增加交易策略、交易指标、量化库代码等文件夹

1.交易策略/999.其他策略/2.松鼠SF12_日内订单流横截面交易策略/使用文稿/定时启动.py

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+import subprocess
+import schedule
+import time
+from datetime import datetime
+
+#   jerome：增加akshare库
+import akshare as ak
+
+#   jerome:增加下列库用于爬虫获取主力连续代码
+import pandas as pd
+import requests
+from bs4 import BeautifulSoup
+import csv
+import re
+import os
+#   jerome:增加文件名修改工作
+import shutil
+
+#   Jerome:需要设置的参数
+new_directory = r"C:/simnow_trader" #设置运行目录为程序所在目录new_directory
+# 定义要启动的文件
+files_to_run = ['dingdanliu_nb.py']
+#   定义生成的保证金、手续费csv文件
+fees_filepath = r'./futures_fees_info.csv'
+contracts_filepath = r'./main_contacts.csv'
+contracts_yd_filepath = r'./main_contacts_yd.csv'
+exchange_filepath = r'./exchange_for_months.csv'
+
+
+
+# jerome:修改运行目录
+# 获取当前工作目录
+current_directory = os.getcwd()
+print("当前工作目录：", current_directory)
+# 设置新的工作目录
+os.chdir(new_directory) 
+# 验证新的工作目录
+updated_directory = os.getcwd()
+print("已更改为新的工作目录：", updated_directory)
+
+def run_scripts():
+    print("启动程序...")
+    for file in files_to_run:
+        time.sleep(1)
+        # 使用subprocess模块运行命令
+        subprocess.Popen(['start', 'cmd', '/k', 'python', file], shell=True)
+        print(file)
+    print(datetime.now(),'程序重新启动完成，等待明天关闭重启')
+
+def close_scripts():
+    print("关闭程序...")
+    # 通过创建一个包含关闭指定窗口命令的批处理文件来关闭CMD窗口
+    def close_specific_cmd_window(cmd_window_title):
+        with open("close_cmd_window.bat", "w") as batch_file:
+            batch_file.write(f'@echo off\nfor /f "tokens=2 delims=," %%a in (\'tasklist /v /fo csv ^| findstr /i "{cmd_window_title}"\') do taskkill /pid %%~a')
+
+        # 运行批处理文件
+        subprocess.run("close_cmd_window.bat", shell=True)
+        
+
+    # 循环关闭所有脚本对应的CMD窗口
+    for title in files_to_run:
+        close_specific_cmd_window(title)
+    print(datetime.now(),'已关闭程序，等待重新运行程序')
+
+#   jerome:增加使用akshare获取期货的手续费等数据，并保存到对应目录下
+def get_futures_fees_info():
+    futures_fees_info_df = ak.futures_fees_info() 
+    futures_fees_info_df[['品种代码', '交割月份']] = futures_fees_info_df['合约代码'].apply(lambda x: pd.Series(split_alpha_numeric(x)))
+    futures_fees_info_df.to_csv(fees_filepath, index=False)
+    print("期货保证金、手续费csv文件已经保存!")
+
+def get_main_contacts():
+    url = "https://www.9qihuo.com/hangqing"
+
+    # 发送GET请求，禁用SSL验证
+    response = requests.get(url, verify=False)
+    response.encoding = 'utf-8'  # 确保编码正确
+
+    # 解析网页内容
+    soup = BeautifulSoup(response.text, 'lxml')
+
+    # 找到目标表格
+    table = soup.find('table', {'id': 'tblhangqinglist'})
+
+    # 初始化CSV文件
+    with open(r'./tmp_main_contacts.csv', mode='w', newline='', encoding='utf-8') as file:
+        writer = csv.writer(file)
+        
+        # 遍历表格的所有行
+        for row in table.find_all('tr'):
+            # 获取每一行的所有单元格
+            cols = row.find_all(['th', 'td'])
+            # 提取文本内容并写入CSV文件
+            writer.writerow([col.text.strip() for col in cols])
+
+    df = pd.read_csv(r'./tmp_main_contacts.csv',encoding='utf-8')
+    df['交易品种'] = df['合约'].str.split(r'[()]', n=1, expand=True)[0]
+    df['主连代码'] = df['合约'].str.split(r'[()]', n=2, expand=True)[1]
+
+    df[['品种代码', '交割月份']] = df['主连代码'].apply(lambda x: pd.Series(split_alpha_numeric(x)))
+    if os.path.exists(contracts_filepath):
+        os.remove(contracts_filepath)
+        print("原有今日期货主连csv文件已经删除!")
