update

Readme.md

@@ -1,25 +0,0 @@
-
-### 依赖
-pip install httpx
-
-### 目录结构
-
-```text
-FactorSimulator/
-├── __init__.py                      # 包初始化文件，定义包级别的导入和元数据
-├── main.py                          # 程序主入口，负责启动批量模拟流程
-├── core/                            # 核心业务逻辑模块
-│   ├── __init__.py                  # 核心模块初始化，定义模块级别的导入
-│   ├── api_client.py                # WorldQuant Brain API客户端封装，处理HTTP请求和认证
-│   └── models.py                    # 数据模型定义，使用dataclass定义各种指标和结果的数据结构
-├── managers/                        # 管理器模块，负责业务流程协调
-│   ├── __init__.py                  # 管理器模块初始化
-│   └── simulation_manager.py        # 模拟管理器，负责批量模拟的调度、线程池管理和结果汇总
-├── utils/                           # 工具函数模块
-│   ├── __init__.py                  # 工具模块初始化
-│   ├── file_utils.py                # 文件操作工具，处理因子列表加载和结果保存
-│   └── time_utils.py                # 时间格式化工具，将秒数转换为可读格式
-└── config/                          # 配置模块
-    ├── __init__.py                  # 配置模块初始化
-    └── settings.py                  # 模拟参数配置，定义默认的模拟设置常量
-```

__init__.py

@@ -1,13 +0,0 @@
-# -*- coding: utf-8 -*-
-"""
-WorldQuant Brain 因子模拟器
-用于批量模拟Alpha因子的工具
-"""
-
-__version__ = "0.0.1"
-__author__ = "Jack"
-
-from .core.api_client import WorldQuantBrainSimulate
-from .managers.simulation_manager import AlphaSimulationManager
-
-__all__ = ['WorldQuantBrainSimulate', 'AlphaSimulationManager']

alpha.txt

@@ -1 +0,0 @@
-ts_delta(ts_mean(close, 5), 10) / ts_std(close, 20) * (ts_mean(close, 20) / ts_mean(close, 100) > 1.02)

config/__init__.py

@@ -1,8 +0,0 @@
-# -*- coding: utf-8 -*-
-"""
-配置模块 - 包含配置常量
-"""
-
-from .settings import DEFAULT_SIMULATION_SETTINGS
-
-__all__ = ['DEFAULT_SIMULATION_SETTINGS']

config/settings.py

@@ -1,19 +1,53 @@
 # -*- coding: utf-8 -*-
-"""
+"""配置文件"""
-模拟配置常量
+
-"""
+import os
-
+from typing import Dict, Any
-DEFAULT_SIMULATION_SETTINGS = {
+
-    'instrumentType': 'EQUITY',
+
-    'region': 'USA',
+class Settings:
-    'universe': 'TOP3000',
+    """应用配置"""
-    'delay': 1,
+
-    'decay': 0,
+    # 数据库配置
-    'neutralization': 'INDUSTRY',
+    DATABASE_CONFIG = {
-    'truncation': 0.08,
+        "host": "localhost",
-    'pasteurization': 'ON',
+        "port": "5432",
-    'unitHandling': 'VERIFY',
+        "user": "jack",
-    'nanHandling': 'OFF',
+        "password": "aaaAAA111",
-    'language': 'FASTEXPR',
+        "database": "alpha"
-    'visualization': False,
+    }
-}
+
+    # API配置
+    BRAIN_API_URL = "https://api.worldquantbrain.com"
+
+    # 模拟配置
+    SIMULATION_SETTINGS = {
+        'instrumentType': 'EQUITY',
+        'region': 'USA',
+        'universe': 'TOP3000',
+        'delay': 1,
+        'decay': 0,
+        'neutralization': 'INDUSTRY',
+        'truncation': 0.08,
+        'pasteurization': 'ON',
+        'unitHandling': 'VERIFY',
+        'nanHandling': 'OFF',
+        'language': 'FASTEXPR',
+        'visualization': False,
+    }
+
+    # 批处理配置
+    BATCH_SIZE = 3
+    CHECK_INTERVAL = 300  # 5分钟
+    TOKEN_REFRESH_THRESHOLD = 1800  # 30分钟
+
+    # 通知配置
+    GOTIFY_URL = "https://gotify.erhe.top/message?token=AvKJCJwQKU6yLP8"
+
+    @property
+    def credentials_file(self) -> str:
+        """获取凭证文件路径"""
+        return os.path.join(os.path.dirname(os.path.dirname(__file__)), 'account.txt')
+
+
+settings = Settings()

core/__init__.py

@@ -1,9 +0,0 @@
-# -*- coding: utf-8 -*-
-"""
-核心模块 - 包含API客户端和数据模型
-"""
-
-from .api_client import WorldQuantBrainSimulate
-from .models import AlphaMetrics, SimulationResult
-
-__all__ = ['WorldQuantBrainSimulate', 'AlphaMetrics', 'SimulationResult']

core/api_client.py

@@ -1,158 +0,0 @@
-# -*- coding: utf-8 -*-
-import os.path
-import httpx
-import time
-from httpx import BasicAuth
-from typing import Dict, Any, Optional, Tuple
-
-
-class WorldQuantBrainSimulate:
-    def __init__(self, credentials_file='account.txt'):
-        self.credentials_file = credentials_file
-        self.client = None
-        self.brain_api_url = 'https://api.worldquantbrain.com'
-
-    """读取本地账号密码"""
-    def load_credentials(self) -> Tuple[str, str]:
-        if not os.path.exists(self.credentials_file):
-            print("未找到 account.txt 文件")
-            with open(self.credentials_file, 'w') as f:
-                f.write("")
-            print("account.txt 文件已创建，请填写账号密码, 格式: ['username', 'password]")
-            exit(1)
-
-        with open(self.credentials_file) as f:
-            credentials = eval(f.read())
-        return credentials[0], credentials[1]
-
-    """登录认证"""
-    def login(self) -> bool:
-        username, password = self.load_credentials()
-        self.client = httpx.Client(auth=BasicAuth(username, password))
-
-        response = self.client.post(f'{self.brain_api_url}/authentication')
-        print(f"登录状态: {response.status_code}")
-
-        if response.status_code == 201:
-            print("登录成功!")
-            print(f"账户信息: {response.json()}")
-            return True
-        else:
-            print(f"登录失败: {response.json()}")
-            return False
-
-    """模拟Alpha因子"""
-    def simulate_alpha(self, expression: str, settings: Optional[Dict[str, Any]] = None) -> Dict[str, Any]:
-        if self.client is None:
-            raise Exception("请先登录")
-
-        default_settings = {
-            'instrumentType': 'EQUITY',
-            'region': 'USA',
-            'universe': 'TOP3000',
-            'delay': 1,
-            'decay': 0,
-            'neutralization': 'INDUSTRY',
-            'truncation': 0.08,
-            'pasteurization': 'ON',
-            'unitHandling': 'VERIFY',
-            'nanHandling': 'OFF',
-            'language': 'FASTEXPR',
-            'visualization': False,
-        }
-
-        if settings:
-            default_settings.update(settings)
-
-        simulation_data = {
-            'type': 'REGULAR',
-            'settings': default_settings,
-            'regular': expression
-        }
-
-        sim_resp = self.client.post(f'{self.brain_api_url}/simulations', json=simulation_data)
-        print(f"模拟提交状态: {sim_resp.status_code}")
-
-        sim_progress_url = sim_resp.headers['location']
-        print(f"进度URL: {sim_progress_url}")
-
-        while True:
-            sim_progress_resp = self.client.get(sim_progress_url)
-            retry_after_sec = float(sim_progress_resp.headers.get("Retry-After", 0))
-
-            if retry_after_sec == 0:
-                break
-            if sim_progress_resp.json():
-                result = sim_progress_resp.json()
-                progress = result['progress']
-                if progress:
-                    print(f"模拟进度: {float(progress)*100}%")
-
-            print(f"等待 {retry_after_sec} 秒...")
-            time.sleep(retry_after_sec)
-
-        # 如果因子模拟不通过, 获取一下失败信息
-        if sim_progress_resp.json()["status"] == "ERROR":
-            result = sim_progress_resp.json()["message"]
-            print(f"因子模拟失败: {result}")
-            # 返回一个特殊标识，表示模拟失败
-            return {"status": "error", "message": result}
-
-        alpha_id = sim_progress_resp.json()["alpha"]
-        print(f"生成的Alpha ID: {alpha_id}")
-
-        # 获取详细的性能指标
-        metrics = self.get_alpha_metrics(alpha_id)
-
-        return {"status": "success", "alpha_id": alpha_id, "metrics": metrics}
-
-    """获取Alpha因子的详细指标"""
-    def get_alpha_metrics(self, alpha_id: str) -> Dict[str, Any]:
-        if self.client is None:
-            raise Exception("请先登录")
-
-        try:
-            # 获取Alpha的基本信息和指标
-            alpha_url = f'{self.brain_api_url}/alphas/{alpha_id}'
-            alpha_resp = self.client.get(alpha_url)
-
-            if alpha_resp.status_code in [200, 201]:
-                alpha_data = alpha_resp.json()
-
-                # 以后可能需要获取其他参数
-                if alpha_data.get('metrics'):
-                    alpha_data = alpha_data.get('metrics')
-
-                return alpha_data or {}
-            else:
-                print(f"获取Alpha指标失败: {alpha_resp.status_code}")
-                # 返回一个空的字典结构
-                return {
-                    "train": {},
-                    "is": {},
-                    "test": {},
-                    "grade": None,
-                    "stage": None,
-                    "status": None,
-                    "dateCreated": None,
-                    "id": alpha_id
-                }
-
-        except Exception as e:
-            print(f"获取指标时出错: {str(e)}")
-            # 返回一个空的字典结构
-            return {
-                "train": {},
-                "is": {},
-                "test": {},
-                "grade": None,
-                "stage": None,
-                "status": None,
-                "dateCreated": None,
-                "id": alpha_id
-            }
-
-    def close(self):
-        """关闭连接"""
-        if self.client:
-            self.client.close()

core/database.py

@@ -0,0 +1,176 @@
+# -*- coding: utf-8 -*-
+"""数据库管理层"""
+
+import psycopg2
+from typing import List, Optional
+from config.settings import settings
+from models.entities import SimulationResult, AlphaExpression
+
+
+class DatabaseManager:
+    """数据库管理类"""
+
+    def __init__(self):
+        self.connection = None
+        self.init_database()
+
+    def create_database(self) -> None:
+        """创建数据库（如果不存在）"""
+        try:
+            # 先连接到默认的postgres数据库来创建alpha数据库
+            conn = psycopg2.connect(
+                host=settings.DATABASE_CONFIG["host"],
+                port=settings.DATABASE_CONFIG["port"],
+                database="postgres",
+                user=settings.DATABASE_CONFIG["user"],
+                password=settings.DATABASE_CONFIG["password"]
+            )
+            conn.autocommit = True
+            cursor = conn.cursor()
+
+            # 检查数据库是否存在
+            cursor.execute("SELECT 1 FROM pg_catalog.pg_database WHERE datname = %s",
+                           (settings.DATABASE_CONFIG["database"],))
+            exists = cursor.fetchone()
+
+            if not exists:
+                cursor.execute(f"CREATE DATABASE {settings.DATABASE_CONFIG['database']}")
+                print(f"数据库 {settings.DATABASE_CONFIG['database']} 创建成功")
+            else:
+                print(f"数据库 {settings.DATABASE_CONFIG['database']} 已存在")
+
+            cursor.close()
+            conn.close()
+
+        except Exception as e:
+            print(f"创建数据库时出错: {e}")
+            raise
+
+    def get_connection(self) -> psycopg2.extensions.connection:
+        """获取数据库连接"""
+        if self.connection is None or self.connection.closed:
+            self.connection = psycopg2.connect(
+                host=settings.DATABASE_CONFIG["host"],
+                port=settings.DATABASE_CONFIG["port"],
+                database=settings.DATABASE_CONFIG["database"],
+                user=settings.DATABASE_CONFIG["user"],
+                password=settings.DATABASE_CONFIG["password"]
+            )
+        return self.connection
+
+    def init_database(self) -> None:
+        """初始化数据库和表结构"""
+        # 先创建数据库
+        self.create_database()
+
+        # 然后连接到此数据库创建表
+        conn = self.get_connection()
+        cursor = conn.cursor()
+
+        # 创建 alpha_prepare 表
+        cursor.execute('''
+                       CREATE TABLE IF NOT EXISTS alpha_prepare
+                       (
+                           id
+                           SERIAL
+                           PRIMARY
+                           KEY,
+                           alpha
+                           TEXT
+                           NOT
+                           NULL
+                           UNIQUE,
+                           unused
+                           BOOLEAN
+                           NOT
+                           NULL
+                           DEFAULT
+                           TRUE,
+                           created_time
+                           TIMESTAMP
+                           DEFAULT
+                           CURRENT_TIMESTAMP
+                       )
+                       ''')
+
+        # 创建 simulation 表
+        cursor.execute('''
+                       CREATE TABLE IF NOT EXISTS simulation
+                       (
+                           id
+                           SERIAL
+                           PRIMARY
+                           KEY,
+                           expression
+                           TEXT
+                           NOT
+                           NULL,
+                           time_consuming
+                           REAL
+                           NOT
+                           NULL,
+                           status
+                           TEXT
+                           NOT
+                           NULL,
+                           timestamp
+                           TEXT
+                           NOT
+                           NULL,
+                           alpha_id
+                           TEXT,
+                           message
+                           TEXT,
+                           created_time
+                           TIMESTAMP
+                           DEFAULT
+                           CURRENT_TIMESTAMP
+                       )
+                       ''')
+
+        conn.commit()
+        print(f"数据库 {settings.DATABASE_CONFIG['database']} 表结构初始化完成")
+
+    def get_unused_alpha(self) -> List[str]:
+        """获取所有未使用的alpha表达式"""
+        conn = self.get_connection()
+        cursor = conn.cursor()
+
+        cursor.execute("SELECT alpha FROM alpha_prepare WHERE unused = TRUE")
+        results = cursor.fetchall()
+
+        alpha_list = [result[0] for result in results]
+        return alpha_list
+
+    def mark_alpha_used(self, alpha: str) -> None:
+        """将alpha标记为已使用"""
+        conn = self.get_connection()
+        cursor = conn.cursor()
+
+        cursor.execute("UPDATE alpha_prepare SET unused = FALSE WHERE alpha = %s", (alpha,))
+        conn.commit()
+
+    def insert_simulation_result(self, result: SimulationResult) -> None:
+        """插入模拟结果到simulation表"""
+        conn = self.get_connection()
+        cursor = conn.cursor()
+
+        cursor.execute('''
+                       INSERT INTO simulation
+                           (expression, time_consuming, status, timestamp, alpha_id, message)
+                       VALUES (%s, %s, %s, %s, %s, %s)
+                       ''', (
+                           result.expression,
+                           result.time_consuming,
+                           result.status,
+                           result.timestamp,
+                           result.alpha_id,
+                           result.message or ""
+                       ))
+
+        conn.commit()
+
+    def close_connection(self) -> None:
+        """关闭数据库连接"""
+        if self.connection and not self.connection.closed:
+            self.connection.close()

core/models.py

@@ -1,62 +0,0 @@
-# -*- coding: utf-8 -*-
-from dataclasses import dataclass
-from typing import Dict, Any, Optional
-
-
-@dataclass
-class TrainMetrics:
-    """训练集指标"""
-    sharpe_ratio: Optional[float] = None
-    annual_return: Optional[float] = None
-    max_drawdown: Optional[float] = None
-    turnover: Optional[float] = None
-    fitness: Optional[float] = None
-    pnl: Optional[float] = None
-    book_size: Optional[float] = None
-    long_count: Optional[float] = None
-    short_count: Optional[float] = None
-    margin: Optional[float] = None
-
-
-@dataclass
-class TestMetrics:
-    """测试集指标"""
-    sharpe_ratio: Optional[float] = None
-    annual_return: Optional[float] = None
-    max_drawdown: Optional[float] = None
-    turnover: Optional[float] = None
-    fitness: Optional[float] = None
-    pnl: Optional[float] = None
-
-
-@dataclass
-class AlphaInfo:
-    """Alpha基本信息"""
-    grade: Optional[str] = None
-    stage: Optional[str] = None
-    status: Optional[str] = None
-    date_created: Optional[str] = None
-    checks: Optional[Dict[str, Any]] = None
-
-
-@dataclass
-class AlphaMetrics:
-    """Alpha因子完整指标"""
-    train_metrics: TrainMetrics
-    is_metrics: TestMetrics
-    test_metrics: TestMetrics
-    alpha_info: AlphaInfo
-    alpha_id: Optional[str] = None
-
-
-@dataclass
-class SimulationResult:
-    """模拟结果"""
-    expression: str
-    time_consuming: float
-    formatted_time: str
-    alpha_id: str
-    status: str
-    description: str
-    simulation_timestamp: str
-    metrics: Optional[Dict[str, Any]] = None

