Go: package main

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

// I/O
type Scanner struct {
	sc *bufio.Scanner
}

func NewScanner() *Scanner {
	sc := bufio.NewScanner(os.Stdin)
	sc.Split(bufio.ScanWords)
	sc.Buffer(make([]byte, 1024), int(1e+9))
	return &Scanner{sc}
}

func (s *Scanner) nextStr() string {
	s.sc.Scan()
	return s.sc.Text()
}

func (s *Scanner) nextInt() int {
	i, e := strconv.Atoi(s.nextStr())
	if e != nil {
		panic(e)
	}
	return i
}

func (s *Scanner) nextFloat() float64 {
	f, e := strconv.ParseFloat(s.nextStr(), 64)
	if e != nil {
		panic(e)
	}
	return f
}

func (s *Scanner) nextRuneSlice() []rune {
	return []rune(s.nextStr())
}

func (s *Scanner) nextIntSlice(n int) []int {
	res := make([]int, n)
	for i := 0; i < n; i++ {
		res[i] = s.nextInt()
	}
	return res
}

func (s *Scanner) nextFloatSlice(n int) []float64 {
	res := make([]float64, n)
	for i := 0; i < n; i++ {
		res[i] = s.nextFloat()
	}
	return res
}

// Arithmetic
func max(nums ...int) int {
	m := nums[0]
	for _, i := range nums {
		if m < i {
			m = i
		}
	}
	return m
}

func min(nums ...int) int {
	m := nums[0]
	for _, i := range nums {
		if m > i {
			m = i
		}
	}
	return m
}

func abs(x int) int {
	if x > 0 {
		return x
	}
	return -x
}

func pow(x, y int) int {
	res := 1
	for i := 0; i < y; i++ {
		res *= x
	}
	return res
}

func ceil(a, b int) int {
	if a%b == 0 {
		return a / b
	} else {
		return a/b + 1
	}
}

// Sort
type RuneSlice []rune

func (a RuneSlice) Len() int           { return len(a) }
func (a RuneSlice) Less(i, j int) bool { return a[i] < a[j] }
func (a RuneSlice) Swap(i, j int)      { a[i], a[j] = a[j], a[i] }

// Main
const INF = 1 << 60

type Edge struct {
	to, cost int
}

type Node struct {
	id, cost int
}

type PQ []Node

func (pq PQ) Len() int           { return len(pq) }
func (pq PQ) Less(i, j int) bool { return pq[i].cost < pq[j].cost }
func (pq PQ) Swap(i, j int)      { pq[i], pq[j] = pq[j], pq[i] }

func (pq *PQ) Push(x interface{}) {
	*pq = append(*pq, x.(Node))
}

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

func main() {
	sc := NewScanner()
	wtr := bufio.NewWriter(os.Stdout)
	N := sc.nextInt()
	E := make([][]Edge, N)
	for i := 0; i < N; i++ {
		id, k := sc.nextInt(), sc.nextInt()
		E[id] = make([]Edge, k)
		for j := 0; j < k; j++ {
			to, cost := sc.nextInt(), sc.nextInt()
			E[id][j] = Edge{to, cost}
		}
	}

	d := make([]int, N)
	for i := 0; i < N; i++ {
		d[i] = INF
	}
	done := make([]bool, N)
	pq := &PQ{}
	heap.Init(pq)
	d[0] = 0
	heap.Push(pq, Node{0, 0})
	for pq.Len() > 0 {
		cur := heap.Pop(pq).(Node).id
		if done[cur] {
			continue
		}
		done[cur] = true
		for i := 0; i < len(E[cur]); i++ {
			to, cost := E[cur][i].to, E[cur][i].cost+d[cur]
			if !done[to] && cost < d[to] {
				d[to] = cost
				heap.Push(pq, Node{to, cost})
			}
		}
	}

	for i := 0; i < N; i++ {
		fmt.Fprintln(wtr, i, d[i])
	}
	wtr.Flush()
}

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)