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: if __name__ == '__main__':
    from sys import stdin
    input = stdin.readline

    import heapq
    from copy import deepcopy

    INFTY = 2**21
    WHITE = 0
    GRAY = 1
    BLACK = 2

    n = int(input())

    adj = [0]*n

    for _ in range(n):
        u, k, *vc = map(int, input().split())
        vc_tuple = [0]*k
        for i, (v, c) in enumerate(zip(vc[::2], vc[1::2])):
            # pythonにはvectorないので、tupleで代用
            vc_tuple[i] = (v, c)
        adj[u] = vc_tuple

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

        d[0] = 0
        PQ = [(0, 0)]
        heapq.heapify(PQ) # PQを優先度付きキューにする
        color[0] = GRAY
        while PQ:  # PQの長さ0でwhile抜ける
            f = heapq.heappop(PQ)
            u = f[1]
            color[u] = BLACK

            # 最小値を取り出し、それが最短でなければ無視
            if d[u] < f[0]: # -1かけない理由は9行下のコメント参照
                continue

            for adj_u in adj[u]:
                v = adj_u[0]
                if color[v] == BLACK:
                    continue
                if d[v] > d[u]+adj_u[1]:
                    d[v] = d[u]+adj_u[1]
                    # pythonのheapqはmin-ヒープを使っているので-1かけなくて良い
                    heapq.heappush(PQ, (d[v], v))
                    color[v] = GRAY

        for i in range(n):
            print(str(i) + ' ' + str(-1 if d[i] == INFTY else d[i]))

    dijkstra()

    """

    nodes = [[] for _ in range(n)]

    for _ in range(n):
        u, k, *vc = map(int, input().split())
        cv = [0]*k
        for i, (v, c) in enumerate(zip(vc[::2], vc[1::2])):
            cv[i] = (c, v)
        nodes[u] = cv

    d = [INFTY]*n
    d[0] = 0

    d_node = nodes[0]
    heapq.heapify(d_node)

    visited = [False]*n
    visited[0] = True

    while d_node:
        min_c, min_v = heapq.heappop(d_node)
        if visited[min_v]:
            continue
        visited[min_v] = True
        d[min_v] = min_c
        for c, v in nodes[min_v]:
            heapq.heappush(d_node, (min_c+c, v))

    for u, dist in enumerate(d):
        print(str(u) + ' ' + str(dist))
    """

Python: import heapq


class Graph(object):

    class Node:
        def __init__(self, dist: int, number: int):
            self.dist = dist
            self.number = number

        def __lt__(self, other):
            return self.dist < other.dist \
                   or (self.dist == other.dist
                       and self.number < other.number)

        def __le__(self, other):
            return self.dist <= other.dist

        def __gt__(self, other):
            return other <= self

        def __ge__(self, other):
            return other < self

        def __str__(self):
            return "Node: (" + str(self.number) + ", " \
                   + str(self.dist) + ")"

    class Edge:
        def __init__(self, to: int, cost: int):
            self.to = to
            self.cost = cost

        def __str__(self):
            return "Edge: (" + str(self.to) + ", " \
                   + str(self.cost) + ")"

    INF = 10e10

    def __init__(self, node_n: int, start: int):
        self.node_n = node_n
        self.start = start
        self.edges = [{} for _ in range(self.node_n)]
        self.dist = [self.INF for _ in range(self.node_n)]

    def set_edge(self, from_pos: int, to_pos: int, cost: int, reversible: bool) -> None:
        self.edges[from_pos][to_pos] = (self.Edge(to_pos, cost))
        if reversible:
            self.edges[to_pos][from_pos] = (self.Edge(from_pos, cost))

    def solve(self) -> list:
        raise NotImplementedError


class Dijkstra(Graph):
    hq = []
    prev: list

    def __init__(self, node_n: int, start: int):
        super(Dijkstra, self).__init__(node_n, start)
        self.dist[self.start] = 0
        self.prev = [None for _ in range(node_n)]

    def solve(self) -> list:
        heapq.heappush(self.hq, self.Node(0, self.start))

        while len(self.hq) != 0:
            node = heapq.heappop(self.hq)
            if node.dist > self.dist[node.number]:
                continue

            for edge in self.edges[node.number].values():
                alt = self.dist[node.number] + edge.cost
                if self.dist[edge.to] > alt:
                    self.dist[edge.to] = alt
                    self.prev[edge.to] = node.number
                    heapq.heappush(self.hq, self.Node(alt, edge.to))

        return self.dist


if __name__ == '__main__':
    n = int(input())
    graph = Dijkstra(n, 0)

    for _ in range(n):
        buff = list(map(int, input().split()))
        u = buff[0]
        k = buff[1]
        for i in range(k):
            graph.set_edge(u,
                           buff[2 + i * 2],
                           buff[3 + i * 2],
                           False)
    dist = graph.solve()
    for i, d in enumerate(dist):
        print(i, d)