Traceback (most recent call last): File "C:\Users\MAC\Desktop\py\筛选股票\121.py", line 9, in <module> today = datetime.date.today().strftime('%Y-%m-%d') AttributeError: 'method_descriptor' object has no attribute 'today'

这个错误通常是因为 `datetime.today()` 和 `datetime.date.today()` 这两个方法名重复导致的。可以尝试使用完整的模块名来调用 `today()` 方法，即将 `datetime.date.today()` 替换为 `datetime.datetime.today().date()`。修改后的代码如下： ```python import tushare as ts import pandas as pd import datetime # 设置tushare token ts.set_token('your_token_here') # 获取今日日期 today = datetime.datetime.today().date().strftime('%Y-%m-%d') # 获取今日及今日前四个交易日的日期 days = [datetime.datetime.today().date() - datetime.timedelta(days=i) for i in range(5)] dates = [d.strftime('%Y-%m-%d') for d in days] # 获取沪市、深市、创业板、科创板股票数据 data = pd.DataFrame() for date in dates: hs_data = ts.get_hist_data('sh', date=date) if hs_data is not None: hs_data['type'] = 'sh' data = data.append(hs_data) sz_data = ts.get_hist_data('sz', date=date) if sz_data is not None: sz_data['type'] = 'sz' data = data.append(sz_data) cyb_data = ts.get_hist_data('cyb', date=date) if cyb_data is not None: cyb_data['type'] = 'cyb' data = data.append(cyb_data) kcb_data = ts.get_hist_data('kcb', date=date) if kcb_data is not None: kcb_data['type'] = 'kcb' data = data.append(kcb_data) # 保存数据 data.to_csv(f'{today}_data.csv', index=False) # 读取数据 data = pd.read_csv(f'{today}_data.csv') # 筛选出五日内每日成交额最多的100支股票 top100 = data.groupby(['code'])['amount'].sum().sort_values(ascending=False)[:100].index.tolist() data = data[data['code'].isin(top100)] # 计算股票今日及前四个交易日收盘价的均价 data['close_mean'] = data.groupby(['code'])['close'].transform(lambda x: x.mean()) # 选出今日收盘价大于五日均价且今日成交量为三日内最少的股票 data = data[data['close'] > data['close_mean']] data = data.groupby(['code']).apply(lambda x: x.nsmallest(3, 'volume')) data = data.groupby(['code']).apply(lambda x: x.nlargest(1, 'date')) data = data.reset_index(drop=True) # 保存结果到文件 data.to_csv(f'{today}_result.csv', index=False) ``` 希望能解决你的问题。