge {
			if g.nodes[e].color != black {
				if g.distance[e] > g.distance[u]+g.nodes[u].weight[i] {
					g.distance[e] = g.distance[u] + g.nodes[u].weight[i]
					g.nodes[e].parent = u
					g.nodes[e].color = gray
				}
			}
		}
	}
	return g.distance
}

func printShortestPath(d []int) {
	for i, v := range d {
		fmt.Printf("%d %d\n", i, v)
	}
}

func main() {
	g := constructgraph()
	d := g.dijkstra(0)
	printShortestPath(d)
}

Python: import heapq

n = int(input())
edges = [None] * n
for _ in range(n):
    l = list(map(int, input().split()))
    edges[l[0]] = set((c, j) for j, c in (l[i:i + 2] for i in range(2, l[1] * 2 + 2, 2)))

min_costs = [0] * n
visited = [False] * n
visited[0] = True
queue = list(edges[0])
heapq.heapify(queue)

while queue:
    total_cost, vertex = heapq.heappop(queue)
    if visited[vertex]:
        continue
    visited[vertex] = True
    min_costs[vertex] = total_cost
    for cost, vertex2 in edges[vertex]:
        if not visited[vertex2]:
            heapq.heappush(queue, (total_cost + cost, vertex2))

for r in enumerate(min_costs):
    print(*r)

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)