Go: // Warshall–Floyd Algorithm

package main

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

var scanner = bufio.NewScanner(os.Stdin)

const INF = 2000000000

func main() {
	for scanner.Scan() {
		buf := strings.Split(scanner.Text(), " ")
		n, _ := strconv.Atoi(buf[0])
		m, _ := strconv.Atoi(buf[1])
		if n == 0 && m == 0 {
			break
		}
		c_matrix := make([][]int, m)
		for i := range c_matrix {
			c_matrix[i] = make([]int, m)
		}
		t_matrix := make([][]int, m)
		for i := range t_matrix {
			t_matrix[i] = make([]int, m)
		}
		for i := 0; i < n; i++ {
			scanner.Scan()
			buf_ := strings.Split(scanner.Text(), " ")
			a, _ := strconv.Atoi(buf_[0])
			b, _ := strconv.Atoi(buf_[1])
			c, _ := strconv.Atoi(buf_[2])
			t, _ := strconv.Atoi(buf_[3])
			c_matrix[a-1][b-1] = c
			c_matrix[b-1][a-1] = c
			t_matrix[a-1][b-1] = t
			t_matrix[b-1][a-1] = t
		}
		c_dist := make([][]int, m)
		c_prev := make([][]int, m)
		t_dist := make([][]int, m)
		t_prev := make([][]int, m)
		for i := 0; i < m; i++ {
			c_dist[i] = make([]int, m)
			c_prev[i] = make([]int, m)
			t_dist[i] = make([]int, m)
			t_prev[i] = make([]int, m)
		}
		for i := 0; i < m; i++ {
			for j := 0; j < m; j++ {
				if c_matrix[i][j] == 0 {
					c_dist[i][j] = INF
					c_prev[i][j] = -1
				} else {
					c_dist[i][j] = c_matrix[i][j]
					c_prev[i][j] = i
				}
				if t_matrix[i][j] == 0 {
					t_dist[i][j] = INF
					t_prev[i][j] = -1
				} else {
					t_dist[i][j] = t_matrix[i][j]
					t_prev[i][j] = i
				}
			}
			c_dist[i][i] = 0
			t_dist[i][i] = 0
		}
		for k := 0; k < m; k++ {
			for i := 0; i < m; i++ {
				for j := 0; j < m; j++ {
					c_newlen := c_dist[i][k] + c_dist[k][j]
					if c_newlen < c_dist[i][j] {
						c_dist[i][j] = c_newlen
						c_prev[i][j] = c_prev[k][j]
					}
				}
			}
		}
		for k := 0; k < m; k++ {
			for i := 0; i < m; i++ {
				for j := 0; j < m; j++ {
					t_newlen := t_dist[i][k] + t_dist[k][j]
					if t_newlen < t_dist[i][j] {
						t_dist[i][j] = t_newlen
						t_prev[i][j] = t_prev[k][j]
					}

				}
			}
		}
		scanner.Scan()
		k, _ := strconv.Atoi(scanner.Text())
		for i := 0; i < k; i++ {
			scanner.Scan()
			buf_ := strings.Split(scanner.Text(), " ")
			p, _ := strconv.Atoi(buf_[0])
			q, _ := strconv.Atoi(buf_[1])
			r, _ := strconv.Atoi(buf_[2])
			switch r {
			case 0:
				fmt.Println(c_dist[p-1][q-1])
			case 1:
				fmt.Println(t_dist[p-1][q-1])
			}
		}
	}
}

Python: import sys
import heapq as h

inf = sys.maxsize

# おまじない
class heapq:
    def __init__(self):
        self.q = []

    def push(self,v):
        h.heappush(self.q, v)
    
    def pop(self):
        return h.heappop(self.q)

    def is_empty(self):
        return len(self.q) == 0

# 入力:graphと始点s
# 出力:始点sから各頂点tへの距離dist
def shortestPath0(graph, s):
    n = len(graph)

    dist    = [inf for _ in range(n)]
    visited = [False for _ in range(n)]
    dist[s] = 0

    while True:
        idx, u  = -1, inf
        for i in range(n):
            if not visited[i] and dist[i] < u:
                idx = i
                u = dist[i]
        
        if u == inf: break
        
        visited[idx] = True

        for (next, w) in graph[idx]:
            newdist = w + dist[idx]
            if newdist < dist[next]:
                dist[next] = newdist
    return dist

def shortestPath1(graph, s):
    n = len(graph)

    dist    = [inf for _ in range(n)]
    visited = [False for _ in range(n)]
    
    q = heapq()
    q.push((0, s))

    while not q.is_empty():
        (cur_dist, v) = q.pop()

        if visited[v] or dist[v] <= cur_dist:
            continue

        dist[v] = cur_dist
        visited[v] = True

        for next, w in graph[v]:
            if not visited[next] and dist[v] + w < dist[next]:
                q.push((dist[v] + w, next))

    return dist

def main():
    n, m = map(int, input().split())
    
