Go: package main

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

// I/O
type Scanner struct {
	sc *bufio.Scanner
}

func NewScanner() *Scanner {
	sc := bufio.NewScanner(os.Stdin)
	sc.Split(bufio.ScanWords)
	sc.Buffer(make([]byte, 1024), int(1e+9))
	return &Scanner{sc}
}

func (s *Scanner) nextStr() string {
	s.sc.Scan()
	return s.sc.Text()
}

func (s *Scanner) nextInt() int {
	i, e := strconv.Atoi(s.nextStr())
	if e != nil {
		panic(e)
	}
	return i
}

func (s *Scanner) nextFloat() float64 {
	f, e := strconv.ParseFloat(s.nextStr(), 64)
	if e != nil {
		panic(e)
	}
	return f
}

func (s *Scanner) nextRuneSlice() []rune {
	return []rune(s.nextStr())
}

func (s *Scanner) nextIntSlice(n int) []int {
	res := make([]int, n)
	for i := 0; i < n; i++ {
		res[i] = s.nextInt()
	}
	return res
}

func (s *Scanner) nextFloatSlice(n int) []float64 {
	res := make([]float64, n)
	for i := 0; i < n; i++ {
		res[i] = s.nextFloat()
	}
	return res
}

// Arithmetic
func max(nums ...int) int {
	m := nums[0]
	for _, i := range nums {
		if m < i {
			m = i
		}
	}
	return m
}

func min(nums ...int) int {
	m := nums[0]
	for _, i := range nums {
		if m > i {
			m = i
		}
	}
	return m
}

func abs(x int) int {
	if x > 0 {
		return x
	}
	return -x
}

func pow(x, y int) int {
	res := 1
	for i := 0; i < y; i++ {
		res *= x
	}
	return res
}

func ceil(a, b int) int {
	if a%b == 0 {
		return a / b
	} else {
		return a/b + 1
	}
}

// Sort
type RuneSlice []rune

func (a RuneSlice) Len() int           { return len(a) }
func (a RuneSlice) Less(i, j int) bool { return a[i] < a[j] }
func (a RuneSlice) Swap(i, j int)      { a[i], a[j] = a[j], a[i] }

// Main
type Node struct {
	cost int
	done bool
}

type Edge struct {
	to, cost int
}

const INF = 1 << 60

func main() {
	sc := NewScanner()
	wtr := bufio.NewWriter(os.Stdout)
	N := sc.nextInt()
	nodes := make([]Node, N)
	for i := 0; i < N; i++ {
		nodes[i].cost = INF
	}
	E := make([][]Edge, N)
	for i := 0; i < N; i++ {
		id, k := sc.nextInt(), sc.nextInt()
		for j := 0; j < k; j++ {
			to, cost := sc.nextInt(), sc.nextInt()
			E[id] = append(E[id], Edge{to, cost})
		}
	}
	nodes[0].cost = 0
	for {
		cur := 0
		minCost := INF
		for i := 0; i < N; i++ {
			n := nodes[i]
			if !n.done && n.cost < minCost {
				cur = i
				minCost = n.cost
			}
		}
		if minCost == INF {
			break
		}
		nodes[cur].done = true
		for i := 0; i < len(E[cur]); i++ {
			to, cost := E[cur][i].to, E[cur][i].cost+nodes[cur].cost
			if !nodes[to].done && cost < nodes[to].cost {
				nodes[to].cost = cost
			}
		}
	}

	for i := 0; i < N; i++ {
		fmt.Fprintln(wtr, i, nodes[i].cost)
	}
	wtr.Flush()
}

Python: # -*- coding: utf-8 -*-
from heapq import heappop, heappush


def dijkstra(edges, start, *, adj_matrix=False, default_value=float('inf')):
    '''
    Returns best costs to each node from 'start' node in the given graph.
    (Single Source Shortest Path - SSSP)

    If edges only include costs and destination nodes on possible edges,
    adj_matrix should be False(default), and it is generally when this functions works much faster

    Note that costs in edges should follow the rules below
    1. The cost from a node itself should be 0,
    2. If there is no edge between nodes, the cost between them should be default_value
    3. The costs can't be negative

    # sample input when given as adjacency matrix (adj_matrix=True)
    edges = [[0, 2, 5, 4, inf, inf],           # node 0
             [2, 0, inf, 3, 6, inf],           # node 1
             [5, inf, 0, 2, inf, 6],           # node 2
             [4, 3, 2, 0, 2, inf],             # node 3
             [inf, 6, inf, 2, 0, 4],           # node 4
             [inf, inf, 6, inf, 4, 0]]         # node 5

