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# -*- coding: utf-8 -*-
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"""
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===================================
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TushareFetcher - 备用数据源 1 (Priority 2)
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===================================
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数据来源：Tushare Pro API（挖地兔）
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特点：需要 Token、有请求配额限制
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优点：数据质量高、接口稳定
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流控策略：
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1. 实现"每分钟调用计数器"
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2. 超过免费配额（80次/分）时，强制休眠到下一分钟
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3. 使用 tenacity 实现指数退避重试
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"""
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import json as _json
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import logging
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import re
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import time
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from datetime import datetime
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from typing import Optional, Tuple, List, Dict, Any
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import pandas as pd
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import requests
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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, RateLimitError, STANDARD_COLUMNS
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from .realtime_types import UnifiedRealtimeQuote
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from src.config import get_config
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import os
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logger = logging.getLogger(__name__)
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# ETF code prefixes by exchange
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# Shanghai: 51xxxx, 52xxxx, 56xxxx, 58xxxx
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# Shenzhen: 15xxxx, 16xxxx, 18xxxx
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_ETF_SH_PREFIXES = ('51', '52', '56', '58')
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_ETF_SZ_PREFIXES = ('15', '16', '18')
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_ETF_ALL_PREFIXES = _ETF_SH_PREFIXES + _ETF_SZ_PREFIXES
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def _is_etf_code(stock_code: str) -> bool:
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"""
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Check if the code is an ETF fund code.
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ETF code ranges:
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- Shanghai ETF: 51xxxx, 52xxxx, 56xxxx, 58xxxx
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- Shenzhen ETF: 15xxxx, 16xxxx, 18xxxx
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"""
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code = stock_code.strip().split('.')[0]
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return code.startswith(_ETF_ALL_PREFIXES) and len(code) == 6
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def _is_us_code(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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class TushareFetcher(BaseFetcher):
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"""
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Tushare Pro 数据源实现
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优先级：2
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数据来源：Tushare Pro API
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关键策略：
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- 每分钟调用计数器，防止超出配额
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- 超过 80 次/分钟时强制等待
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- 失败后指数退避重试
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配额说明（Tushare 免费用户）：
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- 每分钟最多 80 次请求
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- 每天最多 500 次请求
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"""
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name = "TushareFetcher"
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priority = int(os.getenv("TUSHARE_PRIORITY", "2")) # 默认优先级，会在 __init__ 中根据配置动态调整
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def __init__(self, rate_limit_per_minute: int = 80):
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"""
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初始化 TushareFetcher
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Args:
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rate_limit_per_minute: 每分钟最大请求数（默认80，Tushare免费配额）
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"""
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self.rate_limit_per_minute = rate_limit_per_minute
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self._call_count = 0 # 当前分钟内的调用次数
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self._minute_start: Optional[float] = None # 当前计数周期开始时间
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self._api: Optional[object] = None # Tushare API 实例
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# 尝试初始化 API
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self._init_api()
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# 根据 API 初始化结果动态调整优先级
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self.priority = self._determine_priority()
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def _init_api(self) -> None:
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"""
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初始化 Tushare API
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如果 Token 未配置，此数据源将不可用
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"""
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config = get_config()
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if not config.tushare_token:
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logger.warning("Tushare Token 未配置，此数据源不可用")
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return
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try:
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import tushare as ts
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# Set Token
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ts.set_token(config.tushare_token)
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# Get API instance
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self._api = ts.pro_api()
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# Fix: tushare SDK 1.4.x hardcodes api.waditu.com/dataapi which may
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# be unavailable (503). Monkey-patch the query method to use the
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# official api.tushare.pro endpoint which posts to root URL.
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self._patch_api_endpoint(config.tushare_token)
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logger.info("Tushare API 初始化成功")
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except Exception as e:
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logger.error(f"Tushare API 初始化失败: {e}")
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self._api = None
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def _patch_api_endpoint(self, token: str) -> None:
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"""
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Patch tushare SDK to use the official api.tushare.pro endpoint.
