20250314修改:增加dingdanliu_nb_mflow

2025-03-15 22:40:06 +08:00
parent b814dfe535
commit e2c54c6409
89 changed files with 18394 additions and 22830 deletions
@@ -0,0 +1,61 @@
+price,Ask,Bid,symbol,datetime,delta,close,open,high,low,volume,dj
+"['6522.0', '6522.2', '6522.4', '6522.6', '6522.8', '6523.0', '6523.2', '6523.4', '6523.6', '6523.8', '6524.0', '6524.2', '6524.4', '6524.6', '6524.8', '6525.0', '6525.2', '6525.4', '6525.6', '6525.8', '6526.0', '6526.2', '6526.4', '6526.6', '6526.8', '6527.0', '6527.2', '6527.4', '6527.6', '6527.8']","[0, 0, 0, 0, 0, 0, 1, 9, 9, 14, 42, 49, 15, 4, 4, 42, 7, 14, 27, 22, 9, 8, 18, 3, 24, 11, 21, 18, 5, 5]","[12, 17, 5, 18, 40, 22, 10, 22, 0, 0, 47, 87, 0, 27, 22, 18, 19, 13, 55, 42, 6, 7, 13, 4, 0, 8, 0, 13, 0, 0]",IM2503,2025-03-12 13:02:00,-146,6525.6,6525.8,6527.8,6522.0,1112,-4
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+"['6526.6', '6526.8', '6527.0', '6527.2', '6527.4', '6527.6', '6527.8', '6528.0', '6528.4', '6528.8', '6529.0', '6529.2', '6529.4', '6529.6', '6529.8', '6530.0', '6530.2', '6530.4', '6530.6', '6530.8', '6531.0', '6531.2', '6531.4', '6531.6', '6531.8', '6532.0', '6532.2', '6532.4', '6532.6', '6532.8', '6533.0', '6533.2', '6533.4', '6533.6']","[0, 0, 0, 5, 3, 2, 5, 3, 1, 9, 3, 9, 7, 0, 3, 14, 10, 3, 13, 8, 7, 11, 11, 62, 33, 29, 1, 15, 43, 4, 21, 12, 3, 17]","[6, 5, 12, 0, 5, 17, 0, 6, 4, 5, 14, 6, 0, 24, 0, 5, 21, 8, 3, 11, 27, 5, 20, 57, 5, 0, 1, 11, 0, 14, 11, 0, 0, 0]",IM2503,2025-03-12 14:38:00,64,6527.4,6527.4,6533.6,6526.6,830,3,
+"['6526.6', '6526.8', '6527.0', '6527.2', '6527.6', '6528.2', '6528.4', '6528.6', '6529.0', '6529.2', '6529.6', '6529.8', '6530.0', '6530.2', '6530.4', '6530.6', '6530.8', '6531.0', '6531.2', '6531.4', '6531.6', '6531.8', '6532.0', '6532.2', '6532.4', '6532.6', '6532.8', '6533.0', '6533.2', '6533.4']","[0, 0, 6, 3, 5, 1, 0, 11, 4, 9, 12, 8, 13, 10, 1, 2, 5, 11, 6, 0, 7, 21, 8, 9, 8, 18, 34, 48, 18, 9]","[2, 5, 41, 0, 12, 0, 8, 5, 5, 2, 0, 31, 9, 21, 0, 0, 9, 0, 13, 6, 1, 30, 51, 9, 27, 8, 8, 16, 0, 0]",IM2503,2025-03-12 14:40:00,-32,6532.0,6527.6,6533.4,6526.6,750,0,
+"['6526.2', '6526.6', '6526.8', '6527.0', '6527.2', '6527.4', '6527.6', '6527.8', '6528.0', '6528.2', '6528.4', '6528.6', '6528.8', '6529.0', '6529.2', '6529.4', '6529.6', '6529.8', '6530.0', '6530.2', '6530.4', '6530.6', '6530.8', '6531.0', '6531.2', '6531.4', '6531.6', '6531.8', '6532.0', '6532.2', '6532.4', '6532.6', '6532.8', '6533.0', '6533.2', '6533.4', '6533.6', '6533.8']","[0, 0, 7, 0, 11, 0, 0, 0, 10, 26, 1, 0, 2, 8, 0, 4, 24, 1, 1, 7, 7, 4, 4, 0, 0, 0, 12, 3, 10, 0, 7, 24, 31, 29, 4, 20, 37, 12]","[22, 15, 0, 5, 4, 16, 6, 12, 13, 7, 0, 1, 8, 10, 7, 12, 0, 3, 18, 1, 8, 3, 7, 4, 8, 2, 0, 0, 17, 6, 8, 66, 9, 12, 3, 0, 10, 0]",IM2503,2025-03-12 14:42:00,-17,6527.0,6532.0,6533.8,6526.2,745,-1,
+"['6523.4', '6523.6', '6524.0', '6524.2', '6524.4', '6524.6', '6524.8', '6525.0', '6525.2', '6525.4', '6525.6', '6525.8', '6526.0', '6526.2', '6526.4', '6526.6', '6526.8', '6527.0', '6527.2', '6527.4', '6527.6', '6527.8', '6528.0', '6528.2', '6528.4', '6528.6', '6528.8', '6529.0', '6529.2']","[0, 2, 3, 38, 44, 12, 14, 32, 35, 26, 2, 16, 7, 16, 6, 35, 2, 14, 7, 18, 20, 0, 22, 20, 17, 15, 19, 11, 14]","[9, 8, 45, 21, 37, 13, 26, 28, 3, 38, 20, 3, 27, 16, 5, 3, 27, 18, 6, 13, 0, 24, 23, 20, 22, 7, 1, 0, 0]",IM2503,2025-03-12 14:44:00,4,6525.0,6527.4,6529.2,6523.4,1022,0,
