Go: package main

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

type Item struct {
	value    int // The value of the item; arbitrary.
	priority int // The priority of the item in the queue.
	// The index is needed by update and is maintained by the heap.Interface methods.
	index int // The index of the item in the heap.
}
type PriorityQueue []*Item

func (pq PriorityQueue) Len() int { return len(pq) }
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 = i
	pq[j].index = j
}
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
}

type Q struct {
	pq *PriorityQueue
	ds map[int]int // It has always same value as pq. For random access.
}

func newQ() *Q {
	pq := new(PriorityQueue)
	heap.Init(pq)
	return &Q{
		pq: pq,
		ds: make(map[int]int),
	}
}
func (q *Q) pop() (u, d int) {
	item := heap.Pop(q.pq).(*Item)
	delete(q.ds, item.value)
	return item.value, item.priority
}
func (q *Q) get(u int) (int, bool) { // returns d
	d, ok := q.ds[u]
	return d, ok
}
func (q *Q) set(u, d int) {
	q.ds[u] = d
	for _, item := range *q.pq {
		if item.value != u {
			continue
		}

		item.priority = d
		heap.Fix(q.pq, item.index)
		return
	}
	heap.Push(q.pq, &Item{
		priority: d,
		value:    u,
	})
}
func (q *Q) len() int {
	return len(q.ds)
}

func main() {
	r := bufio.NewReader(os.Stdin)

	var n int
	fmt.Fscan(r, &n)
	cs := make([]map[int]int, n) // []v_i -> c_i
	for h := 0; h < n; h++ {
		var u, k int
		fmt.Fscan(r, &u, &k)
		m := make(map[int]int)
		for i := 0; i < k; i++ {
			var v, c int
			fmt.Fscan(r, &v, &c)
			m[v] = c
		}

		cs[u] = m
	}

	q := newQ()
	q.set(0, 0)
	visited := make(map[int]struct{})
	out := make([]int, n)

	for q.len() > 0 {
		u, d := q.pop()
		for uu, c := range cs[u] {
			// Consider the connection between u and uu.
			if _, ok := visited[uu]; ok {
				continue
			}
			dd := d + c
			if d, ok := q.get(uu); !ok || d > dd {
				q.set(uu, dd)
			}
		}

		out[u] = d
		visited[u] = struct{}{}
	}

	for u, d := range out {
		fmt.Println(u, d)
	}
}

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(5e10 + 1)


def generate_adj_table(v_table):
    for each in v_table:
        v_index, v_adj_length, *v_adj_list = map(int, each)
        # assert len(v_adj_list) == v_adj_length * 2
        for pair in zip(v_adj_list[::2], v_adj_list[1::2]):
            init_adj_table[v_index][pair[0]] = pair[1]

    return init_adj_table


def dijkstra_path_heap():
    # path search init
    path_list[init_vertex_index] = 0
    path_heap = []
    # heapq: rank by tuple[0], at here it's d[u]
    hp.heappush(path_heap, (0, init_vertex_index))

    while len(path_heap) >= 1:
        current_vertex = hp.heappop(path_heap)[1]

        color[current_vertex] = BLACK

        for adj_vertex, adj_weight in adj_table[current_vertex].items():
            if color[adj_vertex] is not BLACK:
                # alt: d[u] + w[u,v]
                alt_path = path_list[current_vertex] + 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 = 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_table = tuple(dict() for _ in range(vertices_num))
    init_vertex_index = 0

    adj_table = generate_adj_table(init_vertices_table)
    ans = dijkstra_path_heap()
    for i, v in enumerate(ans):
        print(i, v)

Python: #coding: utf-8

inf = 1000000000000


def dijkstra(s):
    d = [inf for i in range(n)]
    color = ["white" for i in range(n)]
    p = [-1 for i in range(n)]
    d[s] = 0

    while True:
        mincost = inf
        for i in range(n):
            if color[i] != "black" and d[i] < mincost:
                mincost = d[i]
                u = i
        if mincost == inf:
            break

        color[u] = "black"

        for v in range(n):
            if color[v] != "black" and mtrx[u][v] != False:
                if d[u] + mtrx[u][v] < d[v]:
                    d[v] = d[u] + mtrx[u][v]
                    p[v] = u
                    color[v] = "gray"
    return d

n = int(input())
mtrx = [[False for j in range(n)] for i in range(n)]
for i in range(n):
    data = list(map(int,input().split()))
    k = data[1]
    for num in range(k):
        mtrx[i][data[2+2*num]] = data[2+2*num+1]

d = dijkstra(0)

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

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: import sys

f_i = sys.stdin

n = int(f_i.readline())

adj = [[100001 for j in range(n)] for i in range(n)]

for x in f_i:
    x = list(map(int, x.split()))
    u = x[0]
    for v, c in zip(x[2::2], x[3::2]):
        adj[u][v] = c

unvisited = [v for v in range(n)]

distance = [999900001] * n
distance[0] = 0

class VCost:
    def __init__(self, v, cost):
        self.v = v
        self.cost = cost
    def __lt__(self, other):
        return self.cost < other.cost

import heapq

vcost = [VCost(v, 999900001) for v in range(n)]
vcost[0].cost = 0

def dijkstra():
    while vcost:
        uc = heapq.heappop(vcost)
        
        for vc in vcost:
            weight_uv = adj[uc.v][vc.v]
            if weight_uv != 100001:
                t_cost = uc.cost + weight_uv
                if t_cost < vc.cost:
                    distance[vc.v] = t_cost
                    vc.cost = t_cost
                    
        heapq.heapify(vcost)



dijkstra()

for v, d in enumerate(distance):
    print(v, d)

Python: # -*- coding: utf-8 -*-
from heapq import heapify, heappop, heappush

N = int(input())
INF = float("inf")
d = [INF for n in range(N)]
d[0] = 0
adj = [[] for _ in range(N)]

searched = [False for _ in range(N)]
searched[0] = True

for n in range(N):
    inp = tuple(map(int, input().split()))
    assert n == inp[0]
    for i in range(inp[1]):
        adj[n] = list(zip(inp[2::2], inp[3::2]))

heap = [[0, 0]]

while len(heap):
    pcost, p = heappop(heap)
    searched[p] = True
    
    for v, c in adj[p]:
        if not searched[v]:
            new_cost = pcost + c
            if new_cost < d[v]:
                d[v] = new_cost
                heappush(heap, [new_cost, v])

for n in range(N):
    print("{} {}".format(n, d[n]))