Go: package main

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

const (
	MAX_N      = 200
	MAX_WEIGHT = 2000
)

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 := make([][]int, n)
	for i := 0; i < n; i++ {
		adjacentMatrix[i] = make([]int, n)
		for j := 0; j < n; j++ {
			v, err := nextInt(sc)
			if err != nil {
				panic(err)
			}
			adjacentMatrix[i][j] = v
		}
	}

	mst([]int{1}, shortestList, adjacentMatrix)
	fmt.Println(calculateMinWeight(shortestList))
}

func calculateMinWeight(shortestList []ShortestInfo) int {
	visitedList := make([]bool, len(shortestList))
	visitedList[0] = true
	sumWeight := 0
	for !visitedAll(visitedList) {
		shortestInfo := shortestList[0]
		shortestList = shortestList[1:]
		edges := shortestInfo.edges
		for _, edge := range edges {
			if !visitedList[edge.end-1] {
				visitedList[edge.end-1] = true
				sumWeight += edge.weight
			}
		}
	}
	return sumWeight
}

func visitedAll(visitedList []bool) bool {
	for _, v := range visitedList {
		if !v {
			return false
		}
	}
	return true
}

func mst(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]
			s := getShortest(adj.end, shortestList)
			if currentShortest.shortest+adj.weight < s.shortest || (currentShortest.shortest+adj.weight == s.shortest && len(currentShortest.edges)+1 > len(s.edges)) {
				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: # -*- 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)