analysis.py

import os
import json
import jieba
import matplotlib.pyplot as plt
from wordcloud import WordCloud


# 将所有文件夹名转换为 str 类型
folder_name = " ".join(os.listdir(r"D:\mzitu"))

# jieba 分词
jieba.load_userdict(r".\data\jieba.txt")
seg_list = jieba.lcut(folder_name, cut_all=False)

# 利用字典统计词频
counter = dict()
for seg in seg_list:
    counter[seg] = counter.get(seg, 1) + 1
print(counter)
# 根据词频排序字典
counter_sort = sorted(
    counter.items(), key=lambda value: value[1], reverse=True
)
# print(counter_sort)

# 解析成 json 类型并写入文件
words = json.dumps(counter_sort, ensure_ascii=False)
with open(r".\data\words.json", "w+", encoding="utf-8") as f:
    f.write(words)

# 生成词云
wordcloud = WordCloud(
    font_path=r".\font\msyh.ttf", max_words=100, height=600, width=1200
).generate_from_frequencies(
    counter
)
plt.imshow(wordcloud)
plt.axis("off")
plt.show()
wordcloud.to_file("worldcloud.jpg")