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# -*- coding: utf-8 -*-
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"""
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===================================
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YfinanceFetcher - 兜底数据源 (Priority 4)
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===================================
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数据来源：Yahoo Finance（通过 yfinance 库）
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特点：国际数据源、可能有延迟或缺失
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定位：当所有国内数据源都失败时的最后保障
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关键策略：
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1. 自动将 A 股代码转换为 yfinance 格式（.SS / .SZ）
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2. 处理 Yahoo Finance 的数据格式差异
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3. 失败后指数退避重试
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"""
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import logging
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import re
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from datetime import datetime
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from typing import Optional, List, Dict, Any
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import pandas as pd
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from tenacity import (
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retry,
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stop_after_attempt,
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wait_exponential,
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retry_if_exception_type,
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before_sleep_log,
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)
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from .base import BaseFetcher, DataFetchError, STANDARD_COLUMNS
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from .realtime_types import UnifiedRealtimeQuote, RealtimeSource
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import os
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logger = logging.getLogger(__name__)
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class YfinanceFetcher(BaseFetcher):
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"""
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Yahoo Finance 数据源实现
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优先级：4（最低，作为兜底）
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数据来源：Yahoo Finance
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关键策略：
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- 自动转换股票代码格式
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- 处理时区和数据格式差异
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- 失败后指数退避重试
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注意事项：
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- A 股数据可能有延迟
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- 某些股票可能无数据
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- 数据精度可能与国内源略有差异
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"""
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name = "YfinanceFetcher"
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priority = int(os.getenv("YFINANCE_PRIORITY", "4"))
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def __init__(self):
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"""初始化 YfinanceFetcher"""
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pass
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def _convert_stock_code(self, stock_code: str) -> str:
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"""
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转换股票代码为 Yahoo Finance 格式
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Yahoo Finance 代码格式：
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- A股沪市：600519.SS (Shanghai Stock Exchange)
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- A股深市：000001.SZ (Shenzhen Stock Exchange)
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- 港股：0700.HK (Hong Kong Stock Exchange)
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- 美股：AAPL, TSLA, GOOGL (无需后缀)
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Args:
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stock_code: 原始代码，如 '600519', 'hk00700', 'AAPL'
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Returns:
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Yahoo Finance 格式代码
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Examples:
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>>> fetcher._convert_stock_code('600519')
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'600519.SS'
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>>> fetcher._convert_stock_code('hk00700')
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'0700.HK'
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>>> fetcher._convert_stock_code('AAPL')
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'AAPL'
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"""
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import re
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code = stock_code.strip().upper()
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# 美股：1-5个大写字母（可能包含 .），直接返回
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if re.match(r'^[A-Z]{1,5}(\.[A-Z])?$', code):
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logger.debug(f"识别为美股代码: {code}")
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return code
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# 港股：hk前缀 -> .HK后缀
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if code.startswith('HK'):
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hk_code = code[2:].lstrip('0') or '0' # 去除前导0，但保留至少一个0
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hk_code = hk_code.zfill(4) # 补齐到4位
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logger.debug(f"转换港股代码: {stock_code} -> {hk_code}.HK")
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return f"{hk_code}.HK"
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# 已经包含后缀的情况
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if '.SS' in code or '.SZ' in code or '.HK' in code:
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return code
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# 去除可能的 .SH 后缀
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code = code.replace('.SH', '')
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# ETF: Shanghai ETF (51xx, 52xx, 56xx, 58xx) -> .SS; Shenzhen ETF (15xx, 16xx, 18xx) -> .SZ
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if len(code) == 6:
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if code.startswith(('51', '52', '56', '58')):
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return f"{code}.SS"
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if code.startswith(('15', '16', '18')):
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return f"{code}.SZ"
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# A股：根据代码前缀判断市场
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if code.startswith(('600', '601', '603', '688')):
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return f"{code}.SS"
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elif code.startswith(('000', '002', '300')):
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return f"{code}.SZ"
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else:
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logger.warning(f"无法确定股票 {code} 的市场，默认使用深市")
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return f"{code}.SZ"
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@retry(
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stop=stop_after_attempt(3),
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wait=wait_exponential(multiplier=1, min=2, max=30),
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retry=retry_if_exception_type((ConnectionError, TimeoutError)),
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before_sleep=before_sleep_log(logger, logging.WARNING),
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)
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def _fetch_raw_data(self, stock_code: str, start_date: str, end_date: str) -> pd.DataFrame:
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"""
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从 Yahoo Finance 获取原始数据
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使用 yfinance.download() 获取历史数据
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流程：
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1. 转换股票代码格式
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2. 调用 yfinance API
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3. 处理返回数据
