Go: // ダイクストラのアルゴリズム
package main

import (
	"bufio"
	"fmt"
	"log"
	"math"
	"os"
	"strconv"
	"strings"
)

type color int

const (
	white color = iota // 未訪問
	mst                // MSTとして確定
)

// 頂点
type node struct {
	num       int         // 頂点の番号
	weights   map[int]int // 重みMAP
	parent    *node       // MSTへの重み最小の親
	distFromS int         // 始点からの距離
	color     color
}

func main() {
	scanner := bufio.NewScanner(os.Stdin)
	n := eGetInt(scanner)

	nodes := make([]*node, n)
	for i := 0; i < n; i++ {
		weights := eAtoi((strings.Fields(eGetline(scanner))))
		v := &node{weights[0], make(map[int]int, weights[1]), nil, math.MaxInt32, white}
		for j := 0; j < weights[1]; j++ {
			k := weights[j*2+2] // 相手の頂点名
			w := weights[j*2+3] // 重み
			v.weights[k] = w
		}
		nodes[i] = v
	}

	// 初回はnode[0]がMSTに入るように
	nodes[0].distFromS = 0

	for { // 全部チェックするまで

		// どの頂点を新たにMSTに取り込むか

		var minNode *node
		min := math.MaxInt32
		for _, v := range nodes {
			if v.color == mst {
				continue
			}
			if v.distFromS < min {
				min = v.distFromS
				minNode = v
			}
		}
		if minNode == nil {
			// すべて完了している.
			break
		}

		// MSTに追加する頂点決定
		minNode.color = mst

		// fmt.Printf(">[%v]\n", minNode)
		// MSTに属していない頂点それぞれについて,Startからの最小の重みの距離を更新
		for i, v := range nodes {
			if v.color == mst {
				continue
			}
			w, ok := minNode.weights[i]
			if !ok {
				// minNodeと接してない
				continue
			}

			if minNode.distFromS+w < v.distFromS {
				// minNode経由の距離がもっとも重みが少ないので親を変更
				v.distFromS = minNode.distFromS + w
				v.parent = minNode
				// fmt.Printf("[%v %v]\n", v, minNode)
			}
		}
		// fmt.Printf("<\n")
	}

	for i, v := range nodes {
		fmt.Printf("%d %d\n", i, v.distFromS)
	}
}

func eGetInt(scanner *bufio.Scanner) int {
	t := eAtoi(strings.Fields(eGetline(scanner)))
	return t[0]
}

func eGetline(p *bufio.Scanner) string {
	if !p.Scan() {
		if err := p.Err(); err != nil {
			log.Fatal(err.Error())
		}
		return ""
	}
	return p.Text()
}

func eAtoi(s []string) []int {
	ints := make([]int, len(s))
	var err error
	for i, e := range s {
		ints[i], err = strconv.Atoi(e)
		if err != nil {
			log.Fatal(err.Error())
		}
	}
	return ints
}

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)