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: # -*- coding: utf-8 -*-
from heapq import heappop, heappush


def prim(edges, *, start=0, adj_matrix=False, default_value=float('inf')):
    '''
    Returns the Minimum Spanning Tree(MST) of a given graph

    # sample input when given not as adjacency list (adj_matrix=False) (generally works faster)
    edges = [[(1, 2), (2, 5), (3, 4)],         # node 0
             [(0, 2), (3, 3), (4, 6)],         # node 1
             [(0, 5), (3, 2), (5, 6)],         # node 2
             [(0, 4), (1, 3), (2, 2), (4, 2)], # node 3
             [(1, 6), (3, 2), (5, 4)],         # node 4
             [(2, 6), (4, 4)]]                 # node 5

    # sample input when given as adjacency matrix (adj_matrix=True)
    edges = [[0, 2, 5, 4, inf, inf],           # node 0
             [2, 0, inf, 3, 6, inf],           # node 1
             [5, inf, 0, 2, inf, 6],           # node 2
             [4, 3, 2, 0, 2, inf],             # node 3
             [inf, 6, inf, 2, 0, 4],           # node 4
             [inf, inf, 6, inf, 4, 0]]         # node 5
    '''

    n = len(edges)

    prevs = [-1] * n
    costs = [float('inf')] * n
    costs[start] = 0
    pq = [(0, start)]
    T = [True] * n
    rem = n - 1

    while pq and rem:
        tmp_cost, tmp_node = heappop(pq)
        T[tmp_node] = False
        rem -= 1

        nxt_edges = ((node, cost) for node, cost in enumerate(edges[tmp_node]) if cost != default_value and T[node]) if adj_matrix else\
                    ((node, cost) for node, cost in edges[tmp_node] if T[node])

        for nxt_node, nxt_cost in nxt_edges:
            if costs[nxt_node] > nxt_cost:
                costs[nxt_node] = nxt_cost
                prevs[nxt_node] = tmp_node
                heappush(pq, (nxt_cost, nxt_node))
                T[nxt_node] = True

    else:
        if len([prev for prev in prevs if prev != -1]) != n - 1:
            raise NoSpanningError(
                'There is no spanning tree in this graph (search started from node{})'.
                format(start))

        else:
            return prevs, costs


class NoSpanningError(Exception):
    pass


if __name__ == '__main__':
    '''
    an example of using this function
    AIZU ONLINE JUDGE - ALDS_1_12_A
    '''

    n = int(input())
    edges = [[(j, int(cost)) for j, cost in enumerate(input().split())
              if int(cost) != -1] for i in range(n)]

    prevs, costs = prim(edges)
    print(sum(costs))

Python: def prim(cost):
    sumcost = 0
    V = len(cost)
    mincost = [float('inf')] * V
    used = [False] * V
    mincost[0] = 0
    while True:
        j = -1
        for i in range(V):
            if not used[i] and (j == -1 or mincost[i] < mincost[j]):
                j = i
        if j == -1:
            break
        used[j] = True
        sumcost = sumcost + mincost[j]
        for i in range(V):
            if cost[i][j] == -1:
                continue
            mincost[i] = min(mincost[i], cost[j][i])
    return sumcost

Python: n = int(input())
T = [i for i in range(n)]
def root(x):
    path_to_root = []
    while T[x] != x:
        path_to_root.append(x)
        x = T[x]
    for node in path_to_root:
        T[node] = x
    return x
def is_same_set(x,y):
    return root(x) == root(y)
def unite(x,y):
    T[root(x)] = root(y)

A = []
W = []
for i in range(n):
    A.append(list(map(int,input().strip().split(' '))))
    for j in range(i+1,n):
        if A[i][j] != -1:
            W.append([A[i][j],i,j])
W.sort()
sum = 0
for i in range(len(W)):
    if not is_same_set(W[i][1],W[i][2]):
        unite(W[i][1],W[i][2])
        sum += W[i][0]
print(sum)

Python: import heapq

n = int(input())
A = [[int(i) for i in input().split()] for i in range(n)]
h = []
DP = {}
heapq.heappush(h,(0,0))
c = 0
while(len(DP)<n):
    tmp = heapq.heappop(h)
    c += tmp[0]
    DP[tmp[1]] = 1
    for i,j in enumerate(A[tmp[1]]):
        if j > 0 and not i in DP:
            heapq.heappush(h,(j,i))
print(c)

Python: def kruskal(n):
    cost = []
    t = set()
    while edge:
        cmin = min(weight)
        index = weight.index(cmin)
        e = edge[index]
        del weight[index]
        del edge[index]
        if not e <= t:
            cost.append(cmin)
            t |= e
    return sum(cost)

n = int(input())
edge = []
weight = []
for i in range(n):
    for j, c in enumerate(map(int, input().split())):
        if c != -1 and not {i, j} in weight:
            edge.append({i, j})
            weight.append(c)
print(kruskal(n))

Python: n=int(input())
edgeList=[]
for i in range(n):
 a=list(map(int,input().split()))
 for j in range(i):
  if a[j]>=0:edgeList+=[(a[j],i,j)]
rootList=[-1]*n
sumLength=0
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])
for e in edgeList:
 x=getRoot(e[1])
 y=getRoot(e[2])
 if x!=y:
  sumLength+=e[0]
  rootList[x]=rootList[y]=min(x,y)
print(sumLength)