"""AKShare数据源适配器 - 使用新浪接口""" import asyncio import time from datetime import datetime from typing import List, Optional, Dict, Any import akshare as ak import pandas as pd from app.adapters.base import ( DataSourceAdapter, TickData, KLineData, SymbolInfo, TradeCalData, TickCallback ) from app.core.logger import info, error, warning # 缓存字典，用于存储股票基本信息和交易日历 _stock_info_cache: Dict[str, Dict[str, Any]] = {} _trade_calendar_cache: Optional[pd.DataFrame] = None _inst_holding_cache: Dict[str, Dict[str, Any]] = {} class AKShareAdapter(DataSourceAdapter): """AKShare数据源适配器 - 使用新浪接口""" def __init__(self): self.config = {} self._connected = False self._max_retries = 3 self._retry_delay = 2 # 秒 # 实例缓存 self._stock_info_cache: Dict[str, Dict[str, Any]] = {} self._trade_calendar_cache: Optional[pd.DataFrame] = None self._inst_holding_cache: Dict[str, Dict[str, Any]] = {} def _get_stock_code_from_symbol(self, symbol: str) -> str: """从 symbol 中提取股票代码: 000001.SZ -> 000001""" if "." in symbol: return symbol.split(".")[0] return symbol async def _get_trade_calendar(self) -> pd.DataFrame: """获取交易日历（带缓存）""" if self._trade_calendar_cache is None: try: df = await self._fetch_with_retry(ak.tool_trade_date_hist_sina) if df is not None and not df.empty: df['trade_date'] = pd.to_datetime(df['trade_date']) self._trade_calendar_cache = df info(f"Loaded trade calendar with {len(df)} trading days") except Exception as e: error(f"Failed to load trade calendar: {e}") return pd.DataFrame() return self._trade_calendar_cache if self._trade_calendar_cache is not None else pd.DataFrame() async def _get_stock_info(self, stock_code: str) -> Dict[str, Any]: """获取股票基本信息（带缓存）""" if stock_code not in self._stock_info_cache: try: # 使用东财接口获取个股信息 info_df = await self._fetch_with_retry(ak.stock_individual_info_em, symbol=stock_code) if info_df is not None and not info_df.empty: info_dict = dict(zip(info_df['item'], info_df['value'])) self._stock_info_cache[stock_code] = info_dict info(f"Loaded stock info for {stock_code}") except Exception as e: error(f"Failed to get stock info for {stock_code}: {e}") return {} return self._stock_info_cache.get(stock_code, {}) async def _get_trading_days_count(self, stock_code: str, trade_date: datetime) -> int: """获取可交易日数（从上市至今）""" try: stock_info = await self._get_stock_info(stock_code) listing_date_str = str(stock_info.get('上市时间', '')) if not listing_date_str or listing_date_str == 'nan': return 0 listing_date = datetime.strptime(listing_date_str, '%Y%m%d').date() trade_calendar = await self._get_trade_calendar() if trade_calendar.empty: return 0 # 计算从上市到指定日期的交易日数 trade_calendar['trade_date'] = pd.to_datetime(trade_calendar['trade_date']).dt.date trading_days = trade_calendar[ (trade_calendar['trade_date'] >= listing_date) & (trade_calendar['trade_date'] <= trade_date.date()) ] return len(trading_days) except Exception as e: error(f"Failed to calculate trading days for {stock_code}: {e}") return 0 async def _check_limit_up_down(self, stock_code: str, trade_date: str, close_price: float) -> tuple: """检查是否涨停或跌停""" try: # 获取涨停/跌停股票池 zt_df = await self._fetch_with_retry(ak.stock_zt_pool_em, date=trade_date) dt_df = await self._fetch_with_retry(ak.stock_zt_pool_dtgc_em, date=trade_date) is_limit_up = False is_limit_down = False if zt_df is not None and not zt_df.empty: zt_list = zt_df['代码'].astype(str).tolist() is_limit_up = stock_code in zt_list if dt_df is not None and not dt_df.empty: dt_list = dt_df['代码'].astype(str).tolist() is_limit_down = stock_code in dt_list return is_limit_up, is_limit_down except Exception as e: # 涨停跌停池接口可能不支持历史日期，失败时返回False info(f"Could not get limit up/down info for {stock_code} on {trade_date}: {e}") return False, False async def _get_market_cap(self, stock_code: str) -> tuple: """获取总市值和流通市值""" try: stock_info = await self._get_stock_info(stock_code) total_cap = stock_info.get('总市值', 0) float_cap = stock_info.get('流通市值', 0) # 转换为浮点数 total_cap = float(total_cap) if total_cap and str(total_cap) != 'nan' else 0.0 float_cap = float(float_cap) if float_cap and str(float_cap) != 'nan' else 0.0 return total_cap, float_cap except Exception as e: error(f"Failed to get market cap for {stock_code}: {e}") return 0.0, 0.0 async def _get_inst_holding_ratio(self, stock_code: str) -> float: """获取机构持仓占比""" # 缓存键使用季度标识（简化处理，实际应按财报季度） cache_key = f"{stock_code}_latest" if cache_key not in self._inst_holding_cache: try: # 获取基金持仓数据 fund_holder_df = await self._fetch_with_retry(ak.stock_fund_stock_holder, symbol=stock_code) if fund_holder_df is not None and not fund_holder_df.empty: # 获取最新季度的数据 latest_quarter = fund_holder_df['季度'].iloc[0] latest_df = fund_holder_df[fund_holder_df['季度'] == latest_quarter] # 计算机构持仓占比合计 total_ratio = 0.0 if '占总股本比例' in latest_df.columns: ratios = pd.to_numeric(latest_df['占总股本比例'], errors='coerce').fillna(0) total_ratio = ratios.sum() self._inst_holding_cache[cache_key] = { 'quarter': latest_quarter, 'ratio': total_ratio } info(f"Loaded inst holding for {stock_code}: {total_ratio:.4f}% in {latest_quarter}") else: self._inst_holding_cache[cache_key] = {'quarter': '', 'ratio': 0.0} except Exception as e: error(f"Failed to get inst holding for {stock_code}: {e}") return 0.0 return self._inst_holding_cache.get(cache_key, {}).get('ratio', 0.0) async def connect(self, config: dict) -> None: """建立连接（AKShare无需认证）""" self.config = config self._connected = True info("AKShare adapter connected (Sina API)") async def subscribe_ticks(self, symbols: List[str], callback: TickCallback) -> None: """订阅实时Tick（AKShare不支持实时推送）""" raise NotImplementedError("AKShare does not support real-time tick subscription") async def fetch_klines( self, symbol: str, start: str, end: str, freq: str ) -> List[KLineData]: info(f"Fetching KLines from Sina for {symbol} [{freq}] from {start} to {end}") """拉取历史K线""" # 判断是股票还是期货 if ".SH" in symbol or ".SZ" in symbol or ".BJ" in symbol: return await self._fetch_stock_klines(symbol, start, end, freq) elif "." in symbol: # 期货格式: CU2504.SHFE return await self._fetch_futures_klines(symbol, start, end, freq) else: raise ValueError(f"Unknown symbol format: {symbol}") async def _fetch_stock_klines( self, symbol: str, start: str, end: str, freq: str ) -> List[KLineData]: """获取股票K线 - 使用新浪接口""" # 转换symbol格式: 000001.SZ -> sz000001 ts_code = self._normalize_stock_symbol(symbol) if freq in ["1d", "day", "D", ""]: return await self._fetch_stock_daily_sina(ts_code, symbol, start, end) elif freq in ["1m", "5m", "15m", "30m", "60m"]: return await self._fetch_stock_minute_sina(ts_code, symbol, start, end, freq) else: raise ValueError(f"Unsupported frequency: {freq}") def _normalize_stock_symbol(self, symbol: str) -> str: """转换股票代码格式: 000001.SZ -> sz000001""" if "." in symbol: code, exchange = symbol.split(".") exchange_map = { "SH": "sh", "SZ": "sz", "BJ": "bj" } return exchange_map.get(exchange, "sz") + code return symbol def _denormalize_stock_symbol(self, symbol: str) -> str: """还原股票代码格式: sz000001 -> 000001.SZ""" if symbol.startswith("sh"): return symbol[2:] + ".SH" elif symbol.startswith("sz"): return symbol[2:] + ".SZ" elif symbol.startswith("bj"): return symbol[2:] + ".BJ" return symbol async def _fetch_with_retry(self, func, *args, **kwargs): """带重试机制的调用""" last_exception = None for attempt in range(self._max_retries): try: loop = asyncio.get_event_loop() return await loop.run_in_executor(None, lambda: func(*args, **kwargs)) except Exception as e: last_exception = e error_msg = str(e).lower() # 检查是否是可重试的错误 if any(x in error_msg for x in ['connection', 'timeout', 'remote', 'reset', 'closed']): if attempt < self._max_retries - 1: warning(f"Sina API request failed (attempt {attempt + 1}/{self._max_retries}): {e}") await asyncio.sleep(self._retry_delay * (attempt + 1)) # 指数退避 continue # 不可重试的错误，直接抛出 raise raise last_exception async def _fetch_stock_daily_sina( self, ts_code: str, original_symbol: str, start_date: str, end_date: str ) -> List[KLineData]: """获取股票日线 - 使用新浪接口（包含扩展字段）""" try: # 新浪接口获取历史数据 # 使用 stock_zh_a_daily 接口（新浪） df = await self._fetch_with_retry( ak.stock_zh_a_daily, symbol=ts_code, start_date=start_date, end_date=end_date, adjust="qfq" # 前复权 ) if df is None or df.empty: warning(f"No data returned from Sina for {original_symbol}") return [] # 获取股票代码（不带交易所后缀） stock_code = self._get_stock_code_from_symbol(original_symbol) # 预获取市值和机构持仓数据（这些不随日期变化） total_cap, float_cap = await self._get_market_cap(stock_code) inst_ratio = await self._get_inst_holding_ratio(stock_code) results = [] for _, row in df.iterrows(): trade_date = datetime.strptime(str(row['date']), "%Y-%m-%d") trade_date_str = trade_date.strftime("%Y%m%d") close_price = float(row['close']) # 获取可交易日数（只计算一次，以当前日期为准） trading_days = await self._get_trading_days_count(stock_code, trade_date) # 检查涨停跌停（注意：历史数据可能无法准确判断） is_limit_up, is_limit_down = await self._check_limit_up_down( stock_code, trade_date_str, close_price ) results.append(KLineData( symbol=original_symbol, time=int(trade_date.timestamp()), open=float(row['open']), high=float(row['high']), low=float(row['low']), close=close_price, volume=int(row['volume']), amount=float(row.get('amount', 0)), trade_date=trade_date.strftime('%Y-%m-%d'), is_limit_up=is_limit_up, is_limit_down=is_limit_down, total_market_cap=total_cap, float_market_cap=float_cap, inst_holding_ratio=inst_ratio, trading_days=trading_days )) info(f"Fetched {len(results)} daily klines with extended fields from Sina for {original_symbol}") return results except Exception as e: error(f"Failed to fetch stock daily from Sina for {original_symbol}: {e}") # 新浪接口失败时返回空列表 return [] async def _fetch_stock_minute_sina( self, ts_code: str, original_symbol: str, start_date: str, end_date: str, freq: str ) -> List[KLineData]: """获取股票分钟线 - 使用新浪接口""" try: # 新浪分钟线接口 # 使用 stock_zh_a_minute 接口 df = await self._fetch_with_retry( ak.stock_zh_a_minute, symbol=ts_code, period=freq.replace("m", ""), # 1m -> 1 adjust="qfq" ) if df is None or df.empty: return [] # 过滤日期范围 df['date'] = pd.to_datetime(df['date']) start_dt = datetime.strptime(start_date, "%Y%m%d") end_dt = datetime.strptime(end_date, "%Y%m%d") df = df[(df['date'] >= start_dt) & (df['date'] <= end_dt)] results = [] for _, row in df.iterrows(): trade_time = datetime.strptime(str(row['date']), "%Y-%m-%d %H:%M:%S") results.append(KLineData( symbol=original_symbol, time=int(trade_time.timestamp()), open=float(row['open']), high=float(row['high']), low=float(row['low']), close=float(row['close']), volume=int(row['volume']), amount=float(row.get('amount', 0)) )) return results except Exception as e: error(f"Failed to fetch stock minute from Sina for {original_symbol}: {e}") return [] async def _fetch_futures_klines( self, symbol: str, start: str, end: str, freq: str ) -> List[KLineData]: """获取期货K线 - 使用新浪接口""" if freq in ["1d", "day", "D", ""]: return await self._fetch_futures_daily_sina(symbol, start, end) elif freq in ["1m", "5m", "15m", "30m", "60m"]: return await self._fetch_futures_minute_sina(symbol, start, end, freq) else: raise ValueError(f"Unsupported frequency: {freq}") async def _fetch_futures_daily_sina( self, symbol: str, start_date: str, end_date: str ) -> List[KLineData]: """获取期货日线 - 使用新浪接口""" try: # 解析合约代码: CU2504.SHFE -> cu2504 contract_code, exchange = symbol.split(".") contract_code = contract_code.lower() # 新浪期货历史行情接口 df = await self._fetch_with_retry( ak.futures_zh_daily, symbol=contract_code, start_date=start_date, end_date=end_date ) if df is None or df.empty: return [] results = [] for _, row in df.iterrows(): trade_date = datetime.strptime(str(row['date']), "%Y-%m-%d") results.append(KLineData( symbol=symbol, time=int(trade_date.timestamp()), open=float(row['open']), high=float(row['high']), low=float(row['low']), close=float(row['close']), volume=int(row['volume']), amount=float(row.get('amount', 0)), open_interest=int(row.get('hold', 0)) )) return results except Exception as e: error(f"Failed to fetch futures daily from Sina for {symbol}: {e}") return [] async def _fetch_futures_minute_sina( self, symbol: str, start_date: str, end_date: str, freq: str ) -> List[KLineData]: """获取期货分钟线 - 使用新浪接口""" try: # 解析合约代码 contract_code, exchange = symbol.split(".") contract_code = contract_code.lower() # 新浪期货分钟线接口 df = await self._fetch_with_retry( ak.futures_zh_minute_sina, symbol=contract_code, period=freq.replace("m", "") ) if df is None or df.empty: return [] # 过滤日期范围 df['datetime'] = pd.to_datetime(df['datetime']) start_dt = datetime.strptime(start_date, "%Y%m%d") end_dt = datetime.strptime(end_date, "%Y%m%d") df = df[(df['datetime'] >= start_dt) & (df['datetime'] <= end_dt)] results = [] for _, row in df.iterrows(): trade_time = row['datetime'] results.append(KLineData( symbol=symbol, time=int(trade_time.timestamp()), open=float(row['open']), high=float(row['high']), low=float(row['low']), close=float(row['close']), volume=int(row['volume']), amount=0, open_interest=0 )) return results except Exception as e: error(f"Failed to fetch futures minute from Sina for {symbol}: {e}") return [] async def fetch_symbols(self, asset_type: str) -> List[SymbolInfo]: """获取标的列表""" if asset_type == "stock": return await self._fetch_stock_symbols_sina() elif asset_type == "futures": return await self._fetch_futures_symbols_sina() else: raise ValueError(f"Unsupported asset type: {asset_type}") async def _fetch_stock_symbols_sina(self) -> List[SymbolInfo]: """获取A股股票列表 - 使用新浪接口""" try: # 新浪A股列表接口 df = await self._fetch_with_retry(ak.stock_zh_a_spot) if df is None or df.empty: return [] results = [] for _, row in df.iterrows(): # 新浪接口的代码格式 code = str(row['代码']) if code.startswith('6') or code.startswith('5') or code.startswith('9'): ts_code = f"{code}.SH" exchange = "SH" elif code.startswith('8') or code.startswith('4'): ts_code = f"{code}.BJ" exchange = "BJ" else: ts_code = f"{code}.SZ" exchange = "SZ" results.append(SymbolInfo( symbol_id=ts_code, name=str(row['名称']), exchange=exchange )) info(f"Fetched {len(results)} stock symbols from Sina") return results except Exception as e: error(f"Failed to fetch stock symbols from Sina: {e}") return [] async def _fetch_futures_symbols_sina(self) -> List[SymbolInfo]: """获取期货合约列表 - 使用新浪接口""" try: # 新浪期货列表接口 df = await self._fetch_with_retry(ak.futures_zh_realtime, subscribe_list=["0", "1", "2", "3"]) if df is None or df.empty: return [] results = [] for _, row in df.iterrows(): symbol = str(row['symbol']) underlying = ''.join([c for c in symbol if c.isalpha()]).upper() contract_month = ''.join([c for c in symbol if c.isdigit()]) exchange = self._get_futures_exchange(underlying) ts_code = f"{symbol.upper()}.{exchange}" results.append(SymbolInfo( symbol_id=ts_code, name=str(row.get('name', symbol)), exchange=exchange, underlying=underlying, contract_month=contract_month )) info(f"Fetched {len(results)} futures symbols from Sina") return results except Exception as e: error(f"Failed to fetch futures symbols from Sina: {e}") return [] def _get_futures_exchange(self, underlying: str) -> str: """根据品种代码判断交易所""" # 上海期货交易所 if underlying in ['CU', 'AL', 'ZN', 'PB', 'NI', 'SN', 'AU', 'AG', 'RB', 'HC', 'BU', 'RU', 'FU', 'SP', 'WR', 'SS', 'LU', 'NR']: return 'SHFE' # 大连商品交易所 elif underlying in ['A', 'B', 'M', 'Y', 'P', 'C', 'CS', 'JD', 'LH', 'JM', 'J', 'I', 'FB', 'BB', 'RR', 'PG', 'EB', 'EG', 'V', 'PP', 'L']: return 'DCE' # 郑州商品交易所 elif underlying in ['WH', 'PM', 'CF', 'SR', 'TA', 'OI', 'RI', 'MA', 'FG', 'RS', 'RM', 'JR', 'LR', 'SM', 'SF', 'CY', 'AP', 'CJ', 'UR', 'SA', 'PF', 'PK']: return 'CZCE' # 中国金融期货交易所 elif underlying in ['IF', 'IC', 'IH', 'T', 'TF', 'TS', 'IM']: return 'CFFEX' # 上海国际能源交易中心 elif underlying in ['SC', 'BC', 'EC']: return 'INE' else: return 'SHFE' # 默认上海 async def fetch_trading_calendar( self, exchange: str, start: str, end: str ) -> List[TradeCalData]: """获取交易日历 - 使用新浪接口""" try: # 新浪交易日历接口 df = await self._fetch_with_retry(ak.tool_trade_date_hist_sina) if df is None or df.empty: return [] # 过滤日期范围 df['trade_date'] = pd.to_datetime(df['trade_date']) start_dt = datetime.strptime(start, "%Y%m%d") end_dt = datetime.strptime(end, "%Y%m%d") df = df[(df['trade_date'] >= start_dt) & (df['trade_date'] <= end_dt)] results = [] for _, row in df.iterrows(): cal_date = row['trade_date'] results.append(TradeCalData( date=cal_date, is_trading_day=True )) return results except Exception as e: error(f"Failed to fetch trading calendar from Sina: {e}") return [] async def health_check(self) -> bool: """健康检查""" try: if not self._connected: return False # 尝试获取股票列表作为健康检查 df = await self._fetch_with_retry(ak.stock_zh_a_spot) return df is not None and not df.empty except Exception as e: error(f"Health check failed: {e}") return False async def close(self) -> None: """关闭连接""" self._connected = False info("AKShare adapter closed (Sina API)")