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"""
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import yfinance as yf
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# 转换代码格式
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yf_code = self._convert_stock_code(stock_code)
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logger.debug(f"调用 yfinance.download({yf_code}, {start_date}, {end_date})")
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try:
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# 使用 yfinance 下载数据
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df = yf.download(
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tickers=yf_code,
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start=start_date,
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end=end_date,
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progress=False, # 禁止进度条
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auto_adjust=True, # 自动调整价格（复权）
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)
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if df.empty:
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raise DataFetchError(f"Yahoo Finance 未查询到 {stock_code} 的数据")
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return df
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except Exception as e:
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if isinstance(e, DataFetchError):
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raise
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raise DataFetchError(f"Yahoo Finance 获取数据失败: {e}") from e
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def _normalize_data(self, df: pd.DataFrame, stock_code: str) -> pd.DataFrame:
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"""
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标准化 Yahoo Finance 数据
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yfinance 返回的列名：
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Open, High, Low, Close, Volume（索引是日期）
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注意：新版 yfinance 返回 MultiIndex 列名，如 ('Close', 'AMD')
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需要先扁平化列名再进行处理
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需要映射到标准列名：
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date, open, high, low, close, volume, amount, pct_chg
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"""
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df = df.copy()
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# 处理 MultiIndex 列名（新版 yfinance 返回格式）
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# 例如: ('Close', 'AMD') -> 'Close'
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if isinstance(df.columns, pd.MultiIndex):
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logger.debug(f"检测到 MultiIndex 列名，进行扁平化处理")
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# 取第一级列名（Price level: Close, High, Low, etc.）
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df.columns = df.columns.get_level_values(0)
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# 重置索引，将日期从索引变为列
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df = df.reset_index()
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# 列名映射（yfinance 使用首字母大写）
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column_mapping = {
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'Date': 'date',
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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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df = df.rename(columns=column_mapping)
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# 计算涨跌幅（因为 yfinance 不直接提供）
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if 'close' in df.columns:
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df['pct_chg'] = df['close'].pct_change() * 100
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df['pct_chg'] = df['pct_chg'].fillna(0).round(2)
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# 计算成交额（yfinance 不提供，使用估算值）
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# 成交额 ≈ 成交量 * 平均价格
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if 'volume' in df.columns and 'close' in df.columns:
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df['amount'] = df['volume'] * df['close']
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else:
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df['amount'] = 0
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# 添加股票代码列
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df['code'] = stock_code
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# 只保留需要的列
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keep_cols = ['code'] + STANDARD_COLUMNS
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existing_cols = [col for col in keep_cols if col in df.columns]
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df = df[existing_cols]
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return df
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def get_main_indices(self) -> Optional[List[Dict[str, Any]]]:
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"""
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获取主要指数行情 (Yahoo Finance)
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"""
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import yfinance as yf
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# 映射关系：akshare代码 -> (yfinance代码, 名称)
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yf_mapping = {
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'sh000001': ('000001.SS', '上证指数'),
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'sz399001': ('399001.SZ', '深证成指'),
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'sz399006': ('399006.SZ', '创业板指'),
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'sh000688': ('000688.SS', '科创50'),
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'sh000016': ('000016.SS', '上证50'),
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'sh000300': ('000300.SS', '沪深300'),
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}
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results = []
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try:
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for ak_code, (yf_code, name) in yf_mapping.items():
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try:
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ticker = yf.Ticker(yf_code)
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# 获取最近2天数据以计算涨跌
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hist = ticker.history(period='2d')
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if hist.empty:
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continue
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today = hist.iloc[-1]
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prev = hist.iloc[-2] if len(hist) > 1 else today
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price = float(today['Close'])
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prev_close = float(prev['Close'])
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change = price - prev_close
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change_pct = (change / prev_close) * 100 if prev_close else 0
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# 振幅
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high = float(today['High'])
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low = float(today['Low'])
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amplitude = ((high - low) / prev_close * 100) if prev_close else 0
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results.append({
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'code': ak_code,
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'name': name,
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'current': price,
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'change': change,
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'change_pct': change_pct,
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'open': float(today['Open']),
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'high': high,
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'low': low,
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'prev_close': prev_close,
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'volume': float(today['Volume']),
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'amount': 0.0, # Yahoo Finance 可能不提供准确的成交额
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'amplitude': amplitude
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})
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logger.debug(f"[Yfinance] 获取指数 {name} 成功")
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except Exception as e:
