Go: package main

import (
	"bufio"
	"fmt"
	"os"
	"strconv"
)

const BIG_COST = 200000

type Path struct {
	node int
	cost int
}

func main() {
	sc := bufio.NewScanner(os.Stdin)
	sc.Split(bufio.ScanWords)

	nNodes := scanInt(sc)

	// 各頂点につながる頂点一覧を得るための隣接リスト
	graph := make([][]Path, nNodes)

	for i := 0; i < nNodes; i++ {
		u := scanInt(sc)
		k := scanInt(sc)
		graph[i] = make([]Path, k)
		for d := 0; d < k; d++ {
			graph[u][d] = Path{
				node: scanInt(sc),
				cost: scanInt(sc),
			}
		}
	}

	// 0 から各頂点への最小コストを保存する配列
	minCosts := make([]int, nNodes)

	minCosts[0] = 0
	for i := 1; i < nNodes; i++ {
		minCosts[i] = BIG_COST
	}

	// 各頂点が調査済みかどうかを保持する配列
	checked := make([]bool, nNodes)

	// 最小コストのパスを高速に取得するためのヒープ。
	// コストが小さいものほどルートに来るようにする。
	heap := NewHeap(func(a, b Path) bool {
		return a.cost < b.cost
	})

	heap.insert(Path{node: 0, cost: 0})
	for heap.size > 0 {
		u := heap.extractMax()

		// 隣接行列を使っていた時とは違い、ヒープには
		// 同じノードへのパスが複数含まれうる。そのため既によりコストの低い
		// パスが見つかっている場合は無視する。
		if minCosts[u.node] < u.cost {
			continue
		}

		checked[u.node] = true

		for _, v := range graph[u.node] {
			cost := v.cost + u.cost
			if !checked[v.node] && cost < minCosts[v.node] {
				minCosts[v.node] = cost
				heap.insert(Path{node: v.node, cost: cost})
			}
		}
	}

	w := bufio.NewWriter(os.Stdout)
	for i, cost := range minCosts {
		fmt.Fprintf(w, "%d %d\n", i, cost)
	}
	w.Flush()
}

func scanInt(sc *bufio.Scanner) int {
	sc.Scan()
	v, _ := strconv.Atoi(sc.Text())
	return v
}

// --- From ALDS1_9_C: Priority Queue

type Heap struct {
	size   int
	heap   []Path
	isHigh func(a, b Path) bool
}

func NewHeap(isHigh func(a, b Path) bool) Heap {
	heap := make([]Path, 1) // 先頭は不使用
	return Heap{size: 0, heap: heap, isHigh: isHigh}
}

func (h *Heap) insert(v Path) {
	h.size += 1
	if h.size > len(h.heap)-1 {
		h.heap = append(h.heap, v)
	} else {
		h.heap[h.size] = v
	}

	for i := h.size; i > 1; {
		parent := i / 2
		if h.isHigh(h.heap[parent], h.heap[i]) {
			break
		}
		h.heap[i], h.heap[parent] = h.heap[parent], h.heap[i]
		i = parent
	}
}

func (h *Heap) extractMax() Path {
	if h.size <= 0 {
		panic("cannot extract from empty heap")
	}

	max := h.heap[1]
	h.heap[1] = h.heap[h.size]
	h.size -= 1
	h.maxHeapify(1)

	return max
}

func (h *Heap) maxHeapify(idx int) {
	left := idx * 2
	right := left + 1
	largest := idx

	if left <= h.size {
		if h.isHigh(h.heap[left], h.heap[idx]) {
			largest = left
		}
		if right <= h.size && h.isHigh(h.heap[right], h.heap[largest]) {
			largest = right
		}
	}

	if largest != idx {
		h.heap[idx], h.heap[largest] = h.heap[largest], h.heap[idx]
		h.maxHeapify(largest)
	}
}

