Random Walk_python code

import networkx as nx
import numpy as np
import matplotlib.pyplot as plt
G = nx.Graph()
G.add_node('a')
G.add_node('b')
G.add_node('c')
G.add_node('x')
G.add_node('y')
G.add_node('z')
G.add_edges_from([
    ('a', 'b'), ('b', 'c'), ('a', 'c'), ('c', 'x'),
    ('x', 'y'), ('y', 'z'), ('x', 'z')
])

nx.draw(G, with_labels=True)
plt.show()


def find(graph, previous, current):
    probability = {}
    for node in graph.neighbors(current):
        probability[node] = 1

    probability_sum = sum(probability.values())
    probability = {i: j / probability_sum for i, j in probability.items()}

    k = [i for i in probability.keys()]
    v = [i for i in probability.values()]

    next_node = np.random.choice(a=k, p=v)

    return next_node
def random_walk(graph, step, length):
    answer_path = []

    for i in range(step):
        path = [np.random.choice(G.nodes())]

        next_node = find(G, None, path[-1])
        path.append(next_node)

        for j in range(2, length):
            next_node = find(G, path[-2], path[-1])
            path.append(next_node)

        answer_path.append(path)


    return answer_path


random_walk_value = random_walk(G, 10, 10)

for i in random_walk_value:
    print(i)