+"['6518.8', '6519.0', '6519.2', '6520.2', '6520.6', '6521.0', '6521.2', '6521.4', '6521.8', '6522.0', '6522.2', '6522.4', '6522.6', '6522.8', '6523.0', '6523.2', '6523.4', '6523.6', '6523.8', '6524.0', '6524.4', '6524.6', '6524.8', '6525.0', '6525.2', '6525.4', '6525.6', '6525.8', '6526.0', '6526.2', '6526.4', '6526.6', '6526.8', '6527.0', '6527.4', '6527.8']","[0, 0, 30, 39, 0, 10, 3, 22, 6, 9, 29, 11, 4, 44, 3, 14, 10, 24, 19, 11, 10, 10, 3, 5, 13, 3, 7, 2, 7, 5, 21, 2, 1, 3, 0, 5]","[17, 21, 0, 33, 9, 34, 12, 0, 6, 20, 21, 11, 4, 12, 17, 41, 17, 14, 3, 5, 21, 4, 0, 5, 3, 13, 19, 3, 3, 8, 9, 14, 7, 5, 5, 0]",IM2503,2025-03-12 14:46:00,-31,6522.8,6524.8,6527.8,6518.8,965,0,
+"['6507.4', '6507.6', '6507.8', '6508.0', '6508.2', '6508.6', '6509.0', '6509.4', '6510.0', '6510.2', '6510.4', '6511.0', '6511.2', '6511.6', '6512.0', '6512.2', '6512.4', '6512.6', '6513.0', '6513.2', '6513.4', '6513.8', '6514.0', '6514.2', '6515.0', '6515.2', '6515.4', '6515.6', '6516.2', '6516.6', '6516.8', '6517.0', '6517.2', '6517.4', '6517.6', '6517.8', '6518.0', '6518.2', '6518.4', '6518.6', '6518.8', '6519.0', '6519.2', '6519.4', '6519.6', '6519.8', '6520.0', '6520.2', '6520.4', '6521.0', '6521.4', '6521.6', '6521.8', '6522.0', '6522.2', '6522.4', '6522.6', '6522.8', '6523.0', '6523.2', '6523.6', '6523.8', '6524.0', '6524.2', '6524.4', '6524.6']","[0, 13, 8, 19, 18, 28, 0, 0, 11, 3, 13, 12, 26, 0, 15, 10, 26, 5, 4, 29, 0, 9, 14, 7, 0, 0, 0, 8, 0, 0, 3, 0, 2, 5, 10, 0, 5, 19, 13, 0, 6, 59, 16, 34, 36, 27, 0, 33, 1, 0, 0, 0, 0, 0, 3, 3, 0, 0, 2, 1, 5, 2, 7, 2, 3, 8]","[13, 0, 18, 119, 6, 31, 17, 11, 35, 54, 27, 0, 66, 18, 21, 13, 4, 0, 39, 2, 6, 10, 16, 0, 52, 18, 22, 0, 3, 9, 12, 11, 10, 19, 27, 9, 11, 14, 18, 8, 12, 16, 12, 0, 35, 2, 7, 0, 0, 12, 10, 4, 9, 1, 0, 0, 4, 9, 1, 0, 3, 12, 6, 0, 0, 0]",IM2503,2025-03-12 14:48:00,-341,6507.4,6522.8,6524.6,6507.4,1712,-2,
+"['6506.4', '6506.6', '6507.0', '6507.2', '6507.4', '6507.6', '6507.8', '6508.0', '6508.2', '6508.4', '6508.6', '6508.8', '6509.0', '6509.2', '6509.4', '6509.6', '6509.8', '6510.0', '6510.2', '6510.4', '6510.6', '6510.8', '6511.0', '6511.2', '6511.4', '6511.6', '6511.8', '6512.0', '6512.2', '6512.4']","[0, 0, 4, 0, 39, 9, 4, 26, 22, 37, 10, 59, 90, 27, 14, 30, 39, 62, 7, 0, 51, 9, 22, 23, 7, 19, 3, 13, 11, 14]","[19, 55, 31, 15, 2, 27, 46, 93, 58, 29, 21, 11, 47, 2, 3, 34, 8, 51, 19, 5, 26, 30, 15, 15, 7, 18, 8, 10, 3, 6]",IM2503,2025-03-12 14:50:00,-63,6509.4,6508.4,6512.4,6506.4,1583,-1,
+"['6506.0', '6506.2', '6506.4', '6506.6', '6506.8', '6507.0', '6507.2', '6507.4', '6507.6', '6507.8', '6508.0', '6508.2', '6508.4', '6508.6', '6508.8', '6509.0', '6509.2', '6509.4', '6509.6', '6509.8', '6510.0', '6510.2', '6510.4', '6510.6', '6510.8', '6511.0', '6511.2']","[0, 18, 6, 0, 0, 0, 21, 83, 132, 0, 18, 34, 8, 53, 14, 27, 26, 18, 20, 55, 52, 14, 12, 30, 5, 40, 24]","[34, 2, 22, 3, 77, 31, 58, 17, 84, 19, 18, 23, 20, 31, 4, 80, 25, 15, 21, 26, 37, 0, 15, 43, 0, 7, 0]",IM2503,2025-03-12 14:52:00,-2,6509.2,6509.0,6511.2,6506.0,1600,-1,
