Go: package main

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

const (
	MAX_N      = 10000
	MAX_WEIGHT = 100000
)

type Edge struct {
	start  int
	end    int
	weight int
}

type ShortestInfo struct {
	edges    []Edge
	shortest int
}

type Neighbor struct {
	node   int
	weight int
}

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

	n, err := nextInt(sc)
	if err != nil {
		panic(err)
	}

	shortestList := make([]ShortestInfo, n)
	for i := 1; i < n; i++ {
		shortestList[i] = ShortestInfo{edges: []Edge{}, shortest: MAX_N*MAX_WEIGHT + 1}
	}

	adjacentMatrix, err := createAdjacentMatrix(n, sc)
	if err != nil {
		panic(err)
	}

	sssp([]int{0}, shortestList, adjacentMatrix)
	for _, v := range shortestList {
		fmt.Printf("%d %d\n", v.getEnd(), v.shortest)
	}
}

func (si ShortestInfo) getEnd() int {
	if len(si.edges) == 0 {
		return 0
	} else {
		return si.edges[len(si.edges)-1].end
	}
}

func createAdjacentMatrix(n int, sc *bufio.Scanner) ([][]Neighbor, error) {
	adjacentMatrix := make([][]Neighbor, n)
	for i := 0; i < n; i++ {
		id, err := nextInt(sc)
		if err != nil {
			return nil, err
		}
		adjacentMatrix[id] = []Neighbor{}
		vertexNum, err := nextInt(sc)
		if err != nil {
			return nil, err
		}
		for j := 0; j < vertexNum; j++ {
			v, err := nextInt(sc)
			if err != nil {
				return nil, err
			}
			c, err := nextInt(sc)
			if err != nil {
				return nil, err
			}
			adjacentMatrix[id] = append(adjacentMatrix[id], Neighbor{v, c})
		}
	}
	return adjacentMatrix, nil
}

func sssp(nodeStack []int, shortestList []ShortestInfo, adjacentMatrix [][]Neighbor) {
	for len(nodeStack) > 0 {
		currentNode := nodeStack[0]
		nodeStack = nodeStack[1:]
		currentShortest := getShortest(currentNode, shortestList)
		adjacents := findAdjacents(currentNode, adjacentMatrix)
		for i := 0; i < len(adjacents); i++ {
			adj := adjacents[i]
			if currentShortest.shortest+adj.weight < getShortest(adj.end, shortestList).shortest {
				setShortest(adj.end, adj, currentShortest, shortestList)
				nodeStack = append(nodeStack, adj.end)
			}
		}
	}
}

func getShortest(node int, shortestList []ShortestInfo) ShortestInfo {
	return shortestList[node]
}

func setShortest(node int, edge Edge, currentShortest ShortestInfo, shortestList []ShortestInfo) {
	newEdges := make([]Edge, len(currentShortest.edges)+1)
	for i := 0; i < len(newEdges)-1; i++ {
		newEdges[i] = currentShortest.edges[i]
	}
	newEdges[len(newEdges)-1] = edge
	shortestInfo := ShortestInfo{edges: newEdges, shortest: currentShortest.shortest + edge.weight}
	shortestList[node] = shortestInfo
}

func findAdjacents(currentNode int, adjacentMatrix [][]Neighbor) []Edge {
	adjacents := adjacentMatrix[currentNode]
	edges := []Edge{}
	for _, neighbor := range adjacents {
		edges = append(edges, Edge{start: currentNode, end: neighbor.node, weight: neighbor.weight})
	}
	return edges
}

func nextInt(sc *bufio.Scanner) (int, error) {
	sc.Scan()
	return strconv.Atoi(sc.Text())
}

