Go: package main

import (
	"bufio"
	"container/heap"
	"fmt"
	"os"
	"strconv"
)

//make priority queue
type Item struct {
	id       int
	priority int // this state is priority and distans from start
	index    int
}

type PriorityQueue []*Item

func (pq PriorityQueue) Len() int { return len(pq) }

// we want the ascending-priority-queue.
// So we use less than here.
func (pq PriorityQueue) Less(i, j int) bool {
	return pq[i].priority < pq[j].priority
}

func (pq PriorityQueue) Swap(i, j int) {
	pq[i], pq[j] = pq[j], pq[i]
	pq[i].index = j
	pq[j].index = i
}

func (pq *PriorityQueue) Push(x interface{}) {
	n := len(*pq)
	item := x.(*Item)
	item.index = n
	*pq = append(*pq, item)
}

func (pq *PriorityQueue) Pop() interface{} {
	old := *pq
	n := len(old)
	item := old[n-1]
	item.index = -1 //for safety
	*pq = old[0 : n-1]
	return item
}

func (pq *PriorityQueue) update(dist int, id int) {
	for _, i := range *pq {
		if i.id == id {
			if i.priority > dist {
				i.priority = dist
			}
		}
	}
}

// the main code
func nextInt(sc *bufio.Scanner) int {
	sc.Scan()
	n, _ := strconv.Atoi(sc.Text())
	return n
}

func dikstra(dist [][]int, n int) []int {
	// preparate priority queue
	inf := 1 << 30
	pq := make(PriorityQueue, n)
	shortests := make([]int, n)
	for i := 0; i < n; i++ {
		pq[i] = &Item{
			id:       i,
			priority: inf,
			index:    i,
		}

		shortests[i] = inf
	}
	pq[0].priority = 0
	shortests[0] = 0
	heap.Init(&pq)

	for pq.Len() > 0 {
		item := heap.Pop(&pq).(*Item)
		shortests[item.id] = item.priority
		for id, d := range dist[item.id] {
			if d != -1 {
				pq.update(item.priority+d, id)
			}
		}
		heap.Init(&pq)
	}
	return shortests
}

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

	// init
	n := nextInt(sc)
	dist := make([][]int, n)
	for i := 0; i < n; i++ {
		dist[i] = make([]int, n)
		for j := 0; j < n; j++ {
			dist[i][j] = -1
		}
	}

	// std Input
	for i := 0; i < n; i++ {
		u := nextInt(sc)
		k := nextInt(sc)
		for j := 0; j < k; j++ {
			v, c := nextInt(sc), nextInt(sc)
			dist[u][v] = c
		}
	}

	shortests := dikstra(dist, n)
	for i, d := range shortests {
		fmt.Printf("%d %d\n", i, d)
	}
}

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(1e7 + 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

        for adj_vertex_index in range(vertices_num):
            current_adj_weight = adj_table[current_vertex_index].get(adj_vertex_index, -1)
            if current_adj_weight < 0:
                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: # 単一視点最短経路, Dijkstra(ダイクストラ)のアルゴリズム
from collections import deque

n = int(input())
# グラフの作成
INF = float('inf')
M = [[INF]*n for _ in range(n)]
d = [INF]*n
for _ in range(n):
    u, k, *v = map(int, input().split())
    if k == 0:
        continue
    cnt = 0
    for _ in range(k):
        M[u][v[cnt]] = v[cnt+1]
        cnt += 2

# アルゴリズム部分
def djikstra(n, M, d):
    d[0] = 0
    color = ['W']*n
    color[0] = 'G'
    while True:
        mincost = INF
        u = -1
        for i in range(n):
            if mincost > d[i] and color[i] != 'B':
                u = i
                mincost = d[i]
        if u == -1:
            break

        color[u] = 'B'
        for v in range(n):
            if color[v] != 'B' and M[u][v] != INF:
                if d[v] > d[u]+M[u][v]:
                    d[v] = d[u]+M[u][v]
                    color[v] = 'G'
    return d

D = djikstra(n, M, d)
for i, c in enumerate(D):
    print(i, c)

Python: import io, sys, itertools
f = sys.stdin


def take2(iterable):
    i = iter(iterable)
    while True:
        yield next(i), next(i)


n = int(f.readline())
adj =[[(v, c) for v, c in take2(map(int, f.readline().split()[2:]))] for _ in range(n)]
d = [100000 * 100 + 1] * n

d[0] = 0
def search(parent, children):
    global d
    for v, c in children:
        if d[v] > d[parent] + c:
            d[v] = d[parent] + c
            search(v, adj[v])
    
search(0, adj[0])
    
for i in range(n):
    print(i, d[i])

Python: import sys
input = sys.stdin.readline

INF = 100100

def dijkstra(M: list, u: int = 0) -> list:
    global N
    d = [INF] * N
    d[u] = 0
    visited = [False] * N
    while True:
        mincost = INF
        for i in range(N):
            if not visited[i] and d[i] < mincost:
                mincost = d[i]
                u = i
        if mincost == INF:
            return d
        visited[u] = True
        for v in range(N):
            if not visited[v]:
                if d[u] + M[u][v] < d[v] :
                    d[v] = d[u] + M[u][v]


def main():
    global N
    N = int(input())
    M = [[INF]*N for _ in range(N)]
    for _ in range(N):
        A = list(map(int, input().split()))
        u = A[0]
        k = A[1]
        for i in range(k):
            v = A[2+2*i]
            c = A[3+2*i]
            M[u][v] = c
    d = dijkstra(M)
    for i, di in enumerate(d):
        print(i, di)

if __name__ == '__main__': main()

Python: # -*- coding: utf-8 -*-

N = int(input())
INF = float("inf")
adj = [[INF]*N for _ in range(N)]

for n in range(N):
    inp = tuple(map(int, input().split()))
    assert n == inp[0]
    for i in range(inp[1]):
        adj[inp[0]][inp[2*i+2]] = inp[2*i+3]

not_MST = list(range(1, N))
MST = [0]
costs = {n:INF for n in range(N)}
costs[0] = 0

for n in range(1, N):
    if adj[0][n] < INF:
        costs[n] = adj[0][n]

m = 0

while len(not_MST):
    tmp_min = INF
    tmp_idx = -1
    
    for n in not_MST:
        if costs[m] + adj[m][n] < costs[n]:
            costs[n] = costs[m] + adj[m][n]
    
    for m in not_MST:
        if costs[m] < tmp_min:
            tmp_min = costs[m]
            tmp_idx = m
    
    MST.append(tmp_idx)
    not_MST.remove(tmp_idx)
    m = tmp_idx

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