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The SDK (v1.4.x) hardcodes http://api.waditu.com/dataapi and appends
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/{api_name} to the URL. That endpoint may return 503, causing silent
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empty-DataFrame failures. This method replaces the query method to
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POST directly to http://api.tushare.pro (root URL, no path suffix).
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"""
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import types
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TUSHARE_API_URL = "http://api.tushare.pro"
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_token = token
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_timeout = getattr(self._api, '_DataApi__timeout', 30)
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def patched_query(self_api, api_name, fields='', **kwargs):
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req_params = {
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'api_name': api_name,
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'token': _token,
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'params': kwargs,
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'fields': fields,
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}
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res = requests.post(TUSHARE_API_URL, json=req_params, timeout=_timeout)
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if res.status_code != 200:
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raise Exception(f"Tushare API HTTP {res.status_code}")
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result = _json.loads(res.text)
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if result['code'] != 0:
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raise Exception(result['msg'])
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data = result['data']
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columns = data['fields']
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items = data['items']
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return pd.DataFrame(items, columns=columns)
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self._api.query = types.MethodType(patched_query, self._api)
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logger.debug(f"Tushare API endpoint patched to {TUSHARE_API_URL}")
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def _determine_priority(self) -> int:
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"""
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根据 Token 配置和 API 初始化状态确定优先级
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策略：
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- Token 配置且 API 初始化成功：优先级 -1（绝对最高，优于 efinance）
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- 其他情况：优先级 2（默认）
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Returns:
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优先级数字（0=最高，数字越大优先级越低）
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"""
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config = get_config()
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if config.tushare_token and self._api is not None:
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# Token 配置且 API 初始化成功，提升为最高优先级
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logger.info("✅ 检测到 TUSHARE_TOKEN 且 API 初始化成功，Tushare 数据源优先级提升为最高 (Priority -1)")
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return -1
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# Token 未配置或 API 初始化失败，保持默认优先级
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return 2
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def is_available(self) -> bool:
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"""
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检查数据源是否可用
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Returns:
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True 表示可用，False 表示不可用
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"""
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return self._api is not None
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def _check_rate_limit(self) -> None:
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"""
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检查并执行速率限制
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流控策略：
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1. 检查是否进入新的一分钟
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2. 如果是，重置计数器
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3. 如果当前分钟调用次数超过限制，强制休眠
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"""
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current_time = time.time()
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# 检查是否需要重置计数器（新的一分钟）
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if self._minute_start is None:
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self._minute_start = current_time
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self._call_count = 0
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elif current_time - self._minute_start >= 60:
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# 已经过了一分钟，重置计数器
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self._minute_start = current_time
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self._call_count = 0
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logger.debug("速率限制计数器已重置")
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# 检查是否超过配额
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if self._call_count >= self.rate_limit_per_minute:
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# 计算需要等待的时间（到下一分钟）
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elapsed = current_time - self._minute_start
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sleep_time = max(0, 60 - elapsed) + 1 # +1 秒缓冲
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logger.warning(
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f"Tushare 达到速率限制 ({self._call_count}/{self.rate_limit_per_minute} 次/分钟)，"
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f"等待 {sleep_time:.1f} 秒..."