    # sample input when given not as adjacency matrix (adj_matrix=False)
    edges = [[(1, 2), (2, 5), (3, 4)],         # node 0
             [(0, 2), (3, 3), (4, 6)],         # node 1
             [(0, 5), (3, 2), (5, 6)],         # node 2
             [(0, 4), (1, 3), (2, 2), (4, 2)], # node 3
             [(1, 6), (3, 2), (5, 4)],         # node 4
             [(2, 6), (4, 4)]]                 # node 5
    '''

    n = len(edges)

    inf = float('inf')
    costs = [inf] * n
    costs[start] = 0
    pq, rem = [(0, start)], n - 1

    while pq and rem:
        tmp_cost, tmp_node = heappop(pq)
        if costs[tmp_node] < tmp_cost:
            continue
        rem -= 1

        nxt_edges = ((node, cost) for node, cost in enumerate(edges[tmp_node]) if cost != default_value) if adj_matrix else\
                    edges[tmp_node]

        for nxt_node, nxt_cost in nxt_edges:
            new_cost = tmp_cost + nxt_cost
            if costs[nxt_node] > new_cost:
                costs[nxt_node] = new_cost
                heappush(pq, (new_cost, nxt_node))

    return costs


def dijkstra_route(edges,
                   start,
                   goal,
                   *,
                   adj_matrix=False,
                   default_value=float('inf'),
                   verbose=False):
    '''
    Trys to find the best route to the 'goal' from the 'start'
    '''

    n = len(edges)

    inf = float('inf')
    costs = [inf] * n
    costs[start] = 0
    pq, rem = [(0, start)], n - 1
    prevs = [-1 for _ in [None] * n]

    while pq and rem:
        tmp_cost, tmp_node = heappop(pq)
        if costs[tmp_node] < tmp_cost:
            continue
        rem -= 1

        nxt_edges = ((node, cost) for node, cost in enumerate(edges[tmp_node]) if cost != default_value) if adj_matrix else\
                    edges[tmp_node]

        for nxt_node, nxt_cost in nxt_edges:
            new_cost = tmp_cost + nxt_cost
            if costs[nxt_node] > new_cost:
                costs[nxt_node] = new_cost
                heappush(pq, (new_cost, nxt_node))
                prevs[nxt_node] = tmp_node

    min_route = []
    prev = goal
    cnt = 0
    while prev != start:
        min_route.append(prev)
        prev = prevs[prev]

        cnt += 1
        if prev == -1 or cnt > n:
            raise NoRouteError(
                'There is no possible route in this graph \nedges: {} \nstart: {} \ngoal: {}'.
                format(edges, start, goal))

    else:
        min_route.append(prev)
    min_route = min_route[::-1]
    min_cost = costs[goal]

    if verbose:
        print('---route---')
        for node in min_route[:-1]:
            print('{} -> '.format(node), end='')
        else:
            print(min_route[-1])

        print('---distance---')
        print(min_cost)

    return costs, min_route


class NoRouteError(Exception):
    pass


if __name__ == '__main__':
    '''
    an example of using this function
    AIZU ONLINE JUDGE - ALDS_1_12_B
    '''

    n = int(input())
    edges = [[] for i in range(n)]
    for i in range(n):
        i, k, *kedges = map(int, input().split())
        for edge in zip(kedges[::2], kedges[1::2]):
            edges[i].append(edge)

    for i, cost in enumerate(dijkstra(edges, 0)):
        print(i, cost)

Python: INF = 1e9

n = int(input())
adj_matrix = [[INF for i in range(n)] for j in range(n)]

for i in range(n):
    u, k, *line = list(map(int, input().split()))
    for j in range(k):
        adj_matrix[u][line[2*j]] = line[2*j+1]

def dijkstra(x):
    isVisited = [False] * x
    d = [INF] * x 
    d[0] = 0
    p = [0] * x 
    
    while True:
        min_cost = INF
        
        for i in range(x):
            if isVisited[i] != True and d[i] < min_cost:
                min_cost = d[i]
                u = i
        
        if min_cost == INF:
            break
        
        isVisited[u] = True
        
        for v in range(x):
            if isVisited[v] != True and adj_matrix[u][v] != INF:
                if d[u] + adj_matrix[u][v] < d[v]:
                    d[v] = d[u] + adj_matrix[u][v]
                    p[v] = u
    return d

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