feat(strategy): rotation策略支持Flask API数据获取
- 新增 flask_api_source.py: Flask API远程数据源模块 - 修改 strategy.py: get_data() 支持通过Flask API获取数据 使用方式: strategy.get_data(use_flask_api=True) # 通过部署服务获取 strategy.get_data(use_flask_api=False) # 本地HybridDataSource 配置项: flask_api_url: 可在config.yaml中指定API地址
This commit is contained in:
293
datasource/flask_api_source.py
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293
datasource/flask_api_source.py
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"""
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Flask API 数据源
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通过部署后的 Flask API 服务获取 OHLCV 数据
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支持远程调用，无需本地 SSH 隧道
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"""
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import os
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import json
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import requests
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import pandas as pd
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from typing import Optional, Dict, List
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from datetime import datetime
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from pathlib import Path
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from dotenv import load_dotenv
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load_dotenv()
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class FlaskAPIDataSource:
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"""
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Flask API 数据源
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通过 HTTP API 获取数据，无需本地配置 SSH 隧道
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适用于远程调用或生产环境
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用法:
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source = FlaskAPIDataSource(base_url="https://k3s.tokenpluse.xyz")
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df = source.fetch("000300.SH", "2024-01-01", "2024-12-31")
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"""
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def __init__(
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self,
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base_url: str = None,
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api_path: str = "/api/v1/ohlcv",
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timeout: int = 120,
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retries: int = 3
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):
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"""
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初始化
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Args:
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base_url: API 服务基础地址，默认从环境变量读取
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api_path: API 路径
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timeout: 请求超时时间（秒）
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retries: 重试次数
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"""
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self.base_url = base_url or os.getenv(
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'FLASK_API_URL',
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'https://k3s.tokenpluse.xyz'
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)
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self.api_path = api_path
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self.timeout = timeout
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self.retries = retries
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# 确保 base_url 不以 / 结尾
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self.base_url = self.base_url.rstrip('/')
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def fetch(
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self,
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code: str,
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start_date: str,
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end_date: str,
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asset_type: str = None,
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timeframe: str = '1d'
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) -> Optional[pd.DataFrame]:
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"""
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获取单只标的 OHLCV 数据
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Args:
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code: 标的代码
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start_date: 开始日期 YYYY-MM-DD
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end_date: 结束日期 YYYY-MM-DD
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asset_type: 资产类型（可选，用于覆盖自动检测）
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timeframe: K线周期（加密货币需要）
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Returns:
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DataFrame with columns: date, open, high, low, close, volume
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"""
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# 构建请求 URL
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url = f"{self.base_url}{self.api_path}"
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# 构建请求参数
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params = {
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'code': code,
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'start': start_date,
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'end': end_date,
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}
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# 加密货币需要 timeframe 参数
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if asset_type == 'crypto' or code.upper() in ['BTC', 'ETH']:
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params['timeframe'] = timeframe
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# 可选：强制指定 asset_type
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if asset_type:
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params['asset_type'] = asset_type
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for attempt in range(self.retries):
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try:
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response = requests.get(
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url,
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params=params,
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timeout=self.timeout
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)
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if response.status_code != 200:
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if attempt < self.retries - 1:
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continue
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print(f"✗ API请求失败: {response.status_code} - {response.text[:100]}")
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return None
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data = response.json()
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# 检查错误
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if 'error' in data:
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print(f"✗ API返回错误: {data['error']}")
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return None
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# 解析数据
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records = data.get('data', [])
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if not records:
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print(f"⚠ {code}: 无数据返回")
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return None
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# 转换为 DataFrame
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df = pd.DataFrame(records)
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# 处理日期列
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if 'date' in df.columns:
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df['date'] = pd.to_datetime(df['date'])
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df = df.set_index('date')
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# 确保列名标准化
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df = df[['open', 'high', 'low', 'close', 'volume']]
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# 缓存 info 信息（如果有）
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if 'info' in data:
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df.attrs['info'] = data['info']
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print(f"✓ {code}: {len(df)} 条数据 ({start_date} ~ {end_date})")
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return df
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except requests.exceptions.Timeout:
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if attempt < self.retries - 1:
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print(f"⚠ {code}: 请求超时，重试 {attempt + 2}/{self.retries}")
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continue
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print(f"✗ {code}: 请求超时")
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return None
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except requests.exceptions.RequestException as e:
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if attempt < self.retries - 1:
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continue
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print(f"✗ {code}: 请求异常 - {e}")
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return None
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except json.JSONDecodeError as e:
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print(f"✗ {code}: JSON解析失败 - {e}")
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return None
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return None
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def fetch_batch(
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self,
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codes: List[str],
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start_date: str,
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end_date: str,
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asset_types: Dict[str, str] = None
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) -> Dict[str, Optional[pd.DataFrame]]:
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"""
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批量获取多只标的数据
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Args:
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codes: 标的代码列表
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start_date: 开始日期
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end_date: 结束日期
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asset_types: 资产类型映射 {code: asset_type}
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Returns:
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{code: DataFrame}
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"""
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results = {}
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asset_types = asset_types or {}
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print(f"从 Flask API 获取 {len(codes)} 只标的...")