core/simulator.py

@@ -0,0 +1,126 @@
+# -*- coding: utf-8 -*-
+"""Alpha模拟器核心类"""
+
+import time
+import httpx
+from datetime import datetime
+from typing import List, Tuple
+from config.settings import settings
+from models.entities import SimulationResult, TokenInfo
+from core.database import DatabaseManager
+from services.auth_service import AuthService
+from services.alpha_service import AlphaService
+from services.notification_service import NotificationService
+
+
+class AlphaSimulator:
+    """Alpha模拟器主类"""
+
+    def __init__(self):
+        self.db_manager = DatabaseManager()
+        self.auth_service = AuthService()
+        self.client = None
+        self.token_info = None
+        self.alpha_service = None
+
+    def __del__(self):
+        """析构函数，确保数据库连接被关闭"""
+        if hasattr(self, 'db_manager'):
+            self.db_manager.close_connection()
+
+    def initialize(self) -> None:
+        """初始化模拟器"""
+        self.client = httpx.Client()
+        self.login()
+
+    def login(self) -> TokenInfo:
+        """登录并初始化alpha服务"""
+        self.token_info = self.auth_service.login(self.client)
+        self.alpha_service = AlphaService(self.client)
+        return self.token_info
+
+    def needs_token_refresh(self) -> bool:
+        """检查是否需要刷新token"""
+        if not self.token_info:
+            return True
+        return self.token_info.expiry < settings.TOKEN_REFRESH_THRESHOLD
+
+    def load_alpha_list(self) -> List[str]:
+        """从数据库加载未使用的alpha表达式"""
+        return self.db_manager.get_unused_alpha()
+
+    def run_batch_simulation(self, alpha_list: List[str]) -> Tuple[int, int]:
+        """运行批量模拟"""
+        success_count = 0
+        fail_count = 0
+
+        for i in range(0, len(alpha_list), settings.BATCH_SIZE):
+            batch = alpha_list[i:i + settings.BATCH_SIZE]
+            print(f"\n开始处理第 {i // settings.BATCH_SIZE + 1} 批因子，共 {len(batch)} 个")
+
+            for expression in batch:
+                result = self._simulate_single_alpha(expression)
+                if result.status == "ok":
+                    success_count += 1
+                else:
+                    fail_count += 1
+
+            print(f"第 {i // settings.BATCH_SIZE + 1} 批处理完成")
+
+        self._print_summary(success_count, fail_count)
+        return success_count, fail_count
+
+    def _simulate_single_alpha(self, expression: str) -> SimulationResult:
+        """模拟单个Alpha表达式"""
+        print(f"\n模拟因子: {expression}")
+        start_time = time.time()
+
+        try:
+            result = self.alpha_service.simulate_alpha(expression)
+            end_time = time.time()
+            time_consuming = round(end_time - start_time, 2)
+
+            simulation_result = SimulationResult(
+                expression=expression,
+                time_consuming=time_consuming,
+                status=result["status"],
+                timestamp=datetime.now().strftime("%Y-%m-%d %H:%M:%S"),
+                alpha_id=result.get("alpha_id"),
+                message=result.get("message", "")
+            )
+
+            if result["status"] == "ok":
+                print(f"✅ 模拟成功 - Alpha ID: {result['alpha_id']} - 耗时: {time_consuming}秒")
+            else:
+                print(f"❌ 模拟失败 - {result.get('message', '未知错误')}")
+
+        except Exception as e:
+            end_time = time.time()
+            time_consuming = round(end_time - start_time, 2)
+            simulation_result = SimulationResult(
+                expression=expression,
+                time_consuming=time_consuming,
+                status="err",
+                message=str(e),
+                timestamp=datetime.now().strftime("%Y-%m-%d %H:%M:%S")
+            )
+            print(f"❌ 模拟异常 - {str(e)}")
+
+        # 保存结果并标记为已使用
+        self._save_simulation_result(simulation_result)
+        return simulation_result
+
+    def _save_simulation_result(self, result: SimulationResult) -> None:
+        """保存模拟结果到数据库"""
+        self.db_manager.mark_alpha_used(result.expression)
+        self.db_manager.insert_simulation_result(result)
+
+    def _print_summary(self, success_count: int, fail_count: int) -> None:
+        """打印总结信息"""
+        now = datetime.now().strftime('%Y-%m-%d %H:%M:%S')
+        print(f"\n总计: 成功 {success_count} 个, 失败 {fail_count} 个")
+        print(f"完成时间: {now}")
+        print(f"所有结果已保存到 PostgreSQL 数据库 {settings.DATABASE_CONFIG['database']} 的 simulation 表中")
+
+        # 发送通知
+        NotificationService.send_to_gotify(success_count, fail_count)

main.py

@@ -1,21 +1,45 @@
 # -*- coding: utf-8 -*-
-import os
+"""主程序入口"""
-from managers.simulation_manager import AlphaSimulationManager
-from utils.file_utils import load_alpha_list
 
+import time
+from core.simulator import AlphaSimulator
+from config.settings import settings
+from utils.helpers import retry_on_exception
 
-def main():
-    """主程序入口"""
-    # 待模拟因子列表
-    alpha_list = load_alpha_list('alpha.txt')
 
+@retry_on_exception(max_retries=3, delay=5.0)
+def main_loop(simulator: AlphaSimulator) -> None:
+    """主循环"""
+    if simulator.needs_token_refresh():
+        print("Token需要刷新，重新登录...")
+        simulator.login()
+
+    alpha_list = simulator.load_alpha_list()
     if not alpha_list:
-        print("未找到有效的因子表达式，请检查 alpha.txt 文件")
+        print("暂无待处理的alpha表达式，10分钟后重新检查...")
+        time.sleep(600)
         return
 
-    # 创建模拟管理器并运行
+    print(f"共加载 {len(alpha_list)} 个需要模拟的因子表达式")
-    manager = AlphaSimulationManager()
+    success_count, fail_count = simulator.run_batch_simulation(alpha_list)
-    results = manager.run_simulation(alpha_list, batch_size=3)
+    print(f"本轮处理完成: 成功 {success_count} 个, 失败 {fail_count} 个")
+
+
+def main():
+    """主函数"""
+    simulator = AlphaSimulator()
+    simulator.initialize()
+
+    try:
+        while True:
+            main_loop(simulator)
+            print(f"等待{settings.CHECK_INTERVAL // 60}分钟后继续检查...")
+            time.sleep(settings.CHECK_INTERVAL)
+    except KeyboardInterrupt:
+        print("\n程序被用户中断")
+    except Exception as e:
+        print(f"程序执行异常: {e}")
+        raise
 
 
 if __name__ == "__main__":

managers/__init__.py

@@ -1,8 +0,0 @@
-# -*- coding: utf-8 -*-
-"""
-管理模块 - 包含各种管理器类
-"""
-
-from .simulation_manager import AlphaSimulationManager
-
-__all__ = ['AlphaSimulationManager']

managers/simulation_manager.py

@@ -1,232 +0,0 @@
-# -*- coding: utf-8 -*-
-import time
-import json
-import os
-from concurrent.futures import ThreadPoolExecutor, as_completed
-from random import uniform
-from typing import List, Dict, Any
-
-from core.api_client import WorldQuantBrainSimulate
-from core.models import SimulationResult
-from utils.time_utils import format_time
-from utils.file_utils import save_results_to_file, save_success_alpha
-
-
-class AlphaSimulationManager:
-    def __init__(self, credentials_file='account.txt'):
-        self.credentials_file = credentials_file
-        self.results = []
-
-    """模拟单个Alpha因子（线程安全）"""
-    def simulate_single_alpha(self, api: WorldQuantBrainSimulate, expression: str,
-                              settings: Dict[str, Any] = None) -> SimulationResult:
-        alpha_start_time = time.time()
-
-        try:
-            # 模拟Alpha因子
-            simulation_result = api.simulate_alpha(expression, settings)
-            alpha_end_time = time.time()
-            time_consuming = alpha_end_time - alpha_start_time
-
-            # 根据模拟结果类型处理
-            if simulation_result["status"] == "success":
-                # 模拟成功的结果 - 直接使用原始metrics数据
-                metrics = simulation_result["metrics"]
-                result = SimulationResult(
-                    expression=expression,
-                    time_consuming=time_consuming,
-                    formatted_time=format_time(time_consuming),
-                    alpha_id=simulation_result["alpha_id"],
-                    status="success",
-                    description="/",
-                    simulation_timestamp=time.strftime("%Y-%m-%d %H:%M:%S"),
-                    metrics=metrics  # 直接存储原始metrics数据
-                )
-                print(f"✓ 因子模拟成功: {expression}")
-                print(f"  耗时: {format_time(time_consuming)}，Alpha ID: {simulation_result['alpha_id']}")
-
-                # 打印关键指标
-                self._print_success_metrics(metrics)
-
-            else:
-                # 模拟失败的结果（API返回的错误）
-                result = SimulationResult(
-                    expression=expression,
-                    time_consuming=time_consuming,
-                    formatted_time=format_time(time_consuming),
-                    alpha_id="/",
-                    status="error",
-                    description=simulation_result["message"],
-                    simulation_timestamp=time.strftime("%Y-%m-%d %H:%M:%S"),
-                    metrics=None
-                )
-                print(f"✗ 因子模拟失败: {expression}")
-                print(f"  耗时: {format_time(time_consuming)}，错误: {simulation_result['message']}")
-
-        except Exception as e:
-            # 其他异常情况
-            alpha_end_time = time.time()
-            time_consuming = alpha_end_time - alpha_start_time
-
-            result = SimulationResult(
-                expression=expression,
-                time_consuming=time_consuming,
-                formatted_time=format_time(time_consuming),
-                alpha_id="/",
-                status="failed",
-                description=str(e),
-                simulation_timestamp=time.strftime("%Y-%m-%d %H:%M:%S"),
-                metrics=None
-            )
-            print(f"✗ 因子模拟异常: {expression}")
-            print(f"  耗时: {format_time(time_consuming)}，异常: {str(e)}")
-
-        return result
-
-    """打印成功因子的关键指标"""
-    def _print_success_metrics(self, metrics: Dict[str, Any]):
-        # 添加空值检查
-        if not metrics:
-            print("  无指标数据")
-            return
-
-        print("  关键指标 (训练集):")
-        # 从原始metrics数据中提取训练集指标
-        train_data = metrics.get('train', {}) or {}
-        key_metrics = [
-            ('夏普比率', train_data.get('sharpe')),
-            ('年化收益', train_data.get('returns')),
-            ('最大回撤', train_data.get('drawdown')),
-            ('换手率', train_data.get('turnover')),
-            ('适应度', train_data.get('fitness')),
-            ('PNL', train_data.get('pnl')),
-        ]
-
-        for chinese_name, value in key_metrics:
-            if value is not None:
-                if isinstance(value, float):
-                    value = f"{value:.4f}"
-                print(f"    {chinese_name}: {value}")      # 衡量风险调整后的收益
-     # 年化收益率
-        # 显示样本外测试的夏普比率（如果存在）    # 最大亏损幅度
-        test_data = metrics.get('test', {}) or {}      # 交易频率
-        if test_data.get('sharpe') is not None:       # 策略适应度得分
-            print(f"  样本外夏普比率: {test_data.get('sharpe'):.4f}")             # 净盈亏
-
-    """模拟一批Alpha因子（3个一组）"""
-    def simulate_alpha_batch(self, alpha_batch: List[str], batch_number: int) -> List[SimulationResult]:
-        print(f"\n{'=' * 60}")    # 只打印存在的指标
-        print(f"开始第 {batch_number} 批因子模拟 (共 {len(alpha_batch)} 个因子)")    # 格式化浮点数显示
-        print(f"因子列表: {alpha_batch}")
-        print(f"{'=' * 60}")
-
-        batch_start_time = time.time()
-        batch_results = []
-    # 检查是否存在测试集夏普比率
-        # 创建API客户端实例（每个线程独立的客户端）
-        api = WorldQuantBrainSimulate(self.credentials_file)
-
-        try:
-            if api.login():
-                # 使用线程池执行3个因子的模拟
-                with ThreadPoolExecutor(max_workers=3) as executor:
-                    # 提交所有任务
-                    future_to_alpha = {
-                        executor.submit(self.simulate_single_alpha, api, alpha): alpha
-                        for alpha in alpha_batch
-                    }
-
-                    # 等待所有任务完成
-                    for future in as_completed(future_to_alpha):
-                        alpha = future_to_alpha[future]
-                        try:
-                            result = future.result()
-                            batch_results.append(result)
-                        except Exception as e:
-                            print(f"因子 {alpha} 执行异常: {e}")
-        except Exception as e:
-            print(f"第 {batch_number} 批模拟过程中出错: {e}")
-        finally:
-            api.close()
-
-        batch_end_time = time.time()
-        batch_total_time = batch_end_time - batch_start_time
-
-        print(f"\n第 {batch_number} 批模拟完成!")
-        print(f"本批总耗时: {format_time(batch_total_time)}")
-        print(f"{'=' * 60}")
-
-        return batch_results
-
-    """运行批量模拟"""
-    def run_simulation(self, alpha_list: List[str], batch_size: int = 3) -> List[SimulationResult]:
-        print("开始Alpha因子批量模拟...")
-        total_start_time = time.time()
-
-        # 将因子列表分成每批3个
-        batches = [alpha_list[i:i + batch_size] for i in range(0, len(alpha_list), batch_size)]
-
-        all_results = []
-
-        for i, batch in enumerate(batches, 1):
-            # 模拟当前批次
-            batch_results = self.simulate_alpha_batch(batch, i)
-            all_results.extend(batch_results)
-
-            # 如果不是最后一批，则等待3-5秒
-            if i < len(batches):
-                sleep_time = uniform(3, 5)
-                print(f"\n等待 {sleep_time:.2f} 秒后开始下一批...")
-                time.sleep(sleep_time)
-
-        total_end_time = time.time()
-        total_time = total_end_time - total_start_time
-
-        # 输出最终结果汇总
-        self.print_summary(all_results, total_time)
-
-        # 保存结果到文件
-        save_results_to_file(all_results)
-
-        return all_results
-
-    """打印结果汇总"""
-    def print_summary(self, results: List[SimulationResult], total_time: float):
-        print(f"\n{'=' * 60}")
-        print("模拟结果汇总")
-        print(f"{'=' * 60}")
-
-        success_count = sum(1 for r in results if r.status == 'success')
-        error_count = sum(1 for r in results if r.status == 'error')
-        failed_count = sum(1 for r in results if r.status == 'failed')
-
-        print(f"总模拟因子数: {len(results)}")
-        print(f"成功: {success_count} 个")
-        print(f"模拟错误: {error_count} 个")
-        print(f"执行异常: {failed_count} 个")
-        print(f"总耗时: {format_time(total_time)}")
-        print(f"{'=' * 60}")
-
-        success_expression_list = []
-
-        for i, result in enumerate(results, 1):
-            status_icon = "✓" if result.status == 'success' else "✗"
-
-            if result.status == 'success':
-                success_expression_list.append(result.expression)
-
-            line_parts = [
-                f"{i}. {status_icon} {result.expression}",
-                f"状态: {result.status}",
-                f"耗时: {result.formatted_time}"
-            ]
-
-            if result.alpha_id != '/':
-                line_parts.append(f"Alpha ID: {result.alpha_id}")
-
-            if result.status != 'success':
-                line_parts.append(f"原因: {result.description}")
-
-            print("\t".join(line_parts))
-
-        save_success_alpha(success_expression_list)

