""" 美股数据源 使用 yfinance 和 finnhub 获取数据 """ from typing import Dict, List, Any, Optional from datetime import datetime, timedelta import yfinance as yf from app.data_sources.base import BaseDataSource from app.utils.logger import get_logger from app.config import APIKeys, YFinanceConfig logger = get_logger(__name__) class USStockDataSource(BaseDataSource): """美股数据源""" name = "USStock/yfinance" # yfinance 时间周期映射 INTERVAL_MAP = { '1m': '1m', '5m': '5m', '15m': '15m', '30m': '30m', '1H': '1h', '4H': '4h', '1D': '1d', '1W': '1wk' } # 不同周期获取数据的天数范围 DAYS_MAP = { '1m': lambda limit: min(7, max(1, (limit // 390) + 2)), '5m': lambda limit: min(60, max(1, (limit // 78) + 2)), '15m': lambda limit: min(60, max(1, (limit // 26) + 2)), '30m': lambda limit: min(60, max(1, (limit // 13) + 2)), '1H': lambda limit: min(730, max(1, (limit // 24) + 2)), '4H': lambda limit: min(730, max(1, (limit // 6) + 2)), '1D': lambda limit: min(3650, limit + 1), '1W': lambda limit: min(3650, (limit * 7) + 7) } def __init__(self): # 初始化 finnhub 作为备选 self.finnhub_client = None try: import finnhub if APIKeys.is_configured('FINNHUB_API_KEY'): self.finnhub_client = finnhub.Client(api_key=APIKeys.FINNHUB_API_KEY) logger.info("Finnhub client initialized") except Exception as e: logger.warning(f"Finnhub init failed: {e}") def get_ticker(self, symbol: str) -> Dict[str, Any]: """ 获取美股实时报价 优先使用 Finnhub（更实时），降级使用 yfinance fast_info Returns: dict: { 'last': 当前价格, 'change': 涨跌额, 'changePercent': 涨跌幅, 'high': 最高价, 'low': 最低价, 'open': 开盘价, 'previousClose': 昨收价 } """ symbol = (symbol or '').strip().upper() # 优先使用 Finnhub（实时数据） if self.finnhub_client: try: quote = self.finnhub_client.quote(symbol) if quote and quote.get('c'): return { 'last': quote.get('c', 0), # 当前价格 'change': quote.get('d', 0), # 涨跌额 'changePercent': quote.get('dp', 0), # 涨跌幅 'high': quote.get('h', 0), # 日内最高 'low': quote.get('l', 0), # 日内最低 'open': quote.get('o', 0), # 开盘价 'previousClose': quote.get('pc', 0) # 昨收价 } except Exception as e: logger.warning(f"Finnhub quote failed for {symbol}: {e}") # 降级使用 yfinance try: ticker = yf.Ticker(symbol) # 尝试 fast_info（更快） try: fast_info = ticker.fast_info last_price = fast_info.get('lastPrice') or fast_info.get('last_price') prev_close = fast_info.get('previousClose') or fast_info.get('previous_close') or fast_info.get('regularMarketPreviousClose') if last_price: change = (last_price - prev_close) if prev_close else 0 change_pct = (change / prev_close * 100) if prev_close else 0 return { 'last': float(last_price), 'change': round(change, 4), 'changePercent': round(change_pct, 2), 'high': float(fast_info.get('dayHigh') or fast_info.get('day_high') or last_price), 'low': float(fast_info.get('dayLow') or fast_info.get('day_low') or last_price), 'open': float(fast_info.get('open') or fast_info.get('regularMarketOpen') or last_price), 'previousClose': float(prev_close) if prev_close else 0 } except Exception as e: logger.debug(f"yfinance fast_info failed for {symbol}: {e}") # 降级使用 info（较慢但数据更全） try: info = ticker.info last_price = info.get('regularMarketPrice') or info.get('currentPrice') prev_close = info.get('regularMarketPreviousClose') or info.get('previousClose') if last_price: change = (last_price - prev_close) if prev_close else 0 change_pct = (change / prev_close * 100) if prev_close else 0 return { 'last': float(last_price), 'change': round(change, 4), 'changePercent': round(change_pct, 2), 'high': float(info.get('regularMarketDayHigh') or info.get('dayHigh') or last_price), 'low': float(info.get('regularMarketDayLow') or info.get('dayLow') or last_price), 'open': float(info.get('regularMarketOpen') or info.get('open') or last_price), 'previousClose': float(prev_close) if prev_close else 0 } except Exception as e: logger.debug(f"yfinance info failed for {symbol}: {e}") # 最后降级：使用最近的 1 分钟 K 线 try: hist = ticker.history(period='1d', interval='1m') if hist is not None and not hist.empty: last_row = hist.iloc[-1] first_row = hist.iloc[0] last_price = float(last_row['Close']) open_price = float(first_row['Open']) return { 'last': last_price, 'change': round(last_price - open_price, 4), 'changePercent': round((last_price - open_price) / open_price * 100, 2) if open_price else 0, 'high': float(hist['High'].max()), 'low': float(hist['Low'].min()), 'open': open_price, 'previousClose': open_price # 近似 } except Exception as e: logger.debug(f"yfinance history fallback failed for {symbol}: {e}") except Exception as e: logger.error(f"Failed to get ticker for {symbol}: {e}") return {'last': 0, 'symbol': symbol} def get_kline( self, symbol: str, timeframe: str, limit: int, before_time: Optional[int] = None ) -> List[Dict[str, Any]]: """获取美股K线数据""" klines = [] try: interval = self.INTERVAL_MAP.get(timeframe, '1d') days_func = self.DAYS_MAP.get(timeframe, lambda x: x + 1) days = days_func(limit) # 计算日期范围 if before_time: end_date = datetime.fromtimestamp(before_time) start_date = end_date - timedelta(days=days) else: end_date = datetime.now() start_date = end_date - timedelta(days=days) # logger.info(f"使用 yfinance 获取 {symbol}, 周期: {interval}, 日期: {start_date.date()} ~ {end_date.date()}") # 尝试 yfinance df = self._fetch_yfinance(symbol, interval, start_date, end_date) if df is None or df.empty: # 尝试 finnhub if self.finnhub_client and timeframe == '1D': klines = self._fetch_finnhub(symbol, start_date, end_date, limit) if klines: return klines else: klines = self._convert_dataframe(df, limit) # 过滤和限制 klines = self.filter_and_limit(klines, limit, before_time) # 记录结果 self.log_result(symbol, klines, timeframe) except Exception as e: logger.error(f"Failed to fetch US stock K-lines {symbol}: {str(e)}") import traceback logger.error(traceback.format_exc()) return klines def _fetch_yfinance(self, symbol: str, interval: str, start_date: datetime, end_date: datetime): """使用 yfinance 获取数据""" try: ticker = yf.Ticker(symbol) # yfinance 的 end 参数是不包含的（exclusive），所以需要加一天才能包含 end_date 当天的数据 # 例如：end="2026-01-12" 实际只返回到 2026-01-11 的数据 end_date_inclusive = end_date + timedelta(days=1) df = ticker.history( start=start_date.strftime('%Y-%m-%d'), end=end_date_inclusive.strftime('%Y-%m-%d'), interval=interval ) # logger.info(f"yfinance 返回 {len(df) if df is not None and not df.empty else 0} 条数据") return df except Exception as e: logger.warning(f"yfinance fetch failed: {e}") return None def _fetch_finnhub( self, symbol: str, start_date: datetime, end_date: datetime, limit: int ) -> List[Dict[str, Any]]: """使用 finnhub 获取日线数据""" klines = [] try: start_ts = int(start_date.timestamp()) end_ts = int(end_date.timestamp()) # logger.info(f"使用 Finnhub 获取 {symbol} 日线数据") candles = self.finnhub_client.stock_candles(symbol, 'D', start_ts, end_ts) if candles and candles.get('s') == 'ok': for i in range(len(candles['t'])): klines.append(self.format_kline( timestamp=candles['t'][i], open_price=candles['o'][i], high=candles['h'][i], low=candles['l'][i], close=candles['c'][i], volume=candles['v'][i] )) # logger.info(f"Finnhub 返回 {len(klines)} 条数据") except Exception as e: logger.error(f"Finnhub fetch failed: {e}") return klines def _convert_dataframe(self, df, limit: int) -> List[Dict[str, Any]]: """转换 DataFrame 为K线列表""" klines = [] df = df.tail(limit).reset_index() # 确定时间列名（日线是 Date，分钟级是 Datetime） time_col = None if 'Datetime' in df.columns: time_col = 'Datetime' elif 'Date' in df.columns: time_col = 'Date' elif 'index' in df.columns: time_col = 'index' if time_col is None: logger.warning(f"Unable to determine time column; available columns: {df.columns.tolist()}") return klines for _, row in df.iterrows(): try: # 处理时间戳 time_value = row[time_col] if hasattr(time_value, 'timestamp'): ts = int(time_value.timestamp()) else: continue klines.append(self.format_kline( timestamp=ts, open_price=row['Open'], high=row['High'], low=row['Low'], close=row['Close'], volume=row['Volume'] )) except Exception as e: logger.debug(f"Failed to parse row data: {e}") continue return klines