+"['6502.0', '6502.2', '6502.4', '6502.6', '6502.8', '6503.0', '6503.4', '6503.6', '6503.8', '6504.0', '6504.2', '6504.4', '6504.6', '6504.8', '6505.0', '6505.2', '6505.4', '6505.6', '6505.8', '6506.0', '6506.8', '6507.0', '6507.4', '6507.6', '6507.8', '6508.0', '6508.2', '6508.4', '6508.6', '6508.8', '6509.0', '6509.2', '6509.4', '6509.6', '6509.8', '6510.0', '6510.2', '6510.4', '6510.6']","[0, 0, 0, 42, 0, 21, 0, 41, 0, 86, 32, 76, 54, 60, 159, 24, 52, 24, 59, 0, 0, 0, 0, 29, 2, 4, 6, 0, 7, 11, 7, 14, 0, 3, 6, 16, 8, 8, 24]","[13, 11, 36, 15, 17, 45, 15, 81, 65, 56, 14, 102, 38, 29, 115, 13, 6, 12, 0, 26, 7, 25, 4, 14, 0, 22, 10, 8, 8, 0, 5, 7, 30, 0, 14, 20, 0, 6, 29]",IM2503,2025-03-12 14:54:00,-43,6504.4,6509.2,6510.6,6502.0,1930,0,
+"['6504.0', '6504.2', '6504.4', '6504.6', '6504.8', '6505.0', '6505.2', '6505.4', '6505.8', '6506.0', '6506.2', '6506.4', '6506.6', '6506.8', '6507.0', '6507.2', '6507.4', '6507.6', '6507.8', '6508.0', '6508.2', '6508.4', '6508.6', '6509.2', '6509.4', '6509.6', '6509.8', '6510.0', '6510.2', '6510.4', '6510.6', '6510.8', '6511.0', '6511.2', '6511.4', '6511.6', '6511.8', '6512.0', '6512.4']","[0, 14, 6, 17, 18, 36, 13, 10, 17, 4, 9, 13, 0, 12, 0, 0, 42, 29, 8, 9, 8, 3, 22, 9, 20, 46, 0, 22, 27, 25, 53, 63, 93, 48, 7, 35, 33, 37, 3]","[37, 31, 6, 7, 5, 0, 0, 0, 7, 0, 0, 8, 6, 14, 22, 11, 18, 30, 0, 0, 0, 0, 16, 9, 29, 6, 29, 0, 44, 23, 46, 61, 9, 37, 2, 45, 3, 0, 0]",IM2503,2025-03-12 14:56:00,250,6511.8,6504.2,6512.4,6504.0,1504,4,
+"['6511.6', '6511.8', '6512.0', '6512.2', '6512.4', '6512.6', '6512.8', '6513.0', '6513.2', '6513.4', '6513.6', '6513.8', '6514.0', '6514.2', '6514.6', '6514.8', '6515.0', '6515.2', '6515.4', '6515.6', '6515.8', '6516.0', '6516.2', '6516.4', '6516.6', '6516.8', '6517.0', '6517.2', '6517.4', '6517.6', '6517.8', '6518.0', '6518.2', '6518.4', '6518.6', '6518.8', '6519.0', '6519.4', '6519.6', '6519.8', '6520.0']","[0, 0, 7, 5, 31, 42, 80, 53, 17, 19, 34, 83, 19, 8, 16, 21, 50, 6, 12, 8, 15, 43, 26, 36, 51, 2, 47, 28, 61, 36, 14, 23, 5, 19, 4, 26, 42, 37, 6, 30, 166]","[1, 32, 17, 15, 18, 7, 38, 6, 0, 20, 59, 12, 20, 15, 8, 37, 8, 15, 2, 10, 4, 0, 11, 25, 44, 39, 31, 0, 13, 0, 11, 0, 16, 4, 24, 21, 16, 34, 7, 3, 0]",IM2503,2025-03-12 14:58:00,585,6518.8,6512.4,6520.0,6511.6,2041,0,
+"['6513.0', '6513.2', '6513.4', '6513.6', '6513.8', '6514.0', '6514.2', '6514.4', '6514.6', '6514.8', '6515.0', '6515.2', '6515.4', '6515.6', '6515.8', '6516.0', '6516.2', '6516.4', '6516.6', '6517.0', '6517.2', '6517.6', '6517.8', '6518.0', '6518.2', '6518.4', '6518.6', '6518.8', '6519.0', '6519.2', '6519.4', '6519.6', '6519.8', '6520.0', '6520.6', '6520.8']","[14, 0, 45, 67, 68, 40, 19, 0, 49, 105, 0, 33, 10, 0, 0, 45, 30, 24, 0, 2, 0, 0, 0, 8, 11, 15, 39, 13, 24, 9, 24, 40, 5, 7, 0, 24]","[29, 42, 40, 68, 71, 53, 4, 25, 4, 42, 10, 9, 0, 47, 43, 55, 0, 0, 3, 21, 2, 16, 24, 18, 6, 0, 25, 70, 41, 13, 12, 0, 35, 11, 12, 17]",IM2503,2025-03-12 15:00:00,-98,6514.8,6518.8,6520.8,6513.0,1881,-1,
@@ -0,0 +1,302 @@
+from flask import Flask, render_template, jsonify, make_response
+from flask_socketio import SocketIO
+import pandas as pd
+import numpy as np
+import os
+import ast
+import time
+from datetime import datetime
+
+app = Flask(__name__)
+app.config['SECRET_KEY'] = 'secret!'