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for i, code in enumerate(codes, 1):
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asset_type = asset_types.get(code)
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df = self.fetch(code, start_date, end_date, asset_type)
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results[code] = df
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# 显示进度
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if i % 5 == 0 or i == len(codes):
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success = sum(1 for v in results.values() if v is not None)
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print(f" 进度: {i}/{len(codes)} (成功: {success})")
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return results
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def fetch_etf_nav(
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self,
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code: str,
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start_date: str,
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end_date: str
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) -> Optional[pd.DataFrame]:
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"""
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获取 ETF 净值数据
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Args:
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code: ETF代码
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start_date: 开始日期
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end_date: 结束日期
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Returns:
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DataFrame with nav column
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"""
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url = f"{self.base_url}/api/v1/etf/nav"
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params = {
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'code': code,
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'start': start_date,
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'end': end_date
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}
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try:
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response = requests.get(url, params=params, timeout=self.timeout)
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if response.status_code != 200:
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return None
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data = response.json()
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if 'error' in data or 'nav' not in data:
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return None
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nav_data = data.get('nav', {})
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records = nav_data.get('data', [])
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if not records:
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return None
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df = pd.DataFrame(records)
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if 'date' in df.columns:
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df['date'] = pd.to_datetime(df['date'])
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df = df.set_index('date')
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return df
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except Exception as e:
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print(f"✗ {code} 净值获取失败: {e}")
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return None
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def get_health(self) -> Dict:
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"""获取服务健康状态"""
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# 先尝试 ohlcv 端点检查服务是否可用
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url = f"{self.base_url}{self.api_path}"
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params = {'code': '000300.SH', 'start': '2024-01-01', 'end': '2024-01-05'}
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try:
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response = requests.get(url, params=params, timeout=self.timeout)
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if response.status_code == 200:
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data = response.json()
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return {
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'status': 'healthy',
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'ssh_configured': True,
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'available': True
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}
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else:
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return {'status': 'error', 'available': False}
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except Exception as e:
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return {'status': 'error', 'message': str(e), 'available': False}
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def get_service_info(self) -> Dict:
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"""获取服务信息"""
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url = f"{self.base_url}/"
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try:
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response = requests.get(url, timeout=10)
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return response.json()
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except Exception as e:
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return {"error": str(e)}
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# 全局实例
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_flask_api_source: Optional[FlaskAPIDataSource] = None
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def get_flask_api_source(base_url: str = None) -> FlaskAPIDataSource:
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"""获取 Flask API 数据源实例"""
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global _flask_api_source
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if _flask_api_source is None:
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_flask_api_source = FlaskAPIDataSource(base_url=base_url)
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return _flask_api_source
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@@ -105,8 +105,14 @@ class RotationStrategy(StrategyBase):
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group_mapping[code] = cfg.get('market', 'default')
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return group_mapping
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def get_data(self) -> dict:
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"""获取数据（使用新数据源模块）"""
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def get_data(self, use_flask_api: bool = True) -> dict:
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"""
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获取数据
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Args:
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use_flask_api: 是否使用 Flask API 服务获取数据（默认 True）
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False 则使用本地 HybridDataSource
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"""
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code_list_config = self.config.get('code_list', {})
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benchmark_config = self.config.get('benchmark', {})
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benchmark_code = benchmark_config.get('code', '000300.SH')
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@@ -114,7 +120,123 @@ class RotationStrategy(StrategyBase):
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if not code_list_config:
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raise ValueError("配置中未找到 code_list")
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# 使用新数据源模块
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# 获取 Flask API 地址
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flask_api_url = self.config.get('flask_api_url')
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if use_flask_api:
