add stat files.

stockapp/sample/get_futu_.py

@@ -0,0 +1,62 @@
+import pymysql
+import pandas as pd
+from futu import *
+import logging
+from config import db_config  # 引用config.py中的数据库配置
+
+# 设置日志
+logging.basicConfig(level=logging.INFO, format='%(asctime)s %(levelname)s - %(message)s')
+logger = logging.getLogger()
+
+# 数据库连接函数
+def connect_to_db():
+    return pymysql.connect(**db_config)
+
+# 从sp300表中获取所有股票代码
+def fetch_sp300_codes(connection):
+    query = "SELECT code FROM sp300"
+    return pd.read_sql(query, connection)
+
+# 获取市场快照并保存到 CSV 文件
+def get_market_snapshot_and_save_to_csv(stock_codes, output_file):
+    quote_ctx = OpenQuoteContext(host='127.0.0.1', port=11111)
+    ret, data = quote_ctx.get_market_snapshot(stock_codes)
+    
+    if ret == RET_OK:
+        logger.info(f"Successfully fetched market snapshot for {len(stock_codes)} codes.")
+        # 将数据写入CSV文件
+        data.to_csv(output_file, index=False)
+        logger.info(f"Snapshot data saved to {output_file}")
+    else:
+        logger.error(f"Error fetching market snapshot: {data}")
+    
+    quote_ctx.close()
+
+# 主函数
+def main():
+    try:
+        # 连接数据库
+        connection = connect_to_db()
+
+        # 从 sp300 表中获取所有的股票代码
+        sp300_codes_df = fetch_sp300_codes(connection)
+        
+        # 提取股票代码列表
+        stock_codes = sp300_codes_df['code'].tolist()
+
+        if not stock_codes:
+            logger.warning("No stock codes found in sp300 table.")
+            return
+        
+        # 获取市场快照并保存到 CSV 文件
+        output_file = "market_snapshot.csv"
+        get_market_snapshot_and_save_to_csv(stock_codes, output_file)
+
+    except Exception as e:
+        logger.error(f"An error occurred: {e}")
+    finally:
+        if connection:
+            connection.close()
+
+if __name__ == "__main__":
+    main()

stockapp/sample/get_yh_kline.py

@@ -1,15 +1,28 @@
 import yfinance as yf
 import pandas as pd
 
+code = 'KDP'
+
 # 获取AAPL的股票数据
-stock = yf.Ticker("AAPL")
+stock = yf.Ticker(code)
 
 # 获取过去十年的日K线数据（前复权）
+hist_data = stock.history(period="10y", auto_adjust=True)
+
+print (hist_data['Close'].resample('Y').last().pct_change)
+
+# 打印数据前几行
+print(hist_data.head())
+
+# 保存到CSV文件
+hist_data.to_csv(f"{code}_10year_data_adjust.csv")
+
+
+# 获取过去十年的日K线数据（不复权）
 hist_data = stock.history(period="10y", auto_adjust=False)
 
 # 打印数据前几行
 print(hist_data.head())
 
 # 保存到CSV文件
-hist_data.to_csv("AAPL_10year_data.csv")
-
+hist_data.to_csv(f"{code}_10year_data.csv")