+socketio = SocketIO(app)
+
+# 添加安全响应头
+@app.after_request
+def add_security_headers(response):
+    response.headers['X-Content-Type-Options'] = 'nosniff'
+    response.headers['Cache-Control'] = 'no-store, no-cache, must-revalidate, max-age=0'
+    response.headers['Pragma'] = 'no-cache'
+    response.headers['Expires'] = '0'
+    return response
+
+# 加入邮件通知
+import smtplib
+from email.mime.text import MIMEText  # 导入 MIMEText 类发送纯文本邮件
+from email.mime.multipart import (
+    MIMEMultipart,
+)
+
+import akshare as ak
+
+# from email.mime.application import MIMEApplication
+
+# 配置邮件信息
+receivers = ["240884432@qq.com"]  # 设置邮件接收人地址
+subject = "TD_Simnow_Signal"  # 设置邮件主题 订单流策略交易信号
+
+# 配置邮件服务器信息
+smtp_server = "smtp.qq.com"  # 设置发送邮件的 SMTP 服务器地址
+smtp_port = 465  # 设置发送邮件的 SMTP 服务器端口号，一般为 25 端口 465
+sender = "240884432@qq.com"  # 设置发送邮件的邮箱地址
+username = "240884432@qq.com"  # 设置发送邮件的邮箱用户名
+password = "osjyjmbqrzxtbjbf"  # zrmpcgttataabhjh，设置发送邮件的邮箱密码或授权码
+
+last_sent_time = 0
+count = 0 
+time_period = 30
+
+# current_dir = os.path.dirname(os.path.abspath(__file__))
+# os.chdir(current_dir)
+# print("已更改为新的工作目录：", current_dir)
+
+# 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
+new_directory = r"D:\Git_Nas\Quant_Code\999.账户相关\test\0312"
+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)
+
+# 获取当前文件夹中所有包含"ofdata"字符的CSV文件
+def get_csv_files():
+    files = {}
+    for filename in os.listdir():
+        if "ofdata" in filename and filename.endswith(".csv"):
+            files[filename] = os.path.join(os.getcwd(), filename)
+    return files
+
+def send_mail(text):
+    global last_sent_time, count
+
+    # 检查时间间隔
+    current_time = time.time()
+    print('count:',count)
+    if count == 1 and current_time - last_sent_time <1:
+        print("current_time:",current_time)
+        print("last_sent_time:",last_sent_time)
+        print("一分钟内已发送过邮件，本次跳过")
+        return
+    elif count ==1 and current_time - last_sent_time >1:
+        count = 0 
+    if count == 0  and current_time - last_sent_time < 1:
+        msg = MIMEMultipart()
+        msg["From"] = sender
+        msg["To"] = ";".join(receivers)
+        msg["Subject"] = subject
+        html_content = f"""
+        <html>
+        <body>
+            <p>以下是数据的最后一列：</p>
+            {text}
+        </body>
+        </html>
+        """
+        msg.attach(MIMEText(html_content, 'html'))
+        smtp = smtplib.SMTP_SSL(smtp_server, smtp_port)
+        smtp.login(username, password)
+        smtp.sendmail(sender, receivers, msg.as_string())
+        count = 1
+        smtp.quit()
+
+# 根据文件路径加载数据，只读取前12列
+def load_data(file_path):
+    df = pd.read_csv(file_path, usecols=range(12)).iloc[-600:] # 只读取前12列
+
+    df = df.drop_duplicates(subset='datetime', keep='first').reset_index(drop=True)
+    # df = df[df['high'] != df['low']]
+    df["delta"] = df["delta"].astype(float)
+    df['datetime'] = pd.to_datetime(df['datetime'],format='ISO8601')#, dayfirst=True, format='mixed'
+    # df['delta累计'] = df.groupby(df['datetime'].dt.date)['delta'].cumsum()
+
+    # 自定义分组逻辑：前一日21:00至当日15:00为一天
+    def get_trading_day(dt):
+        # 如果时间在21:00之后，属于下一个交易日
+        if dt.hour >= 21:
+            return (dt + pd.Timedelta(days=1)).date()
+        # 如果时间在15:00之前，属于当前交易日
+        elif dt.hour < 15:
+            return dt.date()
+        # 15:00-21:00之间的数据属于当前交易日
+        else:
+            return dt.date()
+    
+    # 添加交易日列并转换为字符串
+    df['trading_day'] = df['datetime'].apply(get_trading_day)
+    df['trading_day'] = df['trading_day'].astype(str)  # 将日期转换为字符串
+    
+    # 按交易日计算delta累计
+    df['delta累计'] = df.groupby('trading_day')['delta'].cumsum()
+
+    df = df.fillna('缺值')
+    df['终极平滑值'],df['趋势方向'] = ultimate_smoother(df['close'],time_period)
+    df['datetime'] = df['datetime'].dt.strftime("%Y-%m-%d %H:%M:%S")
+    df['POC'] = add_poc_column(df)
+    df['最终趋势'] = finall_trend(df['delta累计'],df['趋势方向'])
+    # print(df.tail(1))
+    # print(type(df['delta累计'].iloc[-1]))
+
+    if len(df) >=time_period and (df['最终趋势'].iloc[-1] != df['最终趋势'].iloc[-2]):
+        table_text = df.iloc[:,3:].tail(1).to_html(index=False) #price,Ask,Bid,symbol,datetime,delta,close,open,high,low,volume,dj
+        send_mail(table_text)
+    else:
+        pass
+    return df.to_dict(orient="records")#.iloc[-48:]
+    # return df.iloc[-60:].iloc[::-1].to_dict(orient="records")
+
+def finall_trend(delta_sum,trend):
+    f_trend = [None]*(len(delta_sum))
+    # delta_sum = delta_sum.astype(float)
+    for i in range(len(delta_sum)):
+        if (delta_sum[i] == '缺值') or (trend[i] == '缺值'):
+            f_trend[i] = '方向不明'
+            # return f_trend
+        else:
+            if delta_sum[i] > 0 and (trend[i] == '多头趋势'):
+                f_trend[i] = '强多头'
+            elif delta_sum[i] < 0 and (trend[i] == '空头趋势'):
+                f_trend[i] = '强空头'
+            else:
+                f_trend[i] = '方向不明'
+    return f_trend
+
+    
+
+def safe_literal_eval(x):
+    """带异常处理的安全转换"""
+    try:
+        return ast.literal_eval(x)
+    except:
+        return []  # 返回空列表作为占位符
+
+def add_poc_column(df):
+    # 安全转换列数据
+    df['price'] = df['price'].apply(safe_literal_eval)
+    df['Ask'] = df['Ask'].apply(lambda x: list(map(int, safe_literal_eval(x))))
+    df['Bid'] = df['Bid'].apply(lambda x: list(map(int, safe_literal_eval(x))))
+    
+    # 定义处理函数（带数据验证）
+    def find_poc(row):
+        # 验证三个列表长度一致且非空
+        if not (len(row['price']) == len(row['Ask']) == len(row['Bid']) > 0):
+            return '缺值'  # 返回空值标记异常数据
+        
+        sums = [a + b for a, b in zip(row['Ask'], row['Bid'])]
+        try:
+            max_index = sums.index(max(sums))
+            return row['price'][max_index]
+        except ValueError:
+            return '缺值'  # 处理空求和列表情况
+    
+    # 应用处理函数
+    df['POC'] = df.apply(find_poc, axis=1)
+    
+    # 可选：统计异常数据
+    error_count = df['POC'].isnull().sum()
+    if error_count > 0:
+        print(f"警告：发现 {error_count} 行异常数据（已标记为NaN）")
+    
+    return df['POC']
+
+
+def ultimate_smoother(price,period):
+    # 初始化变量（修正角度单位为弧度）
+    a1 = np.exp(-1.414 * np.pi / period)
+    b1 = 2 * a1 * np.cos(1.414 * np.pi / period)  # 将180改为np.pi
+    c2 = b1
+    c3 = -a1 ** 2
+    c1 = (1 + c2 - c3) / 4
+    
+    # 准备输出序列
+    us = np.zeros(len(price))
+    us_new = np.zeros(len(price))
+    trend = [None]*(len(price))
+    ma_close = np.zeros(len(price))
+    
+    # 前4个点用原始价格初始化
+    for i in range(len(price)):
+        if i < 4:
+            us[i] = price.iloc[i]
+        else:
+            # 应用递归公式
