mirror of
https://github.com/LC044/WeChatMsg
synced 2024-11-15 14:24:12 +08:00
67 lines
2.2 KiB
Python
67 lines
2.2 KiB
Python
from collections import Counter
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from app.DataBase import msg_db, MsgType
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from app.person_pc import ContactPC
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import jieba
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from pyecharts import options as opts
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from pyecharts.charts import Pie, WordCloud, Calendar, Bar, Line, Timeline, Grid
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charts_width = 800
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charts_height = 450
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wordcloud_width = 780
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wordcloud_height = 720
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def wordcloud(wxid):
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import jieba
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txt_messages = msg_db.get_messages_by_type(wxid, MsgType.TEXT)
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text = ''.join(map(lambda x: x[7], txt_messages))
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total_msg_len = len(text)
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# 使用jieba进行分词，并加入停用词
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words = jieba.cut(text)
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# 统计词频
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word_count = Counter(words)
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# 过滤停用词
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stopwords_file = '../data/stopwords.txt'
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with open(stopwords_file, "r", encoding="utf-8") as stopword_file:
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stopwords = set(stopword_file.read().splitlines())
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filtered_word_count = {word: count for word, count in word_count.items() if len(word) > 1 and word not in stopwords}
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# 转换为词云数据格式
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data = [(word, count) for word, count in filtered_word_count.items()]
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# text_data = data
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data.sort(key=lambda x: x[1], reverse=True)
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text_data = data[:100] if len(data) > 100 else data
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# 创建词云图
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keyword, max_num = text_data[0]
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w = (
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WordCloud(init_opts=opts.InitOpts(width=f"{wordcloud_width}px", height=f"{wordcloud_height}px"))
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.add(series_name="聊天文字", data_pair=text_data, word_size_range=[20, 100])
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.set_global_opts(
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title_opts=opts.TitleOpts(
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title=f"词云图", subtitle=f"总计{total_msg_len}字",
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title_textstyle_opts=opts.TextStyleOpts(font_size=23)
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),
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tooltip_opts=opts.TooltipOpts(is_show=True),
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legend_opts=opts.LegendOpts(is_show=False)
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)
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)
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# return w.render_embed()
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return {
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'chart_data': w.dump_options_with_quotes(),
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'keyword': keyword,
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'max_num': str(max_num),
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'dialogs': msg_db.get_messages_by_keyword(wxid, keyword, num=5)
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}
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class Analysis:
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pass
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if __name__ == '__main__':
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msg_db.init_database(path='../DataBase/Msg/MSG.db')
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w = wordcloud('wxid_0o18ef858vnu22')
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print(w)
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