refactor(archive): move unused modules to archive/
Archive legacy framework and utility modules that are no longer referenced by the active core (datasource/ and rotation/): - framework/ -> archive/framework/ - framework_v2/ -> archive/framework_v2/ - strategies/ -> archive/strategies/ - config/ -> archive/config/ - visualization/ -> archive/visualization/ - scripts/ -> archive/scripts/ - tests/ -> archive/tests/ - run_rotation.py, run_us_rotation.py -> archive/single_files/ - compare_*.py, test_api_dates.py -> archive/single_files/
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archive/framework_v2/shared/data/flask_api_fetcher.py
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269
archive/framework_v2/shared/data/flask_api_fetcher.py
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"""
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Flask API 数据获取器（framework_v2 实现）
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继承 DataFetcher 抽象基类，使用 FlaskAPIDataSource 获取线上数据
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支持指数、ETF 数据获取
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"""
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import pandas as pd
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from typing import Dict, List, Optional
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from pathlib import Path
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import sys
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# 添加项目根目录到路径
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project_root = Path(__file__).parent.parent.parent.parent
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if str(project_root) not in sys.path:
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sys.path.insert(0, str(project_root))
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from framework_v2.core.data import DataFetcher
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from datasource.flask_api_source import FlaskAPIDataSource
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class FlaskAPIFetcher(DataFetcher):
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"""
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Flask API 数据获取器
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通过 HTTP API 获取线上数据（指数、ETF）
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无需本地 SSH 隧道配置
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用法:
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fetcher = FlaskAPIFetcher(base_url="https://k3s.tokenpluse.xyz")
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data = fetcher.fetch_indices(["000300.SH"], "2024-01-01", "2024-12-31")
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"""
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name = "flask_api"
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def __init__(
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self,
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base_url: str = None,
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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 服务地址（默认从环境变量读取）
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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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super().__init__(base_url=base_url, timeout=timeout, retries=retries)
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# 创建底层数据源
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self._source = FlaskAPIDataSource(
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base_url=base_url,
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timeout=timeout,
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retries=retries
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)
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def fetch_indices(
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self,
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codes: List[str],
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start: str,
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end: str,
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adj: str = 'raw'
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) -> Dict[str, pd.DataFrame]:
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"""
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获取指数 OHLCV 数据
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Args:
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codes: 指数代码列表（如 ["000300.SH", "000905.SH"]）
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start: 开始日期 (YYYY-MM-DD)
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end: 结束日期 (YYYY-MM-DD)
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adj: 复权类型，默认 'raw'（指数通常用原始价格）
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Returns:
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{code: DataFrame} 字典，DataFrame 包含 OHLCV 列
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示例:
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>>> fetcher = FlaskAPIFetcher()
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>>> data = fetcher.fetch_indices(
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... ["000300.SH", "000905.SH"],
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... "2024-01-01",
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... "2024-12-31"
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... )
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>>> print(data["000300.SH"].head())
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"""
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print(f"\n[FlaskAPI] 获取 {len(codes)} 只指数数据（adj='{adj}'）...")
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results = {}
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for i, code in enumerate(codes, 1):
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print(f" [{i}/{len(codes)}] {code}...")
