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diff --git a/recital_dataset.py b/recital_dataset.py
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+++ b/recital_dataset.py
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+import pandas as pd
+import random
+import json
+
+# 读取CSV文件
+df = pd.read_csv('recitalMachine_dataset.csv')  # 使用制表符分隔
+df['length_of_answer'] = df['answer'].apply(lambda x: len(str(x).split('，')))
+
+# 按difficulty分组并创建子DataFrame列表
+sub_dataframes = [group for _, group in df.groupby('difficulty')]
+
+# 打印每个difficulty的子DataFrame（可选）
+for i, sub_df in enumerate(sub_dataframes):
+    print(f"Difficulty {sub_df['difficulty'].iloc[0]} 的子DataFrame:")
+    print(sub_df)
+    print("-" * 50)
+
+# 创建以difficulty为键的字典
+sub_dataframes_dict = {diff: group for diff, group in df.groupby('difficulty')}
+
+# 访问特定难度的子DataFrame（例如难度4）
+difficulty_4_df = sub_dataframes_dict[4]
+print(difficulty_4_df)
+
+# 创建生成器函数
+def difficulty4_generator(df):
+    indices = list(df.index)
+    random.shuffle(indices)
+    
+    while True:
+        if not indices:
+            # 如果所有记录都已使用，重新洗牌
+            indices = list(df.index)
+            random.shuffle(indices)
+        
+        yield df.loc[indices.pop()]
+
+# 创建生成器
+difficulty4_gen = difficulty4_generator(difficulty_4_df)
+
+# 使用示例
+print("从难度4中随机抽取记录:")
+for i in range(min(10, len(difficulty_4_df) * 2)):  # 演示循环抽取
+    row = next(difficulty4_gen)
+    print(f"{i+1}. {row['question']} -> {row['answer']}")
+
+json_data = {}
+for difficulty, group in df.groupby('difficulty'):
+    # 转换为字典列表，确保所有数据都可序列化
+    json_data[str(difficulty)] = group.to_dict('records')
+
+# 保存为JSON
+with open('recitalMachine_dataset.json', 'w', encoding='utf-8') as f:
+    json.dump(json_data, f, ensure_ascii=False, indent=2)
+
+print("文件已保存!")
+\ No newline at end of file