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()

	route := make([][]Node, n)
	weight := make([]int, n)
	for i := 0; i < n; i++ {
		weight[i] = NIL
	}

	for i := 0; i < n; i++ {
		u := scanInt()
		k := scanInt()
		route[i] = make([]Node, k)
		for j := 0; j < k; j++ {
			route[u][j] = Node{id: scanInt(), weight: scanInt()}
		}
	}

	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 _, nextNode := range route[node.id] {
			if weight[nextNode.id] != NIL {
				continue
			}
			nextNode.weight += node.weight
			heap.Push(h, nextNode)
		}
	}

	for i, w := range weight {
		fmt.Println(i, w)
	}
}

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


class SingleSourceShortestPath(object):
    __slots__ = ('adj_table', 'distance', 'parent', 'visited')

    def __init__(self, in_data):
        v_num = int(in_data[0])
        vertices = map(lambda x: x.split(), in_data[1:])
        adj_table = tuple(dict() for _ in range(v_num))

        for v_info in vertices:
            source, v_adj_length, *v_adj_list = map(int, v_info)
            # assert len(v_adj_list) == v_adj_length * 2
            for target, cost in zip(v_adj_list[::2], v_adj_list[1::2]):
                adj_table[source][target] = cost

        self.adj_table = adj_table
        self.distance = [float('inf')] * v_num
        self.parent = [-1] * v_num
        self.visited = [WHITE] * v_num

    def path_heap_dijkstra(self, root):
        # path search init
        self.distance[root] = 0
        path_heap = list()
        # heapq: rank by tuple[0], at here it's d[u]
        hp.heappush(path_heap, (0, root))

        while path_heap:
            csp, current = hp.heappop(path_heap)
            self.visited[current] = BLACK

            for adj, cost in self.adj_table[current].items():
                if self.visited[adj] != BLACK:
                    # alt: d[u] + w[u,v]
                    alt_path = self.distance[current] + cost
                    if alt_path < self.distance[adj]:
                        # update path_list
                        self.distance[adj] = alt_path
                        # update heap
                        hp.heappush(path_heap, (alt_path, adj))
                        self.visited[adj] = GRAY
                        self.parent[adj] = current

        return self.distance


if __name__ == '__main__':
    _input = sys.stdin.readlines()
    case = SingleSourceShortestPath(in_data=_input)
    ans = case.path_heap_dijkstra(root=0)
    for i, v in enumerate(ans):
        print(i, v)

Python: from heapq import heappush, heappop
from enum import Enum, auto

INFTY = float('inf')

class Color(Enum):
    WHITE = auto()
    GRAY = auto()
    BLACK = auto()

n = int(input())
adj_list = []
for i in range(n):
    u, k, *kv = list(map(int, input().split(' ')))
    adj_list.append(kv)

colors = []
d = []

def dijkstra(s):
    global d
    colors = [Color.WHITE for i in range(n)]
    d = [INFTY for i in range(n)]
    pque = []
    d[s] = 0

    heappush(pque, (0, s))

    while len(pque) >= 1:
        vert_u = heappop(pque)
        u = vert_u[1]
        colors[u] = Color.BLACK
        if d[u] < vert_u[0]: continue
        i = 0
        while i <= len(adj_list[u])-2:
            v = adj_list[u][i]
            if colors[v] != Color.BLACK:
                if d[u] + adj_list[u][i+1] < d[v]:
                    d[v] = d[u] + adj_list[u][i+1]
                    colors[v] = Color.GRAY
                    heappush(pque, (d[v], v))
            i += 2

dijkstra(0)
for i in range(n):
    print(i, d[i])

Python: import heapq


def dijkstra(adj, s):
    INF = 200000
    n = len(adj)
    state, d, p = [False] * n, [INF] * n, [-1] * n
    d[s] = 0
    pq = [(d[s], s)]
    while pq:
        f, u = heapq.heappop(pq)
        state[u] = True
        if d[u] < f:
            continue
        for v, c in adj[u]:
            if state[v]:
                continue
            if d[u] + c < d[v]:
                d[v] = d[u] + c
                p[v] = u
                heapq.heappush(pq, (d[v], v))
    return d


def main():
    n = int(input())
    adj = [[] for _ in range(n)]
    for _ in range(n):
        u, _, *vc = map(int, input().split())
        for v, c in zip(vc[::2], vc[1::2]):
            adj[u].append((v, c))
    dist = dijkstra(adj, 0)
    for i, d in enumerate(dist):
        print(i, d)


if __name__ == '__main__':
    main()

Python: class RadixHeap:
    __slots__ = ["data", "last", "siz", "used"]

    # (max_key - min_key) <= C
    def __init__(self, N, C):
        self.data = [[] for i in range(C.bit_length() + 1)]
        self.last = self.siz = 0
        self.used = [0]*N

    def push(self, x, key):
        #assert self.last <= x
        self.siz += 1
        self.data[(x ^ self.last).bit_length()].append((x, key))

    def pop(self):
        data = self.data
        used = self.used
        #assert self.siz > 0
        if not data[0]:
            i = 1
            while not data[i]:
                i += 1
            d = data[i]
            new_last, new_key = min(d)
            used[new_key] = 1
            for val in d:
                x, key = val
                if used[key]:
                    self.siz -= 1
                    continue
                data[(x ^ new_last).bit_length()].append(val)
            self.last = new_last
            data[i] = []
        else:
            new_last, new_key = data[0].pop()
            used[new_key] = 1
            self.siz -= 1
        return new_last, new_key

    def __len__(self):
        return self.siz

import sys
readline = sys.stdin.readline
write = sys.stdout.write


N = int(readline())
G = [None] * N
for i in range(N):
    u, k, *V = map(int, readline().split())
    G[i] = [(v, c) for v, c in zip(V[::2], V[1::2])]

def dijkstra(N, G, s):
    que = RadixHeap(N, 10**9 + 1)

    dist = [10**18]*N
    dist[s] = 0
    que.push(0, s)
    while que:
        cost, v = que.pop()
        if dist[v] < cost:
            continue
        for w, c in G[v]:
            if cost + c < dist[w]:
                dist[w] = r = cost + c
                que.push(r, w)
    return dist
dist = dijkstra(N, G, 0)
write("\n".join("%d %d" % (i, d) for i, d in enumerate(dist)))
write("\n")