用python编程在10个顶点的无向图中，每对顶点之间以概率0.6存在一条权重为[1,10]上随机整数的边，首先生成该图。然后求解下列问题：（2）求顶点v1到顶点v10的最短距离和最短路径。分别用Prim和Kruskal算法实现

好的，针对你的问题，我可以为你提供以下Python代码实现，其中用到了networkx库和heapq库：

import random
import networkx as nx
import heapq

# 生成无向图
G = nx.Graph()
for i in range(1, 11):
    for j in range(i+1, 11):
        if random.random() <= 0.6:
            weight = random.randint(1, 10)
            G.add_edge(i, j, weight=weight)

# Prim算法实现最短距离和最短路径
def prim(G, start):
    visited = set([start])
    candidate_edges = [(weight, start, to) for to, weight in G[start].items()]
    heapq.heapify(candidate_edges)
    mst = []
    total_weight = 0

    while candidate_edges:
        weight, frm, to = heapq.heappop(candidate_edges)
        if to not in visited:
            visited.add(to)
            mst.append((frm, to))
            total_weight += weight
            for to_next, weight in G[to].items():
                if to_next not in visited:
                    heapq.heappush(candidate_edges, (weight, to, to_next))

    return mst, total_weight

mst_prim, weight_prim = prim(G, 1)
print("Prim算法求解：")
print("最短距离：", nx.shortest_path_length(G, source=1, target=10, weight='weight'))
print("最短路径：", nx.shortest_path(G, source=1, target=10, weight='weight'))
print("Prim算法求得的最小生成树边集：", mst_prim)
print("Prim算法求得的最小生成树权重：", weight_prim)

# Kruskal算法实现最短距离和最短路径
def kruskal(G):
    edges = [(G[u][v]['weight'], u, v) for u, v in G.edges()]
    edges.sort()
    mst = []
    total_weight = 0
    uf = {u:u for u in G.nodes()}

    for weight, u, v in edges:
        if uf[u] != uf[v]:
            mst.append((u, v))
            total_weight += weight
            old = uf[u]
            new = uf[v]
            for w, k in uf.items():
                if k == old:
                    uf[w] = new

    return mst, total_weight

mst_kruskal, weight_kruskal = kruskal(G)
print("Kruskal算法求解：")
print("最短距离：", nx.shortest_path_length(G, source=1, target=10, weight='weight'))
print("最短路径：", nx.shortest_path(G, source=1, target=10, weight='weight'))
print("Kruskal算法求得的最小生成树边集：", mst_kruskal)
print("Kruskal算法求得的最小生成树权重：", weight_kruskal)

解释一下代码的思路：首先使用networkx库生成一个10个节点的空图，然后遍历所有节点对，以0.6的概率添加一条边，边的权重在[1,10]之间随机生成。接下来，使用Prim算法和Kruskal算法分别求出该图的最小生成树，并输出最小生成树的边集和权重。最后，使用networkx库提供的`shortest_path_length`和`shortest_path`函数求出顶点v1到顶点v10的最短距离和最短路径，并输出结果。

希望这个代码可以帮助到你！