Go: package main

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

// Define disjoint-set forests

type vertexNo int

type vertex struct {
	number vertexNo
	rank int
	parent *vertex
}

func makeSet(number vertexNo) vertex {
	return vertex {
		number: number,
		rank: 0,
		parent: nil,
	}
}

func union(x, y *vertex) *vertex {
	return link(findSet(x), findSet(y))
}

func link(x, y *vertex) *vertex {
	if x.rank > y.rank {
		y.parent = x
		return x
	} else {
		x.parent = y
		if x.rank == y.rank {
			y.rank += 1
		}
		return y
	}
}

func findSet(v *vertex) *vertex {
	if v.parent == nil {
		return v
	}
	v.parent = findSet(v.parent)
	return v.parent
}

// Function to calculate minimum spanning tree

type matrix [][]int

type edge struct {
	one vertexNo
	two vertexNo
	weight int
}

const(
	MAX_VERTICES = 100
)

func newEdgesFromMatrix(matrix matrix) []edge {
	edges := make([]edge, 0, MAX_VERTICES * MAX_VERTICES)

	for i := 0; i < len(matrix); i++ {
		row := matrix[i]
		for j := i; j < len(row); j++ {
			if row[j] >= 0 {
				edge := edge{one: vertexNo(i+1), two: vertexNo(j+1), weight: row[j]}
				edges = append(edges, edge)
			}
		}
	}

	return edges
}

func solve(matrix matrix) int {
	nVertices := len(matrix)

	// initialize vertices
	vertices := make([]vertex, nVertices)
	for i := 0; i < nVertices; i++ {
		vertices[i] = makeSet(vertexNo(i+1))
	}

	// prepare edges sorted in the ascending order of weight
	edges := newEdgesFromMatrix(matrix)
	sort.Slice(edges, func(i, j int) bool {
		return edges[i].weight < edges[j].weight
	})

	unionCount := 0
	weightSum := 0
	for unionCount < nVertices-1 {
		for i := 0; i < len(edges); i++ {
			edge := edges[i]
			v1 := &vertices[edge.one-1]
			v2 := &vertices[edge.two-1]
			rep1 := findSet(v1)
			rep2 := findSet(v2)
			if rep1.number == rep2.number {
				continue
			}
			union(rep1, rep2)
			edges = append(edges[0:i], edges[i+1:]...)
			weightSum += edge.weight
			unionCount++
			break
		}
	}

	return weightSum
}

// main

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

	n, err := nextInt(sc)
	if err != nil {
		panic(err)
	}

	matrix := parseMatrix(n, sc)

	edges := newEdgesFromMatrix(matrix)
	sort.Slice(edges, func(i, j int) bool {
		return edges[i].weight < edges[j].weight
	})

	fmt.Println(solve(matrix))
}

func parseMatrix(n int, sc *bufio.Scanner) [][]int {
	matrix := make([][]int, n)
	for i := 0; i < n; i++ {
		matrix[i] = make([]int, n)
		for j := 0; j < n; j++ {
			x, err := nextInt(sc)
			if err != nil {
				panic(err)
			}
			matrix[i][j] = x
		}
	}
	return matrix
}

func nextText(sc *bufio.Scanner) string {
	sc.Scan()
	return sc.Text()
}

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

Python: class UnionFind:
    def __init__(self, n: int):
        self.nodes = n
        self.parents = [-1] * n
        self.rank = [0] * n

    # retrun the root of element x
    def find(self, x):
        if self.parents[x] < 0:
            return x
        else:
            self.parents[x] = self.find(self.parents[x])
            return self.parents[x]

    # unite the group include element x and group include element y
    def unite(self, x, y):
        x = self.find(x)
        y = self.find(y)
        if x == y:
            return
        if self.rank[x] < self.rank[y]:
            self.parents[y] += self.parents[x]
            self.parents[x] = y
        else:
            self.parents[x] += self.parents[y]
            self.parents[y] = x
            if self.rank[x] == self.rank[y]:
                self.rank[x] += 1

