249 lines
10 KiB
Python
249 lines
10 KiB
Python
"""
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行情数据管理模块 - 支持多数据源(Tushare/AKShare)
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"""
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import pandas as pd
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import tushare as ts
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import akshare as ak
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from typing import List, Dict, Optional # 添加 Optional 导入
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import logging
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import time
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from enum import Enum, auto
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import threading
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# 添加 Tushare Token 设置
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ts.set_token('9343e641869058684afeadfcfe7fd6684160852e52e85332a7734c8d')
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# 通用股票排除规则
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STOCK_EXCLUSION_RULES = {
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'exclude_st': True, # 排除ST/*ST股票
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'exclude_b_share': True, # 排除B股
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'exclude_star_market': True, # 排除科创板(688开头)
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'exclude_gem': False, # 排除创业板(300开头) - 默认不排除
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'exclude_bj': True, # 排除北交所股票
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'custom_exclusions': [] # 自定义排除列表
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}
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class DataSource(Enum):
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TUSHARE = "tushare"
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AKSHARE = "akshare"
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LOCAL = "local"
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class QuoteManager:
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_instance = None
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_lock = threading.Lock()
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def __new__(cls):
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with cls._lock:
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if cls._instance is None:
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cls._instance = super().__new__(cls)
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cls._instance._init_manager()
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return cls._instance
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def _init_manager(self):
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self._cache = {}
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self._cache_ttl = 60
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self._data_source = DataSource.TUSHARE
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self.max_retries = 3 # 默认最大重试次数
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self.retry_interval = 2 # 默认重试间隔(秒)
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def set_retry_policy(self, max_retries: int, retry_interval: float = 2):
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"""设置重试策略"""
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self.max_retries = max_retries
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self.retry_interval = retry_interval
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def set_data_source(self, source: DataSource):
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"""设置数据源"""
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self._data_source = source
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def get_realtime_quotes(self, codes: List[str]) -> Dict[str, pd.DataFrame]:
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"""获取实时行情(带重试机制)"""
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last_error = None
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for attempt in range(self.max_retries):
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try:
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if self._data_source == DataSource.TUSHARE:
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return self._get_tushare_quotes(codes)
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elif self._data_source == DataSource.AKSHARE:
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return self._get_akshare_quotes(codes)
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else:
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raise ValueError("不支持的数据源")
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except Exception as e:
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last_error = e
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if attempt < self.max_retries - 1: # 不是最后一次尝试
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time.sleep(self.retry_interval)
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continue
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raise Exception(f"获取行情失败(尝试{self.max_retries}次): {str(last_error)}")
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def _get_tushare_quotes(self, codes: List[str], max_retries: int = 3, retry_interval: float = 2) -> Dict[str, pd.DataFrame]:
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"""使用 Tushare 获取实时行情(带重试机制)"""
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for attempt in range(max_retries):
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try:
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df = ts.realtime_quote(ts_code=','.join(codes))
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if df is None or df.empty:
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raise Exception("返回数据为空")
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return {row['TS_CODE']: row for _, row in df.iterrows()}
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except Exception as e:
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if attempt < max_retries - 1:
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time.sleep(retry_interval)
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continue
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raise Exception(f"Tushare 行情获取失败(尝试{max_retries}次): {str(e)}")
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def _get_akshare_quotes(self, codes: List[str]) -> Dict[str, pd.DataFrame]:
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"""使用 AKShare 获取实时行情"""
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# 这里需要实现 AKShare 的获取逻辑
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raise NotImplementedError("AKShare 实现待完成")
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def _convert_akshare_format(self, row) -> Dict:
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"""将AKShare数据格式转换为统一格式"""
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return {
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'TS_CODE': row['代码'],
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'PRICE': row['最新价'],
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'OPEN': row['今开'],
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'PRE_CLOSE': row['昨收'],
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'HIGH': row['最高'],
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'LOW': row['最低'],
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'VOLUME': row['成交量']
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}
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# ... existing code ...
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def _get_tushare_all_stocks(self) -> List[str]:
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"""使用Tushare获取所有A股股票列表"""
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try:
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pro = ts.pro_api() # 获取Tushare专业版API接口
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# 获取所有股票列表
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stock_basic = pro.stock_basic(exchange='', list_status='L',
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fields='ts_code,symbol,name,area,industry,list_date')
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# 根据通用规则过滤股票
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filtered_stocks = self._filter_stocks(stock_basic['ts_code'].tolist())
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return filtered_stocks
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except Exception as e:
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logging.error(f"获取股票列表失败: {str(e)}")
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return []
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def _filter_stocks(self, stock_list: List[str]) -> List[str]:
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"""
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根据通用规则过滤股票列表
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:param stock_list: 原始股票列表
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:return: 过滤后的股票列表
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"""
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filtered_stocks = []
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for stock in stock_list:
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exclude = False
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# 检查是否在自定义排除列表中
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if stock in STOCK_EXCLUSION_RULES.get('custom_exclusions', []):
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exclude = True
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# 检查是否排除ST/*ST股票
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if STOCK_EXCLUSION_RULES.get('exclude_st', True):
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# 注意：这里需要获取股票名称来判断是否为ST股票
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# 在实际应用中，您可能需要通过其他方式获取股票名称
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pass # ST股票的判断需要额外的数据支持
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# 检查是否排除B股
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if STOCK_EXCLUSION_RULES.get('exclude_b_share', True) and stock.endswith('.BJ'):
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exclude = True
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# 检查是否排除科创板股票(688开头)
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if STOCK_EXCLUSION_RULES.get('exclude_star_market', True) and stock.startswith('688'):
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exclude = True
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# 检查是否排除创业板股票(300开头)
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if STOCK_EXCLUSION_RULES.get('exclude_gem', False) and stock.startswith('300'):
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exclude = True
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# 检查是否排除北交所股票
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if STOCK_EXCLUSION_RULES.get('exclude_bj', True) and stock.endswith('.BJ'):
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exclude = True
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# 如果没有被排除，则添加到结果列表中
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if not exclude:
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filtered_stocks.append(stock)
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return filtered_stocks
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def set_exclusion_rules(self, rules: Dict):
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"""
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设置股票排除规则
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:param rules: 排除规则字典
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"""
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global STOCK_EXCLUSION_RULES
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STOCK_EXCLUSION_RULES.update(rules)
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def get_exclusion_rules(self) -> Dict:
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"""
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获取当前的股票排除规则
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:return: 排除规则字典
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"""
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global STOCK_EXCLUSION_RULES
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return STOCK_EXCLUSION_RULES.copy()
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def get_quote(self, code: str) -> Optional[Dict]:
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"""获取单个股票行情(兼容旧接口)"""
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try:
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quotes = self.get_realtime_quotes([code])
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if not quotes or code not in quotes:
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return None
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row = quotes[code]
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return {
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'price': row['PRICE'],
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'avg_price': (row['OPEN'] + row['PRE_CLOSE']) / 2,
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'volume': row['VOLUME']
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}
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except Exception as e:
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logging.error(f"获取股票{code}行情失败: {str(e)}")
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return None
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def get_daily_data(self, codes: List[str], start_date: str = None, end_date: str = None,
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max_retries: Optional[int] = None, retry_interval: Optional[float] = None) -> Dict[
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str, pd.DataFrame]:
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"""获取股票日线数据"""
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# 如果没有传入参数，则使用实例的默认值
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max_retries = max_retries if max_retries is not None else self.max_retries
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retry_interval = retry_interval if retry_interval is not None else self.retry_interval
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try:
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if self._data_source == DataSource.TUSHARE:
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return self._get_tushare_daily_data(codes, start_date, end_date, max_retries, retry_interval)
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elif self._data_source == DataSource.AKSHARE:
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return self._get_akshare_daily_data(codes, start_date, end_date, max_retries, retry_interval)
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else:
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raise ValueError("不支持的数据源")
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except Exception as e:
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logging.error(f"获取日线数据失败: {str(e)}")
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return {}
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def _get_tushare_daily_data(self, codes: List[str], start_date: str = None, end_date: str = None,
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max_retries: int = 3, retry_interval: float = 2) -> Dict[str, pd.DataFrame]:
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"""使用Tushare获取日线数据"""
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daily_data = {}
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pro = ts.pro_api() # 获取Tushare专业版API接口
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for code in codes:
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for attempt in range(max_retries):
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try:
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# 如果没有指定日期范围，默认获取最近30天的数据
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if not end_date:
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end_date = pd.Timestamp.now().strftime('%Y%m%d')
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if not start_date:
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start_date = (pd.Timestamp.now() - pd.Timedelta(days=30)).strftime('%Y%m%d')
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df = pro.daily(ts_code=code, start_date=start_date, end_date=end_date)
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if df is not None and not df.empty:
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df = df.sort_values('trade_date')
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daily_data[code] = df
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break # 成功获取数据，跳出重试循环
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except Exception as e:
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if attempt < max_retries - 1:
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time.sleep(retry_interval)
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continue
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logging.error(f"获取{code}日线数据失败: {str(e)}")
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break
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return daily_data
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def _get_akshare_daily_data(self, codes: List[str], start_date: str = None, end_date: str = None,
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max_retries: int = 3, retry_interval: float = 2) -> Dict[str, pd.DataFrame]:
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"""使用AKShare获取日线数据"""
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# AKShare实现待完成
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raise NotImplementedError("AKShare日线数据获取待实现")
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