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# QuantDinger Python API Server
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# QuantDinger Python API (backend)
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Python 后端服务，提供金融数据获取、技术指标分析、AI 智能体分析和回测功能。
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Flask-based local-first backend for QuantDinger: market data, indicators, AI analysis, backtesting, and a strategy runtime (with an optional pending-order worker).
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## 项目结构
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This repository is intentionally simple: **no external database is required by default**. Data is stored in a local SQLite file (`quantdinger.db`) created/updated automatically on startup.
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```
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## What you get
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- **Multi-market data layer**: factory-based providers (crypto / US stocks / CN&HK stocks / futures, etc.)
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- **Indicators + backtesting**: persisted runs/history in SQLite
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- **AI multi-agent analysis**: optional web search + OpenRouter LLM integration
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- **Strategy runtime**: thread-based executor, with optional auto-restore on startup
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- **Pending orders worker (optional)**: polls queued orders and dispatches signals (webhook/notifications)
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- **Local auth (single-user)**: `/login` with env-configured admin credentials (JWT)
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## Project layout
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```text
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backend_api_python/
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├── app/ # 应用主目录
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│ ├── __init__.py # Flask 应用工厂
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│ ├── config/ # 配置模块 ⭐ (支持数据库动态配置)
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│ │ ├── __init__.py # 配置统一导出
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│ │ ├── settings.py # 服务配置
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│ │ ├── api_keys.py # API 密钥集中管理
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│ │ ├── database.py # 数据库/Redis/缓存配置
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│ │ └── data_sources.py # 数据源配置
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│ ├── data_sources/ # 数据源模块
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│ │ ├── base.py # 数据源基类
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│ │ ├── factory.py # 数据源工厂
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│ │ ├── crypto.py # 加密货币 (CCXT)
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│ │ ├── us_stock.py # 美股 (yfinance/Finnhub)
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│ │ ├── cn_stock.py # A股/港股 (yfinance/akshare)
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│ │ └── futures.py # 期货数据源
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│ ├── services/ # 业务服务层
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│ │ ├── agents/ # AI 智能体系统 (多智能体架构) ⭐
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│ │ │ ├── coordinator.py # 智能体协调器
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│ │ │ ├── tools.py # 智能体工具集 (含搜索/数据获取)
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│ │ │ ├── analyst_agents.py # 各类分析师 (技术/基本面/新闻等)
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│ │ │ └── researcher_agents.py # 研究员 (多空辩论)
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│ │ ├── kline.py # K线数据服务
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│ │ ├── search.py # 搜索服务 (Google/Bing)
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│ │ ├── llm.py # LLM 调用封装 (OpenRouter)
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│ │ └── analysis.py # 分析服务入口
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│ ├── routes/ # API 路由
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│ │ ├── health.py # 健康检查
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│ │ ├── kline.py # K线数据 API
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│ │ ├── analysis.py # AI 分析 API
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│ │ └── market.py # 市场数据 API
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│ └── utils/ # 工具模块
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│ ├── config_loader.py # 数据库配置加载器
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│ ├── logger.py # 日志工具
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│ └── http.py # HTTP 请求
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├── run.py # 入口文件 ⭐
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├── gunicorn_config.py # Gunicorn 配置
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├── requirements.txt # 依赖列表
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├── start.sh # 启动脚本
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└── README.md
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├─ app/
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│ ├─ __init__.py # Flask app factory + startup hooks
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│ ├─ config/ # Settings (env-driven)
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│ ├─ data_sources/ # Data sources + factory
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│ ├─ routes/ # REST endpoints
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│ ├─ services/ # Analysis, agents, strategies, search, ...