models/entities.py

@@ -0,0 +1,32 @@
+# -*- coding: utf-8 -*-
+"""数据实体模型"""
+
+from dataclasses import dataclass
+from datetime import datetime
+from typing import Optional
+
+
+@dataclass
+class SimulationResult:
+    """模拟结果实体"""
+    expression: str
+    time_consuming: float
+    status: str  # 'ok' or 'err'
+    timestamp: str
+    alpha_id: Optional[str] = None
+    message: Optional[str] = None
+
+
+@dataclass
+class AlphaExpression:
+    """Alpha表达式实体"""
+    expression: str
+    unused: bool = True
+    created_time: Optional[datetime] = None
+
+
+@dataclass
+class TokenInfo:
+    """认证令牌信息"""
+    token: str
+    expiry: int

reference/yearly-stats.json

@@ -1,168 +0,0 @@
-{
-    "schema": {
-        "name": "yearly-stats",
-        "title": "Yearly Stats",
-        "properties": [
-            {
-                "name": "year",
-                "title": "Year",
-                "type": "year"
-            },
-            {
-                "name": "pnl",
-                "title": "PnL",
-                "type": "amount"
-            },
-            {
-                "name": "bookSize",
-                "title": "Book Size",
-                "type": "amount"
-            },
-            {
-                "name": "longCount",
-                "title": "Long Count",
-                "type": "integer"
-            },
-            {
-                "name": "shortCount",
-                "title": "Short Count",
-                "type": "integer"
-            },
-            {
-                "name": "turnover",
-                "title": "Turnover",
-                "type": "percent"
-            },
-            {
-                "name": "sharpe",
-                "title": "Sharpe",
-                "type": "decimal"
-            },
-            {
-                "name": "returns",
-                "title": "Returns",
-                "type": "percent"
-            },
-            {
-                "name": "drawdown",
-                "title": "Drawdown",
-                "type": "percent"
-            },
-            {
-                "name": "margin",
-                "title": "Margin",
-                "type": "permyriad"
-            },
-            {
-                "name": "fitness",
-                "title": "Fitness",
-                "type": "decimal"
-            },
-            {
-                "name": "stage",
-                "title": "Stage",
-                "type": "string"
-            }
-        ]
-    },
-    "records": [
-        [
-            "2018",
-            347052.0,
-            20000000,
-            1081,
-            1083,
-            0.3727,
-            1.54,
-            0.0365,
-            0.0156,
-            0.000196,
-            0.48,
-            "TRAIN"
-        ],
-        [
-            "2019",
-            190205.0,
-            20000000,
-            1364,
-            1359,
-            0.3659,
-            0.83,
-            0.0189,
-            0.0353,
-            0.000103,
-            0.19,
-            "TRAIN"
-        ],
-        [
-            "2020",
-            1554201.0,
-            20000000,
-            1348,
-            1340,
-            0.3639,
-            4.49,
-            0.1682,
-            0.0145,
-            0.000925,
-            3.05,
-            "TRAIN"
-        ],
-        [
-            "2021",
-            584087.0,
-            20000000,
-            1435,
-            1424,
-            0.3652,
-            1.41,
-            0.0579,
-            0.0253,
-            0.000317,
-            0.56,
-            "TRAIN"
-        ],
-        [
-            "2022",
-            31117.0,
-            20000000,
-            1441,
-            1434,
-            0.3446,
-            2.08,
-            0.0648,
-            0.004,
-            0.000376,
-            0.9,
-            "TRAIN"
-        ],
-        [
-            "2022",
-            443804.0,
-            20000000,
-            1415,
-            1417,
-            0.3623,
-            1.19,
-            0.0464,
-            0.0349,
-            0.000256,
-            0.43,
-            "TEST"
-        ],
-        [
-            "2023",
-            68779.0,
-            20000000,
-            1405,
-            1394,
-            0.3554,
-            6.22,
-            0.1323,
-            0.0019,
-            0.000744,
-            3.79,
-            "TEST"
-        ]
-    ]
-}

reference/指标.json

@@ -1,137 +0,0 @@
-{
-    "id": "KP0WWZ6l",
-    "type": "REGULAR",
-    "author": "YC93384",
-    "settings": {
-        "instrumentType": "EQUITY",
-        "region": "USA",
-        "universe": "TOP3000",
-        "delay": 1,
-        "decay": 0,
-        "neutralization": "SUBINDUSTRY",
-        "truncation": 0.08,
-        "pasteurization": "ON",
-        "unitHandling": "VERIFY",
-        "nanHandling": "OFF",
-        "maxTrade": "OFF",
-        "language": "FASTEXPR",
-        "visualization": false,
-        "startDate": "2018-01-20",
-        "endDate": "2023-01-20",
-        "testPeriod": "P1Y"
-    },
-    "regular": {
-        "code": "rank(ts_sum(vec_avg(nws12_afterhsz_sl), 60)) * 0.7 + rank(-ts_delta(close, 2)) * 0.3",
-        "description": null,
-        "operatorCount": 9
-    },
-    "dateCreated": "2025-11-13T09:22:47-05:00",
-    "dateSubmitted": null,
-    "dateModified": "2025-11-13T09:22:47-05:00",
-    "name": null,
-    "favorite": false,
-    "hidden": false,
-    "color": null,
-    "category": null,
-    "tags": [],
-    "classifications": [],
-    "grade": "INFERIOR",
-    "stage": "IS",
-    "status": "UNSUBMITTED",
-    "is": {
-        "pnl": 3219244,
-        "bookSize": 20000000,
-        "longCount": 1332,
-        "shortCount": 1328,
-        "turnover": 0.3657,
-        "returns": 0.0651,
-        "drawdown": 0.0353,
-        "margin": 0.000356,
-        "sharpe": 1.93,
-        "fitness": 0.81,
-        "startDate": "2018-01-20",
-        "checks": [
-            {
-                "name": "LOW_SHARPE",
-                "result": "PASS",
-                "limit": 1.25,
-                "value": 1.93
-            },
-            {
-                "name": "LOW_FITNESS",
-                "result": "FAIL",
-                "limit": 1.0,
-                "value": 0.81
-            },
-            {
-                "name": "LOW_TURNOVER",
-                "result": "PASS",
-                "limit": 0.01,
-                "value": 0.3657
-            },
-            {
-                "name": "HIGH_TURNOVER",
-                "result": "PASS",
-                "limit": 0.7,
-                "value": 0.3657
-            },
-            {
-                "name": "CONCENTRATED_WEIGHT",
-                "result": "PASS"
-            },
-            {
-                "name": "LOW_SUB_UNIVERSE_SHARPE",
-                "result": "PASS",
-                "limit": 0.84,
-                "value": 1.7
-            },
-            {
-                "name": "SELF_CORRELATION",
-                "result": "PENDING"
-            },
-            {
-                "name": "MATCHES_COMPETITION",
-                "result": "PASS",
-                "competitions": [
-                    {
-                        "id": "challenge",
-                        "name": "Challenge"
-                    }
-                ]
-            }
-        ]
-    },
-    "os": null,
-    "train": {
-        "pnl": 2718449,
-        "bookSize": 20000000,
-        "longCount": 1311,
-        "shortCount": 1306,
-        "turnover": 0.3665,
-        "returns": 0.0689,
-        "drawdown": 0.0353,
-        "margin": 0.000376,
-        "fitness": 0.92,
-        "sharpe": 2.13,
-        "startDate": "2018-01-20"
-    },
-    "test": {
-        "pnl": 512583,
-        "bookSize": 20000000,
-        "longCount": 1415,
-        "shortCount": 1416,
-        "turnover": 0.362,
-        "returns": 0.0509,
-        "drawdown": 0.0349,
-        "margin": 0.000281,
-        "fitness": 0.5,
-        "sharpe": 1.33,
-        "startDate": "2022-01-20"
-    },
-    "prod": null,
-    "competitions": null,
-    "themes": null,
-    "pyramids": null,
-    "pyramidThemes": null,
-    "team": null
-}

reference/进度.json

@@ -1,22 +0,0 @@
-{
-    "id": "3q4OCMgw4MFa8k16tdsYLml",
-    "type": "REGULAR",
-    "settings": {
-        "instrumentType": "EQUITY",
-        "region": "USA",
-        "universe": "TOP3000",
-        "delay": 1,
-        "decay": 0,
-        "neutralization": "SUBINDUSTRY",
-        "truncation": 0.08,
-        "pasteurization": "ON",
-        "unitHandling": "VERIFY",
-        "nanHandling": "OFF",
-        "maxTrade": "OFF",
-        "language": "FASTEXPR",
-        "visualization": false
-    },
-    "regular": "rank(ts_sum(vec_avg(nws12_afterhsz_sl), 60)) * 0.7 + rank(-ts_delta(close, 2)) * 0.3",
-    "status": "COMPLETE",
-    "alpha": "KP0WWZ6l"
-}

