Go: package main

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

var scanner = bufio.NewScanner(os.Stdin)

func nextString() string {
	scanner.Scan()
	return scanner.Text()
}

func nextInt() int {
	n, err := strconv.Atoi(nextString())
	if err != nil {
		fmt.Printf("strconv.Atoi failed: %v\n", err)
	}
	return n
}

type ElementKey int
type Node struct {
	key    ElementKey
	parent *Node
	rank   int
}

func newNode(key ElementKey) *Node {
	node := Node{}
	node.key = key
	node.parent = &node
	node.rank = 0

	return &node
}

func union(x, y *Node) {
	xSet := findSet(x)
	ySet := findSet(y)
	link(xSet, ySet)
}

func link(x, y *Node) {
	if x.rank > y.rank {
		y.parent = x
	} else {
		x.parent = y

		if x.rank == y.rank {
			y.rank++
		}
	}
}

func findSet(x *Node) *Node {
	if x != x.parent {
		x.parent = findSet(x.parent)
	}
	return x.parent
}

func newDisjointSets(nSets int) *DisjointSets {
	sets := DisjointSets{}
	sets.keyToNode = map[ElementKey]*Node{}
	for i := 0; i < nSets; i++ {
		key := ElementKey(i)
		sets.keyToNode[key] = newNode(key)
	}
	return &sets
}

type DisjointSets struct {
	keyToNode map[ElementKey]*Node
}

func (sets *DisjointSets) union(x, y ElementKey) {
	xNode := sets.keyToNode[x]
	yNode := sets.keyToNode[y]
	union(xNode, yNode)
}

func (sets DisjointSets) findSet(x ElementKey) *Node {
	xNode := sets.keyToNode[x]
	return findSet(xNode)
}

type Edge struct {
	i, j   int
	weight int
}

func main() {
	scanner.Split(bufio.ScanWords)

	n := nextInt()
	sets := newDisjointSets(n)
	edges := []Edge{}
	a := make([][]int, n)
	for i := 0; i < n; i++ {
		a[i] = make([]int, n)
		for j := 0; j < n; j++ {
			a[i][j] = nextInt()
			if a[i][j] >= 0 {
				e := Edge{
					i:      i,
					j:      j,
					weight: a[i][j],
				}
				edges = append(edges, e)
			}
		}
	}
	sort.Slice(edges, func(i, j int) bool { return edges[i].weight < edges[j].weight })
	totalWeight := 0
	for _, edge := range edges {
		i := ElementKey(edge.i)
		j := ElementKey(edge.j)
		if sets.findSet(i) != sets.findSet(j) {
			totalWeight += edge.weight
			sets.union(i, j)
		}
	}
	fmt.Println(totalWeight)
}

Python: #!/usr/bin/env python3


# Union find
class UnionFind:
    def __init__(self, N):
        self.N = N
        self.parent = list(range(N))

    def root(self, x):
        path_to_root = []
        while self.parent[x] != x:
            path_to_root.append(x)
            x = self.parent[x]
        for node in path_to_root:
            self.parent[node] = x  # パス圧縮
        return x

    def same(self, x, y):
        return self.root(x) == self.root(y)

    def unite(self, x, y):
        self.parent[self.root(x)] = self.root(y)

    def __str__(self):
        groups = {}
        for x in range(self.N):
            root = self.root(x)
            if root in groups.keys():
                groups[root].append(x)
            else:
                groups[root] = [x]
        result = ""
        for root in groups.keys():
            result += str(groups[root]) + "\n"
        return result


# Kruscal法: 最小全域木
# num_vertices: int
# edges=(vertex1, vertex2, weight): List[int, int, int]
# edgesについて破壊的
def kruskal(num_vertices, edges):
    total_weight = 0
    edges.sort(key=lambda e: e[2])
    u = UnionFind(num_vertices)
    for e in edges:
        x = e[0]
        y = e[1]
        weight = e[2]
        if u.same(x, y):
            continue
        u.unite(x, y)
        total_weight += weight
    return total_weight


n = int(input())
edges = []
for i in range(n):
    row = list(map(int, input().split()))
    for j in range(i, n):
        if row[j] != -1:
            edges.append([i, j, row[j]])
print(kruskal(n, edges))

Python: import itertools

n = int(input())
A = [list(map(int, input().strip().split(' '))) for _ in range(n)]
uvc = [] # A list of tuples of start, end, and cost
for i in range(n-1):
    for j in range(i+1, n):
        if A[i][j] >= 0:
            uvc.append((i, j, A[i][j]))

# コストでソート
uvc.sort(key=lambda x: x[2])

uf = list(range(n))

def find_root(x):
    global uf
    if x == uf[x]:
        return x
    else:
        uf[x] = find_root(uf[x])
        return uf[x]

def union(x, y):
    global uf
    uf[find_root(x)] = find_root(y)

def is_same_set(x, y):
    return find_root(x) == find_root(y)

def costs():
    global uvc
    for u, v, c in uvc:
        if not is_same_set(u, v):
            union(u, v)
            yield c
print(sum(itertools.islice(costs(), n - 1)))

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)