Go: package main

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

type Item struct {
	value    int // The value of the item; arbitrary.
	priority int // The priority of the item in the queue.
	// The index is needed by update and is maintained by the heap.Interface methods.
	index int // The index of the item in the heap.
}
type PriorityQueue []*Item

func (pq PriorityQueue) Len() int { return len(pq) }
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 = i
	pq[j].index = j
}
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
}

type Q struct {
	pq *PriorityQueue
	ds map[int]int // It has always same value as pq. For random access.
}

func newQ() *Q {
	pq := new(PriorityQueue)
	heap.Init(pq)
	return &Q{
		pq: pq,
		ds: make(map[int]int),
	}
}
func (q *Q) pop() (u, d int) {
	item := heap.Pop(q.pq).(*Item)
	delete(q.ds, item.value)
	return item.value, item.priority
}
func (q *Q) get(u int) (int, bool) { // returns d
	d, ok := q.ds[u]
	return d, ok
}
func (q *Q) set(u, d int) {
	q.ds[u] = d
	for _, item := range *q.pq {
		if item.value != u {
			continue
		}

		item.priority = d
		heap.Fix(q.pq, item.index)
		return
	}
	heap.Push(q.pq, &Item{
		priority: d,
		value:    u,
	})
}
func (q *Q) len() int {
	return len(q.ds)
}

func main() {
	r := bufio.NewReader(os.Stdin)

	var n int
	fmt.Fscan(r, &n)
	cs := make([]map[int]int, n) // []v_i -> c_i
	for h := 0; h < n; h++ {
		var u, k int
		fmt.Fscan(r, &u, &k)
		m := make(map[int]int)
		for i := 0; i < k; i++ {
			var v, c int
			fmt.Fscan(r, &v, &c)
			m[v] = c
		}

		cs[u] = m
	}

	q := newQ()
	q.set(0, 0)
	visited := make(map[int]struct{})
	out := make([]int, n)

	for q.len() > 0 {
		u, d := q.pop()
		for uu, c := range cs[u] {
			// Consider the connection between u and uu.
			if _, ok := visited[uu]; ok {
				continue
			}
			dd := d + c
			if d, ok := q.get(uu); !ok || d > dd {
				q.set(uu, dd)
			}
		}

		out[u] = d
		visited[u] = struct{}{}
	}

	for u, d := range out {
		fmt.Println(u, d)
	}
}

Python: # coding: utf-8

import heapq


class Dijkstra:

    """
    Dijkstra's algorithm: find the shortest path from a vertex
    O(E + log(V))
    verified:
        https://onlinejudge.u-aizu.ac.jp/#/courses/lesson/1/ALDS1/12/ALDS1_12_B
    """

    def __init__(self, V, G, INF=float("inf")):

        """
        V: the number of vertexes
        E: adjacency list (all edge in G must be 0 or positive)
        INF: Infinity distance
        """
        self.V = V
        self.G = G
        self.INF = INF
        self.distance, self.prev = list(), list()


    def dijkstra(self, start):

        Q = list()
        self.distance = [self.INF for _ in range(self.V)]
        self.prev = [-1 for _ in range(self.V)]

        self.distance[start] = 0
        heapq.heappush(Q, (0, start))

        while len(Q) > 0:
            dist, from_v = heapq.heappop(Q)
            if self.distance[from_v] < dist:
                continue
            for to_v, nxt_dist in self.G[from_v]:
                if self.distance[from_v] + nxt_dist >= self.distance[to_v]:
                    continue
                self.distance[to_v] = self.distance[from_v] + nxt_dist
                heapq.heappush(Q, (self.distance[to_v], to_v))
                self.prev[to_v] = from_v
        
        return self.distance


    def get_path(self, goal):

        path = [goal]
        while self.prev[goal] != -1:
            path.append(prev[goal])
            goal = self.prev[end]

        return path[::-1]


if __name__ == "__main__":
    
    """
    an example of use
    """

    n = int(input())
    g = [[] for _ in range(n)]
    for _ in range(n):
        v, _, *e = map(int, input().split())
        for u, d in zip(e[::2], e[1::2]):
            g[v].append((u, d))
 

    dist = Dijkstra(n, g).dijkstra(0)
    for i, d in enumerate(dist):
        print(i, d)