+            us[i] = (1 - c1) * price.iloc[i] + (2 * c1 - c2) * price.iloc[i-1] \
+                    - (c1 + c3) * price.iloc[i-2] + c2 * us[i-1] + c3 * us[i-2]
+            
+        us_new = np.around(us, decimals=2)
+        ma_close = price.rolling(window=4*period).mean()#5*
+
+        # if us_new[i]>price[i] and ma_close[i]>price[i]:
+        #     trend[i] = '空头趋势'
+        # elif us_new[i]<price[i] and ma_close[i]<price[i]:
+        #     trend[i] = '多头趋势'
+        # else:
+        #     trend[i] = '无趋势'
+
+        if us_new[i] < ma_close.iloc[i]:
+            trend[i] = '空头趋势'
+        elif us_new[i] > ma_close.iloc[i]:
+            trend[i] = '多头趋势'
+        else:
+            trend[i] = '无趋势'
+
+    
+    return us_new,trend
+
+
+@app.route("/")
+def index():
+    return render_template("index.html")
+
+@app.route("/kline")
+def kline():
+    return render_template("kline.html")
+
+@app.route("/api/data")
+def get_data():
+    try:
+        files = get_csv_files()
+        data = {}
+        for symbol, filename in files.items():
+            loaded_data = load_data(filename)
+            if loaded_data:
+                data[symbol] = loaded_data
+        return jsonify(data)
+    except Exception as e:
+        return jsonify({"error": str(e)})
+
+def should_update():
+    """检查是否应该在当前时间更新数据"""
+    now = datetime.now()
+    # 检查是否是整点5分钟
+    if now.minute % 2 == 0:
+        # 检查是否在5秒内
+        if now.second < 2:
+            return True
+    return False
+
+def background_thread():
+    """后台线程，在每整点5分钟的5秒内发送数据更新"""
+    while True:
+        if should_update():
+            files = get_csv_files()
+            data = {}
+            for file_name, file_path in files.items():
+                data[file_name] = load_data(file_path)
+            socketio.emit('data_update', data)
+            print(f"数据更新完成 - {datetime.now().strftime('%Y-%m-%d %H:%M:%S')}")
+        time.sleep(1)  # 每秒检查一次
+
+@socketio.on('connect')
+def handle_connect():
+    print('Client connected')
+    # 启动后台线程
+    socketio.start_background_task(background_thread)
+
+@socketio.on('disconnect')
+def handle_disconnect():
+    print('Client disconnected')
+
+if __name__ == "__main__":
+    socketio.run(app, host='0.0.0.0', port=5000, debug=True)  # 监听所有网络接口
@@ -0,0 +1,135 @@
+<!DOCTYPE html>
+<html lang="en">
+<head>
+    <meta charset="UTF-8">
+    <meta name="viewport" content="width=device-width, initial-scale=1.0">
+    <title>订单流实时数据监控</title>
+    <link rel="stylesheet" href="https://cdn.jsdelivr.net/npm/bootstrap@5.1.3/dist/css/bootstrap.min.css">
+    <link rel="stylesheet" type="text/css" href="https://cdn.datatables.net/1.11.5/css/dataTables.bootstrap5.min.css">
+    <script src="https://cdnjs.cloudflare.com/ajax/libs/socket.io/4.0.1/socket.io.js"></script>
+    <style>
+        table {
+            width: 100%;
+            border-collapse: collapse;
+        }
+        table, th, td {
+            border: 1px solid black;
+        }
+        th, td {
+            padding: 8px;
+            text-align: center;
+        }
+        button {
+            margin: 10px;
+            padding: 10px;
+            cursor: pointer;
+        }
+        .active-symbol {
+            background-color: #e0e0e0;
+        }
+    </style>
+</head>
+<body>
+    <h1>Real-Time CSV Data Viewer</h1>
+
+    <div id="symbol-buttons">
+        <!-- 动态生成按钮 -->
+    </div>
+
+    <h3>Data for <span id="current-symbol">Loading...</span></h3>
+    <table id="data-table">
+        <thead>
+            <tr>
+                <th>Symbol</th>
+                <th>Datetime</th>
+                <th>Delta</th>
+                <th>Close</th>
+                <th>Open</th>
+                <th>High</th>
+                <th>Low</th>
+                <th>Volume</th>
+                <th>DJ</th>
+                <th>Delta累计</th>
+                <th>POC</th>
+                <th>终极平滑值</th>
+                <th>趋势方向</th>
+                <th>最终趋势</th>
+            </tr>
+        </thead>
+        <tbody>
+        </tbody>
+    </table>
+
+    <script>
+        let currentSymbol = null;
+        const socket = io();
+        const symbolButtons = document.getElementById('symbol-buttons');
+        const currentSymbolDisplay = document.getElementById('current-symbol');
+        const tableBody = document.querySelector("#data-table tbody");
+
+        // 初始化数据
+        fetch('/api/data')
+            .then(response => response.json())
+            .then(data => {
+                updateSymbolButtons(data);
+                if (Object.keys(data).length > 0) {
+                    currentSymbol = Object.keys(data)[0];
+                    updateTable(data[currentSymbol]);
+                }
+            });
+
+        // WebSocket事件处理
+        socket.on('connect', () => {
+            console.log('Connected to server');
+        });
+
+        socket.on('data_update', (data) => {
+            updateSymbolButtons(data);
+            if (currentSymbol && data[currentSymbol]) {
+                updateTable(data[currentSymbol]);
+            }
+        });
+
+        function updateSymbolButtons(data) {
+            symbolButtons.innerHTML = '';
+            Object.keys(data).forEach(symbol => {
+                const button = document.createElement('button');
+                button.textContent = symbol;
+                button.onclick = () => {
+                    currentSymbol = symbol;
+                    updateTable(data[symbol]);
+                };
+                if (symbol === currentSymbol) {
+                    button.classList.add('active-symbol');
+                }
+                symbolButtons.appendChild(button);
+            });
+        }
+
+        function updateTable(data) {
+            currentSymbolDisplay.textContent = currentSymbol;
+            tableBody.innerHTML = '';
+            data.forEach(row => {
+                const rowElement = document.createElement('tr');
+                rowElement.innerHTML = `
+                    <td>${row.symbol || ''}</td>
+                    <td>${row.datetime || ''}</td>
+                    <td>${row.delta || ''}</td>
+                    <td>${row.close || ''}</td>
+                    <td>${row.open || ''}</td>
+                    <td>${row.high || ''}</td>
+                    <td>${row.low || ''}</td>
+                    <td>${row.volume || ''}</td>
+                    <td>${row.dj !== undefined ? row.dj : ''}</td>
+                    <td>${row.delta累计 || ''}</td>
+                    <td>${row.POC || ''}</td>
+                    <td>${row.终极平滑值 || ''}</td>