    # 隣接リスト
    tgraph = [[] for _ in range(m)]
    cgraph = [[] for _ in range(m)]
    
    for i in range(n):
        a, b, cost, time = map(int, input().split())
        a -= 1
        b -= 1
        cgraph[a].append((b, cost))
        cgraph[b].append((b, cost))
        tgraph[a].append((b, time))
        tgraph[b].append((b, time))

    c_dist = [shortestPath1(cgraph, s) for s in range(m)]
    t_dist = [shortestPath1(tgraph, s) for s in range(m)]

    k = int(input())
    for i in range(k):
        p, q, r = map(int, input().split())
        p-=1
        q-=1
        if r == 0:
            print(c_dist[p][q])
        else:
            print(t_dist[p][q])
main()

Python: import heapq
def dijkstra(graph, size, start, r):
    distance = [float('inf')] * size
    distance[start] = 0
    que = []
    heapq.heappush(que, (0, start))
    while len(que):
        _, u = heapq.heappop(que)
        for length, vi in graph[u]:
            if distance[vi] > distance[u] + length[r]:
                distance[vi] = distance[u] + length[r]
                heapq.heappush(que, (distance[vi], vi))
    return distance

import sys
f = sys.stdin

import collections

while True:
    n, m = map(int, f.readline().split())
    if n == 0:
        break
    abct = [list(map(int, f.readline().split())) for _ in range(n)]
    graph = collections.defaultdict(list)
    for ai, bi, cost, time in abct:
        graph[ai].append(((cost, time), bi))
        graph[bi].append(((cost, time), ai))
        
    k = int(f.readline())
    for i in range(k):
        p, q, r = map(int, f.readline().split())
        dist = dijkstra(graph, m + 1, p, r)
        print(dist[q])

Python: from heapq import heappop, heappush


class WeightedEdge:
    """Weighted edge."""

    def __init__(self, a, b, weight):
        self.a = a
        self.b = b
        self.weight = weight

    def __repr__(self):
        return "(%d - %d: %d)" % (self.a, self.b, self.weight)

    def __lt__(self, other):
        return self.a < other.b


class EdgeWeightedGraph:
    """Undirected Edge-weighted graph (1-n indexed)."""

    def __init__(self, V):
        self.__adj = [[] for _ in range(V + 1)]

    def add_edge(self, a, b, weight):
        self.__adj[a].append(WeightedEdge(a, b, weight))
        self.__adj[b].append(WeightedEdge(b, a, weight))

    def adj(self, a):
        return self.__adj[a]

    def num_nodes(self):
        return len(self.__adj) - 1


class Dijkstra:
    """Single root shortest path by Dijkstra."""

    def __init__(self, graph, s, t):
        self.dist_to = [float('inf') for _ in range(graph.num_nodes() + 1)]
        self.dist_to[s] = 0
        pq = []
        heappush(pq, (0, s))
        while pq:
            w, a = heappop(pq)
            if a == t:
                return
            if self.dist_to[a] < w:
                continue
            for edge in graph.adj(a):
                if self.dist_to[edge.b] > self.dist_to[a] + edge.weight:
                    self.dist_to[edge.b] = self.dist_to[a] + edge.weight
                    heappush(pq, (self.dist_to[edge.b], edge.b))


if __name__ == '__main__':
    while True:
        n, m = map(int, input().split())
        if n == 0 and m == 0:
            break

        g_cost = EdgeWeightedGraph(m)
        g_time = EdgeWeightedGraph(m)
        for _ in range(n):
            a, b, cost, time = map(int, input().split())
            g_cost.add_edge(a, b, cost)
            g_time.add_edge(a, b, time)

        k = int(input())
        for _ in range(k):
            p, q, r = map(int, input().split())
            if r == 0:
                fw_cost = Dijkstra(g_cost, p, q)
                ans = fw_cost.dist_to[q]
            else:
                fw_time = Dijkstra(g_time, p, q)
                ans = fw_time.dist_to[q]
            print(ans)