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│ └─ utils/ # SQLite helpers, config loader, logging, HTTP utils
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├─ env.example # Copy to .env for local config
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├─ requirements.txt
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├─ run.py # Entrypoint (loads .env, applies proxy env, starts Flask)
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├─ gunicorn_config.py # Optional production config
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└─ README.md
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```
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## 快速开始
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## Quick start (local development)
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### 1. 安装依赖
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### Prerequisites
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- Python 3.10+ recommended
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### 1) Install dependencies
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```bash
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cd backend_api_python
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pip install -r requirements.txt
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```
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### 2. 数据库配置
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### 2) Create your local `.env`
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本系统依赖 MySQL 数据库中的 `qd_addon_config` 表进行配置管理。请确保导入 `update_config_search.sql` 等 SQL 文件以初始化配置。
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Windows (CMD):
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### 3. 启动服务
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```bash
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copy env.example .env
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```
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Windows (PowerShell):
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```bash
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Copy-Item env.example .env
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```
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Then edit `.env` and set at least:
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- `SECRET_KEY`
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- `ADMIN_USER`
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- `ADMIN_PASSWORD`
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Optional but common:
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- `OPENROUTER_API_KEY` (for AI analysis)
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- `FINNHUB_API_KEY` / `SEARCH_GOOGLE_*` / `SEARCH_BING_API_KEY` (for richer data/search)
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- `PROXY_PORT` or `PROXY_URL` (if your network blocks some providers)
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### 3) Start the API server
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**开发环境：**
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```bash
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python run.py
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```
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**生产环境（使用 Gunicorn）：**
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Default address: `http://localhost:5000`
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## Database (SQLite)
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- Default file: `backend_api_python/quantdinger.db` (override via `SQLITE_DATABASE_FILE`)
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- Tables are created/updated automatically on startup (see `app/utils/db.py`)
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- `qd_addon_config` exists for backward compatibility, but **this backend reads secrets from `.env` / OS env**, not from the database (see `app/utils/config_loader.py`)
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## Frontend integration (Vue dev server)
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The Vue dev server proxies `/api/*` to this backend by default:
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- Frontend: `http://localhost:8000`
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- Backend: `http://localhost:5000`
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Proxy config: `quantdinger_vue/vue.config.js`
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## Useful endpoints
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```text
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GET /health
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POST /login
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GET /info
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GET /api/indicator/kline
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POST /api/analysis/multi
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```
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## Production (optional)
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Gunicorn example:
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```bash
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gunicorn -c gunicorn_config.py "run:app"
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```
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服务将在 `http://localhost:5000` 启动
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## Troubleshooting
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## 主要功能
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### 1. 多维度 AI 分析
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基于多智能体架构 (Multi-Agent Architecture)，模拟真实投研团队：
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- **市场分析师**: 技术面分析 (K线, MACD, RSI, 均线)
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- **基本面分析师**: 公司财务、估值、行业地位
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- **新闻分析师**: 实时新闻、舆情分析 (集成 Finnhub + Google/Bing 搜索)
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- **情绪分析师**: 市场情绪评估
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- **风险分析师**: 波动率、流动性风险评估
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- **多空辩论**: 模拟看涨/看跌研究员辩论，提供平衡观点
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### 2. 数据获取增强
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- **美股**: 实时行情 (Finnhub/yfinance) + 深度公司资料
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- **加密货币**: 实时行情 (CCXT/Binance) + 项目资讯搜索
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- **A股/港股**: 延迟行情 + 网络资讯搜索补充
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### 3. 智能搜索集成
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支持 Google Custom Search 和 Bing Search，自动补全传统数据源缺失的信息（如公司简介、最新突发新闻）。
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## API 接口
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### 健康检查
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```
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GET /health
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```
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### K线数据
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```
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GET /api/indicator/kline
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参数: market (Crypto/USStock/AShare), symbol, timeframe, limit
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```
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### AI 多维度分析
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```
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POST /api/analysis/multi
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{
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"market": "USStock",
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"symbol": "NVDA",
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"language": "zh-CN"
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}
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```
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## 配置说明
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系统配置采用 **数据库 + 环境变量** 混合模式，支持热更新。
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### 核心环境变量 (启动参数)
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| 变量名 | 说明 |
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|--------|------|
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| PYTHON_API_HOST | 监听地址 |
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| PYTHON_API_PORT | 监听端口 |
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| MYSQL_HOST | MySQL 主机 |
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| REDIS_HOST | Redis 主机 |
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### 数据库配置 (`qd_addon_config` 表)
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大部分业务配置已迁移至数据库，支持动态调整：
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- **API Keys**: Finnhub, Google Search, Bing Search
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- **AI 模型**: OpenRouter 模型选择
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- **系统参数**: 超时时间、重试次数、缓存策略
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- If outbound data/search requests fail, configure `PROXY_PORT` (or `PROXY_URL`) in `.env`.
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- If you don’t want strategies to auto-restore on startup, set `DISABLE_RESTORE_RUNNING_STRATEGIES=true`.
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- If you don’t want the pending-order worker, set `ENABLE_PENDING_ORDER_WORKER=false`.
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## License
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This project is released under the Apache License 2.0.
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See the repository root `LICENSE` for details.
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Apache License 2.0. See repository root `LICENSE`.
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Reference in New Issue
Block a user