+
+    df.to_csv(r'./main_contacts.csv')
+    os.remove(r'./tmp_main_contacts.csv')
+    print("今日期货主连csv文件已经保存!")
+
+#   拆分字母和数字的函数
+def split_alpha_numeric(s):
+    match = re.match(r"([a-zA-Z]+)([0-9]+)", s)
+    if match:
+        return match.groups()
+    else:
+        return (s, None)  # 如果没有匹配，返回原始字符串和None
+    
+def rename_file():
+    # source_file = r'./main_contacts.csv'
+    # target_file = r'./main_contacts_yd.csv'
+    
+    # 检查是否存在 main_contacts_yd.csv，如果存在则删除
+    if os.path.exists(contracts_yd_filepath):
+        os.remove(contracts_yd_filepath)
+        print("原有昨日期货主连csv文件已经删除!")
+
+    shutil.copy(contracts_filepath, contracts_yd_filepath)
+    # print(f"{contracts_filepath} has been copied to {contracts_yd_filepath}")
+    print("今日期货主连csv文件已经修改为昨日主连csv文件!")
+    
+    # # 重命名文件
+    # if os.path.exists(source_file):
+    #     os.rename(source_file, target_file)
+    #     print(f'Renamed {source_file} to {target_file}')
+    # else:
+    #     print(f'{source_file} does not exist')
+
+def exchange_for_months():
+    td_df = pd.read_csv(contracts_filepath, header = 0, usecols= [16, 17],names=['主连代码', '品种代码'])
+    if not os.path.exists(contracts_yd_filepath):       
+        shutil.copy(contracts_filepath, contracts_yd_filepath)
+        print("昨日主连csv文件不存在,已经使用今日主连csv替代!")
+    yd_df = pd.read_csv(contracts_yd_filepath, header = 0, usecols= [16, 17],names=['主连代码', '品种代码']) 
+
+    # 合并两个 DataFrame
+    merged_df = pd.merge(td_df, yd_df, on='品种代码', suffixes=('_今日', '_昨日'))
+    # 检查 '主连代码' 是否相等
+    merged_df['主连代码_相等'] = merged_df['主连代码_今日'] == merged_df['主连代码_昨日']
+
+    if os.path.exists(exchange_filepath):
+        os.remove(exchange_filepath)
+        print("原有换月对比csv文件已经删除!")
+    merged_df.to_csv(exchange_filepath)
+    print("换月对比csv文件已经生成!")
+
+#   程序时间建议(以每晚9点交易为最开始时间）：1生成费率表和今日主连文件;2生成换月对比文件；3、启动晚间交易程序并登录账户；
+#   4关闭晚间交易程序；5启动白天交易程序并登录账户；6生成昨日主连文件；7关闭白天交易程序。
+# 设置定时任务，关闭程序
+schedule.every().day.at("15:10").do(close_scripts)
+schedule.every().day.at("03:00").do(close_scripts)
+
+# 设置定时任务，启动程序
+schedule.every().day.at("08:55").do(run_scripts)
+schedule.every().day.at("20:55").do(run_scripts)
+
+# 设置定时任务，生成费率表文件和今日主连文件
+schedule.every().day.at("20:53").do(get_futures_fees_info)
+schedule.every().day.at("20:53").do(get_main_contacts)
+
+# 设置定时任务，生成换月对比文件
+schedule.every().day.at("20:55").do(exchange_for_months)
+
+# 设置定时任务，安排任务每天15:30执行, 生成昨日主连文件
+schedule.every().day.at("15:05").do(rename_file)
+
+# 保持脚本运行，等待定时任务触发
+while True:
+    schedule.run_pending()
+    time.sleep(1)