From 76abe83fb0503efcc2febd08ab0dc721ab4a0731 Mon Sep 17 00:00:00 2001
From: p3eilcsbk <2285669185@qq.com>
Date: Wed, 12 Nov 2025 19:56:35 +0800
Subject: [PATCH] ADD file via upload

---
 process.py | 149 +++++++++++++++++++++++++++++++++++++++++++++++++++++
 1 file changed, 149 insertions(+)
 create mode 100644 process.py

diff --git a/process.py b/process.py
new file mode 100644
index 0000000..c44b1c1
--- /dev/null
+++ b/process.py
@@ -0,0 +1,149 @@
+r"""
+-弹幕统计.xlsx（原句/排名 /TopN三个工作表）
+前8条弹幕.txt（TopN文本）
+词云图.png
+"""
+import argparse
+from pathlib import Path
+from typing import List, Tuple, Dict
+import pandas as pd
+from collections import Counter
+import re
+
+# 词云依赖
+try:
+    from wordcloud import WordCloud  # type: ignore
+except ImportError:
+    WordCloud = None  #跳过词云生成
+
+
+def read_lines_from_file(f: Path) -> List[str]:
+    try:
+        return [line.strip() for line in f.read_text(encoding='utf-8', errors='ignore').splitlines()]
+    except Exception:
+        return []
+
+
+def collect_texts(input_path: Path) -> List[str]:
+    texts: List[str] = []
+    if input_path.is_dir():
+        for f in input_path.rglob('*.txt'):
+            texts.extend(read_lines_from_file(f))
+    else:
+        texts.extend(read_lines_from_file(input_path))
+    texts = [t for t in texts if t]
+    return texts
+
+
+def rank_exact_sentences(texts: List[str]) -> pd.DataFrame:
+    # 统计一样的弹幕的数量
+    if not texts:
+        return pd.DataFrame(columns=['原句', '数量', '排名'])
+    s = pd.Series(texts, name='原句')
+    vc = s.value_counts(dropna=False)
+    df = vc.rename('数量').reset_index().rename(columns={'index': '原句'})
+    # 添加到排名
+    df['排名'] = df['数量'].rank(method='dense', ascending=False).astype(int)
+    return df
+
+
+def write_excel(raw_texts: List[str], rank_df: pd.DataFrame, out_dir: Path, topn: int):
+    out_dir.mkdir(parents=True, exist_ok=True)
+    excel_path = out_dir / '弹幕统计.xlsx'
+    # 排名表的排序
+    rank_sorted = rank_df.sort_values(by=['数量', '原句'], ascending=[False, True])
+    with pd.ExcelWriter(excel_path, engine='openpyxl') as writer:
+        pd.DataFrame({'原句': raw_texts}).to_excel(writer, index=False, sheet_name='原句')
+        rank_sorted.to_excel(writer, index=False, sheet_name='排名')
+        rank_sorted.head(topn).to_excel(writer, index=False, sheet_name='TopN')
+    # 同时输出TopN的文本
+    top_txt = out_dir / '前8条弹幕.txt'
+    with top_txt.open('w', encoding='utf-8') as f:
+        for _, row in rank_sorted.head(topn).iterrows():
+            f.write(f"{int(row['数量'])}\t{row['原句']}\n")
+    return excel_path, top_txt
+
+
+def _pick_chinese_font() -> str:
+    """确定字体"""
+    candidates = [
+        r"C:\\Windows\\Fonts\\simhei.ttf",   # 黑体
+        r"C:\\Windows\\Fonts\\msyh.ttc",    # 微软雅黑
+        r"C:\\Windows\\Fonts\\simsun.ttc",  # 宋体
+    ]
+    for p in candidates:
+        if Path(p).exists():
+            return p
+    return ''
+
+
+def _simple_tokenize_for_wc(texts: List[str]) -> Counter:
+    #词云用的简单切分
+    stop = set("""的 了 啊 吗 呢 吧 是 在 我 你 他 她 它 这 那 也 与 和 很 都 就 还 不 没 有 说 啊呀 哦 嗯 呃 啊？ 吧？ 吗？ 呢？ ？ ! ！ ， 。 、 . , ~ ～ 哈 哈哈 啊啊 啊啊啊 666 233""".split())
+    joined = '\n'.join(texts)
+    tokens: List[str] = []
+    rough = re.split(r"[^\w\u4e00-\u9fff]+", joined)
+    for tk in rough:
+        tk = tk.strip()
+        if len(tk) < 2 or tk in stop:
+            continue
+        if re.fullmatch(r"\d+", tk):
+            continue
+        tokens.append(tk)
+    return Counter(tokens)
+
+
+def generate_wordcloud(raw_texts: List[str], out_dir: Path) -> Path:
+    if WordCloud is None:
+        print('未安装wordcloud，已跳过词云生成。')
+        return Path()
+    out_dir.mkdir(parents=True, exist_ok=True)
+    freq = _simple_tokenize_for_wc(raw_texts)
+    if not freq:
+        print('词云：未得到有效分词，已跳过。')
+        return Path()
+    font_path = _pick_chinese_font() or None
+    wc = WordCloud(
+        width=1600,
+        height=900,
+        background_color='white',
+        font_path=font_path,
+        collocations=False,
+        prefer_horizontal=0.9,
+    )
+    wc.generate_from_frequencies(freq)
+    out_path = out_dir / '词云图.png'
+    wc.to_file(str(out_path))
+    return out_path
+
+
+def main():
+    parser = argparse.ArgumentParser()
+    parser.add_argument('-i', '--input', required=True, help='输入：txt 文件或目录（目录下将递归读取 *.txt）')
+    parser.add_argument('-o', '--out', required=True, help='输出目录')
+    parser.add_argument('-n', '--topn', type=int, default=8, help='TopN 的数量（默认 8）')
+    args = parser.parse_args()
+
+    input_path = Path(args.input)
+    out_dir = Path(args.out)
+
+    texts = collect_texts(input_path)
+    if not texts:
+        print('没有读取到任何弹幕文本，请检查路径。')
+        return
+
+    rank_df = rank_exact_sentences(texts)
+    excel, top_txt = write_excel(texts, rank_df, out_dir, args.topn)
+    wc_path = generate_wordcloud(texts, out_dir)
+
+    print('完成：')
+    print(f'  统计结果 Excel: {excel}')
+    print(f'  前{args.topn} 文本:  {top_txt}')
+    if wc_path and wc_path.exists():
+        print(f'  词云图:         {wc_path}')
+    print('TopN预览：')
+    print(rank_df.head(args.topn).to_string(index=False))
+
+
+if __name__ == '__main__':
+    main()
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