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# 使用 Flask API 服务获取数据（远程调用）
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return self._get_data_from_flask_api(
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code_list_config,
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benchmark_code,
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flask_api_url
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)
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else:
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# 使用本地 HybridDataSource（需要本地 SSH 隧道）
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return self._get_data_from_local(
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code_list_config,
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benchmark_code
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)
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def _get_data_from_flask_api(
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self,
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code_list_config: dict,
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benchmark_code: str,
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flask_api_url: str = None
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) -> dict:
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"""通过 Flask API 服务获取数据"""
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from datasource.flask_api_source import FlaskAPIDataSource
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# 初始化 Flask API 数据源
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api_source = FlaskAPIDataSource(base_url=flask_api_url)
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# 检查服务状态
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health = api_source.get_health()
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if health.get('status') != 'healthy':
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print(f"⚠ Flask API 服务状态: {health}")
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else:
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print(f"✓ Flask API 服务正常 (SSH: {health.get('ssh_configured', False)})")
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# 获取指数代码列表
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index_codes = list(code_list_config.keys())
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# 获取 ETF 代码映射
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etf_code_map = {}
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etf_codes = []
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for index_code, cfg in code_list_config.items():
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if isinstance(cfg, dict) and cfg.get('etf'):
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etf_code_map[index_code] = cfg['etf']
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etf_codes.append(cfg['etf'])
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# 获取指数 OHLCV 数据
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print(f"\n获取指数数据 ({len(index_codes)} 只)...")
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index_ohlcv_data = api_source.fetch_batch(
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index_codes,
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self.start_date,
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self.end_date
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)
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# 过滤有效代码
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valid_codes = [code for code, df in index_ohlcv_data.items() if df is not None and len(df) > 0]
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print(f"有效指数: {len(valid_codes)} 只")
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# 获取 ETF 价格数据
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print(f"\n获取 ETF 数据 ({len(etf_codes)} 只)...")
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etf_ohlcv_data = api_source.fetch_batch(
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etf_codes,
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self.start_date,
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self.end_date
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)
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# 转换为宽格式 DataFrame
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etf_data = None
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if etf_ohlcv_data:
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etf_close_dict = {}
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for etf_code, df in etf_ohlcv_data.items():
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if df is not None and 'close' in df.columns:
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etf_close_dict[etf_code] = df['close']
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if etf_close_dict:
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etf_data = pd.DataFrame(etf_close_dict)
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# 获取基准数据
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print(f"\n获取基准数据 ({benchmark_code})...")
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benchmark_ohlcv = api_source.fetch(benchmark_code, self.start_date, self.end_date)
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benchmark_data = None
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if benchmark_ohlcv is not None:
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benchmark_data = benchmark_ohlcv['close']
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# 构建指数收盘价宽格式 DataFrame（用于因子计算）
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index_close_dict = {}
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for code in valid_codes:
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df = index_ohlcv_data.get(code)
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if df is not None and 'close' in df.columns:
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index_close_dict[code] = df['close']
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index_close = pd.DataFrame(index_close_dict) if index_close_dict else None
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# 获取 ETF 净值数据（用于溢价率计算）
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print(f"\n获取 ETF 净值数据...")
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etf_nav_data = {}
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for etf_code in etf_codes:
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nav_df = api_source.fetch_etf_nav(etf_code, self.start_date, self.end_date)
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if nav_df is not None:
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etf_nav_data[etf_code] = nav_df
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print(f"有效净值: {len(etf_nav_data)} 只")
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return {
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'index_data': index_ohlcv_data, # 原始 OHLCV 数据 {code: DataFrame}
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'index_close': index_close, # 对齐后的收盘价（宽格式）
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'etf_data': etf_data, # ETF 收盘价（宽格式）
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'etf_nav_data': etf_nav_data, # ETF 净值数据 {code: DataFrame}
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'benchmark_data': benchmark_data, # 基准收盘价 Series
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'valid_codes': valid_codes, # 有效指数代码列表
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'etf_code_map': etf_code_map # {指数代码: ETF代码} 映射
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}
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def _get_data_from_local(
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self,
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code_list_config: dict,
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benchmark_code: str
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) -> dict:
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"""使用本地 HybridDataSource 获取数据"""
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from datasource import HybridDataSource
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ssh_config = self.config.get('ssh_tunnel', {})
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