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 -*-
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 as adjacency matrix
    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

    # sample input when given not as adjacency matrix
    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
    '''

    n = len(edges)
    mst = []
    cost = 0
    T = [start]

    while True:
        tmp_edges = [(cost, (u, v)) for u in T for v, cost in enumerate(edges[u]) if cost != default_value and v not in T] if adj_matrix else\
                    [(cost, (u, v)) for u in T for v, cost in edges[u] if v not in T]

        if tmp_edges:
            min_cost, min_edge = min(tmp_edges)
            mst.append(min_edge)
            cost += min_cost
            T.append(min_edge[1])

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

            else:
                return mst, cost


class NoSpanningError(Exception):
    pass


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

    n = int(input())
    edges = [[int(cost) if int(cost) != -1 else float('inf') for cost in input().split()] for i in range(n)]

    print(prim(edges, adj_matrix=True)[1])

Python: import heapq

def root(x):
    path_to_root = []
    while P[x] != x:
        path_to_root.append(x)
        x = P[x]
    for node in path_to_root:
        P[node] = x
    return x
def is_same_set(x,y):
    return root(x) == root(y)
def unite(x,y):
    P[root(x)] = root(y)

W = 0
N = int(input().strip())
P = [i for i in range(N)]
A = []
for i in range(N):
    v = list(map(int,input().strip().split(' ')))
    A.append(v)
edges = [] 
for i in range(N):
    for j in range(i,N):
        edge = [A[i][j],i,j]
        heapq.heappush(edges,edge)
while len(edges) > 0:
    e = heapq.heappop(edges)
    I = e[1]
    J = e[2]
    if e[0] != -1:
        if not is_same_set(I,J):
            unite(I,J)
            W += e[0]
print(W)

Python: # -*- coding: utf-8 -*-
from itertools import product

N = int(input())
INF = float("inf")
adj = []

for _ in range(N):
    adj.append([int(n) if n != "-1" else float("inf") for n in input().split()])

not_MST = list(range(1, N))
MST = [0]

cost = 0
while len(not_MST):
    tmp_min = INF
    tmp_idx = -1
    for m, n in product(MST, not_MST):
        if adj[m][n] < tmp_min:
            tmp_min = adj[m][n]
            tmp_idx = n
    MST.append(tmp_idx)
    not_MST.remove(tmp_idx)
    cost += tmp_min

print(cost)

Python: import heapq


class MST:
    """Given weighted graph, find minimum spanning tree.

    >>> mst = MST([[-1, 2, 3, 1, -1], \
                   [2, -1, -1, 4, -1], \
                   [3, -1, -1, 1, 1], \
                   [1, 4, 1, -1, 3], \
                   [-1, -1, 1, 3, -1]]);
    >>> mst.weight()
    5
    """
    MAX_WEIGHT = 2001

    def __init__(self, graph):
        self.graph = graph
        self.size = len(graph)
        self.tree = []
        self._search()

    def weight(self):
        return sum([self.graph[i][j] for i, j in self.tree])

    def _search(self):
        visited = [0]

        while len(visited) < self.size:
            h = []
            for node in visited:
                for i, w in enumerate(self.graph[node]):
                    if w == -1:
                        continue
                    if i in visited:
                        continue
                    heapq.heappush(h, (w, node, i))

            weight, src, dst = heapq.heappop(h)
            visited.append(dst)
            self.tree.append((src, dst))


def run():
    n = int(input())

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

    mst = MST(nodes)
    print(mst.weight())


if __name__ == '__main__':
    run()