Go: package main

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

const NIL = -1

type Node struct {
	id     int
	weight int
}

func init() {
	sc.Split(bufio.ScanWords)
}

type NodeHeap []Node

func (h NodeHeap) Len() int           { return len(h) }
func (h NodeHeap) Less(i, j int) bool { return h[i].weight < h[j].weight }
func (h NodeHeap) Swap(i, j int)      { h[i], h[j] = h[j], h[i] }

func (h *NodeHeap) Push(x interface{}) {
	*h = append(*h, x.(Node))
}

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

var sc = bufio.NewScanner(os.Stdin)

func scanInt() int {
	num, _ := strconv.Atoi(scanString())
	return num
}

func scanString() string {
	sc.Scan()
	return sc.Text()
}

func init() {
	sc.Split(bufio.ScanWords)
}

func main() {
	n := scanInt()

	list := make([][]int, n)
	weight := make([]int, n)
	for i := range list {
		list[i] = make([]int, n)
		weight[i] = NIL
		for j := range list[i] {
			list[i][j] = NIL
		}
	}

	for i := 0; i < n; i++ {
		u := scanInt()
		k := scanInt()
		for j := 0; j < k; j++ {
			v := scanInt()
			w := scanInt()
			list[u][v] = w
		}
	}

	start := Node{id: 0, weight: 0}
	h := &NodeHeap{start}
	heap.Init(h)

	for h.Len() > 0 {
		node := heap.Pop(h).(Node)
		if weight[node.id] != NIL {
			continue
		}
		weight[node.id] = node.weight

		for i, w := range list[node.id] {
			if w == NIL {
				continue
			}
			heap.Push(h, Node{id: i, weight: w + node.weight})
		}
	}

	w := bufio.NewWriter(os.Stdout)
	for i := 0; i < n; i++ {
		fmt.Fprint(w, i)
		fmt.Fprint(w, " ")
		fmt.Fprint(w, weight[i])
		fmt.Fprintln(w)
	}
	w.Flush()
}

Python: from heapq import heappush, heappop
from typing import List, Tuple
import sys


if __name__ == "__main__":
    num_vertices = int(input())
    adj_list: List[List[Tuple[int, int]]] = [[] for _ in range(num_vertices)]

    for _ in range(num_vertices):
        vertex, adj_num, *adjs = map(lambda x: int(x), input().split())
        for i in range(adj_num):
            # (cost, adj)
            adj_list[vertex].append((adjs[2 * i + 1], adjs[2 * i]))

    distances: List[int] = [sys.maxsize] * num_vertices
    distances[0] = 0
    que: List[Tuple[int, int]] = []
    heappush(que, (0, 0))

    while [] != que:
        base_distance, parent = heappop(que)
        for cost, adj in adj_list[parent]:
            distance = base_distance + cost
            if distance < distances[adj]:
                distances[adj] = distance
                heappush(que, (distance, adj))

    for vertex, distance in enumerate(distances):
        print(f"{vertex} {distance}")

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: n = int(input())

adj = [[100001 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

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

distance = [9900001] * n


def dijkstra(s):
    distance[s] = 0

    while True:
        mincost = 9900001
        for i in unvisited:
            if distance[i] < mincost:
                mincost = distance[i]
                u = i

        if mincost == 9900001:
            break

        unvisited.remove(u)

        for v in unvisited:
            weight_uv = adj[u][v]
            if weight_uv != 100001:
                t_d = distance[u] + weight_uv
                if t_d < distance[v]:
                    distance[v] = t_d



dijkstra(0)

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

Python: #!/usr/bin/python3
n = int(input())
inf = 100 * 100000

M = [[inf for i in range(n)] for j in range(n)]

for i in range(n):
    L = list(map(int, input().split()))
    u = L[0]
    k = L[1]
    v = L[2::2]
    c = L[3::2]
    for j in range(k):
        M[u][v[j]] = M[v[j]][u] = c[j]

S = set()
V = set(range(n))
S.add(0)
d = [inf for i in range(n)]
d[0] = 0
count = 0
while len(V - S) != 0:
    T = V - S
    nd = [inf for i in range(n)]
    for s in S:
        for m, c in enumerate(M[s]):
            if d[s] + c < nd[m] and m in T:
                nd[m] = d[s] + c

    min_nd = min(nd)
    u = nd.index(min_nd)
    S.add(u)
    d[u] = min_nd


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

Python: INF = 1000000


def diikstraMethd(G, s):
    # ?????????
    n = len(G)
    # White:0 Gyay:1 Black:2
    color = [0 for _ in range(n)]
    d = [INF for _ in range(n)]
    p = [None for _ in range(n)]

    d[s] = 0

    while True:
        mincost = INF
        for i in range(n):
            if color[i] != 2 and d[i] < mincost:
                mincost = d[i]
                u = i

        if mincost == INF: break

        color[u] = 2

        for v in range(n):
            if color[v] != 2 and M[u][v] != INF:
                if d[u] + M[u][v] < d[v]:
                    d[v] = d[u] + M[u][v]
                    p[v] = u
                    color[u] = 1

    return d


if __name__ == '__main__':
    n = int(input())
    M = [[INF for _ in range(n)] for i in range(n)]
    for _ in range(n):
        tmp = list(map(int, input().split()))
        u = tmp.pop(0)
        k = tmp.pop(0)
        for _ in range(k):
            v = tmp.pop(0)
            c = tmp.pop(0)
            M[u][v] = c
    d = diikstraMethd(M, 0)

    for i in range(n):
        print('{0} {1}'.format(i, d[i]))

Python: import sys
inf = float('inf')

def debug(x, table):
    for name, val in table.items():
        if x is val:
            print('DEBUG:{} -> {}'.format(name, val), file=sys.stderr)
            return None

def SSSP(n, Adj):
    d = [inf] * n
    p = [-1] * n
    checked = [False] * n
    d[0] = 0
    checked[0] = True
    u = 0

    for i in range(n - 1):
        for v, cost in Adj[u]:
            if d[u] + cost < d[v]:
                p[v] = u
                d[v] = d[u] + cost

        min_n = 0
        min_w = inf
        for v in range(n):
            if not checked[v] and d[v] < min_w:
                min_n = v
                min_w = d[v]

        u = min_n
        checked[u] = True

    return d

def solve():
    n = int(input())
    Adj = [[] for i in range(n)]

    for i in range(n):
        u, k, *line = [int(i) for i in input().split()]
        for j in range(k):
            Adj[u].append((line[2*j], line[2*j + 1]))

    # debug(Adj, locals())

    d = SSSP(n, Adj)

    for i in range(n):
        print(i, d[i])

if __name__ == '__main__':
    solve()