add stat files.

stockapp/stat_yield_rate.py

@@ -1,3 +1,18 @@
+"""
+Script Name: 
+Description: 统计过去十年来，hs300 和 sp500成分股的投资胜率，年化回报率等数据。
+
+Author: [Your Name]
+Created Date: YYYY-MM-DD
+Last Modified: YYYY-MM-DD
+Version: 1.0
+
+Modification History:
+    - YYYY-MM-DD [Your Name]: 
+    - YYYY-MM-DD [Your Name]: 
+    - YYYY-MM-DD [Your Name]: 
+"""
+
 import pymysql
 import logging
 import sys
@@ -5,6 +20,7 @@ import time
 import numpy as np
 from datetime import datetime
 import argparse
+import config
 
 # 设置默认值
 default_min_stat_years = 5
@@ -40,45 +56,25 @@ def parse_arguments():
 # 获取用户输入的参数
 min_stat_years, debug, market_key = parse_arguments()
 
-
-# 配置日志格式
-formatter = logging.Formatter('%(asctime)s %(levelname)s [%(filename)s:%(lineno)d] - %(message)s')
-
-# 动态生成日志文件名，基于 min_stat_years 的值
-log_filename = f'./log/stat_yield_{market_key}_{min_stat_years}years_rate.log'
-file_handler = logging.FileHandler(log_filename)
-file_handler.setFormatter(formatter)
-
-console_handler = logging.StreamHandler(sys.stdout)
-console_handler.setFormatter(formatter)
-
-logging.basicConfig(level=logging.INFO, handlers=[file_handler, console_handler])
-
-
-# MySQL 配置
-db_config = {
-    'host': '172.18.0.2',
-    'user': 'root',
-    'password': 'mysqlpw',
-    'database': 'stockdb'
-}
+# 配置日志
+config.setup_logging(f'./log/stat_yield_{market_key}_{min_stat_years}years_rate.log')
 
 # 传入表名的映射
 table_mapping = {
     "hs300": {
         "codes": "hs300",
-        "his_data": "hs300_qfq_his",
+        "his_data": "hs300_ajust_kline_202410",
         "stat_res": f"hs300_{min_stat_years}years_yield_stats_2410"
     },
     "sp500": {
         "codes": "sp500",
-        "his_data": "sp500_qfq_his_202410",
+        "his_data": "sp500_ajust_kline_202410",
         "stat_res": f"sp500_{min_stat_years}years_yield_stats_2410"
     }
 }
 
 # 连接 MySQL
-connection = pymysql.connect(**db_config)
+connection = pymysql.connect(**config.db_config)
 
 # 获取股票代码
 def get_codes(table_mapping, index_name):
@@ -89,7 +85,7 @@ def get_codes(table_mapping, index_name):
                 sql = f"SELECT code, code_name FROM {table_mapping[index_name]['codes']} LIMIT 1"
             else:
                 # 否则查询所有数据
-                sql = f"SELECT code, code_name FROM {table_mapping[index_name]['codes']}"
+                sql = f"SELECT code, code_name FROM {table_mapping[index_name]['codes']} "
             cursor.execute(sql)
             return cursor.fetchall()
     except pymysql.MySQLError as e:
@@ -172,8 +168,9 @@ def calculate_yield_rate(data):
                 if time_diff < min_stat_years:
                     continue
 
-                close_start = data[i]['close']
-                close_end = data[j]['close']
+                # 使用后复权数据，避免前复权中出现负数，0，从而影响统计。
+                close_start = data[i]['hfq_close']
+                close_end = data[j]['hfq_close']
                 yield_rate = (close_end / close_start) - 1
                 annual_yield_rate = yield_rate * 365 / (end_time_key - start_time_key).days
 
@@ -182,7 +179,7 @@ def calculate_yield_rate(data):
                 max_deficit_start = start_time_key
                 max_deficit_end = end_time_key
                 for k in range(i + 1, j):
-                    if data[k]['close'] > close_start:
+                    if data[k]['hfq_close'] > close_start:
                         deficit_days = (data[k]['time_key'] - start_time_key).days
                         max_deficit_days = deficit_days
                         max_deficit_end = data[k]['time_key']
@@ -273,6 +270,7 @@ def main(index_name):
             compute_statistics(connection, table_mapping, index_name, code, name, results)
 
             logging.info(f"完成 {code} 的处理")
+            time.sleep(1)
     except Exception as e:
         logging.error(f"处理过程中出现错误: {e}", exc_info=True)
     finally: