Go: package main

import (
	"fmt"
	"os"
	"bufio"
	"strings"
	"strconv"
)
var MAX = 1000000
type Vertex struct{
	Value int
	Routes map[int]int
	Done bool
}
func NewVertex(value int) *Vertex{
	routes := make(map[int]int)
	// for i, _ := range routes {
	// 	routes[i] = MAX
	// }
	return &Vertex{ value, routes, false }
}

func (v *Vertex) SetRoute(key, weight int) {
	v.Routes[key] = weight
}

type Path struct {
	Key int
	Weight int
}

var count = 0
func ShortestRoutes(list []*Vertex) []int {
	// create result table
	result  := make([]int, len(list))
	// fmt.Println(result)
	for i, _ := range result {
		result[i] = MAX
	}

	queue := make([]Path, 0)
	queue = append(queue, Path{0, 0})
	result[0] = 0

	for len(queue) != 0 {
		count++
		path := queue[0]
		queue = queue[1:]
		for key, weight := range list[path.Key].Routes {
			// fmt.Println(list[path.Key].Routes)
			// set to result
			// fmt.Printf("Path(%d, %d) ? result[%d] => %d, wieght: %d\n", path.Key, path.Weight, key, result[key], weight)
			if path.Weight + weight < result[key] {
				result[key] = path.Weight + weight 
				queue = append(queue, Path{key, result[key]})
			// } else if !list[key].Done {
			// 	queue = append(queue, Path{key, result[key]})
			}
		}
		list[path.Key].Done = true
	}
	return result
}
func main() {
	var n int
	fmt.Scanf("%d", &n)
	list := make([]*Vertex, n)
	scanner := bufio.NewScanner(os.Stdin)
	for i := 0; i < n; i++ {
		scanner.Scan()
		elements := strings.Split(scanner.Text(), " ")
		value, _ := strconv.Atoi(elements[0])
		list[i] = NewVertex(value)
		for j := 2; j < len(elements); j += 2 {
			key, _    := strconv.Atoi(elements[j])
			weight, _ := strconv.Atoi(elements[j + 1])
			list[i].SetRoute(key, weight)
		}
	}

	result := ShortestRoutes(list)
	for i := 0; i < len(result); i++ {
		fmt.Printf("%d %d\n", i, result[i]);
	}
	// fmt.Printf("count: %d\n", count)
}

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][int(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_index = hp.heappop(path_heap)[1]

        color[current_vertex_index] = BLACK

        for adj_vertex_index in range(vertices_num):
            current_adj_weight = adj_matrix[current_vertex_index].get(adj_vertex_index, -1)
            if current_adj_weight < 0:
                continue
            elif color[adj_vertex_index] is not BLACK:
                # d[u] + w[u,v]
                alt_path = path_list[current_vertex_index] + current_adj_weight
                if alt_path < path_list[adj_vertex_index]:
                    # update path_list
                    path_list[adj_vertex_index] = alt_path
                    # update heap
                    hp.heappush(path_heap, (alt_path, adj_vertex_index))
                    parent_list[adj_vertex_index] = current_vertex_index
                    color[adj_vertex_index] = 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: import heapq

class Dijkstra:
    """
        Dijkstra's algorithm: find the shortest paths from a vertex
        complexity:
            O(E + logV)
    """
    def __init__(self, V, E, start, INF=10**9):
        """
        :param V: the number of vertices
        :param E: adjacency list (all edge in E must be non negative)
        :param start: start vertex
        :param INF: Infinity distance
        """
        self.V = V
        self.E = E
        self.dijkstra(start, INF)

    def dijkstra(self, start, INF):
        que = list()
        self.distance = [INF] * self.V
        self.prev = [-1] * self.V
        self.distance[start] = 0
        heapq.heappush(que, (0, start))
        while len(que) > 0:
            dist, fr = heapq.heappop(que)
            if self.distance[fr] < dist:
                continue
            for to, cost in self.E[fr]:
                if self.distance[fr] + cost < self.distance[to]:
                    self.distance[to] = self.distance[fr] + cost
                    heapq.heappush(que, (self.distance[to], to))
                    self.prev[to] = fr

    def get_path(self, end):
        path = [end]
        while self.prev[end] != -1:
            end = self.prev[end]
            path.append(end)
            return path[::-1]


V = int(input())
edges = [[] for _ in range(V)]
for _ in range(V):
    u, _, *e = map(int, input().split())
    for t, d in zip(e[::2], e[1::2]):
        edges[u].append((t, d))

djk = Dijkstra(V, edges, 0)
for i, d in enumerate(djk.distance):
    print(i, d)

Python: import heapq


INFINITY = 10 ** 10
WHITE = 0
GRAY = 1
BLACK = 2


n = int(input())
dict_adjacency = {}

for _ in range(n):
    u, k, *list_num = map(int, input().split())

    list_temp = []

    dict_adjacency[str(u)] = {}

    for i in range(0, k * 2, 2):
        dict_adjacency[str(u)][str(list_num[i])] = list_num[i + 1]


d = [INFINITY] * n

def dijkstra(top_start):
    color = [WHITE] * n

    d[top_start] = 0
    h = []

    heapq.heappush(h, (d[top_start], top_start))

    while len(h) >= 1:
        cost_now, top_now = heapq.heappop(h)

        color[top_now] = BLACK

        if d[top_now] < cost_now:
            continue

        for top_next in dict_adjacency[str(top_now)].keys():
            top_next = int(top_next)
            if color[top_next] == BLACK:
                continue


            cost_next = d[top_now] + dict_adjacency[str(top_now)][str(top_next)]
            if cost_next < d[top_next]:
                d[top_next] = cost_next
                color[top_next] = GRAY
                heapq.heappush(h, (d[top_next], top_next))


dijkstra(top_start = 0)

for i, cost in enumerate(d):
    print(i, cost)

Python: #!/usr/bin/env python
from __future__ import division, print_function
from sys import stdin, maxsize


def main():
    num = int(stdin.readline())

    edges = []
    for _ in range(num):
        ns = [int(s) for s in stdin.readline().split()]
        for i in range(ns[1]):
            edges.append((ns[0], ns[2*i+2], ns[2*i+3]))

    dis = [maxsize] * num
    dis[0] = 0

    while 1:
        update = False
        for from_, to, cost in edges:
            if dis[from_] < maxsize and dis[to] > cost + dis[from_]:
                dis[to] = cost + dis[from_]
                update = True

        if not update:
            break

    for i, d in enumerate(dis):
        print(i, d)


main()