requirements.txt

@@ -0,0 +1,714 @@
+aiobotocore @ file:///private/var/folders/sy/f16zz6x50xz3113nwtb9bvq00000gp/T/abs_b3e4znaej2/croot/aiobotocore_1680004294920/work
+aiofiles==24.1.0
+aiohappyeyeballs==2.6.1
+aiohttp==3.11.14
+aioitertools @ file:///tmp/build/80754af9/aioitertools_1607109665762/work
+aiosignal @ file:///tmp/build/80754af9/aiosignal_1637843061372/work
+aiosqlite @ file:///private/var/folders/sy/f16zz6x50xz3113nwtb9bvq00000gp/T/abs_13w97vul7u/croot/aiosqlite_1683773912122/work
+alabaster @ file:///home/ktietz/src/ci/alabaster_1611921544520/work
+altgraph==0.17.4
+anaconda-catalogs @ file:///private/var/folders/sy/f16zz6x50xz3113nwtb9bvq00000gp/T/abs_737qok84ed/croot/anaconda-catalogs_1685727302903/work
+anaconda-client==1.11.3
+anaconda-navigator==2.4.2
+anaconda-project @ file:///Users/ec2-user/ci_py311/anaconda-project_1678395481364/work
+annotated-types==0.7.0
+anyio==3.7.1
+appdirs==1.4.4
+applaunchservices @ file:///Users/ec2-user/ci_py311/applaunchservices_1678390181983/work
+appnope @ file:///Users/ec2-user/ci_py311/appnope_1678317440516/work
+appscript @ file:///Users/ec2-user/ci_py311/appscript_1678390203562/work
+argon2-cffi @ file:///opt/conda/conda-bld/argon2-cffi_1645000214183/work
+argon2-cffi-bindings @ file:///Users/ec2-user/ci_py311/argon2-cffi-bindings_1678317076583/work
+arrow @ file:///Users/ec2-user/ci_py311/arrow_1678325845580/work
+art==6.4
+astroid @ file:///Users/ec2-user/ci_py311/astroid_1678323235198/work
+astropy @ file:///Users/ec2-user/ci_py311_2/astropy_1679335070862/work
+asttokens @ file:///opt/conda/conda-bld/asttokens_1646925590279/work
+astunparse==1.6.3
+async-timeout @ file:///Users/ec2-user/ci_py311/async-timeout_1678320112070/work
+atomicwrites==1.4.0
+attrs==25.3.0
+Automat @ file:///tmp/build/80754af9/automat_1600298431173/work
+autopep8 @ file:///opt/conda/conda-bld/autopep8_1650463822033/work
+Babel @ file:///Users/ec2-user/ci_py311/babel_1678318085010/work
+backcall @ file:///home/ktietz/src/ci/backcall_1611930011877/work
+backoff==2.2.1
+backports.functools-lru-cache @ file:///tmp/build/80754af9/backports.functools_lru_cache_1618170165463/work
+backports.tempfile @ file:///home/linux1/recipes/ci/backports.tempfile_1610991236607/work
+backports.weakref==1.0.post1
+base58==2.1.1
+bcrypt @ file:///Users/ec2-user/ci_py311/bcrypt_1678325873219/work
+beautifulsoup4==4.14.0
+better-proxy==1.1.5
+betterproto2==0.5.1
+bidict==0.23.1
+binaryornot @ file:///tmp/build/80754af9/binaryornot_1617751525010/work
+bip39==0.0.2
+bitarray==2.9.2
+black @ file:///private/var/folders/sy/f16zz6x50xz3113nwtb9bvq00000gp/T/abs_1f1pcodmuo/croot/black_1680737253550/work
+bleach @ file:///opt/conda/conda-bld/bleach_1641577558959/work
+blinker==1.7.0
+bokeh @ file:///private/var/folders/sy/f16zz6x50xz3113nwtb9bvq00000gp/T/abs_f0dguf6k4i/croot/bokeh_1684534020835/work
+boltons @ file:///Users/ec2-user/ci_py311/boltons_1678396074811/work
+boto3 @ file:///Users/ec2-user/ci_py311_2/boto3_1679335351182/work
+botocore @ file:///Users/ec2-user/ci_py311/botocore_1678320133200/work
+Bottleneck @ file:///Users/ec2-user/ci_py311/bottleneck_1678322312632/work
+Brotli==1.1.0
+brotlipy==0.7.0
+bs4==0.0.2
+build==1.2.2.post1
+buildozer==1.5.0
+cairocffi==1.6.1
+CairoSVG==2.7.1
+candlelite==1.0.17
+canoser==0.8.2
+captchatools==1.5.0
+certifi==2025.8.3
+cffi @ file:///Users/ec2-user/ci_py311/cffi_1678315312775/work
+chardet @ file:///Users/ec2-user/ci_py311/chardet_1678326102860/work
+charset-normalizer @ file:///tmp/build/80754af9/charset-normalizer_1630003229654/work
+ci-info==0.3.0
+ckzg==1.0.1
+click @ file:///Users/ec2-user/ci_py311/click_1678318124837/work
+cloudpickle @ file:///private/var/folders/sy/f16zz6x50xz3113nwtb9bvq00000gp/T/abs_c57ujq_pgm/croot/cloudpickle_1683040025620/work
+clyent==1.2.2
+colorama @ file:///Users/ec2-user/ci_py311/colorama_1678320227414/work
+colorcet @ file:///Users/ec2-user/ci_py311/colorcet_1678380145131/work
+comm @ file:///Users/ec2-user/ci_py311/comm_1678317779525/work
+conda @ file:///private/var/folders/sy/f16zz6x50xz3113nwtb9bvq00000gp/T/abs_a9qfrev42r/croot/conda_1685025193092/work
+conda-build @ file:///private/var/folders/sy/f16zz6x50xz3113nwtb9bvq00000gp/T/abs_e5ocr04fqn/croot/conda-build_1685026138121/work
+conda-content-trust @ file:///Users/ec2-user/ci_py311/conda-content-trust_1678409283937/work
+conda-libmamba-solver @ file:///private/var/folders/sy/f16zz6x50xz3113nwtb9bvq00000gp/T/abs_b7jucd8kvj/croot/conda-libmamba-solver_1685032330942/work/src
+conda-pack @ file:///tmp/build/80754af9/conda-pack_1611163042455/work
+conda-package-handling @ file:///private/var/folders/sy/f16zz6x50xz3113nwtb9bvq00000gp/T/abs_f61sssj1s3/croot/conda-package-handling_1685024797154/work
+conda-repo-cli==1.0.41
+conda-token @ file:///Users/paulyim/miniconda3/envs/c3i/conda-bld/conda-token_1662660369760/work
+conda-verify==3.4.2
+conda_index @ file:///Users/ec2-user/ci_py311/conda-index_1678409305677/work
+conda_package_streaming @ file:///private/var/folders/sy/f16zz6x50xz3113nwtb9bvq00000gp/T/abs_78ue32m8ay/croot/conda-package-streaming_1685019689310/work
+configobj==5.0.8
+configparser==6.0.0
+constantly==15.1.0
+contourpy @ file:///Users/ec2-user/ci_py311/contourpy_1678322361099/work
+cookiecutter @ file:///opt/conda/conda-bld/cookiecutter_1649151442564/work
+cryptography @ file:///Users/ec2-user/ci_py311_2/cryptography_1679335457662/work
+cssselect==1.1.0
+cssselect2==0.7.0
+cycler @ file:///tmp/build/80754af9/cycler_1637851556182/work
+Cython==3.0.11
+cytoolz @ file:///Users/ec2-user/ci_py311/cytoolz_1678326214370/work
+dask @ file:///private/var/folders/sy/f16zz6x50xz3113nwtb9bvq00000gp/T/abs_ccdxmmxbox/croot/dask-core_1686782920612/work
+dataclasses-json==0.6.7
+DataRecorder==3.6.2
+datashader @ file:///private/var/folders/sy/f16zz6x50xz3113nwtb9bvq00000gp/T/abs_93l60mzvvb/croot/datashader_1685542975569/work
+datashape==0.5.4
+debugpy @ file:///Users/ec2-user/ci_py311/debugpy_1678317801115/work
+decorator @ file:///opt/conda/conda-bld/decorator_1643638310831/work
+defusedxml @ file:///tmp/build/80754af9/defusedxml_1615228127516/work
+Deprecated==1.2.18
+diff-match-patch @ file:///Users/ktietz/demo/mc3/conda-bld/diff-match-patch_1630511840874/work
+dill @ file:///Users/ec2-user/ci_py311/dill_1678323290904/work
+distlib==0.3.9
+distributed @ file:///private/var/folders/sy/f16zz6x50xz3113nwtb9bvq00000gp/T/abs_95i88jlqtp/croot/distributed_1686866052419/work
+distro==1.9.0
+dnspython==2.4.1
+docstring-to-markdown @ file:///Users/ec2-user/ci_py311/docstring-to-markdown_1678326320721/work
+docutils==0.22.1
+docx==0.2.4
+DownloadKit==2.0.7
+DrissionPage==4.1.0.17
+dukpy==0.4.0
+easygui==0.98.3
+email-validator==2.0.0.post2
+entrypoints @ file:///Users/ec2-user/ci_py311/entrypoints_1678316169365/work
+epcpy==0.1.7
+et-xmlfile==1.1.0
+etelemetry==0.3.1
+eth-account==0.11.2
+eth-hash==0.7.0
+eth-keyfile==0.8.1
+eth-keys==0.5.1
+eth-rlp==1.0.1
+eth-typing==4.2.1
+eth-utils==4.1.0
+eth_abi==5.1.0
+executing @ file:///opt/conda/conda-bld/executing_1646925071911/work
+fake-useragent==1.5.1
+fastapi==0.104.1
+fastjsonschema @ file:///Users/ec2-user/ci_py311_2/python-fastjsonschema_1679338737111/work
+filelock==3.16.1
+filetype==1.2.0
+fitz==0.0.1.dev2
+flake8 @ file:///Users/ec2-user/ci_py311/flake8_1678326404511/work
+Flask @ file:///Users/ec2-user/ci_py311/flask_1678380788105/work
+fonttools==4.25.0
+fqdn==1.5.1
+frozenlist @ file:///Users/ec2-user/ci_py311/frozenlist_1678318685088/work
+fsspec @ file:///private/var/folders/sy/f16zz6x50xz3113nwtb9bvq00000gp/T/abs_d9zxascxg8/croot/fsspec_1679418997424/work
+future @ file:///Users/ec2-user/ci_py311_2/future_1679335881731/work
+genshinhelper==2.1.3
+gensim @ file:///Users/ec2-user/ci_py311/gensim_1678412014794/work
+glob2 @ file:///home/linux1/recipes/ci/glob2_1610991677669/work
+gmpy2 @ file:///Users/ec2-user/ci_py311/gmpy2_1678380831980/work
+gql==3.5.3
+graphql-core==3.2.6
+greenlet==3.1.1
+grpclib==0.4.8
+h11==0.16.0
+h2==4.1.0
+h5py @ file:///Users/ec2-user/ci_py311/h5py_1678381005308/work
+HeapDict @ file:///Users/ktietz/demo/mc3/conda-bld/heapdict_1630598515714/work
+hexbytes==0.3.1
+holoviews @ file:///private/var/folders/sy/f16zz6x50xz3113nwtb9bvq00000gp/T/abs_7a7dicrx1g/croot/holoviews_1686339350598/work
+hpack==4.0.0
+httpcore==1.0.9
+httplib2==0.22.0
+httptools==0.6.0
+httpx==0.25.2
+httpx-sse==0.4.0
+hvplot @ file:///private/var/folders/sy/f16zz6x50xz3113nwtb9bvq00000gp/T/abs_4dben4g_th/croot/hvplot_1685998195310/work
+hyperframe==6.0.1
+hyperlink @ file:///tmp/build/80754af9/hyperlink_1610130746837/work
+idna @ file:///Users/ec2-user/ci_py311/idna_1678315819133/work
+ifaddr==0.2.0
+imagecodecs @ file:///Users/ec2-user/ci_py311_2/imagecodecs_1679336141260/work
+imageio @ file:///private/var/folders/sy/f16zz6x50xz3113nwtb9bvq00000gp/T/abs_47v6nbs3l9/croot/imageio_1687264946242/work
+imagesize @ file:///Users/ec2-user/ci_py311/imagesize_1678377399148/work
+imap-tools==1.10.0
+imbalanced-learn @ file:///private/var/folders/sy/f16zz6x50xz3113nwtb9bvq00000gp/T/abs_a1ju_tsc7c/croot/imbalanced-learn_1685020900729/work
+importlib-metadata @ file:///private/var/folders/sy/f16zz6x50xz3113nwtb9bvq00000gp/T/abs_81_20mq0d8/croot/importlib-metadata_1678997090664/work
+incremental @ file:///tmp/build/80754af9/incremental_1636629750599/work
+inflection==0.5.1
+iniconfig @ file:///home/linux1/recipes/ci/iniconfig_1610983019677/work
+intake @ file:///Users/ec2-user/ci_py311_2/intake_1679336302724/work
+intervaltree @ file:///Users/ktietz/demo/mc3/conda-bld/intervaltree_1630511889664/work
+ipykernel @ file:///Users/ec2-user/ci_py311/ipykernel_1678318220696/work
+ipython @ file:///private/var/folders/sy/f16zz6x50xz3113nwtb9bvq00000gp/T/abs_cd4ia5pr17/croot/ipython_1680701875298/work
+ipython-genutils @ file:///tmp/build/80754af9/ipython_genutils_1606773439826/work
+ipywidgets @ file:///private/var/folders/sy/f16zz6x50xz3113nwtb9bvq00000gp/T/abs_f5atknkudc/croot/ipywidgets_1679394812720/work
+isodate==0.6.1
+isoduration==20.11.0
+isort @ file:///tmp/build/80754af9/isort_1628603791788/work
+itemadapter @ file:///tmp/build/80754af9/itemadapter_1626442940632/work
+itemloaders @ file:///opt/conda/conda-bld/itemloaders_1646805235997/work
+itsdangerous==2.2.0
+jaraco.classes @ file:///tmp/build/80754af9/jaraco.classes_1620983179379/work
+jedi @ file:///Users/ec2-user/ci_py311_2/jedi_1679336327335/work
+jellyfish @ file:///Users/ec2-user/ci_py311/jellyfish_1678392216202/work
+Jinja2==3.1.6
+jinja2-time @ file:///opt/conda/conda-bld/jinja2-time_1649251842261/work
+jiter==0.8.2
+jittor==1.3.8.5
+jmespath @ file:///Users/ktietz/demo/mc3/conda-bld/jmespath_1630583964805/work
+joblib @ file:///private/var/folders/sy/f16zz6x50xz3113nwtb9bvq00000gp/T/abs_dfriz0qjwt/croot/joblib_1685113297703/work
+Js2Py_3.13==0.74.1
+json5 @ file:///tmp/build/80754af9/json5_1624432770122/work
+jsonalias==0.1.1
+jsonpatch==1.33
+jsonpointer==2.1
+jsonschema==4.23.0
+jsonschema-specifications==2025.4.1
+jtorch==0.1.7
+jupyter @ file:///Users/ec2-user/ci_py311/jupyter_1678377791770/work
+jupyter-console @ file:///private/var/folders/sy/f16zz6x50xz3113nwtb9bvq00000gp/T/abs_e8qcp1kdie/croot/jupyter_console_1679999714867/work
+jupyter-events @ file:///private/var/folders/sy/f16zz6x50xz3113nwtb9bvq00000gp/T/abs_f0yqwpn5u1/croot/jupyter_events_1684268046871/work
+jupyter-ydoc @ file:///private/var/folders/sy/f16zz6x50xz3113nwtb9bvq00000gp/T/abs_79b9hk1z3q/croot/jupyter_ydoc_1683747244664/work
+jupyter_client @ file:///private/var/folders/sy/f16zz6x50xz3113nwtb9bvq00000gp/T/abs_5e4bbpqn9e/croot/jupyter_client_1680171866753/work
+jupyter_core @ file:///private/var/folders/sy/f16zz6x50xz3113nwtb9bvq00000gp/T/abs_b82fz_h369/croot/jupyter_core_1679906581737/work
+jupyter_server @ file:///private/var/folders/sy/f16zz6x50xz3113nwtb9bvq00000gp/T/abs_b7pddqvxoj/croot/jupyter_server_1686059483368/work
+jupyter_server_fileid @ file:///private/var/folders/sy/f16zz6x50xz3113nwtb9bvq00000gp/T/abs_b0lffopjbp/croot/jupyter_server_fileid_1684273621123/work
+jupyter_server_terminals @ file:///private/var/folders/sy/f16zz6x50xz3113nwtb9bvq00000gp/T/abs_257krljdmq/croot/jupyter_server_terminals_1686870730796/work
+jupyter_server_ydoc @ file:///private/var/folders/sy/f16zz6x50xz3113nwtb9bvq00000gp/T/abs_6848h2a_93/croot/jupyter_server_ydoc_1686768718335/work
+jupyterlab @ file:///private/var/folders/sy/f16zz6x50xz3113nwtb9bvq00000gp/T/abs_502x016ek3/croot/jupyterlab_1686179671461/work
+jupyterlab-pygments @ file:///tmp/build/80754af9/jupyterlab_pygments_1601490720602/work
+jupyterlab-widgets @ file:///private/var/folders/sy/f16zz6x50xz3113nwtb9bvq00000gp/T/abs_9btffb27id/croot/jupyterlab_widgets_1679055288818/work
+jupyterlab_server @ file:///private/var/folders/sy/f16zz6x50xz3113nwtb9bvq00000gp/T/abs_9039tf6tpv/croot/jupyterlab_server_1680792539169/work
+kaitaistruct==0.10
+keyring @ file:///private/var/folders/sy/f16zz6x50xz3113nwtb9bvq00000gp/T/abs_2ds0bchnl2/croot/keyring_1678999223818/work
+Kivy==2.3.0
+Kivy-Garden==0.1.5
+kiwisolver @ file:///Users/ec2-user/ci_py311/kiwisolver_1678322457192/work
+langchain==0.3.14
+langchain-community==0.3.14
+langchain-core==0.3.29
+langchain-text-splitters==0.3.4
+langsmith==0.2.10
+lazy-object-proxy @ file:///Users/ec2-user/ci_py311/lazy-object-proxy_1678322504286/work
+lazy_loader @ file:///private/var/folders/sy/f16zz6x50xz3113nwtb9bvq00000gp/T/abs_02apt1h75k/croot/lazy_loader_1687264081288/work
+libarchive-c @ file:///tmp/build/80754af9/python-libarchive-c_1617780486945/work
+libmambapy @ file:///private/var/folders/sy/f16zz6x50xz3113nwtb9bvq00000gp/T/abs_65seb320zf/croot/mamba-split_1680093070986/work/libmambapy
+linkify-it-py @ file:///Users/ec2-user/ci_py311/linkify-it-py_1678413480728/work
+llvmlite @ file:///private/var/folders/sy/f16zz6x50xz3113nwtb9bvq00000gp/T/abs_39tj5og13d/croot/llvmlite_1683555130919/work
+lmdb @ file:///private/var/folders/sy/f16zz6x50xz3113nwtb9bvq00000gp/T/abs_88zbo0vn66/croot/python-lmdb_1682522360781/work
+locket @ file:///Users/ec2-user/ci_py311/locket_1678322541585/work
+loguru==0.7.2
+looseversion==1.3.0
+lru-dict==1.2.0
+lxml==6.0.2
+lz4 @ file:///private/var/folders/sy/f16zz6x50xz3113nwtb9bvq00000gp/T/abs_7fl2lzb5wh/croot/lz4_1686057901919/work
+m3u8==6.0.0
+macholib==1.16.3
+Markdown @ file:///Users/ec2-user/ci_py311/markdown_1678377870854/work
+markdown-it-py @ file:///private/var/folders/sy/f16zz6x50xz3113nwtb9bvq00000gp/T/abs_43xjt6hz0x/croot/markdown-it-py_1684279911135/work
+markdown2==2.5.4
+MarkupSafe==3.0.3
+marshmallow==3.24.1
+matplotlib @ file:///private/var/folders/sy/f16zz6x50xz3113nwtb9bvq00000gp/T/abs_41fhwn4tj9/croot/matplotlib-suite_1679593479845/work
+matplotlib-inline @ file:///Users/ec2-user/ci_py311/matplotlib-inline_1678317544666/work
+mccabe @ file:///opt/conda/conda-bld/mccabe_1644221741721/work
+mdit-py-plugins @ file:///Users/ec2-user/ci_py311/mdit-py-plugins_1678417716573/work
+mdurl @ file:///Users/ec2-user/ci_py311/mdurl_1678381820326/work
+mistune @ file:///Users/ec2-user/ci_py311/mistune_1678317272228/work
+mmh3==4.1.0
+mnemonic==0.21
+modulegraph==0.19.6
+more-itertools @ file:///tmp/build/80754af9/more-itertools_1637733554872/work
+mpmath==1.2.1
+msgpack @ file:///Users/ec2-user/ci_py311/msgpack-python_1678318264150/work
+multidict @ file:///Users/ec2-user/ci_py311/multidict_1678318765630/work
+multipledispatch @ file:///Users/ec2-user/ci_py311/multipledispatch_1678392901644/work
+munkres==1.1.4
+mutf8==1.0.6
+mypy==1.18.2
+mypy_extensions==1.1.0
+names==0.3.0
+navigator-updater==0.4.0
+nbclassic @ file:///private/var/folders/sy/f16zz6x50xz3113nwtb9bvq00000gp/T/abs_e9be4uk5qu/croot/nbclassic_1681756175065/work
+nbclient @ file:///Users/ec2-user/ci_py311/nbclient_1678317300721/work
+nbconvert @ file:///Users/ec2-user/ci_py311/nbconvert_1678317567483/work
+nbformat @ file:///Users/ec2-user/ci_py311/nbformat_1678317010390/work
+nest-asyncio @ file:///Users/ec2-user/ci_py311/nest-asyncio_1678316288195/work
+networkx @ file:///private/var/folders/sy/f16zz6x50xz3113nwtb9bvq00000gp/T/abs_1a72gktq2s/croot/networkx_1678964337061/work
+nibabel==5.1.0
+nicegui==2.24.1
+nipype==1.8.6
+nltk @ file:///opt/conda/conda-bld/nltk_1645628263994/work
+nodeenv==1.9.1
+notebook @ file:///private/var/folders/sy/f16zz6x50xz3113nwtb9bvq00000gp/T/abs_be_2kh1kd4/croot/notebook_1681756176866/work
+notebook_shim @ file:///Users/ec2-user/ci_py311/notebook-shim_1678318293647/work
+numba @ file:///private/var/folders/sy/f16zz6x50xz3113nwtb9bvq00000gp/T/abs_93pzbiav_e/croot/numba_1684245526578/work
+numexpr @ file:///private/var/folders/sy/f16zz6x50xz3113nwtb9bvq00000gp/T/abs_1b50c1js9s/croot/numexpr_1683227065029/work
+numpy==1.26.3
+numpydoc @ file:///Users/ec2-user/ci_py311/numpydoc_1678393034712/work
+OdooRPC==0.10.1
+okx==2.1.1
+okx-api==1.0.5
+ollama==0.4.5
+openai==1.59.6
+opencv-python==4.8.1.78
+openpyxl==3.0.10
+orjson==3.10.13
+outcome==1.3.0.post0
+packaging==24.2
+pandas==1.5.3
+pandocfilters @ file:///opt/conda/conda-bld/pandocfilters_1643405455980/work
+panel @ file:///private/var/folders/sy/f16zz6x50xz3113nwtb9bvq00000gp/T/abs_dfq8ysliwf/croot/panel_1686058338704/work
+param @ file:///private/var/folders/sy/f16zz6x50xz3113nwtb9bvq00000gp/T/abs_eb_xu6rgzh/croot/param_1684915322419/work
+parsel @ file:///Users/ec2-user/ci_py311/parsel_1678382184303/work
+parsimonious==0.10.0
+parso @ file:///opt/conda/conda-bld/parso_1641458642106/work
+partd @ file:///opt/conda/conda-bld/partd_1647245470509/work
+pathlib @ file:///Users/ktietz/demo/mc3/conda-bld/pathlib_1629713961906/work
+pathspec @ file:///Users/ec2-user/ci_py311_2/pathspec_1679337122817/work
+patsy==0.5.3
+paux==1.0.14
+pdfminer==20191125
+pdfminer3k==1.3.4
+pdfparanoia==0.0.17
+pendulum==3.0.0
+pep8==1.7.1
+pexpect @ file:///tmp/build/80754af9/pexpect_1605563209008/work
+pickleshare @ file:///tmp/build/80754af9/pickleshare_1606932040724/work
+pika==1.3.2
+Pillow==9.4.0
+pkginfo @ file:///private/var/folders/sy/f16zz6x50xz3113nwtb9bvq00000gp/T/abs_d976p03z5u/croot/pkginfo_1679431175529/work
+platformdirs==4.3.6
+playwright==1.50.0
+plotly @ file:///Users/ec2-user/ci_py311/plotly_1678382250051/work
