Go: package main

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

const (
	MAX_N      = 100
	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{1}, shortestList, adjacentMatrix)
	for _, v := range shortestList {
		fmt.Printf("%d %d\n", v.getEnd()-1, v.shortest)
	}
}

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

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-1] = shortestInfo
}

func findAdjacents(currentNode int, adjacentMatrix [][]int) []Edge {
	adjacents := adjacentMatrix[currentNode-1]
	edges := []Edge{}
	for i, v := range adjacents {
		if v > 0 {
			edges = append(edges, Edge{start: currentNode, end: i + 1, weight: v})
		}
	}
	return edges
}

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

Python: rootList = [-1 for i in range(n)]
parent = [0 for i in range(n)]
lenList = [0 for i in range(n)]

def getRoot(x):
    r = rootList[x]
    if r < 0:
        rootList[x] = x
    elif r != x:
        rootList[x] = getRoot(r)
    return rootList[x]


edgeList.sort(key=lambda x: x[0])
flag = True
while flag:
    flag = False
    for e in edgeList:    # weight:e[0], e[1]->e[2]
        if e[2] == 0:
            continue
        x = getRoot(e[1])
        y = getRoot(e[2])
        if x == 0 != y:
            parent[e[2]] = e[1]
            lenList[e[2]] += lenList[e[1]] + e[0]
            rootList[y] = 0
            flag = True
            break

for i, j in zip(range(n), lenList):
    print(i, j)

Python: n = int(input())
from collections import defaultdict
G = defaultdict(list)
for i in range(n):
    i = [int(i) for i in input().split()]
    k = i[1]
    G[i[0]] = list(zip(i[2::2],i[3::2]))

def mind(Q, d):
    c = float('inf')
    ret = 0
    for i, j in enumerate(d):
        if c > j and i in Q:
            c = j
            ret = i
    return ret

def dijkstra(G):
    d = [0] + [float('inf')] * (n - 1)
    Q = set(range(n))
    while len(Q) != 0:
        u = mind(Q, d)
        Q = Q - set([u])
        for v, c in G[u]:
            if d[v] > d[u] + c:
                d[v] = d[u] + c
    return d

for i,j in enumerate(dijkstra(G)):
    print(i, j)

Python: from collections import namedtuple

Edge = namedtuple('Edge', ('fr', 'to', 'cost'))
inf = 1e9


def bellman_ford(n, start, edges):
    dists = [inf for _ in range(n)]
    dists[start] = 0
    while True:
        updated = False
        for e in edges:
            if dists[e.fr] != inf and dists[e.fr] + e.cost < dists[e.to]:
                updated = True
                dists[e.to] = dists[e.fr] + e.cost

        if not updated:
            break

    return dists


def dijkstra(n, costs):
    dists = [inf for _ in range(n)]
    dists[0] = 0
    determined = [False for _ in range(n)]

    while True:
        v, min_d = -1, inf
        for i in range(n):
            if determined[i]:
                continue
            if dists[i] < min_d:
                v, min_d = i, dists[i]

        if v == -1:
            break

        determined[v] = True

        for i in range(n):
            if determined[i] or costs[v][i] == -1:
                continue

            dists[i] = min(dists[i], dists[v] + costs[v][i])

    return dists


n = int(input())

m = [[-1 for _ in range(n)] for _ in range(n)]
es = []
for i in range(n):
    fs = list(map(int, input().split()))
    ne = fs[1]
    for j in range(ne):
        v = fs[2+2*j]
        c = fs[2+2*j+1]
        m[i][v] = c
        es.append(Edge(i, v, c))


# d = bellman_ford(n, 0, es)
d = dijkstra(n, m)
for (i, di) in enumerate(d):
    print(i, di)

Python: 
def graph_to_edges(graph):
    '''(cosr,from,to)を要素に持つリストに変換 未verify'''
    # edgeへの変換
    edges = []
    for ot, v in graph.items():
        for to, c in v:
            edges.append((c, ot, to))
    return edges

def bellman_ford(edges, s, N):
    '''
    edges ... (cost,from,to)を各要素に持つリスト
    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
    '''
    P = [None] * N
    inf = float('inf')
    D = [inf] * N
    D[s] = 0
    for n in range(N):  # N-1回で十分だけど、N回目にもアップデートがあったらnegative loopを検出できる
        update = False  # 早期終了用
        for c, ot, to in edges:
            if D[ot] != inf and D[to] > D[ot] + c:
                update = True
                D[to] = D[ot] + c
                P[to] = ot
        if not update:
            break  # 早期終了
        if n == len(edges) - 1:
            raise ValueError('NegativeCycleError')
    return D, P

# load datas
N = int(input())
from collections import defaultdict
adj = defaultdict(lambda:[])
'''
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]))
            
edges=graph_to_edges(adj)


D, P = bellman_ford(edges,0,N)

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

Python: n = int(input())

adj = [[100001 for j in range(n)] for i in range(n)]

for u in range(n):
    x = list(map(int, input().split()))
    for v, c in zip(x[2::2], x[3::2]):
        adj[u][v] = c

unvisited = {v for v in range(n)}

distance = [9900001] * n


def dijkstra(s):
    distance[s] = 0

    while True:
        mincost = 9900001
        for i in unvisited:
            if distance[i] < mincost:
                mincost = distance[i]
                u = i

        if mincost == 9900001:
            break

        unvisited.discard(u)

        for v in unvisited:
            weight_uv = adj[u][v]
            if weight_uv != 100001:
                t_d = distance[u] + weight_uv
                if t_d < distance[v]:
                    distance[v] = t_d



dijkstra(0)

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