Python: from sys import stdin
from collections import deque
import heapq

def read_graph(n):
    A = [ [] for _ in range(n) ]
    for _ in range(n):
        line = deque(stdin.readline().strip().split())
        u = line.popleft()
        line.popleft()
        for l, k in enumerate(line):
            if l % 2 == 0:
                v = k
            else:
                A[int(u)].append((int(v), int(k)))
    return A

def dijkstra(n, A, s):
    color = [ 'WHITE' for i in range(n) ]
    d = [ float('inf') for i in range(n) ]
    d[s] = 0
    pq = []

    heapq.heappush(pq, (s, 0))

    while pq:
        costu, u = heapq.heappop(pq)
        color[u] = 'BLACK'

        if d[u] < costu:
            continue

        for v, costv in A[u]:
            if color[v] != 'BLACK':
                if d[u] + costv < d[v]:
                    d[v] = d[u] + costv
                    color[v] = 'GRAY'
                    heapq.heappush(pq, (d[v], v))
    return d

n = int(input())
A = read_graph(n)
for i, k in enumerate(dijkstra(n, A, 0)):
    print(i, k)

Python: from heapq import heappop, heappush
import sys


class SSSP:
    """Given weighted graph, find Single Sorce Shortest Path from node 0.

    >>> st = SSSP([[(2, 3), (3, 1), (1, 2)], \
                   [(0, 2), (3, 4)], \
                   [(0, 3), (3, 1), (4, 1)], \
                   [(2, 1), (0, 1), (1, 4), (4, 3)], \
                   [(2, 1), (3, 3)]])
    >>> [st.weight(n) for n in range(5)]
    [0, 2, 2, 1, 3]
    """
    def __init__(self, graph):
        self.size = len(graph)
        self.tree = []
        self.weights = [0] * self.size
        self._search(graph)

    def weight(self, n):
        return self.weights[n]

    def _search(self, graph):
        h = []
        count = 1
        for i, w in graph[0]:
            heappush(h, (w, 0, i))

        while count < self.size:
            while len(h) > 0:
                weight, src, dst = heappop(h)
                if self.weights[dst] == 0 and dst > 0:
                    self.weights[dst] = weight
                    count += 1
                    self.tree.append((src, dst))
                    for i, w in graph[dst]:
                        if self.weights[i] == 0 and dst > 0:
                            heappush(h, (w+weight, dst, i))
                    break


def run():
    n = int(input())

    nodes = [None] * n
    for line in sys.stdin:
        id_, deg, *edges = [int(i) for i in line.split()]
        nodes[id_] = []
        for _ in range(deg):
            tgt, wgt, *edges = edges
            nodes[id_].append((tgt, wgt))

    st = SSSP(nodes)
    for node in range(n):
        print('{} {}'.format(node, st.weight(node)))


if __name__ == '__main__':
    run()

Python: #from heapdict import heapdict
import sys
import heapq
input=sys.stdin.readline

def dijkstra(G,start,n):#グラフ,初期頂点,頂点数
    INF=2<<28
    dist=[INF]*n;dist[start]=0
    used=[False]*n;used[start]=True
    q=[]

    for v in G[start]:
        heapq.heappush(q,v)
    
    while len(q)>0:
        now1,now2=heapq.heappop(q)
        #print(now1,now2)
        if used[now2]:
            continue
        v=now2
        dist[v]=now1
        used[v]=True

        for e1,e2 in G[v]:
            if not used[e2]:
                heapq.heappush(q,(e1+dist[v],e2))

    return dist

def main():
    N=int(input().rstrip())
    g=[[] for _ in range(N)]
    for _ in range(N):
        u,k,*c=map(int,input().split())
        for j in range(0,k*2,2):
            g[u].append((c[j+1],c[j]))

    ans=dijkstra(g,0,N)
    for i,x in enumerate(ans):
        print(i,x)

if __name__=="__main__":
    main()

Python: import heapq

INFTY = 1<<20

N = int(input())
M = [[] for _ in range(N)]
for i in range(N):
    u, k, *adjacents = map(int, input().split())
    for j in range(k):
        edge = adjacents[2*j]
        weight = adjacents[2*j+1]
        M[i].append((weight, edge))

mst = [False for _ in range(N)]
d = [INFTY for _ in range(N)]
d[0] = 0
pq = []
heapq.heappush(pq, (0, 0))

while len(pq) != 0:
    u = heapq.heappop(pq)
    u_edge = u[1]
    u_cost = u[0]

    mst[u_edge] = True

    if d[u_edge] < u_cost:
        continue

    for v in M[u_edge]:
        v_edge = v[1]
        v_cost = v[0]
        if mst[v_edge] == True:
            continue
        if d[u_edge]+v_cost < d[v_edge]:
            d[v_edge] = d[u_edge]+v_cost
            heapq.heappush(pq, (d[v_edge], v_edge))

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