+                    <td>${row.趋势方向 || ''}</td>
+                    <td>${row.最终趋势 || ''}</td>
+                `;
+                tableBody.appendChild(rowElement);
+            });
+        }
+    </script>
+</body>
+</html>
@@ -0,0 +1,531 @@
+<!DOCTYPE html>
+<html lang="en">
+<head>
+    <meta charset="UTF-8">
+    <meta name="viewport" content="width=device-width, initial-scale=1.0">
+    <meta http-equiv="X-Content-Type-Options" content="nosniff">
+    <meta http-equiv="Cache-Control" content="no-cache, no-store, must-revalidate">
+    <meta http-equiv="Pragma" content="no-cache">
+    <meta http-equiv="Expires" content="0">
+    <title>实时K线图</title>
+    <script src="https://cdnjs.cloudflare.com/ajax/libs/socket.io/4.0.1/socket.io.js"></script>
+    <script src="https://cdn.jsdelivr.net/npm/echarts@5.4.3/dist/echarts.min.js"></script>
+    <style>
+        #kline-chart {
+            width: 100%;
+            height: 800px;
+            margin: 20px auto;
+        }
+        .symbol-selector {
+            margin: 20px;
+            text-align: center;
+        }
+        button {
+            margin: 10px;
+            padding: 10px;
+            cursor: pointer;
+        }
+        .active-symbol {
+            background-color: #e0e0e0;
+        }
+        body {
+            margin: 0;
+            padding: 0;
+            background-color: #f5f5f5;
+        }
+    </style>
+</head>
+<body>
+    <div class="symbol-selector" id="symbol-buttons">
+        <!-- 动态生成按钮 -->
+    </div>
+    <div id="kline-chart"></div>
+
+    <script>
+        let currentSymbol = null;
+        const socket = io();
+        const symbolButtons = document.getElementById('symbol-buttons');
+        let chart = null;
+
+        // 初始化图表
+        function initChart() {
+            if (!chart) {
+                chart = echarts.init(document.getElementById('kline-chart'));
+            }
+        }
+
+        // 初始化数据
+        fetch('/api/data')
+            .then(response => response.json())
+            .then(data => {
+                updateSymbolButtons(data);
+                if (Object.keys(data).length > 0) {
+                    currentSymbol = Object.keys(data)[0];
+                    updateChart(data[currentSymbol]);
+                }
+            })
+            .catch(error => {
+                console.error('Error fetching data:', error);
+            });
+
+        // WebSocket事件处理
+        socket.on('connect', () => {
+            console.log('Connected to server');
+        });
+
+        socket.on('data_update', (data) => {
+            updateSymbolButtons(data);
+            if (currentSymbol && data[currentSymbol]) {
+                updateChart(data[currentSymbol]);
+            }
+        });
+
+        function updateSymbolButtons(data) {
+            symbolButtons.innerHTML = '';
+            Object.keys(data).forEach(symbol => {
+                const button = document.createElement('button');
+                button.textContent = symbol;
+                button.onclick = () => {
+                    currentSymbol = symbol;
+                    updateChart(data[symbol]);
+                };
+                if (symbol === currentSymbol) {
+                    button.classList.add('active-symbol');
+                }
+                symbolButtons.appendChild(button);
+            });
+        }
+
+        function updateChart(data) {
+            initChart();
+
+            // 准备数据
+            const dates = data.map(item => item.datetime);
+            const klineData = data.map(item => [
+                parseFloat(item.open),
+                parseFloat(item.close),
+                parseFloat(item.low),
+                parseFloat(item.high)
+            ]);
+            const volumes = data.map(item => parseFloat(item.volume));
+            const ultimateValues = data.map(item => parseFloat(item.终极平滑值));
+            const deltaSums = data.map(item => parseFloat(item.delta累计));
+            const djValues = data.map(item => parseFloat(item.dj));
+            const deltaValues = data.map(item => parseFloat(item.delta));
+
+            // 处理POC数据，将缺值替换为前一个有效值
+            let pocValues = data.map(item => item.POC);
+            let lastValidPoc = null;
+            pocValues = pocValues.map(value => {
+                if (value === '缺值') {
+                    return lastValidPoc;
+                } else {
+                    lastValidPoc = parseFloat(value);
+                    return lastValidPoc;
+                }
+            });
+
+            // 计算120日均线
+            const closes = data.map(item => parseFloat(item.close));
+            const ma120 = calculateMA(closes, 120);
+
+            // 处理 delta 累计数据，用于标记箭头
+            const arrowMarks = [];
+            for (let i = 1; i < deltaSums.length; i++) {
+                if (deltaSums[i - 1] < 0 && deltaSums[i] > 0 && ultimateValues[i] > ma120[i]) {
+                    // 前一个值小于0，后一个值大于0，标记向上箭头
+                    arrowMarks.push({
+                        coord: [dates[i], data[i].low - 0.1], // 标记在 K 线下方
+                        symbol: 'path://M0,10 L5,0 L10,10 Z',
+                        symbolSize: [10, 10],
+                        symbolOffset: [0, 5],
+                        itemStyle: {
+                            color: 'red'
+                        }
+                    });
+                } else if (deltaSums[i - 1] > 0 && deltaSums[i] < 0  && ultimateValues[i] < ma120[i] ) {
+                    // 前一个值大于0，后一个值小于0，标记向下箭头
+                    arrowMarks.push({
+                        coord: [dates[i], data[i].high + 0.1], // 标记在 K 线上方
+                        symbol: 'path://M0,0 L5,10 L10,0 Z',
+                        symbolSize: [10, 10],
+                        symbolOffset: [0, -5],
+                        itemStyle: {
+                            color: 'green'
+                        }
+                    });
+                }
+            }
+
+            // 处理 dj 数据，用于标记圆
+            const circleMarks = [];
+            for (let i = 0; i < djValues.length; i++) {
+                let startIndex = Math.max(0, i - 119);
+                let recentDJValues = djValues.slice(startIndex, i + 1);
+                let maxDJ = Math.max(...recentDJValues);
+                let minDJ = Math.min(...recentDJValues);
+                if (djValues[i] >= maxDJ * 0.8  && ultimateValues[i] > ma120[i]) {
+                    // dj 大于等于最近120个dj值的最大值的80%，标记向上的红色圆
+                    circleMarks.push({
+                        coord: [dates[i], data[i].low - 5.1], // 标记在 K 线下方