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)
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time.sleep(sleep_time)
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# 重置计数器
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self._minute_start = time.time()
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self._call_count = 0
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# 增加调用计数
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self._call_count += 1
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logger.debug(f"Tushare 当前分钟调用次数: {self._call_count}/{self.rate_limit_per_minute}")
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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 Tushare 格式
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Tushare 要求的格式：
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- 沪市股票：600519.SH
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- 深市股票：000001.SZ
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- 沪市 ETF：510050.SH, 563230.SH
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- 深市 ETF：159919.SZ
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Args:
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stock_code: 原始代码，如 '600519', '000001', '563230'
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Returns:
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Tushare 格式代码，如 '600519.SH', '000001.SZ', '563230.SH'
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"""
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code = stock_code.strip()
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# Already has suffix
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if '.' in code:
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return code.upper()
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# ETF: determine exchange by prefix
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if code.startswith(_ETF_SH_PREFIXES) and len(code) == 6:
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return f"{code}.SH"
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if code.startswith(_ETF_SZ_PREFIXES) and len(code) == 6:
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return f"{code}.SZ"
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# Regular stocks
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# Shanghai: 600xxx, 601xxx, 603xxx, 688xxx (STAR Market)
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# Shenzhen: 000xxx, 002xxx, 300xxx (ChiNext)
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if code.startswith(('600', '601', '603', '688')):
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return f"{code}.SH"
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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 Tushare 获取原始数据
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根据代码类型选择不同接口：
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- 普通股票：daily()
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- ETF 基金：fund_daily()
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流程：
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1. 检查 API 是否可用
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2. 检查是否为美股（不支持）
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3. 执行速率限制检查
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4. 转换股票代码格式
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5. 根据代码类型选择接口并调用
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"""
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if self._api is None:
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raise DataFetchError("Tushare API 未初始化，请检查 Token 配置")
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# US stocks not supported
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if _is_us_code(stock_code):
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raise DataFetchError(f"TushareFetcher 不支持美股 {stock_code}，请使用 AkshareFetcher 或 YfinanceFetcher")
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# Rate-limit check
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self._check_rate_limit()
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# Convert code format
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ts_code = self._convert_stock_code(stock_code)
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# Convert date format (Tushare requires YYYYMMDD)
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ts_start = start_date.replace('-', '')
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ts_end = end_date.replace('-', '')
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is_etf = _is_etf_code(stock_code)