    # get size of the gourp which element x belongs
    def get_size(self, x):
        return -self.parents[self.find(x)]

    # check if element x and element y is same group
    def same(self, x, y):
        return self.find(x) == self.find(y)


def kruskal(n: int, edges: list):
    """
    n: count of nodes
    edges: list of edges, format: (node1,node2,weight)
    """
    union = UnionFind(n + 1)  # 1-indexed
    mst_sum = 0
    mst = []
    for edge in edges:
        n1, n2, w = edge
        if not union.same(n1, n2):
            union.unite(n1, n2)
            mst_sum += w
            mst.append(edge)
    return mst, mst_sum


n = int(input())
graph_table = []

for _ in range(n):
    graph_table.append([int(i) for i in input().split()])

edges = []
# edge一覧を取得
for i in range(n - 1):
    for j in range(i + 1, n):
        if graph_table[i][j] != -1:
            edges.append((i, j, graph_table[i][j]))  # node1,node2,weight

# edgeを重みの昇順にソート
edges = sorted(edges, key=lambda x: x[2])

_, mst_sum = kruskal(n, edges)
print(mst_sum)

Python: n = int(input())
a = [list(map(int, input().split())) for i in range(n)]
m = [2001] * n
f = [0] * n
sum = 0

m[0] = 0
f[0] = 1
v = 0

for i in range(n-1) :
    for j in range(n) :
        if (a[v][j] < m[j]) & (f[j] == 0) & (a[v][j] != -1):
            m[j] = a[v][j]
    
    min = 2001
    minj = 0
    for j in range(n) :
        if (m[j] < min) & (f[j] == 0):
            min = m[j]
            minj = j
    
    v = minj
    f[minj] = 1
    sum += min

print(sum)

Python: def solv(G):
  n = len(G)
  V = {0:0}
  new_V = []
  cost = 0

  while len(new_V) < n:
    u, e = min(V.items(), key=lambda x:x[1])
    V.pop(u)
    new_V.append(u)
    cost += e
    for v, e in enumerate(G[u]):
      if e < 0 or v == u or v in new_V: continue
      V[v] = min(V[v], e) if v in V else e

  return cost

n = int(input())
G = [list(map(int, input().split())) for _ in range(n)]
print(solv(G))

Python: import heapq

n = int(input())
edges = [set((w, j) for j, w in enumerate(map(int, input().split())) if w > -1) for _ in range(n)]

visited = [False] * n
visited[0] = True
queue = list(edges[0])
heapq.heapify(queue)
total_cost, remains = 0, n - 1
while True:
    cost, vertex = heapq.heappop(queue)
    if visited[vertex]:
        continue
    visited[vertex] = True
    total_cost += cost
    remains -= 1
    if not remains:
        break
    for t in edges[vertex]:
        if not visited[t[1]]:
            heapq.heappush(queue, t)

print(total_cost)

Python: n = int(input())
m = [[-1 for i in range(n)] for j in range(n)] #お隣さんへのコストを保存（この中から最小を探す）

v = set()
v.add(0)

for i in range(n): #隣接の辺のコストを入力
  nums = list(map(int, input().split()))
  for j in range(n):
    m[i][j] = nums[j]


def prim_mst(n):
  isVisited = [False] * n
  d = [0] + [2001] * (n-1)      #TとV-Tのを繋ぐ最小辺の重みを格納する

  while  True:
    mincost = 2001
    for i in range(n):
      if not (isVisited[i]) and d[i] < mincost:
        mincost = d[i]
        u = i
    isVisited[u] = True


    if mincost == 2001:        #mincostが2001になったら繰り返し作業終了
      break

    for v in range (n):
      if (not isVisited[v]) and (m[u][v] != -1):
        if m[u][v] < d[v]:
          d[v] = m[u][v]
  print(sum(d))

prim_mst(n)

Python: import heapq

n = int(input())
M = [list(map(int,input().split())) for _ in range(n)]

q = []

visited = [False]*n

adjs = []
sum_cost = 0
node = 0
visited[node] = True
cnt = 1

while 1:
    for i in range(n):
        if M[node][i] != -1 and visited[i] == False:
            heapq.heappush(q, (M[node][i], i))
    while 1:
        mincost,node = heapq.heappop(q)
        if visited[node] == False:
            break
    sum_cost += mincost
    visited[node] = True
    cnt += 1
    if cnt == n:
        break


print(sum_cost)

Python: N = 100

n = int(input())
adj = [[0 for i in range(n)] for j in range(n)]

for i in range(n):
    tmp = list(map(int, input().split()))
    u = tmp[0]
    u = u -1
    k = tmp[1]
    v = tmp[2:]
    for j in range(k):
        adj[u][v[j]-1] = 1
        
for i in range(n):
        print(" ".join(list(map(str, adj[i]))))