+                        symbol: 'circle',
+                        symbolSize: 10,
+                        symbolOffset: [0, 5],
+                        itemStyle: {
+                            color: 'red'
+                        }
+                    });
+                } else if (djValues[i] <= minDJ * 0.8  && ultimateValues[i] < ma120[i]) {
+                    // dj 小于等于最近120个dj值的最小值的80%，标记向下的绿色圆
+                    circleMarks.push({
+                        coord: [dates[i], data[i].high + 5.1], // 标记在 K 线上方
+                        symbol: 'circle',
+                        symbolSize: 10,
+                        symbolOffset: [0, -5],
+                        itemStyle: {
+                            color: 'green'
+                        }
+                    });
+                }
+            }
+
+            // 处理 delta 值数据，用于标记方块
+            const squareMarks = [];
+            for (let i = 0; i < deltaValues.length; i++) {
+                let startIndex = Math.max(0, i - 119);
+                let recentDeltaValues = deltaValues.slice(startIndex, i + 1);
+                let maxDelta = Math.max(...recentDeltaValues);
+                let minDelta = Math.min(...recentDeltaValues);
+                if (deltaValues[i] >= maxDelta * 0.8  && ultimateValues[i] > ma120[i]) {
+                    // delta 值大于等于最近120个delta值的最大值的80%，标记向上的红色方块
+                    squareMarks.push({
+                        coord: [dates[i], data[i].low - 10.1], 
+                        symbol: 'rect',
+                        symbolSize: 10,
+                        symbolOffset: [0, 5],
+                        itemStyle: {
+                            color: 'red'
+                        }
+                    });
+                } else if (deltaValues[i] <= minDelta * 0.8  && ultimateValues[i] < ma120[i]) {
+                    // delta 值小于等于最近120个delta值的最小值的80%，标记向上的绿色方块
+                    squareMarks.push({
+                        coord: [dates[i], data[i].high + 10.1], 
+                        symbol: 'rect',
+                        symbolSize: 10,
+                        symbolOffset: [0, -5],
+                        itemStyle: {
+                            color: 'green'
+                        }
+                    });
+                }
+            }
+
+            // 合并箭头标记、圆标记和方块标记
+            const allMarks = arrowMarks.concat(circleMarks).concat(squareMarks);
+
+            // 配置图表选项
+            const option = {
+                title: {
+                    text: `${currentSymbol} K线图`,
+                    left: 'center'
+                },
+                tooltip: {
+                    trigger: 'axis',
+                    axisPointer: {
+                        type: 'cross'
+                    }
+                },
+                legend: {
+                    data: ['K线', '120日均线', '终极平滑值', 'POC', '成交量', 'Delta累计', 'DJ值', 'Delta值'],
+                    top: 30
+                },
+                grid: [
+                    {
+                        left: '10%',
+                        right: '8%',
+                        height: '40%'
+                    },
+                    {
+                        left: '10%',
+                        right: '8%',
+                        top: '50%',
+                        height: '10%'
+                    },
+                    {
+                        left: '10%',
+                        right: '8%',
+                        top: '60%',
+                        height: '10%'
+                    },
+                    {
+                        left: '10%',
+                        right: '8%',
+                        top: '70%',
+                        height: '10%'
+                    },
+                    {
+                        left: '10%',
+                        right: '8%',
+                        top: '80%',
+                        height: '10%'
+                    }
+                ],
+                xAxis: [
+                    {
+                        type: 'category',
+                        data: dates,
+                        scale: true,
+                        boundaryGap: false,
+                        axisLine: {onZero: false},
+                        splitLine: {show: false},
+                        splitNumber: 20,
+                        gridIndex: 0
+                    },
+                    {
+                        type: 'category',
+                        gridIndex: 1,
+                        data: dates,
+                        axisLabel: {show: false}
+                    },
+                    {
+                        type: 'category',
+                        gridIndex: 2,
+                        data: dates,
+                        axisLabel: {show: false}
+                    },
+                    {
+                        type: 'category',
+                        gridIndex: 3,
+                        data: dates,
+                        axisLabel: {show: false}
+                    },
+                    {
+                        type: 'category',
+                        gridIndex: 4,
+                        data: dates,
+                        axisLabel: {show: true}
+                    }
+                ],
+                yAxis: [
+                    {
+                        scale: true,
+                        splitArea: {
+                            show: true
+                        },
+                        gridIndex: 0
+                    },
+                    {
+                        scale: true,
+                        gridIndex: 1,
+                        splitNumber: 2,
+                        axisLabel: {show: true},
+                        axisLine: {show: true},
+                        splitLine: {show: false}
+                    },
+                    {
+                        scale: true,
+                        gridIndex: 2,
+                        splitNumber: 2,
+                        axisLabel: {show: true},
+                        axisLine: {show: true},
+                        splitLine: {show: false}
+                    },
+                    {
+                        scale: true,
+                        gridIndex: 3,
+                        splitNumber: 2,
+                        axisLabel: {show: true},
+                        axisLine: {show: true},
+                        splitLine: {show: false}
+                    },
+                    {
+                        scale: true,
+                        gridIndex: 4,