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
D_MAX = int(5e20 + 1)


def generate_adj_matrix(v_info):
    for each in v_info:
        v_index, v_adj_length, *v_adj_list = map(int, each)
        # assert len(v_adj_list) == v_adj_length * 2
        for pair in zip(v_adj_list[::2], v_adj_list[1::2]):
            init_adj_matrix[v_index][pair[0]] = pair[1]

    return init_adj_matrix


def dijkstra_path():
    # path search init
    path_list[init_vertex_index] = 0
    path_heap = []
    # heapq: rank by tuple[0], here ranked by d[u]
    hp.heappush(path_heap, (0, init_vertex_index))
    while len(path_heap) >= 1:
        current_vertex_index = hp.heappop(path_heap)[1]

        color[current_vertex_index] = BLACK

        current_vertex_index_info = adj_table[current_vertex_index]
        for adj_vertex_index in current_vertex_index_info.keys():
            current_adj_weight = current_vertex_index_info.get(adj_vertex_index)
            if not current_adj_weight:
                continue
            elif color[adj_vertex_index] is not BLACK:
                # alt: d[u] + w[u,v]
                alt_path = path_list[current_vertex_index] + current_adj_weight
                if alt_path < path_list[adj_vertex_index]:
                    # update path_list
                    path_list[adj_vertex_index] = alt_path
                    # update heap
                    hp.heappush(path_heap, (alt_path, adj_vertex_index))
                    parent_list[adj_vertex_index] = current_vertex_index
                    color[adj_vertex_index] = GRAY

    return path_list


if __name__ == '__main__':
    _input = sys.stdin.readlines()
    vertices_num = int(_input[0])
    init_vertices_table = map(lambda x: x.split(), _input[1:])
    # assert len(init_vertices_table) == vertices_num

    parent_list, path_list = [-1] * vertices_num, [D_MAX] * vertices_num
    color = [WHITE] * vertices_num
    init_adj_matrix = tuple(dict() for _ in range(vertices_num))
    init_vertex_index = 0

    adj_table = generate_adj_matrix(init_vertices_table)
    ans = dijkstra_path()
    for i, v in enumerate(ans):
        print(i, v)

Python: import heapq

INF = 1e9

n = int(input())
adj_list = [[]] * n

for u in range(n):
    U = list(map(int, input().split()[2:]))
    adj_list[u] = zip(U[0::2], U[1::2]) # adj_list[u] = (v, cost)


def dijkstra(x):
    d = [INF] * x
    d[0] = 0
    isVisited = [False] * x
    hq = [(0, 0)] # (distance, v)??????????????¬??????????????????(key, ????´?)???????????????push, pop?????????
    
    while hq:
        u = heapq.heappop(hq)[1]
        isVisited[u] = True
        
        for v, c in adj_list[u]:
            if not isVisited[v] and d[v] > d[u] + c:
                d[v] = d[u] + c
                heapq.heappush(hq, (d[u] + c, v))
                
    return d

for i, di in enumerate(dijkstra(n)):
    print(i,di)

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


def heap_increase_key(heap, i):
    parent = i // 2
    while i > 1 and heap[parent][0] > heap[i][0]:
        heap[i], heap[parent] = heap[parent], heap[i]
        i //= 2
        parent = i // 2


def min_heapify(heap, i):
    heap_size = len(heap)-1
    L = i * 2
    R = L + 1
    if L <= heap_size and heap[L][0] < heap[i][0]:
        smallest = L
    else:
        smallest = i
    if R <= heap_size and heap[R][0] < heap[smallest][0]:
        smallest = R
    if smallest != i:
        heap[i], heap[smallest] = heap[smallest], heap[i]
        min_heapify(heap, smallest)


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

    while V:
        i = maxint
        for v, cost in L[index]:
            if v not in V:
                continue
            cost += weight[index][0]
            if weight[v][0] > cost:
                weight[v][0] = cost
                heap_increase_key(W, W.index(weight[v]))
            #weight[v][0] = min(weight[v][0], cost + weight[index][0])

        index = W.pop(1)[1]
        min_heapify(W, 1)
        V.remove(index)

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


main()