Python: import sys
readline = sys.stdin.readline
from heapq import heapify, heappush, heappop
INF = float("inf")
def MAIN():
    n = int(input())
    G = [[i, INF] for i in range(n)]
    G[0][1] = 0
    m = {}
    for _ in range(n):
        A = list(map(int, readline().split()))
        m[A[0]] = {}
        for i in range(2, len(A), 2):
            m[A[0]][A[i]] = A[i + 1]
    dp = [(0, 0)]
    while dp:
        cost, u = heappop(dp)
        for v, c in m[u].items():
            if G[v][1] > G[u][1] + c:
                G[v][1] = G[u][1] + c
                heappush(dp, (G[v][1], v))
    print("\n".join(" ".join(map(str, a)) for a in G))
MAIN()

Python: from heapq import*
def m():
 n=int(input())
 A=[]
 for _ in[0]*n:
  e=list(map(int,input().split()))
  A+=[zip(e[2::2],e[3::2])]
 d=[0]+[float('inf')]*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()

Python: from heapq import*
I=float("inf")
def m():
 n=int(input())
 A=[]
 for _ in[0]*n:
  e=list(map(int,input().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()

Python: from heapq import heapify, heappop, heappush, heappushpop


class PriorityQueue:
    def __init__(self, heap):
        '''
        heap ... list
        '''
        self.heap = heap
        heapify(self.heap)

    def push(self, item):
        heappush(self.heap, item)

    def pop(self):
        return heappop(self.heap)

    def pushpop(self, item):
        return heappushpop(self.heap, item)

    def __call__(self):
        return self.heap

    def __len__(self):
        return len(self.heap)


def dijkstra(graph, s, N):
    '''
    graph...隣接リスト形式 リスト内要素は(ノード, エッジ長)
    s...始点ノード
    N...頂点数

    return
    ----------
    D ... 各点までの最短距離
    P ... 最短経路木における親
    '''
    pq = PriorityQueue([])
    P = [None] * N
    D = [float('inf')] * N
    D[s] = 0
    pq.push((D[s], s))  # (最短距離, 次のノード)
    while pq:
        d, v = pq.pop()
        if D[v] < d:  # この辺を扱っても最短距離にならない
            continue  # is_visitedなくてもこれを使うことで最小のものを再び探索するのを防げる
        for to, cost in graph[v]:
            if D[to] > D[v] + cost:  # v周りにおける最短経路の候補の更新
                D[to] = D[v] + cost
                pq.push((D[to], to))
                P[to] = v
    return D, P

# load datas
N = int(input())
adj = [[] for _ in range(N)]  # (node_id, 隣接要素, 隣接nodeidとコスト)の順で格納する
'''
例
[
(0について) [(1,1235), (4,65)]
(1について) [(20,6000)]
...
]
'''
for _ in range(N):
    tmp = list(map(int, input().split()))
    if tmp[1] != 0:
        node = tmp[0]
        for i in range(2, 2 + tmp[1] * 2, 2):
            adj[node].append((tmp[i], tmp[i + 1]))

D, P = dijkstra(adj, 0,N)

for i in range(N):
    print(i, D[i])

Python: # coding: utf-8

import heapq

def dj(adjm, start):
    n = len(adjm)
    d = [float("inf")] * n
    d[start] = 0
    q = []
    heapq.heappush(q, (0, start))

    while(q):
        td, v = heapq.heappop(q)
        for k in adjm[v].keys():
            nd = td + adjm[v][k]
            if d[k] > nd:
                d[k] = nd
                heapq.heappush(q, (nd, k))
    return d


def main():
    n = int(input())
    # 隣接行列
    adjm = [{} for _ in range(n)]
    for i in range(n):
        vdata = list(map(int, input().split()))
        for j in range(vdata[1]):
            v, c = vdata[j * 2 + 2], vdata[j * 2 + 3]
            adjm[i][v] = c
    ans = dj(adjm, 0)
    for i, d in enumerate(ans):
        print(i, d)


if __name__ == "__main__":
    main()