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 maxsize
from heapq import heappop, heappush


class Node:
    WHITE = 0
    GRAY = 1
    BLACK = 2

    def __init__(self):
        self.adjs = []
        self.color = Node.WHITE
        self.dist = maxsize

    def __lt__(self, other):
        return self.dist < other.dist

    def __repr__(self):
        return "Node({},{},{})".format(self.adjs, self.color, self.dist)


def read_adj():
    n = int(input())
    nodes = [Node() for _ in range(n)]

    for i in range(n):
        u, _, *rest = [int(x) for x in input().split()]
        for i in range(0, len(rest) - 1, 2):
            nodes[u].adjs.append((rest[i], rest[i+1]))

    return nodes


def shortest_path(nodes):
    h = []

    nodes[0].dist = 0
    nodes[0].color = Node.GRAY
    heappush(h, (0, 0))

    while len(h) > 0:
        min_dist, min_node = heappop(h)

        nodes[min_node].color = Node.BLACK
        if nodes[min_node].dist < min_dist:
            continue

        for adj, c in nodes[min_node].adjs:
            if nodes[adj].color == Node.BLACK:
                continue
            if nodes[min_node].dist + c < nodes[adj].dist:
                nodes[adj].dist = nodes[min_node].dist + c
                nodes[adj].color = Node.GRAY
                heappush(h, (nodes[adj].dist, adj))


def print_dist(nodes):
    for u, n in enumerate(nodes):
        print(u, n.dist)


def main():
    nodes = read_adj()
    print(nodes)
    shortest_path(nodes)
    print_dist(nodes)


if __name__ == '__main__':
    main()

Python: #!/usr/bin/env python
from __future__ import division, print_function
from sys import stdin, maxint
from operator import itemgetter
from heapq import heappush, heappop, heapify


def main():
    num = int(stdin.readline())

    edges = []
    for _ in xrange(num):
        it = iter(int(s) for s in stdin.readline().split()[1:])
        edges.append([(next(it), next(it)) for _ in xrange(next(it))])

    distances = [[maxint, i] for i in xrange(num)]
    distances[0][0] = 0
    V = set(xrange(1, num))
    W = []#distances[1:]
    mark = set()
    index = 0

    while V:
        for v, cost in edges[index]:
            if v not in V:
                continue
            cost += distances[index][0]
            if distances[v][0] > cost:
                distances[v][0] = cost
                if v not in mark:
                    W.append(distances[v])
                    mark.add(v)

        a = min(W, key=itemgetter(0))
        index = a[1]
        W.remove(a)
        mark.remove(index)
        V.remove(index)

    for d, i in distances:
        print(i, d)

main()

Python: import heapq
import sys
readline = sys.stdin.readline
def dijkstra(n):
    inf = 10 ** 6 + 1
    dist = [0] + [inf] * (n - 1)
    q = [(0, 0)]
    while q:
        u = heapq.heappop(q)[1]
        for (v, c) in edge[u]:
            alt = dist[u] + c
            if dist[v] > alt:
                dist[v] = alt
                heapq.heappush(q, (alt, v))
    return dist
n = int(input())
edge = [[]] * n
for _ in range(n):
    l = list(map(int, readline().split()))
    edge[l[0]] = (e for e in zip(l[2::2], l[3::2]))
for i, c in enumerate(dijkstra(n)):
    print(i, c)

Python: #!/usr/bin/env python
from __future__ import division, print_function
from sys import stdin, maxint
from operator import itemgetter


def main():
    num = int(stdin.readline())

    L = []
    for _ in xrange(num):
        it = iter(int(s) for s in stdin.readline().split()[1:])
        L.append([(next(it), next(it)) for _ in xrange(next(it))])

    weight = [[i, maxint] for i in xrange(num)]
    weight[0][1] = 0
    V = set(xrange(1, num))
    W = weight[1:]
    index = 0

    while V:
        for v, cost in L[index]:
            if v not in V:
                continue
            weight[v][1] = min(weight[v][1], cost + weight[index][1])

        W.sort(key=itemgetter(1), reverse=True)
        index = W.pop()[0]

        V.remove(index)

    for i, d in weight:
        print(i, d)


main()

Python: # Graph II - Single Source Shortest Path II
def dijkstra(length, adj_list):
    INFTY = float('inf')
    d = [INFTY for _ in range(length)]
    d[0] = 0
    Q = [i for i in range(length)]
    while Q:
        idx = INFTY
        minv = INFTY
        for q in Q:
            if d[q] < minv:
                idx, minv = q, d[q]
        u = Q.pop(Q.index(idx))
        for v in adj_list[u]:
            if d[v[0]] > d[u] + v[1]:
                d[v[0]] = d[u] + v[1]
    return d

n = int(input())
adj_list = [set() for _ in range(n)]
for _ in range(n):
    ss = list(map(int, input().split()))
    u, k = ss[0], ss[1]
    for i in range(k):
        vi,ci = ss[2*i+2], ss[2*i+3]
        adj_list[u].add((vi,ci))
d = dijkstra(n, adj_list)
for i,v in enumerate(d): print(i,v)

Python: import sys
from heapq import*
e=sys.stdin.readline
I=float("inf")
def m():
 n=int(e())
 A=[]
 for _ in[0]*n:
  e=list(map(int,e().split()))
  A+=[zip(e[2::2],e[3::2])]
 d=[0]+[I]*n
 H=[(0,0)]
 while H:
  u=heappop(H)[1]
  for v,c in A[u]:
   t=d[u]+c
   if d[v]>t:
    d[v]=t
    heappush(H,(t,v))
 print('\n'.join(f'{i} {d[i]}'for i in range(n)))
m()