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
}

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) ([][]int, error) {
	adjacentMatrix := make([][]int, n)
	for i := 0; i < n; i++ {
		id, err := nextInt(sc)
		if err != nil {
			return nil, err
		}
		adjacentMatrix[id] = make([]int, n)
		for j := 0; j < n; j++ {
			adjacentMatrix[id][j] = -1
		}
		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][v] = c
		}
	}
	return adjacentMatrix, nil
}

func sssp(nodeStack []int, shortestList []ShortestInfo, adjacentMatrix [][]int) {
	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 [][]int) []Edge {
	adjacents := adjacentMatrix[currentNode]
	edges := []Edge{}
	for i, v := range adjacents {
		if v >= 0 {
			edges = append(edges, Edge{start: currentNode, end: i, weight: v})
		}
	}
	return edges
}

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

Python: import sys

f_i = sys.stdin

n = int(f_i.readline())

adj = [[]] * n
for x in f_i:
    x = list(map(int, x.split()))
    adj[x[0]] = [c_v for c_v in zip(x[3::2], x[2::2])]

import heapq

def dijkstra():
    PQ = [(0, 0)]
    isVisited = [False] * n
    distance = [999900001] * n

    distance[0] = 0
    
    while PQ:
        uc, u = heapq.heappop(PQ)

        if uc > distance[u]:
            continue

        isVisited[u] = True
        
        for vc, v in adj[u]:
            if isVisited[v] == True:
                continue
            t_cost = distance[u] + vc
            if t_cost < distance[v]:
                distance[v] = t_cost
                heapq.heappush(PQ, (t_cost, v))

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


dijkstra()

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()

Python: import heapq

def Sigle_Source_Shortest_Path_2(adj_list, Cost, Color):

    Cost[0] = 0
    H = list()
    heapq.heappush(H, [0, 0])

    while len(H) != 0:
        _, u = heapq.heappop(H)
        Color[u] = "B"

        for i in range(len(adj_list[u])):

            c = adj_list[u][i][0]
            v = adj_list[u][i][1]
           
            if Color[v] != "B":
                if Cost[v] > Cost[u] + c:
                    Cost[v] = Cost[u] + c
                    Color[v] = "G"
                    heapq.heappush(H, [Cost[v], v])

def Main():
    N = int(input())
    adj_list = [list() for n in range(N)]
    Cost = [1000000 for n in range(N)]
    Color = ["W" for n in range(N)]

    for n in range(N):
        u, K, *p = map(int, input().split())

        if K > 0:
            for k in range(K):
                v, c = p[2*k], p[2*k + 1]
                adj_list[u].append([c, v])

    Sigle_Source_Shortest_Path_2(adj_list, Cost, Color)

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

Main()

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 heapq as hp
import sys

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 = [{} 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 = []
        # 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)