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df = self._source.fetch(
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code=code,
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start_date=start,
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end_date=end,
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adj=adj # 使用传入的 adj 参数
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)
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if df is not None:
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results[code] = df
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print(f" ✓ {len(df)} 条数据")
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else:
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print(f" ✗ 获取失败")
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success = len(results)
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print(f"\n[FlaskAPI] 指数数据获取完成: {success}/{len(codes)} 成功")
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return results
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def fetch_etf(
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self,
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codes: List[str],
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start: str,
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end: str,
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adj: str = 'hfq'
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) -> Dict[str, pd.DataFrame]:
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"""
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获取 ETF 数据（价格 + 净值）
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Args:
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codes: ETF 代码列表（如 ["510300.SH", "159919.SZ"]）
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start: 开始日期 (YYYY-MM-DD)
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end: 结束日期 (YYYY-MM-DD)
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adj: 复权类型，默认 'hfq'（ETF 收益计算推荐后复权）
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Returns:
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{code: DataFrame} 字典
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DataFrame 包含 OHLCV 列
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df.attrs['nav'] 包含净值数据
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df.attrs['premium_series'] 包含溢价率序列
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示例:
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>>> fetcher = FlaskAPIFetcher()
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>>> # 默认使用 hfq（后复权）
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>>> data = fetcher.fetch_etf(
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... ["510300.SH", "159919.SZ"],
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... "2024-01-01",
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... "2024-12-31"
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... )
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>>> # 或者显式指定 raw（原始价格，用于计算溢价率）
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>>> data_raw = fetcher.fetch_etf(
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... ["510300.SH"],
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... "2024-01-01",
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... "2024-12-31",
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... adj='raw'
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... )
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>>> # 访问净值
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>>> nav = data["510300.SH"].attrs.get('nav')
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"""
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print(f"\n[FlaskAPI] 获取 {len(codes)} 只 ETF 数据（adj='{adj}'）...")
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results = {}
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for i, code in enumerate(codes, 1):
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print(f" [{i}/{len(codes)}] {code}...")
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df = self._source.fetch(
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code=code,
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start_date=start,
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end_date=end,
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adj=adj, # 使用传入的 adj 参数
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asset_type='china_etf' # 强制指定 ETF 类型
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)
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if df is not None:
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results[code] = df
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# 显示附加信息
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nav_count = len(df.attrs.get('nav', pd.DataFrame()))
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premium = df.attrs.get('latest_premium', 'N/A')
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print(f" ✓ {len(df)} 条价格, {nav_count} 条净值, 溢价率: {premium}%")
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else:
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print(f" ✗ 获取失败")
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success = len(results)
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print(f"\n[FlaskAPI] ETF 数据获取完成: {success}/{len(codes)} 成功")
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return results
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def get_trading_calendar(
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self,
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market: str = 'A',
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start: str = None,
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end: str = None
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) -> pd.Index:
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"""
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获取交易日历（通过 API）
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Args:
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market: 市场代码
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- 'A' 或 'china': A股（上交所/深交所）
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- 'US' 或 'us': 美股（NYSE）
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- 'HK' 或 'hk': 港股（HKEX）
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start: 开始日期 YYYY-MM-DD（默认 2020-01-01）
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end: 结束日期 YYYY-MM-DD（默认 2025-12-31）
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Returns:
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交易日历 DatetimeIndex
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示例:
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>>> fetcher = FlaskAPIFetcher()
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>>> # 获取 A 股 2024 年交易日历
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>>> calendar = fetcher.get_trading_calendar('A', '2024-01-01', '2024-12-31')
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>>> # 获取美股交易日历
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>>> calendar = fetcher.get_trading_calendar('US', '2024-01-01', '2024-12-31')
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"""
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# 默认日期范围
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if start is None:
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start = '2020-01-01'
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if end is None:
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end = '2025-12-31'
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# 调用 API 获取准确日历
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calendar = self._source.get_trading_calendar(
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market=market,
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start_date=start,
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end_date=end
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)
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if calendar is None:
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# API 失败，抛出异常（不应静默降级）
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raise ValueError(
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f"交易日历获取失败: market={market}, {start} ~ {end}。"
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f"请检查 API 服务是否可用。"
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)
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return calendar
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def get_benchmark(
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self,
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code: str = "000300.SH",
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start: str = "2020-01-01",
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end: str = "2025-12-31"
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) -> pd.Series:
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"""
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获取基准数据
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Args:
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code: 基准代码（默认沪深 300）
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start: 开始日期
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end: 结束日期
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Returns:
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基准收盘价 Series
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"""
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df = self._source.fetch(
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code=code,
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start_date=start,
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end_date=end,
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adj='raw'
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)
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if df is None:
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raise ValueError(f"基准数据获取失败: {code}")
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return df['close']
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def get_health(self) -> Dict:
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"""
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检查 API 服务健康状态
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Returns:
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健康状态字典
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"""
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return self._source.get_health()
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def __repr__(self) -> str:
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return f"FlaskAPIFetcher(base_url={self._source.base_url})"
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