Python代码优化：将重复数据处理逻辑封装成函数

def optimize_code(tj_config, categore_type, save_path, save_categorefile, now_day, record_txt, df_Increment, df_lose):
    '''
    该函数用于比较两个数据集并记录重复、新增和丢弃的数据量。

    Args:
        tj_config (str): 天机配置名称
        categore_type (str): 数据类别
        save_path (str): 保存路径
        save_categorefile (str): 保存文件名
        now_day (str): 当前日期
        record_txt (str): 记录信息的字符串
        df_Increment (pd.DataFrame): 新增数据的DataFrame
        df_lose (pd.DataFrame): 丢弃数据的DataFrame

    Returns:
        tuple: 包含更新后的record_txt, df_Increment, df_lose
    '''
    previous_name = tj_config + '_' + categore_type + '_'
    previous_file = TianJiIocs.get_previousFile(save_path, save_categorefile, previous_name)
    columns = ['category', 'value', 'score']
    now_data = TianJiIocs.pickUpDataColumns(categore_type_data, columns)
    previous_data = TianJiIocs.pickUpDataColumns(pd.read_csv(previous_file), columns)
    
    repeat_num = len(TianJiIocs.repeatData(now_data, previous_data, 'value'))
    record_txt += f'{tj_config}--{categore_type}类型-重复数量{repeat_num}' + '\n'

    Increment_tmpData = TianJiIocs.incrementData(now_data, previous_data, 'value', now_day)
    if Increment_tmpData is not None:
        record_txt += f'{tj_config}--{categore_type}类型-增量：{len(Increment_tmpData)}' + '\n'
        df_Increment = pd.concat([Increment_tmpData, df_Increment], ignore_index=True)
    else:
        record_txt += f'{tj_config}--{categore_type}类型-增量：0' + '\n'

    lose_tmpData = TianJiIocs.loseData(previous_data, now_data, 'value', now_day)
    if lose_tmpData is not None:
        record_txt += f'{tj_config}--{categore_type}类型-丢弃：{len(lose_tmpData)}' + '\n'
        df_lose = pd.concat([lose_tmpData, df_lose], ignore_index=True)
    else:
        record_txt += f'{tj_config}--{categore_type}类型-丢弃：0' + '\n'
    
    return record_txt, df_Increment, df_lose