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logger.warning(f"[Yfinance] 获取指数 {name} 失败: {e}")
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continue
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if results:
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logger.info(f"[Yfinance] 成功获取 {len(results)} 个指数行情")
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return results
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except Exception as e:
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logger.error(f"[Yfinance] 获取指数行情失败: {e}")
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return None
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def _is_us_stock(self, stock_code: str) -> bool:
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"""
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判断代码是否为美股
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美股代码规则：
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- 1-5个大写字母，如 'AAPL', 'TSLA'
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- 可能包含 '.'，如 'BRK.B'
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"""
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code = stock_code.strip().upper()
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return bool(re.match(r'^[A-Z]{1,5}(\.[A-Z])?$', code))
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def get_realtime_quote(self, stock_code: str) -> Optional[UnifiedRealtimeQuote]:
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"""
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获取美股实时行情数据
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数据来源：yfinance Ticker.info
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Args:
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stock_code: 美股代码，如 'AMD', 'AAPL', 'TSLA'
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Returns:
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UnifiedRealtimeQuote 对象，获取失败返回 None
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"""
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import yfinance as yf
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# 仅处理美股
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if not self._is_us_stock(stock_code):
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logger.debug(f"[Yfinance] {stock_code} 不是美股，跳过")
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return None
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try:
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symbol = stock_code.strip().upper()
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logger.debug(f"[Yfinance] 获取美股 {symbol} 实时行情")
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ticker = yf.Ticker(symbol)
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# 尝试获取 fast_info（更快，但字段较少）
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try:
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info = ticker.fast_info
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if info is None:
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raise ValueError("fast_info is None")
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price = getattr(info, 'lastPrice', None) or getattr(info, 'last_price', None)
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prev_close = getattr(info, 'previousClose', None) or getattr(info, 'previous_close', None)
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open_price = getattr(info, 'open', None)
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high = getattr(info, 'dayHigh', None) or getattr(info, 'day_high', None)
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low = getattr(info, 'dayLow', None) or getattr(info, 'day_low', None)
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volume = getattr(info, 'lastVolume', None) or getattr(info, 'last_volume', None)
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market_cap = getattr(info, 'marketCap', None) or getattr(info, 'market_cap', None)
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except Exception:
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# 回退到 history 方法获取最新数据
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logger.debug(f"[Yfinance] fast_info 失败，尝试 history 方法")
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hist = ticker.history(period='2d')
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if hist.empty:
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logger.warning(f"[Yfinance] 无法获取 {symbol} 的数据")
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return None
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today = hist.iloc[-1]
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prev = hist.iloc[-2] if len(hist) > 1 else today
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price = float(today['Close'])
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prev_close = float(prev['Close'])
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open_price = float(today['Open'])
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high = float(today['High'])
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low = float(today['Low'])
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volume = int(today['Volume'])
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market_cap = None
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# 计算涨跌幅
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change_amount = None
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change_pct = None
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if price is not None and prev_close is not None and prev_close > 0:
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change_amount = price - prev_close
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change_pct = (change_amount / prev_close) * 100
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# 计算振幅
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amplitude = None
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if high is not None and low is not None and prev_close is not None and prev_close > 0:
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amplitude = ((high - low) / prev_close) * 100
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# 获取股票名称
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try:
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name = ticker.info.get('shortName', '') or ticker.info.get('longName', '') or symbol
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except Exception:
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name = symbol
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quote = UnifiedRealtimeQuote(
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code=symbol,
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name=name,
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source=RealtimeSource.FALLBACK,
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price=price,
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change_pct=round(change_pct, 2) if change_pct is not None else None,
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change_amount=round(change_amount, 4) if change_amount is not None else None,
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volume=volume,
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amount=None, # yfinance 不直接提供成交额
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volume_ratio=None,
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turnover_rate=None,
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amplitude=round(amplitude, 2) if amplitude is not None else None,
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open_price=open_price,
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high=high,
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low=low,
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pre_close=prev_close,
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pe_ratio=None,
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pb_ratio=None,
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total_mv=market_cap,
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circ_mv=None,
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)
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logger.info(f"[Yfinance] 获取美股 {symbol} 实时行情成功: 价格={price}")
|
|
|
return quote
|
|
|
|
|
|
except Exception as e:
|
|
|
logger.warning(f"[Yfinance] 获取美股 {stock_code} 实时行情失败: {e}")
|
|
|
return None
|
|
|
|
|
|
|
|
|
if __name__ == "__main__":
|
|
|
# 测试代码
|
|
|
logging.basicConfig(level=logging.DEBUG)
|
|
|
|
|
|
fetcher = YfinanceFetcher()
|
|
|
|
|
|
try:
|
|
|
df = fetcher.get_daily_data('600519') # 茅台
|
|
|
print(f"获取成功，共 {len(df)} 条数据")
|
|
|
print(df.tail())
|
|
|
except Exception as e:
|
|
|
print(f"获取失败: {e}")
|
