aszerW
ecd8d6539f
- yfinance_source.py: stock_info 存储在 df.attrs['info'] 中
- flask_server.py: dataframe_to_json 从 df.attrs 提取 info 放到最外层
- flask_server.py: 缓存切片函数保留 info 字段
- Dockerfile: 启用 Flask 服务作为默认 CMD（端口80）
响应结构示例:
{
"data": [{"date": "2024-01-01", "code": "AAPL", ...}],
"info": {"sector": "Technology", "industry": "...", ...}
}
124 lines
3.9 KiB
Python
124 lines
3.9 KiB
Python
"""
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YFinance数据源
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获取港股、美股数据（通过SSH隧道）
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"""
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import os
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import time
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from typing import Optional
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from datetime import datetime, timedelta
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import pandas as pd
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import urllib3
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# 禁用SSL警告
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urllib3.disable_warnings(urllib3.exceptions.InsecureRequestWarning)
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class YFinanceSource:
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"""YFinance数据源"""
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# 代码映射（项目代码 -> YFinance格式）
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CODE_MAP = {
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# 港股
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"HSTECH.HK": "3033.HK", # 恒生科技指数
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"HSI": "^HSI", # 恒生指数
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# 美股指数
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"NDX": "^NDX", # 纳斯达克100
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"SPX": "^GSPC", # 标普500
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"DJI": "^DJI", # 道琼斯
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# 日本/欧洲
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"N225": "^N225", # 日经225
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"GDAXI": "^GDAXI", # 德国DAX
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# 商品
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"CL.NYM": "CL=F", # WTI原油期货
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}
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def __init__(self, use_ssh_tunnel: bool = False):
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"""
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初始化YFinance数据源
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Args:
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use_ssh_tunnel: 是否使用SSH隧道（需先启动SSHTunnelManager）
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"""
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self.use_ssh_tunnel = use_ssh_tunnel
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self._delay = 0.5 # 请求延迟（避免限流）
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def fetch(self, code: str, start_date: str, end_date: str) -> Optional[pd.DataFrame]:
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"""
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获取数据
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Args:
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code: 代码（如 'NDX', 'N225', 'HSI'）
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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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Returns:
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DataFrame with columns: date, open, high, low, close, volume
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股票元信息存储在 df.attrs['info'] 中
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"""
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import yfinance as yf
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# 添加延迟避免限流
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time.sleep(self._delay)
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# 转换代码格式
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yf_code = self.CODE_MAP.get(code, code)
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try:
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ticker = yf.Ticker(yf_code)
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# 获取股票信息（仅对股票/ETF有效，指数可能没有）
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stock_info = {}
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try:
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stock_info = ticker.info or {}
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except Exception:
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pass # 指数可能没有info
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# end_date 需要加一天（yfinance的end是排他的）
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end_dt = datetime.strptime(end_date, "%Y-%m-%d") + timedelta(days=1)
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# auto_adjust=False 获取不复权价格
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df = ticker.history(
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start=start_date,
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end=end_dt.strftime("%Y-%m-%d"),
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auto_adjust=False
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)
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if df is None or len(df) == 0:
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return None
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# 标准化列名
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df = df.rename(columns={
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"Open": "open",
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"High": "high",
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"Low": "low",
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"Close": "close",
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"Volume": "volume",
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})
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# 确保索引是日期格式
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df.index = pd.to_datetime(df.index, utc=True).tz_localize(None).normalize()
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df.index.name = "date"
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# 添加代码列
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df["code"] = code
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# 将股票信息存储到 DataFrame.attrs 中（最外层结构）
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df.attrs['info'] = stock_info
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df.attrs['code'] = code
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return df[['code', 'open', 'high', 'low', 'close', 'volume']]
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except Exception as e:
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print(f"YFinance下载 {code} ({yf_code}) 失败: {e}")
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return None
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def is_yfinance_code(self, code: str) -> bool:
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"""判断是否需要YFinance获取"""
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# 非A股代码
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china_suffixes = ['.SH', '.SZ', '.SS', '.CSI']
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futures_suffixes = ['.SHF', '.NYM', '.DCE', '.CZC']
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# A股或期货用Tushare，其他用YFinance
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return not any(code.endswith(s) for s in china_suffixes + futures_suffixes) |