+                        splitNumber: 2,
+                        axisLabel: {show: true},
+                        axisLine: {show: true},
+                        splitLine: {show: false}
+                    }
+                ],
+                dataZoom: [
+                    {
+                        type: 'inside',
+                        xAxisIndex: [0, 1, 2, 3, 4],
+                        start: 50,
+                        end: 100
+                    },
+                    {
+                        show: true,
+                        xAxisIndex: [0, 1, 2, 3, 4],
+                        type: 'slider',
+                        bottom: '2%',
+                        start: 50,
+                        end: 100
+                    }
+                ],
+                series: [
+                    {
+                        name: 'K线',
+                        type: 'candlestick',
+                        data: klineData,
+                        itemStyle: {
+                            color: 'none', // 空心 K 线，填充颜色设为无
+                            color0: 'none',
+                            borderColor: '#ef232a',
+                            borderColor0: '#14b143',
+                            borderWidth: 1
+                        },
+                        // 添加标记点
+                        markPoint: {
+                            data: allMarks
+                        }
+                    },
+                    {
+                        name: '120日均线',
+                        type: 'line',
+                        data: ma120,
+                        smooth: true,
+                        lineStyle: {
+                            opacity: 0.5
+                        }
+                    },
+                    {
+                        name: '终极平滑值',
+                        type: 'line',
+                        data: ultimateValues,
+                        smooth: true,
+                        lineStyle: {
+                            opacity: 0.5
+                        }
+                    },
+                    {
+                        name: 'POC',
+                        type: 'line',
+                        data: pocValues,
+                        smooth: true,
+                        lineStyle: {
+                            color: '#FFD700',
+                            width: 2,
+                            opacity: 0.8
+                        },
+                        symbol: 'circle',
+                        symbolSize: 6
+                    },
+                    {
+                        name: '成交量',
+                        type: 'bar',
+                        xAxisIndex: 1,
+                        yAxisIndex: 1,
+                        data: volumes
+                    },
+                    {
+                        name: 'Delta累计',
+                        type: 'line',
+                        xAxisIndex: 2,
+                        yAxisIndex: 2,
+                        data: deltaSums,
+                        smooth: true,
+                        lineStyle: {
+                            color: '#4169E1',
+                            width: 2,
+                            opacity: 0.8
+                        },
+                        markLine: {
+                            silent: true,
+                            data: [
+                                {
+                                    yAxis: 0,
+                                    lineStyle: {
+                                        color: '#999',
+                                        type: 'dashed'
+                                    }
+                                }
+                            ]
+                        }
+                    },
+                    {
+                        name: 'DJ值',
+                        type: 'line',
+                        xAxisIndex: 3,
+                        yAxisIndex: 3,
+                        data: djValues,
+                        smooth: true,
+                        lineStyle: {
+                            color: '#9932CC',
+                            width: 2,
+                            opacity: 0.8
+                        },
+                        markLine: {
+                            silent: true,
+                            data: [
+                                {
+                                    yAxis: 0,
+                                    lineStyle: {
+                                        color: '#999',
+                                        type: 'dashed'
+                                    }
+                                }
+                            ]
+                        }
+                    },
+                    {
+                        name: 'Delta值',
+                        type: 'line',
+                        xAxisIndex: 4,
+                        yAxisIndex: 4,
+                        data: deltaValues,
+                        smooth: true,
+                        lineStyle: {
+                            color: '#FF8C00',
+                            width: 2,
+                            opacity: 0.8
+                        },
+                        markLine: {
+                            silent: true,
+                            data: [
+                                {
+                                    yAxis: 0,
+                                    lineStyle: {
+                                        color: '#999',
+                                        type: 'dashed'
+                                    }
+                                }
+                            ]
+                        }
+                    }
+                ]
+            };
+
+            // 使用配置项显示图表
+            chart.setOption(option);
+        }
+
+        function calculateMA(data, dayCount) {
+            const result = [];
+            for (let i = 0, len = data.length; i < len; i++) {
+                if (i < dayCount - 1) {
+                    result.push('-');
+                    continue;
+                }
+                let sum = 0;
+                for (let j = 0; j < dayCount; j++) {
+                    sum += data[i - j];
+                }
+                result.push(+(sum / dayCount).toFixed(2));
+            }
+            return result;
+        }
+
+        // 响应窗口大小变化
+        window.addEventListener('resize', function() {
+            if (chart) {
+                chart.resize();
+            }
+        });
+
+        // 初始化图表
+        initChart();
+    </script>
+</body>
+</html>