+pluggy @ file:///Users/ec2-user/ci_py311/pluggy_1678315400971/work
+ply==3.11
+pooch @ file:///tmp/build/80754af9/pooch_1623324770023/work
+potracer==0.0.4
+poyo @ file:///tmp/build/80754af9/poyo_1617751526755/work
+prometheus-client @ file:///Users/ec2-user/ci_py311_2/prometheus_client_1679340232148/work
+prompt-toolkit @ file:///Users/ec2-user/ci_py311/prompt-toolkit_1678317707969/work
+propcache==0.3.0
+Protego @ file:///tmp/build/80754af9/protego_1598657180827/work
+protobuf==5.26.1
+prov==2.0.0
+pscript==0.7.7
+psutil @ file:///Users/ec2-user/ci_py311_2/psutil_1679337242143/work
+psycopg2==2.9.9
+ptyprocess @ file:///tmp/build/80754af9/ptyprocess_1609355006118/work/dist/ptyprocess-0.7.0-py2.py3-none-any.whl
+pure-eval @ file:///opt/conda/conda-bld/pure_eval_1646925070566/work
+py-cpuinfo @ file:///Users/ktietz/demo/mc3/conda-bld/py-cpuinfo_1629480366017/work
+py2app==0.28.6
+pyarrow==11.0.0
+pyasn1 @ file:///Users/ktietz/demo/mc3/conda-bld/pyasn1_1629708007385/work
+pyasn1-modules==0.2.8
+pycodestyle @ file:///Users/ec2-user/ci_py311/pycodestyle_1678324331308/work
+pycosat @ file:///Users/ec2-user/ci_py311/pycosat_1678378899646/work
+pycparser @ file:///tmp/build/80754af9/pycparser_1636541352034/work
+pycryptodome==3.19.0
+pyct @ file:///Users/ec2-user/ci_py311/pyct_1678378955854/work
+pycurl==7.45.2
+pydantic==2.11.9
+pydantic-extra-types==2.0.0
+pydantic-settings==2.7.1
+pydantic_core==2.33.2
+PyDispatcher==2.0.5
+pydocstyle @ file:///Users/ec2-user/ci_py311/pydocstyle_1678378981125/work
+pydoll-python==1.3.3
+pydot==1.4.2
+pyee==12.0.0
+pyerfa @ file:///Users/ec2-user/ci_py311/pyerfa_1678379006730/work
+pyflakes @ file:///Users/ec2-user/ci_py311/pyflakes_1678324357242/work
+Pygments @ file:///private/var/folders/sy/f16zz6x50xz3113nwtb9bvq00000gp/T/abs_cflayrfqsi/croot/pygments_1684279981084/work
+PyICU==2.12
+pyinstaller==6.2.0
+pyinstaller-hooks-contrib==2023.10
+pyjsparser==2.7.1
+PyJWT @ file:///Users/ec2-user/ci_py311/pyjwt_1678379090382/work
+pylint @ file:///Users/ec2-user/ci_py311/pylint_1678379112162/work
+pylint-venv @ file:///Users/ec2-user/ci_py311/pylint-venv_1678393629931/work
+pyls-spyder==0.4.0
+PyMuPDF==1.23.6
+PyMuPDFb==1.23.6
+pynanosvg==0.3.1
+pyobjc==10.3.1
+pyobjc-core==10.3.1
+pyobjc-framework-Accessibility==10.3.1
+pyobjc-framework-Accounts==10.3.1
+pyobjc-framework-AddressBook==10.3.1
+pyobjc-framework-AdServices==10.3.1
+pyobjc-framework-AdSupport==10.3.1
+pyobjc-framework-AppleScriptKit==10.3.1
+pyobjc-framework-AppleScriptObjC==10.3.1
+pyobjc-framework-ApplicationServices==10.3.1
+pyobjc-framework-AppTrackingTransparency==10.3.1
+pyobjc-framework-AudioVideoBridging==10.3.1
+pyobjc-framework-AuthenticationServices==10.3.1
+pyobjc-framework-AutomaticAssessmentConfiguration==10.3.1
+pyobjc-framework-Automator==10.3.1
+pyobjc-framework-AVFoundation==10.3.1
+pyobjc-framework-AVKit==10.3.1
+pyobjc-framework-AVRouting==10.3.1
+pyobjc-framework-BackgroundAssets==10.3.1
+pyobjc-framework-BusinessChat==10.3.1
+pyobjc-framework-CalendarStore==10.3.1
+pyobjc-framework-CallKit==10.3.1
+pyobjc-framework-CFNetwork==10.3.1
+pyobjc-framework-ClassKit==10.3.1
+pyobjc-framework-CloudKit==10.3.1
+pyobjc-framework-Cocoa==10.3.1
+pyobjc-framework-Collaboration==10.3.1
+pyobjc-framework-ColorSync==10.3.1
+pyobjc-framework-Contacts==10.3.1
+pyobjc-framework-ContactsUI==10.3.1
+pyobjc-framework-CoreAudio==10.3.1
+pyobjc-framework-CoreAudioKit==10.3.1
+pyobjc-framework-CoreBluetooth==10.3.1
+pyobjc-framework-CoreData==10.3.1
+pyobjc-framework-CoreHaptics==10.3.1
+pyobjc-framework-CoreLocation==10.3.1
+pyobjc-framework-CoreMedia==10.3.1
+pyobjc-framework-CoreMediaIO==10.3.1
+pyobjc-framework-CoreMIDI==10.3.1
+pyobjc-framework-CoreML==10.3.1
+pyobjc-framework-CoreMotion==10.3.1
+pyobjc-framework-CoreServices==10.3.1
+pyobjc-framework-CoreSpotlight==10.3.1
+pyobjc-framework-CoreText==10.3.1
+pyobjc-framework-CoreWLAN==10.3.1
+pyobjc-framework-CryptoTokenKit==10.3.1
+pyobjc-framework-DataDetection==10.3.1
+pyobjc-framework-DeviceCheck==10.3.1
+pyobjc-framework-DictionaryServices==10.3.1
+pyobjc-framework-DiscRecording==10.3.1
+pyobjc-framework-DiscRecordingUI==10.3.1
+pyobjc-framework-DiskArbitration==10.3.1
+pyobjc-framework-DVDPlayback==10.3.1
+pyobjc-framework-EventKit==10.3.1
+pyobjc-framework-ExceptionHandling==10.3.1
+pyobjc-framework-ExecutionPolicy==10.3.1
+pyobjc-framework-ExtensionKit==10.3.1
+pyobjc-framework-ExternalAccessory==10.3.1
+pyobjc-framework-FileProvider==10.3.1
+pyobjc-framework-FileProviderUI==10.3.1
+pyobjc-framework-FinderSync==10.3.1
+pyobjc-framework-FSEvents==10.3.1
+pyobjc-framework-GameCenter==10.3.1
+pyobjc-framework-GameController==10.3.1
+pyobjc-framework-GameKit==10.3.1
+pyobjc-framework-GameplayKit==10.3.1
+pyobjc-framework-HealthKit==10.3.1
+pyobjc-framework-ImageCaptureCore==10.3.1
+pyobjc-framework-InputMethodKit==10.3.1
+pyobjc-framework-InstallerPlugins==10.3.1
+pyobjc-framework-InstantMessage==10.3.1
+pyobjc-framework-Intents==10.3.1
+pyobjc-framework-IntentsUI==10.3.1
+pyobjc-framework-IOBluetooth==10.3.1
+pyobjc-framework-IOBluetoothUI==10.3.1
+pyobjc-framework-IOSurface==10.3.1
+pyobjc-framework-iTunesLibrary==10.3.1
+pyobjc-framework-KernelManagement==10.3.1
+pyobjc-framework-LatentSemanticMapping==10.3.1
+pyobjc-framework-LaunchServices==10.3.1
+pyobjc-framework-libdispatch==10.3.1
+pyobjc-framework-libxpc==10.3.1
+pyobjc-framework-LinkPresentation==10.3.1
+pyobjc-framework-LocalAuthentication==10.3.1
+pyobjc-framework-LocalAuthenticationEmbeddedUI==10.3.1
+pyobjc-framework-MailKit==10.3.1
+pyobjc-framework-MapKit==10.3.1
+pyobjc-framework-MediaAccessibility==10.3.1
+pyobjc-framework-MediaLibrary==10.3.1
+pyobjc-framework-MediaPlayer==10.3.1
+pyobjc-framework-MediaToolbox==10.3.1
+pyobjc-framework-Metal==10.3.1
+pyobjc-framework-MetalFX==10.3.1
+pyobjc-framework-MetalKit==10.3.1
+pyobjc-framework-MetalPerformanceShaders==10.3.1
+pyobjc-framework-MetalPerformanceShadersGraph==10.3.1
+pyobjc-framework-MetricKit==10.3.1
+pyobjc-framework-MLCompute==10.3.1
+pyobjc-framework-ModelIO==10.3.1
+pyobjc-framework-MultipeerConnectivity==10.3.1
+pyobjc-framework-NaturalLanguage==10.3.1
+pyobjc-framework-NetFS==10.3.1
+pyobjc-framework-Network==10.3.1
+pyobjc-framework-NetworkExtension==10.3.1
+pyobjc-framework-NotificationCenter==10.3.1
+pyobjc-framework-OpenDirectory==10.3.1
+pyobjc-framework-OSAKit==10.3.1
+pyobjc-framework-OSLog==10.3.1
+pyobjc-framework-PassKit==10.3.1
+pyobjc-framework-PencilKit==10.3.1
+pyobjc-framework-PHASE==10.3.1
+pyobjc-framework-Photos==10.3.1
+pyobjc-framework-PhotosUI==10.3.1
+pyobjc-framework-PreferencePanes==10.3.1
+pyobjc-framework-PushKit==10.3.1
+pyobjc-framework-Quartz==10.3.1
+pyobjc-framework-QuickLookThumbnailing==10.3.1
+pyobjc-framework-ReplayKit==10.3.1
+pyobjc-framework-SafariServices==10.3.1
+pyobjc-framework-SafetyKit==10.3.1
+pyobjc-framework-SceneKit==10.3.1
+pyobjc-framework-ScreenCaptureKit==10.3.1
+pyobjc-framework-ScreenSaver==10.3.1
+pyobjc-framework-ScreenTime==10.3.1
+pyobjc-framework-ScriptingBridge==10.3.1
+pyobjc-framework-SearchKit==10.3.1
+pyobjc-framework-Security==10.3.1
+pyobjc-framework-SecurityFoundation==10.3.1
+pyobjc-framework-SecurityInterface==10.3.1
+pyobjc-framework-ServiceManagement==10.3.1
+pyobjc-framework-SharedWithYou==10.3.1
+pyobjc-framework-SharedWithYouCore==10.3.1
+pyobjc-framework-ShazamKit==10.3.1
+pyobjc-framework-Social==10.3.1
+pyobjc-framework-SoundAnalysis==10.3.1
+pyobjc-framework-Speech==10.3.1
+pyobjc-framework-SpriteKit==10.3.1
+pyobjc-framework-StoreKit==10.3.1
+pyobjc-framework-SyncServices==10.3.1
+pyobjc-framework-SystemConfiguration==10.3.1
+pyobjc-framework-SystemExtensions==10.3.1
+pyobjc-framework-ThreadNetwork==10.3.1
+pyobjc-framework-UniformTypeIdentifiers==10.3.1
+pyobjc-framework-UserNotifications==10.3.1
+pyobjc-framework-UserNotificationsUI==10.3.1
+pyobjc-framework-VideoSubscriberAccount==10.3.1
+pyobjc-framework-VideoToolbox==10.3.1
+pyobjc-framework-Virtualization==10.3.1
+pyobjc-framework-Vision==10.3.1
+pyobjc-framework-WebKit==10.3.1
+pyodbc @ file:///Users/ec2-user/ci_py311/pyodbc_1678420730897/work
+pyOpenSSL @ file:///private/var/folders/sy/f16zz6x50xz3113nwtb9bvq00000gp/T/abs_19gfn1ib_u/croot/pyopenssl_1678965300171/work
+pyotp==2.9.0
+pyparsing @ file:///Users/ec2-user/ci_py311/pyparsing_1678322828710/work
+PyPDF2==1.26.0
+PyPDF4==1.27.0
+pyproject_hooks==1.2.0
+PyQt5-sip==12.11.0
+PyQt6==6.4.2
+pyqt6-plugins==6.4.2.2.3
+PyQt6-Qt6==6.4.3
+PyQt6-sip==13.6.0
+pyqt6-tools==6.4.2.3.3
+PyQt6-WebEngine==6.6.0
+PyQt6-WebEngine-Qt6==6.6.0
+pyright==1.1.405
+pyrsistent @ file:///Users/ec2-user/ci_py311/pyrsistent_1678316053523/work
+PySocks @ file:///Users/ec2-user/ci_py311/pysocks_1678315868424/work
+pysui==0.85.0
+pysui-fastcrypto==0.7.0
+pytest @ file:///private/var/folders/sy/f16zz6x50xz3113nwtb9bvq00000gp/T/abs_bcnsxh_kaf/croot/pytest_1684171610545/work
+python-barcode==0.15.1
+python-dateutil @ file:///tmp/build/80754af9/python-dateutil_1626374649649/work
+python-dotenv==1.0.0
+python-engineio==4.12.2
+python-json-logger @ file:///private/var/folders/sy/f16zz6x50xz3113nwtb9bvq00000gp/T/abs_49p5x2bjzn/croot/python-json-logger_1683823814668/work
+python-lsp-black @ file:///Users/ec2-user/ci_py311/python-lsp-black_1678393907972/work
+python-lsp-jsonrpc==1.0.0
+python-lsp-server @ file:///private/var/folders/sy/f16zz6x50xz3113nwtb9bvq00000gp/T/abs_1fkjjx0yhx/croot/python-lsp-server_1681930400163/work
+python-multipart==0.0.6
+python-slugify @ file:///tmp/build/80754af9/python-slugify_1620405669636/work
+python-snappy @ file:///Users/ec2-user/ci_py311/python-snappy_1678388765172/work
+python-socketio==5.13.0
+python-socks==2.7.1
+pytoolconfig @ file:///Users/ec2-user/ci_py311/pytoolconfig_1678324412360/work
+pytz @ file:///Users/ec2-user/ci_py311/pytz_1678318034461/work
+pyunormalize==15.1.0
+pyviz-comms @ file:///private/var/folders/sy/f16zz6x50xz3113nwtb9bvq00000gp/T/abs_13yvjs0iia/croot/pyviz_comms_1685030724461/work
+PyWavelets @ file:///Users/ec2-user/ci_py311/pywavelets_1678379192795/work
+pyxnat==1.6
+PyYAML==6.0.2
+pyzmq @ file:///private/var/folders/sy/f16zz6x50xz3113nwtb9bvq00000gp/T/abs_e6wiufh44w/croot/pyzmq_1686601381524/work
+QDarkStyle @ file:///tmp/build/80754af9/qdarkstyle_1617386714626/work
+qstylizer @ file:///Users/ec2-user/ci_py311/qstylizer_1678393978214/work/dist/qstylizer-0.2.2-py2.py3-none-any.whl
+qt6-applications==6.4.3.2.3
+qt6-tools==6.4.3.1.3
+QtAwesome @ file:///Users/ec2-user/ci_py311/qtawesome_1678393953815/work
+qtconsole @ file:///private/var/folders/sy/f16zz6x50xz3113nwtb9bvq00000gp/T/abs_dexq2hi2gu/croot/qtconsole_1681394223590/work
+QtPy @ file:///Users/ec2-user/ci_py311/qtpy_1678322936834/work
+queuelib==1.5.0
+RandomWords==0.4.0
+rdflib==7.0.0
+redis==5.2.0
+referencing==0.36.2
+regex @ file:///Users/ec2-user/ci_py311/regex_1678394018661/work
+reportlab==4.0.6
+requests==2.32.3
+requests-file @ file:///Users/ktietz/demo/mc3/conda-bld/requests-file_1629455781986/work
+requests-toolbelt==1.0.0
+rfc3339-validator @ file:///private/var/folders/sy/f16zz6x50xz3113nwtb9bvq00000gp/T/abs_07a1ken4gz/croot/rfc3339-validator_1683077050666/work
+rfc3986-validator @ file:///private/var/folders/sy/f16zz6x50xz3113nwtb9bvq00000gp/T/abs_6dzvsqx89i/croot/rfc3986-validator_1683059150431/work
+rich==13.5.2
+rlp==4.0.1
+rope @ file:///Users/ec2-user/ci_py311/rope_1678379265159/work
+rpds-py==0.25.1
+rstream==0.30.0
+Rtree @ file:///Users/ec2-user/ci_py311/rtree_1678394103092/work
+ruamel-yaml-conda @ file:///Users/ec2-user/ci_py311/ruamel_yaml_1678394125333/work
+ruamel.yaml @ file:///Users/ec2-user/ci_py311/ruamel.yaml_1678379291841/work
+rumps==0.4.0
+s3fs @ file:///private/var/folders/sy/f16zz6x50xz3113nwtb9bvq00000gp/T/abs_3dy0qlp99f/croot/s3fs_1680018510125/work
+s3transfer @ file:///Users/ec2-user/ci_py311/s3transfer_1678324574832/work
+sacremoses @ file:///tmp/build/80754af9/sacremoses_1633107328213/work
+scapy==2.5.0
+scikit-image @ file:///private/var/folders/sy/f16zz6x50xz3113nwtb9bvq00000gp/T/abs_3fh5dyitqb/croot/scikit-image_1682530834592/work
+scikit-learn @ file:///private/var/folders/sy/f16zz6x50xz3113nwtb9bvq00000gp/T/abs_506rr4lm7n/croot/scikit-learn_1684954727383/work
+scipy==1.10.1
+Scrapy @ file:///Users/ec2-user/ci_py311/scrapy_1678422467931/work
+seaborn @ file:///Users/ec2-user/ci_py311/seaborn_1678394152964/work
+selenium==4.18.1
+selenium-wire==5.1.0
+Send2Trash @ file:///tmp/build/80754af9/send2trash_1632406701022/work
+service-identity @ file:///Users/ktietz/demo/mc3/conda-bld/service_identity_1629460757137/work
+sh==1.14.3
+simple-websocket==1.1.0
+simplejson==3.19.2
+sip @ file:///Users/ec2-user/ci_py311/sip_1678318421743/work
+six @ file:///tmp/build/80754af9/six_1644875935023/work
+smart-open @ file:///Users/ec2-user/ci_py311/smart_open_1678389689993/work
+sniffio==1.3.0
+snowballstemmer @ file:///tmp/build/80754af9/snowballstemmer_1637937080595/work
+socksio==1.0.0
+solders==0.25.0
+sortedcontainers @ file:///tmp/build/80754af9/sortedcontainers_1623949099177/work
+soupsieve==2.8
+Sphinx @ file:///Users/ec2-user/ci_py311/sphinx_1678389735529/work
+sphinxcontrib-applehelp @ file:///home/ktietz/src/ci/sphinxcontrib-applehelp_1611920841464/work
+sphinxcontrib-devhelp @ file:///home/ktietz/src/ci/sphinxcontrib-devhelp_1611920923094/work
+sphinxcontrib-htmlhelp @ file:///tmp/build/80754af9/sphinxcontrib-htmlhelp_1623945626792/work
+sphinxcontrib-jsmath @ file:///home/ktietz/src/ci/sphinxcontrib-jsmath_1611920942228/work
+sphinxcontrib-qthelp @ file:///home/ktietz/src/ci/sphinxcontrib-qthelp_1611921055322/work
+sphinxcontrib-serializinghtml @ file:///tmp/build/80754af9/sphinxcontrib-serializinghtml_1624451540180/work
+spyder @ file:///private/var/folders/sy/f16zz6x50xz3113nwtb9bvq00000gp/T/abs_b93e0at0ak/croot/spyder_1681934083239/work
+spyder-kernels @ file:///private/var/folders/sy/f16zz6x50xz3113nwtb9bvq00000gp/T/abs_30ws3nleek/croot/spyder-kernels_1681307303955/work
+SQLAlchemy @ file:///Users/ec2-user/ci_py311/sqlalchemy_1678379321154/work
+stack-data @ file:///opt/conda/conda-bld/stack_data_1646927590127/work
+starlette==0.27.0
+statsmodels @ file:///Users/ec2-user/ci_py311/statsmodels_1678394299954/work
+supervisor==4.2.5
+svgwrite==1.4.3
+sympy @ file:///Users/ec2-user/ci_py311_2/sympy_1679338337660/work
+tables @ file:///private/var/folders/sy/f16zz6x50xz3113nwtb9bvq00000gp/T/abs_ccbzs9wm7e/croot/pytables_1685123223946/work
+tabulate @ file:///Users/ec2-user/ci_py311/tabulate_1678423547338/work
+TBB==0.2
+tblib @ file:///Users/ktietz/demo/mc3/conda-bld/tblib_1629402031467/work
+tenacity==8.2.3
+termcolor==2.5.0
+terminado @ file:///Users/ec2-user/ci_py311/terminado_1678317735543/work
+text-unidecode @ file:///Users/ktietz/demo/mc3/conda-bld/text-unidecode_1629401354553/work
+textdistance @ file:///tmp/build/80754af9/textdistance_1612461398012/work
+threadpoolctl @ file:///Users/ktietz/demo/mc3/conda-bld/threadpoolctl_1629802263681/work
+three-merge @ file:///tmp/build/80754af9/three-merge_1607553261110/work
+tifffile @ file:///tmp/build/80754af9/tifffile_1627275862826/work
+time-machine==2.16.0
+tinycss2 @ file:///Users/ec2-user/ci_py311/tinycss2_1678317366076/work
+tinydb==4.8.2
+tldextract==5.1.3
+toml @ file:///tmp/build/80754af9/toml_1616166611790/work
+tomli @ file:///Users/ec2-user/ci_py311/tomli_1678315243316/work
+tomlkit @ file:///Users/ec2-user/ci_py311/tomlkit_1678317388739/work
+toolz @ file:///Users/ec2-user/ci_py311/toolz_1678323009669/work
+torch==2.0.0
+torchvision==0.15
+tornado @ file:///Users/ec2-user/ci_py311/tornado_1678316833426/work
+tqdm==4.67.1
+traitlets @ file:///Users/ec2-user/ci_py311/traitlets_1678316097905/work
+traits==6.3.2
+transformers @ file:///tmp/build/80754af9/transformers_1633098115425/work
+trio==0.24.0
+trio-websocket==0.11.1
+tushare==1.2.89
+twikit==2.3.3
+Twisted @ file:///private/var/folders/sy/f16zz6x50xz3113nwtb9bvq00000gp/T/abs_3cf4rqmb9n/croot/twisted_1683796897214/work
+typing-inspect==0.9.0
+typing-inspection==0.4.1
+typing-utils==0.1.0
+typing_extensions==4.12.2
+tzdata==2024.2
+tzlocal==5.3.1
+uc-micro-py @ file:///Users/ec2-user/ci_py311/uc-micro-py_1678394873457/work
+ujson @ file:///Users/ec2-user/ci_py311/ujson_1678325349324/work
+Unidecode @ file:///tmp/build/80754af9/unidecode_1614712377438/work
+uri-template==1.3.0
+urllib3==1.26.18
+uvicorn==0.24.0
+uvloop==0.17.0
+vbuild==0.8.2
+virtualenv==20.27.0
+w3lib @ file:///Users/ktietz/demo/mc3/conda-bld/w3lib_1629359764703/work
+watchdog @ file:///Users/ec2-user/ci_py311/watchdog_1678395046770/work
+watchfiles==0.19.0
+wcwidth @ file:///Users/ktietz/demo/mc3/conda-bld/wcwidth_1629357192024/work
+web3==6.17.2
+webcolors==24.11.1
+webencodings==0.5.1
+websocket-client==0.57.0
+websockets==12.0
+webvtt-py==0.5.1
+Werkzeug @ file:///private/var/folders/sy/f16zz6x50xz3113nwtb9bvq00000gp/T/abs_fegt3z60s3/croot/werkzeug_1679489762631/work
+whatthepatch @ file:///Users/ec2-user/ci_py311/whatthepatch_1678379478749/work
+widgetsnbextension @ file:///private/var/folders/sy/f16zz6x50xz3113nwtb9bvq00000gp/T/abs_8feupjw2ld/croot/widgetsnbextension_1679313870305/work
+wrapt @ file:///Users/ec2-user/ci_py311/wrapt_1678323111850/work
+wsproto==1.2.0
+wurlitzer @ file:///Users/ec2-user/ci_py311/wurlitzer_1678390004531/work
+xarray @ file:///Users/ec2-user/ci_py311/xarray_1678395099624/work
+XlsxWriter==3.1.2
+xlwings @ file:///Users/ec2-user/ci_py311_2/xlwings_1679338568565/work
+xyzservices @ file:///Users/ec2-user/ci_py311/xyzservices_1678325391212/work
+y-py @ file:///private/var/folders/sy/f16zz6x50xz3113nwtb9bvq00000gp/T/abs_7dvnlnkj12/croot/y-py_1683555629284/work
+yapf @ file:///tmp/build/80754af9/yapf_1615749224965/work
+yarl==1.18.3
+you-get==0.4.1730
+ypy-websocket @ file:///private/var/folders/sy/f16zz6x50xz3113nwtb9bvq00000gp/T/abs_75t89iv95n/croot/ypy-websocket_1684171758794/work
+zict @ file:///private/var/folders/sy/f16zz6x50xz3113nwtb9bvq00000gp/T/abs_59schmcson/croot/zict_1682698747213/work
+zipp @ file:///Users/ec2-user/ci_py311/zipp_1678318061389/work
+zope.interface @ file:///Users/ec2-user/ci_py311/zope.interface_1678379536727/work
+zstandard @ file:///Users/ec2-user/ci_py311_2/zstandard_1679338593428/work