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api_name = "fund_daily" if is_etf else "daily"
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logger.debug(f"调用 Tushare {api_name}({ts_code}, {ts_start}, {ts_end})")
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try:
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if is_etf:
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# ETF uses fund_daily interface
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df = self._api.fund_daily(
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ts_code=ts_code,
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start_date=ts_start,
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end_date=ts_end,
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)
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else:
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# Regular stocks use daily interface
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df = self._api.daily(
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ts_code=ts_code,
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start_date=ts_start,
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end_date=ts_end,
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)
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return df
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except Exception as e:
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error_msg = str(e).lower()
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# 检测配额超限
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if any(keyword in error_msg for keyword in ['quota', '配额', 'limit', '权限']):
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logger.warning(f"Tushare 配额可能超限: {e}")
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raise RateLimitError(f"Tushare 配额超限: {e}") from e
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raise DataFetchError(f"Tushare 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 Tushare 数据
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Tushare daily 返回的列名：
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ts_code, trade_date, open, high, low, close, pre_close, change, pct_chg, vol, amount
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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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# 列名映射
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column_mapping = {
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'trade_date': 'date',
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'vol': 'volume',
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# open, high, low, close, amount, pct_chg 列名相同
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}
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df = df.rename(columns=column_mapping)
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# 转换日期格式（YYYYMMDD -> YYYY-MM-DD）
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if 'date' in df.columns:
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df['date'] = pd.to_datetime(df['date'], format='%Y%m%d')
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# 成交量单位转换（Tushare 的 vol 单位是手，需要转换为股）
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if 'volume' in df.columns:
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df['volume'] = df['volume'] * 100
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# 成交额单位转换（Tushare 的 amount 单位是千元，转换为元）
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if 'amount' in df.columns:
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df['amount'] = df['amount'] * 1000
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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_stock_name(self, stock_code: str) -> Optional[str]:
|
|
|
"""
|
|
|
获取股票名称
|
|
|
|
|
|
使用 Tushare 的 stock_basic 接口获取股票基本信息
|
|
|
|
|
|
Args:
|
|
|
stock_code: 股票代码
|
|
|
|
|
|
Returns:
|
|
|
股票名称，失败返回 None
|
|
|
"""
|
|
|
if self._api is None:
|
|
|
logger.warning("Tushare API 未初始化，无法获取股票名称")
|
|
|
return None
|
|
|
|
|
|
# 检查缓存
|
|
|
if hasattr(self, '_stock_name_cache') and stock_code in self._stock_name_cache:
|
|
|
return self._stock_name_cache[stock_code]
|
|
|
|
|
|
# 初始化缓存
|
|
|
if not hasattr(self, '_stock_name_cache'):
|
|
|
self._stock_name_cache = {}
|
|
|
|
|
|
try:
|
|
|
# 速率限制检查
|
|
|
self._check_rate_limit()
|
|
|
|
|
|
# 转换代码格式
|
|
|
ts_code = self._convert_stock_code(stock_code)
|
|
|
|
|
|
# ETF uses fund_basic, regular stocks use stock_basic
|
|
|
if _is_etf_code(stock_code):
|
|
|
df = self._api.fund_basic(
|
|
|
ts_code=ts_code,
|
|
|
fields='ts_code,name'
|
|
|
)
|
|
|
else:
|
|
|
df = self._api.stock_basic(
|
|
|
ts_code=ts_code,
|
|
|
