72 lines
2.4 KiB
Python
72 lines
2.4 KiB
Python
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import pandas as pd
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from tqdm import tqdm
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from utils import load_config, get_trade_cal
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from utils import save_df_to_db, load_df_from_db, get_existing_trade_dates
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# 加载配置并初始化tushare
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config = load_config()
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import tushare as ts
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ts.set_token(config['tushare_token'])
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pro = ts.pro_api()
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def get_sector_moneyflow_data(start_date=None, end_date=None):
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"""
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获取指定时间段内的板块资金流向数据，使用数据库缓存
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参数:
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start_date (str): 开始日期，格式'YYYYMMDD'
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end_date (str): 结束日期，格式'YYYYMMDD'
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返回:
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pandas.DataFrame: 所有板块资金流向数据
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"""
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# 获取目标交易日历
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all_trade_dates = get_trade_cal(start_date, end_date)
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# 从数据库获取已有的交易日期，使用表键名
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existing_dates = get_existing_trade_dates(table_key='moneyflow_ind_dc')
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# 筛选出需要新获取的日期
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new_dates = [date for date in all_trade_dates if date not in existing_dates]
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if not new_dates:
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print("所有数据已在数据库中，无需更新")
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return load_df_from_db(table_key='moneyflow_ind_dc')
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print(f"需要获取 {len(new_dates)} 个新交易日的数据")
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# 获取新日期的数据
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all_new_data = []
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# 使用tqdm显示进度
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for trade_date in tqdm(new_dates):
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try:
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# 从tushare获取当日板块资金流向数据
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df = pro.moneyflow_ind_dc(trade_date=trade_date)
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# 如果有数据，添加到列表
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if not df.empty:
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all_new_data.append(df)
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else:
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print(f"日期 {trade_date} 无数据")
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except Exception as e:
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print(f"获取 {trade_date} 的数据时出错: {e}")
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# 如果有新数据，合并并保存到数据库
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if all_new_data:
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# 将所有新数据合并为一个DataFrame
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new_df = pd.concat(all_new_data, ignore_index=True)
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# 保存到数据库，使用表键名
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save_df_to_db(new_df, table_key='moneyflow_ind_dc', if_exists='append')
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print(f"已将 {len(new_df)} 条新记录保存到数据库")
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else:
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print("未获取到任何新数据")
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return load_df_from_db(table_key='moneyflow_ind_dc')
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if __name__ == "__main__":
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# 指定日期范围
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start_date = '20250401'
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end_date = None
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# 获取板块资金流向数据
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get_sector_moneyflow_data(start_date, end_date)
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