result/simulation_results-1763109446.json

@@ -1,289 +0,0 @@
-[
-  {
-    "expression": "-ts_correlation(open, close, 20)",
-    "time_consuming": 21.09,
-    "formatted_time": "21.09秒",
-    "alpha_id": "/",
-    "status": "error",
-    "description": "Attempted to use inaccessible or unknown operator \"ts_correlation\"",
-    "simulation_timestamp": "2025-11-14 16:35:40",
-    "metrics": null
-  },
-  {
-    "expression": "ts_mean(volume / ts_mean(volume, 20), 30)",
-    "time_consuming": 90.94,
-    "formatted_time": "1分30.94秒",
-    "alpha_id": "akZ63dm1",
-    "status": "success",
-    "description": "/",
-    "simulation_timestamp": "2025-11-14 16:36:50",
-    "metrics": {
-      "id": "akZ63dm1",
-      "type": "REGULAR",
-      "author": "YC93384",
-      "settings": {
-        "instrumentType": "EQUITY",
-        "region": "USA",
-        "universe": "TOP3000",
-        "delay": 1,
-        "decay": 0,
-        "neutralization": "INDUSTRY",
-        "truncation": 0.08,
-        "pasteurization": "ON",
-        "unitHandling": "VERIFY",
-        "nanHandling": "OFF",
-        "maxTrade": "OFF",
-        "language": "FASTEXPR",
-        "visualization": false,
-        "startDate": "2018-01-20",
-        "endDate": "2023-01-20"
-      },
-      "regular": {
-        "code": "ts_mean(volume / ts_mean(volume, 20), 30)",
-        "description": null,
-        "operatorCount": 3
-      },
-      "dateCreated": "2025-11-14T03:36:48-05:00",
-      "dateSubmitted": null,
-      "dateModified": "2025-11-14T03:36:48-05:00",
-      "name": null,
-      "favorite": false,
-      "hidden": false,
-      "color": null,
-      "category": null,
-      "tags": [],
-      "classifications": [
-        {
-          "id": "DATA_USAGE:SINGLE_DATA_SET",
-          "name": "Single Data Set Alpha"
-        }
-      ],
-      "grade": "INFERIOR",
-      "stage": "IS",
-      "status": "UNSUBMITTED",
-      "is": {
-        "pnl": 752501,
-        "bookSize": 20000000,
-        "longCount": 1462,
-        "shortCount": 1666,
-        "turnover": 0.1707,
-        "returns": 0.0152,
-        "drawdown": 0.1146,
-        "margin": 0.000178,
-        "sharpe": 0.25,
-        "fitness": 0.07,
-        "startDate": "2018-01-20",
-        "checks": [
-          {
-            "name": "LOW_SHARPE",
-            "result": "FAIL",
-            "limit": 1.25,
-            "value": 0.25
-          },
-          {
-            "name": "LOW_FITNESS",
-            "result": "FAIL",
-            "limit": 1.0,
-            "value": 0.07
-          },
-          {
-            "name": "LOW_TURNOVER",
-            "result": "PASS",
-            "limit": 0.01,
-            "value": 0.1707
-          },
-          {
-            "name": "HIGH_TURNOVER",
-            "result": "PASS",
-            "limit": 0.7,
-            "value": 0.1707
-          },
-          {
-            "name": "CONCENTRATED_WEIGHT",
-            "result": "PASS"
-          },
-          {
-            "name": "LOW_SUB_UNIVERSE_SHARPE",
-            "result": "PASS",
-            "limit": 0.11,
-            "value": 0.83
-          },
-          {
-            "name": "SELF_CORRELATION",
-            "result": "PENDING"
-          },
-          {
-            "name": "MATCHES_COMPETITION",
-            "result": "PASS",
-            "competitions": [
-              {
-                "id": "challenge",
-                "name": "Challenge"
-              }
-            ]
-          }
-        ]
-      },
-      "os": null,
-      "train": null,
-      "test": null,
-      "prod": null,
-      "competitions": null,
-      "themes": null,
-      "pyramids": null,
-      "pyramidThemes": null,
-      "team": null
-    }
-  },
-  {
-    "expression": "ts_rank((high - low) / (close - open + 0.001), 15)",
-    "time_consuming": 116.93,
-    "formatted_time": "1分56.93秒",
-    "alpha_id": "VkjVoGGb",
-    "status": "success",
-    "description": "/",
-    "simulation_timestamp": "2025-11-14 16:37:16",
-    "metrics": {
-      "id": "VkjVoGGb",
-      "type": "REGULAR",
-      "author": "YC93384",
-      "settings": {
-        "instrumentType": "EQUITY",
-        "region": "USA",
-        "universe": "TOP3000",
-        "delay": 1,
-        "decay": 0,
-        "neutralization": "INDUSTRY",
-        "truncation": 0.08,
-        "pasteurization": "ON",
-        "unitHandling": "VERIFY",
-        "nanHandling": "OFF",
-        "maxTrade": "OFF",
-        "language": "FASTEXPR",
-        "visualization": false,
-        "startDate": "2018-01-20",
-        "endDate": "2023-01-20"
-      },
-      "regular": {
-        "code": "ts_rank((high - low) / (close - open + 0.001), 15)",
-        "description": null,
-        "operatorCount": 5
-      },
-      "dateCreated": "2025-11-14T03:37:13-05:00",
-      "dateSubmitted": null,
-      "dateModified": "2025-11-14T03:37:14-05:00",
-      "name": null,
-      "favorite": false,
-      "hidden": false,
-      "color": null,
-      "category": null,
-      "tags": [],
-      "classifications": [
-        {
-          "id": "DATA_USAGE:SINGLE_DATA_SET",
-          "name": "Single Data Set Alpha"
-        }
-      ],
-      "grade": "INFERIOR",
-      "stage": "IS",
-      "status": "UNSUBMITTED",
-      "is": {
-        "pnl": -1933631,
-        "bookSize": 20000000,
-        "longCount": 1562,
-        "shortCount": 1565,
-        "turnover": 1.3813,
-        "returns": -0.0391,
-        "drawdown": 0.2222,
-        "margin": -5.7e-05,
-        "sharpe": -1.15,
-        "fitness": -0.19,
-        "startDate": "2018-01-20",
-        "checks": [
-          {
-            "name": "LOW_SHARPE",
-            "result": "FAIL",
-            "limit": 1.25,
-            "value": -1.15
-          },
-          {
-            "name": "LOW_FITNESS",
-            "result": "FAIL",
-            "limit": 1.0,
-            "value": -0.19
-          },
-          {
-            "name": "LOW_TURNOVER",
-            "result": "PASS",
-            "limit": 0.01,
-            "value": 1.3813
-          },
-          {
-            "name": "HIGH_TURNOVER",
-            "result": "FAIL",
-            "limit": 0.7,
-            "value": 1.3813
-          },
-          {
-            "name": "CONCENTRATED_WEIGHT",
-            "result": "PASS"
-          },
-          {
-            "name": "LOW_SUB_UNIVERSE_SHARPE",
-            "result": "FAIL",
-            "limit": -0.5,
-            "value": -0.73
-          },
-          {
-            "name": "UNITS",
-            "result": "WARNING",
-            "message": "Incompatible unit for input of \"add\" at index 1, expected \"Unit[CSPrice:1]\", found \"Unit[]\""
-          },
-          {
-            "name": "SELF_CORRELATION",
-            "result": "PENDING"
-          },
-          {
-            "name": "MATCHES_COMPETITION",
-            "result": "PASS",
-            "competitions": [
-              {
-                "id": "challenge",
-                "name": "Challenge"
-              }
-            ]
-          }
-        ]
-      },
-      "os": null,
-      "train": null,
-      "test": null,
-      "prod": null,
-      "competitions": null,
-      "themes": null,
-      "pyramids": null,
-      "pyramidThemes": null,
-      "team": null
-    }
-  },
-  {
-    "expression": "-ts_rank(ts_skewness(returns(close), 10), 25)",
-    "time_consuming": 1.44,
-    "formatted_time": "1.44秒",
-    "alpha_id": "/",
-    "status": "error",
-    "description": "Attempted to use inaccessible or unknown operator \"ts_skewness\"",
-    "simulation_timestamp": "2025-11-14 16:37:22",
-    "metrics": null
-  },
-  {
-    "expression": "(close - ts_min(low, 50)) / (ts_max(high, 50) - ts_min(low, 50) + 0.001)",
-    "time_consuming": 5.76,
-    "formatted_time": "5.76秒",
-    "alpha_id": "/",
-    "status": "error",
-    "description": "Attempted to use inaccessible or unknown operator \"ts_min\"",
-    "simulation_timestamp": "2025-11-14 16:37:26",
-    "metrics": null
-  }
-]

result/simulation_results-1763110929.json

@@ -1,524 +0,0 @@
-[
-  {
-    "expression": "ts_rank(close - vwap, 12)",
-    "time_consuming": 15.79,
-    "formatted_time": "15.79秒",
-    "alpha_id": "/",
-    "status": "failed",
-    "description": "The read operation timed out",
-    "simulation_timestamp": "2025-11-14 16:58:48",
-    "metrics": null
-  },
-  {
-    "expression": "ts_mean((close - open) / (high - low + 0.001), 20)",
-    "time_consuming": 109.71,
-    "formatted_time": "1分49.71秒",
-    "alpha_id": "VkjVwxrG",
-    "status": "success",
-    "description": "/",
-    "simulation_timestamp": "2025-11-14 17:00:22",
-    "metrics": {
-      "id": "VkjVwxrG",
-      "type": "REGULAR",
-      "author": "YC93384",
-      "settings": {
-        "instrumentType": "EQUITY",
-        "region": "USA",
-        "universe": "TOP3000",
-        "delay": 1,
-        "decay": 0,
-        "neutralization": "INDUSTRY",
-        "truncation": 0.08,
-        "pasteurization": "ON",
-        "unitHandling": "VERIFY",
-        "nanHandling": "OFF",
-        "maxTrade": "OFF",
-        "language": "FASTEXPR",
-        "visualization": false,
-        "startDate": "2018-01-20",
-        "endDate": "2023-01-20"
-      },
-      "regular": {
-        "code": "ts_mean((close - open) / (high - low + 0.001), 20)",
-        "description": null,
-        "operatorCount": 5
-      },
-      "dateCreated": "2025-11-14T04:00:17-05:00",
-      "dateSubmitted": null,
-      "dateModified": "2025-11-14T04:00:18-05:00",
-      "name": null,
-      "favorite": false,
-      "hidden": false,
-      "color": null,
-      "category": null,
-      "tags": [],
-      "classifications": [
-        {
-          "id": "DATA_USAGE:SINGLE_DATA_SET",
-          "name": "Single Data Set Alpha"
-        }
-      ],
-      "grade": "INFERIOR",
-      "stage": "IS",
-      "status": "UNSUBMITTED",
-      "is": {
-        "pnl": -4252305,
-        "bookSize": 20000000,
-        "longCount": 1570,
-        "shortCount": 1558,
-        "turnover": 0.3075,
-        "returns": -0.0859,
-        "drawdown": 0.5096,
-        "margin": -0.000559,
-        "sharpe": -0.83,
-        "fitness": -0.44,
-        "startDate": "2018-01-20",
-        "checks": [
-          {
-            "name": "LOW_SHARPE",
-            "result": "FAIL",
-            "limit": 1.25,
-            "value": -0.83
-          },
-          {
-            "name": "LOW_FITNESS",
-            "result": "FAIL",
-            "limit": 1.0,
-            "value": -0.44
-          },
-          {
-            "name": "LOW_TURNOVER",
-            "result": "PASS",
-            "limit": 0.01,
-            "value": 0.3075
-          },
-          {
-            "name": "HIGH_TURNOVER",
-            "result": "PASS",
-            "limit": 0.7,
-            "value": 0.3075
-          },
-          {
-            "name": "CONCENTRATED_WEIGHT",
-            "result": "PASS"
-          },
-          {
-            "name": "LOW_SUB_UNIVERSE_SHARPE",
-            "result": "FAIL",
-            "limit": -0.36,
-            "value": -0.7
-          },
-          {
-            "name": "UNITS",
-            "result": "WARNING",
-            "message": "Incompatible unit for input of \"add\" at index 1, expected \"Unit[CSPrice:1]\", found \"Unit[]\""
-          },
-          {
-            "name": "SELF_CORRELATION",
-            "result": "PENDING"
-          },
-          {
-            "name": "MATCHES_COMPETITION",
-            "result": "PASS",
-            "competitions": [
-              {
-                "id": "challenge",
-                "name": "Challenge"
-              }
-            ]
-          }
-        ]
-      },
-      "os": null,
-      "train": null,
-      "test": null,
-      "prod": null,
-      "competitions": null,
-      "themes": null,
-      "pyramids": null,
-      "pyramidThemes": null,
-      "team": null
-    }
-  },
-  {
-    "expression": "-ts_rank(ts_decay_linear(volume, 10), 30)",
-    "time_consuming": 124.43,
-    "formatted_time": "2分4.43秒",
-    "alpha_id": "E5W10mem",
-    "status": "success",
-    "description": "/",
-    "simulation_timestamp": "2025-11-14 17:00:37",
-    "metrics": {
-      "id": "E5W10mem",
-      "type": "REGULAR",
-      "author": "YC93384",
-      "settings": {
-        "instrumentType": "EQUITY",
-        "region": "USA",
-        "universe": "TOP3000",
-        "delay": 1,
-        "decay": 0,
-        "neutralization": "INDUSTRY",
-        "truncation": 0.08,
-        "pasteurization": "ON",
-        "unitHandling": "VERIFY",
-        "nanHandling": "OFF",
-        "maxTrade": "OFF",
-        "language": "FASTEXPR",
-        "visualization": false,
-        "startDate": "2018-01-20",
-        "endDate": "2023-01-20"
-      },
-      "regular": {
-        "code": "-ts_rank(ts_decay_linear(volume, 10), 30)",
-        "description": null,
-        "operatorCount": 3
-      },
-      "dateCreated": "2025-11-14T04:00:33-05:00",
-      "dateSubmitted": null,
-      "dateModified": "2025-11-14T04:00:34-05:00",
-      "name": null,
-      "favorite": false,
-      "hidden": false,
-      "color": null,
-      "category": null,
-      "tags": [],
-      "classifications": [
-        {
-          "id": "DATA_USAGE:SINGLE_DATA_SET",
-          "name": "Single Data Set Alpha"
-        }
-      ],
-      "grade": "INFERIOR",
-      "stage": "IS",
-      "status": "UNSUBMITTED",
-      "is": {
-        "pnl": -1352690,
-        "bookSize": 20000000,
-        "longCount": 1610,
-        "shortCount": 1517,
-        "turnover": 0.3383,
-        "returns": -0.0273,
-        "drawdown": 0.2176,
-        "margin": -0.000162,
-        "sharpe": -0.58,
-        "fitness": -0.16,
-        "startDate": "2018-01-20",
-        "checks": [
-          {
-            "name": "LOW_SHARPE",
-            "result": "FAIL",
-            "limit": 1.25,
-            "value": -0.58
-          },
-          {
-            "name": "LOW_FITNESS",
-            "result": "FAIL",
-            "limit": 1.0,
-            "value": -0.16
-          },
-          {
-            "name": "LOW_TURNOVER",
-            "result": "PASS",
-            "limit": 0.01,
-            "value": 0.3383
-          },
-          {
-            "name": "HIGH_TURNOVER",
-            "result": "PASS",
-            "limit": 0.7,
-            "value": 0.3383
-          },
-          {
-            "name": "CONCENTRATED_WEIGHT",
-            "result": "PASS"
-          },
-          {
-            "name": "LOW_SUB_UNIVERSE_SHARPE",
-            "result": "FAIL",
-            "limit": -0.25,
-            "value": -0.66
-          },
-          {
-            "name": "SELF_CORRELATION",
-            "result": "PENDING"
-          },
-          {
-            "name": "MATCHES_COMPETITION",
-            "result": "PASS",
-            "competitions": [
-              {
-                "id": "challenge",
-                "name": "Challenge"
-              }
-            ]
-          }
-        ]
-      },
-      "os": null,
-      "train": null,
-      "test": null,
-      "prod": null,
-      "competitions": null,
-      "themes": null,
-      "pyramids": null,
-      "pyramidThemes": null,
-      "team": null
-    }
-  },
-  {
-    "expression": "ts_rank(adv20 - volume, 15) + ts_rank(volume, 15)",
-    "time_consuming": 85.26,
-    "formatted_time": "1分25.26秒",
-    "alpha_id": "0m3qkZN1",
-    "status": "success",
-    "description": "/",
-    "simulation_timestamp": "2025-11-14 17:02:08",
-    "metrics": {
-      "id": "0m3qkZN1",
-      "type": "REGULAR",
-      "author": "YC93384",
-      "settings": {
-        "instrumentType": "EQUITY",
-        "region": "USA",
-        "universe": "TOP3000",
-        "delay": 1,
-        "decay": 0,
-        "neutralization": "INDUSTRY",
-        "truncation": 0.08,
-        "pasteurization": "ON",
-        "unitHandling": "VERIFY",
-        "nanHandling": "OFF",
-        "maxTrade": "OFF",
-        "language": "FASTEXPR",
-        "visualization": false,
-        "startDate": "2018-01-20",
-        "endDate": "2023-01-20"
-      },
-      "regular": {
-        "code": "ts_rank(adv20 - volume, 15) + ts_rank(volume, 15)",
-        "description": null,
-        "operatorCount": 4
-      },
-      "dateCreated": "2025-11-14T04:02:06-05:00",
-      "dateSubmitted": null,
-      "dateModified": "2025-11-14T04:02:07-05:00",
-      "name": null,
-      "favorite": false,
-      "hidden": false,
-      "color": null,
-      "category": null,
-      "tags": [],
-      "classifications": [
-        {
-          "id": "DATA_USAGE:SINGLE_DATA_SET",
-          "name": "Single Data Set Alpha"
-        }
-      ],
-      "grade": "INFERIOR",
-      "stage": "IS",
-      "status": "UNSUBMITTED",
-      "is": {
-        "pnl": 1607957,
-        "bookSize": 20000000,
-        "longCount": 1749,
-        "shortCount": 1375,
-        "turnover": 0.8699,
-        "returns": 0.0325,
-        "drawdown": 0.0811,
-        "margin": 7.5e-05,
-        "sharpe": 0.71,
-        "fitness": 0.14,
-        "startDate": "2018-01-20",
-        "checks": [
-          {
-            "name": "LOW_SHARPE",
-            "result": "FAIL",
-            "limit": 1.25,
-            "value": 0.71
-          },
-          {
-            "name": "LOW_FITNESS",
-            "result": "FAIL",
-            "limit": 1.0,
-            "value": 0.14
-          },
-          {
-            "name": "LOW_TURNOVER",
-            "result": "PASS",
-            "limit": 0.01,
-            "value": 0.8699
-          },
-          {
-            "name": "HIGH_TURNOVER",
-            "result": "FAIL",
-            "limit": 0.7,
-            "value": 0.8699
-          },
-          {
-            "name": "CONCENTRATED_WEIGHT",
-            "result": "PASS"
-          },
-          {
-            "name": "LOW_SUB_UNIVERSE_SHARPE",
-            "result": "PASS",
-            "limit": 0.31,
-            "value": 0.84
-          },
-          {
-            "name": "SELF_CORRELATION",
-            "result": "PENDING"
-          },
-          {
-            "name": "MATCHES_COMPETITION",
-            "result": "PASS",
-            "competitions": [
-              {
-                "id": "challenge",
-                "name": "Challenge"
-              }
-            ]
-          }
-        ]
-      },
-      "os": null,
-      "train": null,
-      "test": null,
-      "prod": null,
-      "competitions": null,
-      "themes": null,
-      "pyramids": null,
-      "pyramidThemes": null,
-      "team": null
-    }
-  },
-  {
-    "expression": "ts_mean(high - ts_delay(high, 1), 60) - ts_mean(low - ts_delay(low, 1), 60)",
-    "time_consuming": 86.01,
-    "formatted_time": "1分26.01秒",
-    "alpha_id": "wpxqw73d",
-    "status": "success",
-    "description": "/",
-    "simulation_timestamp": "2025-11-14 17:02:09",
-    "metrics": {
-      "id": "wpxqw73d",
-      "type": "REGULAR",
-      "author": "YC93384",
-      "settings": {
-        "instrumentType": "EQUITY",
-        "region": "USA",
-        "universe": "TOP3000",
-        "delay": 1,
-        "decay": 0,
-        "neutralization": "INDUSTRY",
-        "truncation": 0.08,
-        "pasteurization": "ON",
-        "unitHandling": "VERIFY",
-        "nanHandling": "OFF",
-        "maxTrade": "OFF",
-        "language": "FASTEXPR",
-        "visualization": false,
-        "startDate": "2018-01-20",
-        "endDate": "2023-01-20"
-      },
-      "regular": {
-        "code": "ts_mean(high - ts_delay(high, 1), 60) - ts_mean(low - ts_delay(low, 1), 60)",
-        "description": null,
-        "operatorCount": 7
-      },
-      "dateCreated": "2025-11-14T04:02:06-05:00",
-      "dateSubmitted": null,
-      "dateModified": "2025-11-14T04:02:06-05:00",
-      "name": null,
-      "favorite": false,
-      "hidden": false,
-      "color": null,
-      "category": null,
-      "tags": [],
-      "classifications": [
-        {
-          "id": "DATA_USAGE:SINGLE_DATA_SET",
-          "name": "Single Data Set Alpha"
-        }
-      ],
-      "grade": "INFERIOR",
-      "stage": "IS",
-      "status": "UNSUBMITTED",
-      "is": {
-        "pnl": -1454336,
-        "bookSize": 20000000,
-        "longCount": 1602,
-        "shortCount": 1526,
-        "turnover": 1.0897,
-        "returns": -0.0294,
-        "drawdown": 0.5598,
-        "margin": -5.4e-05,
-        "sharpe": -0.19,
-        "fitness": -0.03,
-        "startDate": "2018-01-20",
-        "checks": [
-          {
-            "name": "LOW_SHARPE",
-            "result": "FAIL",
-            "limit": 1.25,
-            "value": -0.19
-          },
-          {
-            "name": "LOW_FITNESS",
-            "result": "FAIL",
-            "limit": 1.0,
-            "value": -0.03
-          },
-          {
-            "name": "LOW_TURNOVER",
-            "result": "PASS",
-            "limit": 0.01,
-            "value": 1.0897
-          },
-          {
-            "name": "HIGH_TURNOVER",
-            "result": "FAIL",
-            "limit": 0.7,
-            "value": 1.0897
-          },
-          {
-            "name": "CONCENTRATED_WEIGHT",
-            "result": "FAIL",
-            "date": "2022-10-27",
-            "limit": 0.1,
-            "value": 0.298634
-          },
-          {
-            "name": "LOW_SUB_UNIVERSE_SHARPE",
-            "result": "FAIL",
-            "limit": -0.08,
-            "value": -0.37
-          },
-          {
-            "name": "SELF_CORRELATION",
-            "result": "PENDING"
-          },
-          {
-            "name": "MATCHES_COMPETITION",
-            "result": "PASS",
-            "competitions": [
-              {
-                "id": "challenge",
-                "name": "Challenge"
-              }
-            ]
-          }
-        ]
-      },
-      "os": null,
-      "train": null,
-      "test": null,
-      "prod": null,
-      "competitions": null,
-      "themes": null,
-      "pyramids": null,
-      "pyramidThemes": null,
-      "team": null
-    }
-  }
-]

result/simulation_results-1763112962.json

@@ -1,82 +0,0 @@
-[
-  {
-    "expression": "ts_mean(close, 20) / ts_mean(close, 100) > 1.05 and ts_std(close / ts_mean(close, 10), 20) / ts_mean(close, 20) < 0.15",
-    "time_consuming": 5.94,
-    "formatted_time": "5.94秒",
-    "alpha_id": "/",
-    "status": "error",
-    "description": "Unexpected character 'a' near \"0) > 1.05 and ts_std\"",
-    "simulation_timestamp": "2025-11-14 17:35:28",
-    "metrics": null
-  },
-  {
-    "expression": "ts_min(low, 20) / ts_max(high, 60) > 0.8 and market_cap > ts_mean(market_cap, all)",
-    "time_consuming": 6.53,
-    "formatted_time": "6.53秒",
-    "alpha_id": "/",
-    "status": "error",
-    "description": "Unexpected character 'a' near \"60) > 0.8 and market\"",
-    "simulation_timestamp": "2025-11-14 17:35:29",
-    "metrics": null
-  },
-  {
-    "expression": "close > ts_mean(close, 50) and ts_delta(ts_rank(volume, 10), 5) > 0",
-    "time_consuming": 7.6,
-    "formatted_time": "7.60秒",
-    "alpha_id": "/",
-    "status": "error",
-    "description": "Unexpected character 'a' near \"lose, 50) and ts_del\"",
-    "simulation_timestamp": "2025-11-14 17:35:30",
-    "metrics": null
-  },
-  {
-    "expression": "ts_corr(close, vwap, 30) < 0.3 and ts_mean(volume, 5) / ts_mean(volume, 60) < 0.8",
-    "time_consuming": 5.8,
-    "formatted_time": "5.80秒",
-    "alpha_id": "/",
-    "status": "error",
-    "description": "Unexpected character 'a' near \"30) < 0.3 and ts_mea\"",
-    "simulation_timestamp": "2025-11-14 17:35:40",
-    "metrics": null
-  },
-  {
-    "expression": "abs(close - vwap) / vwap < 0.02 and volume < ts_mean(volume, 20)",
-    "time_consuming": 6.62,
-    "formatted_time": "6.62秒",
-    "alpha_id": "/",
-    "status": "error",
-    "description": "Unexpected character 'a' near \"ap < 0.02 and volume\"",
-    "simulation_timestamp": "2025-11-14 17:35:41",
-    "metrics": null
-  },
-  {
-    "expression": "(close - ts_mean(close, 30)) / ts_std(close, 30) > 1.5 and ts_delta(close, 5) < 0",
-    "time_consuming": 15.51,
-    "formatted_time": "15.51秒",
-    "alpha_id": "/",
-    "status": "error",
-    "description": "Unexpected character 'a' near \"30) > 1.5 and ts_del\"",
-    "simulation_timestamp": "2025-11-14 17:35:50",
-    "metrics": null
-  },
-  {
-    "expression": "ts_std(log(close / close[1]), 20) > ts_mean(ts_std(log(close / close[1]), 20), 60)",
-    "time_consuming": 1.2,
-    "formatted_time": "1.20秒",
-    "alpha_id": "/",
-    "status": "error",
-    "description": "Unexpected character '[' near \"se / close[1]), 20)\"",
-    "simulation_timestamp": "2025-11-14 17:35:56",
-    "metrics": null
-  },
-  {
-    "expression": "ts_range(high - low, 5) / ts_mean(high - low, 60) > 1.5 and ts_delta(ts_std(close, 10), 5) > 0",
-    "time_consuming": 7.38,
-    "formatted_time": "7.38秒",
-    "alpha_id": "/",
-    "status": "error",
-    "description": "Unexpected character 'a' near \"60) > 1.5 and ts_del\"",
-    "simulation_timestamp": "2025-11-14 17:36:02",
-    "metrics": null
-  }
-]

result/simulation_results-1763113286.json

@@ -1,12 +0,0 @@
-[
-  {
-    "expression": "ts_delta(ts_mean(close, 5), 10) / ts_std(close, 20) * (ts_mean(close, 20) / ts_mean(close, 100) > 1.02)",
-    "time_consuming": 6.62,
-    "formatted_time": "6.62秒",
-    "alpha_id": "/",
-    "status": "error",
-    "description": "Attempted to use inaccessible or unknown operator \"ts_std\"",
-    "simulation_timestamp": "2025-11-14 17:41:26",
-    "metrics": null
-  }
-]

services/alpha_service.py

@@ -0,0 +1,60 @@
+# -*- coding: utf-8 -*-
+"""Alpha表达式服务"""
+
+import time
+import httpx
+from typing import List, Dict, Any
+from config.settings import settings
+
+
+class AlphaService:
+    """Alpha表达式服务类"""
+
+    def __init__(self, client: httpx.Client):
+        self.client = client
+
+    def simulate_alpha(self, expression: str) -> Dict[str, Any]:
+        """模拟单个Alpha表达式"""
+        simulation_data = {
+            'type': 'REGULAR',
+            'settings': settings.SIMULATION_SETTINGS,
+            'regular': expression
+        }
+
+        sim_resp = self.client.post(f'{settings.BRAIN_API_URL}/simulations', json=simulation_data)
+        print(f"模拟提交状态: {sim_resp.status_code}")
+
+        if 'location' not in sim_resp.headers:
+            return {"status": "err", "message": "No location header in response"}
+
+        sim_progress_url = sim_resp.headers['location']
+        return self._wait_for_simulation_result(sim_progress_url)
+
+    def _wait_for_simulation_result(self, progress_url: str) -> Dict[str, Any]:
+        """等待模拟结果"""
+        while True:
+            sim_progress_resp = self.client.get(progress_url)
+            retry_after_sec = float(sim_progress_resp.headers.get("Retry-After", 0))
+
+            if retry_after_sec == 0:
+                break
+
+            if sim_progress_resp.json():
+                result = sim_progress_resp.json()
+                progress = result.get('progress', 0)
+                print(f"模拟进度: {float(progress) * 100}%")
+
+            print(f"等待 {retry_after_sec} 秒...")
+            time.sleep(retry_after_sec)
+
+        result_data = sim_progress_resp.json()
+
+        if result_data.get("status") == "ERROR":
+            error_message = result_data.get("message", "未知错误")
+            print(f"因子模拟失败: {error_message}")
+            return {"status": "err", "message": error_message}
+
+        alpha_id = result_data.get("alpha")
+        print(f"生成的Alpha ID: {alpha_id}")
+
+        return {"status": "ok", "alpha_id": alpha_id}

services/auth_service.py

@@ -0,0 +1,57 @@
+# -*- coding: utf-8 -*-
+"""认证服务"""
+
+import os
+import httpx
+from httpx import BasicAuth
+from typing import Tuple, Dict, Any
+from config.settings import settings
+from models.entities import TokenInfo
+
+
+class AuthService:
+    """认证服务类"""
+
+    def __init__(self):
+        self.credentials_file = settings.credentials_file
+
+    def load_credentials(self) -> Tuple[str, str]:
+        """加载凭证"""
+        if not os.path.exists(self.credentials_file):
+            self._create_credentials_file()
+
+        with open(self.credentials_file, 'r', encoding='utf-8') as f:
+            credentials = eval(f.read())
+        return credentials[0], credentials[1]
+
+    def _create_credentials_file(self) -> None:
+        """创建凭证文件"""
+        print("未找到 account.txt 文件")
+        with open(self.credentials_file, 'w', encoding='utf-8') as f:
+            f.write("")
+        print("account.txt 文件已创建，请填写账号密码, 格式: ['username', 'password']")
+        exit(1)
+
+    def login(self, client: httpx.Client) -> TokenInfo:
+        """登录并获取token"""
+        username, password = self.load_credentials()
+
+        # 设置 BasicAuth
+        client.auth = BasicAuth(username, password)
+
+        response = client.post(f'{settings.BRAIN_API_URL}/authentication')
+        print(f"登录状态: {response.status_code}")
+
+        if response.status_code == 201:
+            login_data = response.json()
+            print(f"登录成功!: {login_data}")
+            return TokenInfo(
+                token=login_data['token'],
+                expiry=int(login_data['token']['expiry'])
+            )
+        elif response.status_code == 429:
+            print("API rate limit exceeded")
+            exit(1)
+        else:
+            print(f"登录失败: {response.json()}")
+            raise Exception(f"登录失败: {response.json()}")

services/notification_service.py

@@ -0,0 +1,27 @@
+# -*- coding: utf-8 -*-
+"""通知服务"""
+
+import httpx
+from datetime import datetime
+from config.settings import settings
+
+
+class NotificationService:
+    """通知服务类"""
+
+    @staticmethod
+    def send_to_gotify(success_count: int, fail_count: int) -> None:
+        """发送结果到Gotify"""
+        now = datetime.now().strftime('%Y-%m-%d %H:%M:%S')
+        text = f"总计: 成功 {success_count} 个, 失败 {fail_count} 个\n\n完成时间: {now}"
+        title = f"alpha模拟结果 时间: {now}"
+
+        try:
+            resp = httpx.post(
+                settings.GOTIFY_URL,
+                json={'title': title, 'message': text},
+                timeout=10
+            )
+            print("通知发送成功")
+        except Exception as e:
+            print(f"通知发送失败: {e}")

success.txt

@@ -1,4 +0,0 @@
-ts_mean((close - open) / (high - low + 0.001), 20)
--ts_rank(ts_decay_linear(volume, 10), 30)
-ts_rank(adv20 - volume, 15) + ts_rank(volume, 15)
-ts_mean(high - ts_delay(high, 1), 60) - ts_mean(low - ts_delay(low, 1), 60)

utils/__init__.py

@@ -1,9 +0,0 @@
-# -*- coding: utf-8 -*-
-"""
-工具模块 - 包含各种工具函数
-"""
-
-from .file_utils import load_alpha_list, save_results_to_file
-from .time_utils import format_time
-
-__all__ = ['load_alpha_list', 'save_results_to_file', 'format_time']

utils/file_utils.py

@@ -1,84 +0,0 @@
-# -*- coding: utf-8 -*-
-import os
-import json
-import time
-from typing import List, Any
-
-
-def load_alpha_list(file_path: str) -> List[str]:
-    """从文件加载Alpha因子列表"""
-    if not os.path.exists(file_path):
-        print(f"{file_path} 文件不存在")
-        with open(file_path, 'w', encoding='utf-8') as file:
-            file.write("")
-        print(f"已创建 {file_path} 文件, 请添加因子后重新运行, 一行一个因子")
-        return []
-
-    with open(file_path, 'r', encoding='utf-8') as file:
-        alpha_list = [line.strip() for line in file if line.strip()]
-
-    return alpha_list
-
-
-def save_results_to_file(results: List[Any], result_dir: str = 'result') -> str:
-    """保存结果到文件"""
-    # 转换为可序列化的格式
-    serializable_results = []
-    for result in results:
-        if hasattr(result, '__dict__'):
-            # 如果是dataclass对象，转换为字典
-            result_dict = result.__dict__.copy()
-        else:
-            # 如果是字典
-            result_dict = result.copy()
-
-        # 处理时间消耗
-        if 'time_consuming' in result_dict:
-            result_dict['time_consuming'] = round(result_dict['time_consuming'], 2)
-
-        # 只需要确保所有浮点数精度一致
-        def round_floats(obj):
-            if isinstance(obj, float):
-                return round(obj, 6)
-            elif isinstance(obj, dict):
-                return {k: round_floats(v) for k, v in obj.items()}
-            elif isinstance(obj, list):
-                return [round_floats(item) for item in obj]
-            else:
-                return obj
-
-        # 对结果中的所有浮点数进行精度处理
-        result_dict = round_floats(result_dict)
-
-        serializable_results.append(result_dict)
-
-    # 确保结果目录存在
-    if not os.path.exists(result_dir):
-        os.makedirs(result_dir)
-
-    result_name = f"{result_dir}/simulation_results-{str(int(time.time()))}.json"
-    with open(result_name, 'w', encoding='utf-8') as f:
-        json.dump(serializable_results, f, ensure_ascii=False, indent=2)
-
-    print(f"结果已保存到 {result_name}")
-    return result_name
-
-
-def save_success_alpha(success_expression_list):
-    """
-    将成功的表达式列表保存到 success.txt 文件中
-    如果文件不存在则创建，如果存在则追加写入
-    """
-    if not success_expression_list:
-        print("没有成功的表达式需要保存")
-        return
-
-    try:
-        with open('success.txt', 'a', encoding='utf-8') as f:
-            for expression in success_expression_list:
-                f.write(expression + '\n')
-
-        print(f"成功保存 {len(success_expression_list)} 个表达式到 success.txt")
-
-    except Exception as e:
-        print(f"保存文件时出错: {e}")

utils/helpers.py

@@ -0,0 +1,23 @@
+# -*- coding: utf-8 -*-
+"""工具函数"""
+
+import time
+from typing import Callable, Any
+
+
+def retry_on_exception(max_retries: int = 3, delay: float = 5.0) -> Callable:
+    """异常重试装饰器"""
+    def decorator(func: Callable) -> Callable:
+        def wrapper(*args, **kwargs) -> Any:
+            for attempt in range(max_retries):
+                try:
+                    return func(*args, **kwargs)
+                except Exception as e:
+                    if attempt == max_retries - 1:
+                        raise e
+                    print(f"尝试 {attempt + 1}/{max_retries} 失败: {e}")
+                    print(f"{delay}秒后重试...")
+                    time.sleep(delay)
+            return None
+        return wrapper
+    return decorator

utils/time_utils.py

@@ -1,9 +0,0 @@
-# -*- coding: utf-8 -*-
-def format_time(seconds: float) -> str:
-    """将秒数格式化为 xx分xx秒 格式"""
-    if seconds < 60:
-        return f"{seconds:.2f}秒"
-    else:
-        minutes = int(seconds // 60)
-        remaining_seconds = seconds % 60
-        return f"{minutes}分{remaining_seconds:.2f}秒"