fields='ts_code,name'
|
|
|
)
|
|
|
|
|
|
if df is not None and not df.empty:
|
|
|
name = df.iloc[0]['name']
|
|
|
self._stock_name_cache[stock_code] = name
|
|
|
logger.debug(f"Tushare 获取股票名称成功: {stock_code} -> {name}")
|
|
|
return name
|
|
|
|
|
|
except Exception as e:
|
|
|
logger.warning(f"Tushare 获取股票名称失败 {stock_code}: {e}")
|
|
|
|
|
|
return None
|
|
|
|
|
|
def get_stock_list(self) -> Optional[pd.DataFrame]:
|
|
|
"""
|
|
|
获取股票列表
|
|
|
|
|
|
使用 Tushare 的 stock_basic 接口获取全部股票列表
|
|
|
|
|
|
Returns:
|
|
|
包含 code, name 列的 DataFrame，失败返回 None
|
|
|
"""
|
|
|
if self._api is None:
|
|
|
logger.warning("Tushare API 未初始化，无法获取股票列表")
|
|
|
return None
|
|
|
|
|
|
try:
|
|
|
# 速率限制检查
|
|
|
self._check_rate_limit()
|
|
|
|
|
|
# 调用 stock_basic 接口获取所有股票
|
|
|
df = self._api.stock_basic(
|
|
|
exchange='',
|
|
|
list_status='L',
|
|
|
fields='ts_code,name,industry,area,market'
|
|
|
)
|
|
|
|
|
|
if df is not None and not df.empty:
|
|
|
# 转换 ts_code 为标准代码格式
|
|
|
df['code'] = df['ts_code'].apply(lambda x: x.split('.')[0])
|
|
|
|
|
|
# 更新缓存
|
|
|
if not hasattr(self, '_stock_name_cache'):
|
|
|
self._stock_name_cache = {}
|
|
|
for _, row in df.iterrows():
|
|
|
self._stock_name_cache[row['code']] = row['name']
|
|
|
|
|
|
logger.info(f"Tushare 获取股票列表成功: {len(df)} 条")
|
|
|
return df[['code', 'name', 'industry', 'area', 'market']]
|
|
|
|
|
|
except Exception as e:
|
|
|
logger.warning(f"Tushare 获取股票列表失败: {e}")
|
|
|
|
|
|
return None
|
|
|
|
|
|
def get_realtime_quote(self, stock_code: str) -> Optional[UnifiedRealtimeQuote]:
|
|
|
"""
|
|
|
获取实时行情
|
|
|
|
|
|
策略：
|
|
|
1. 优先尝试 Pro 接口（需要2000积分）：数据全，稳定性高
|
|
|
2. 失败降级到旧版接口：门槛低，数据较少
|
|
|
|
|
|
Args:
|
|
|
stock_code: 股票代码
|
|
|
|
|
|
Returns:
|
|
|
UnifiedRealtimeQuote 对象，失败返回 None
|
|
|
"""
|
|
|
if self._api is None:
|
|
|
return None
|
|
|
|
|
|
from .realtime_types import (
|
|
|
RealtimeSource,
|
|
|
safe_float, safe_int
|
|
|
)
|
|
|
|
|
|
# 速率限制检查
|
|
|
self._check_rate_limit()
|
|
|
|
|
|
# 尝试 Pro 接口
|
|
|
try:
|
|
|
ts_code = self._convert_stock_code(stock_code)
|
|
|
# 尝试调用 Pro 实时接口 (需要积分)
|
|
|
df = self._api.quotation(ts_code=ts_code)
|
|
|
|
|
|
if df is not None and not df.empty:
|
|
|
row = df.iloc[0]
|
|
|
logger.debug(f"Tushare Pro 实时行情获取成功: {stock_code}")
|
|
|
|
|
|
return UnifiedRealtimeQuote(
|
|
|
code=stock_code,
|
|
|
name=str(row.get('name', '')),
|
|
|
source=RealtimeSource.TUSHARE,
|
|
|
price=safe_float(row.get('price')),
|
|
|
change_pct=safe_float(row.get('pct_chg')), # Pro 接口通常直接返回涨跌幅
|
|
|
change_amount=safe_float(row.get('change')),
|
|
|
volume=safe_int(row.get('vol')),
|
|
|
amount=safe_float(row.get('amount')),
|
|
|
high=safe_float(row.get('high')),
|
|
|
low=safe_float(row.get('low')),
|
|
|
open_price=safe_float(row.get('open')),
|
|
|
pre_close=safe_float(row.get('pre_close')),
|
|
|
turnover_rate=safe_float(row.get('turnover_ratio')), # Pro 接口可能有换手率
|
|
|
pe_ratio=safe_float(row.get('pe')),
|
|
|
pb_ratio=safe_float(row.get('pb')),
|
|
|
total_mv=safe_float(row.get('total_mv')),
|
|
|
)
|
|
|
except Exception as e:
|
|
|
# 仅记录调试日志，不报错，继续尝试降级
|
|
|
logger.debug(f"Tushare Pro 实时行情不可用 (可能是积分不足): {e}")
|
|
|
|
|
|
# 降级：尝试旧版接口
|
|
|
try:
|
|
|
import tushare as ts
|
|
|
|
|
|
# Tushare 旧版接口使用 6 位代码
|
|
|
code_6 = stock_code.split('.')[0] if '.' in stock_code else stock_code
|
|
|
|
|
|
# 特殊处理指数代码：旧版接口需要前缀 (sh000001, sz399001)
|
|
|
# 简单的指数判断逻辑
|
|
|
if code_6 == '000001': # 上证指数
|
|
|
symbol = 'sh000001'
|
|
|
elif code_6 == '399001': # 深证成指
|
|
|
symbol = 'sz399001'
|
|
|
elif code_6 == '399006': # 创业板指
|
|
|
symbol = 'sz399006'
|
|
|
elif code_6 == '000300': # 沪深300
|
|
|
symbol = 'sh000300'
|
|
|
else:
|
|
|
symbol = code_6
|
|
|
|
|
|
# 调用旧版实时接口 (ts.get_realtime_quotes)
|
|
|
df = ts.get_realtime_quotes(symbol)
|
|
|
|
|
|
if df is None or df.empty:
|
|
|
return None
|
|
|
|
|
|
row = df.iloc[0]
|
|
|
|
|
|
# 计算涨跌幅
|
|
|
price = safe_float(row['price'])
|
|
|
pre_close = safe_float(row['pre_close'])
|
|
|
change_pct = 0.0
|
|
|
change_amount = 0.0
|
|
|
|
|
|
if price and pre_close and pre_close > 0:
|
|
|
change_amount = price - pre_close
|
|
|
change_pct = (change_amount / pre_close) * 100
|
|
|
|
|
|
# 构建统一对象
|
|
|
return UnifiedRealtimeQuote(
|
|
|
code=stock_code,
|
|
|
name=str(row['name']),
|
|
|
source=RealtimeSource.TUSHARE,
|
|
|
price=price,
|
|
|
change_pct=round(change_pct, 2),
|
|
|
change_amount=round(change_amount, 2),
|
|
|
volume=safe_int(row['volume']) // 100, # 转换为手
|
|
|
amount=safe_float(row['amount']),
|
|
|
high=safe_float(row['high']),
|
|
|
low=safe_float(row['low']),
|
|
|
open_price=safe_float(row['open']),
|
|
|
pre_close=pre_close,
|
|
|
)
|
|
|
|
|
|
except Exception as e:
|
|
|
logger.warning(f"Tushare (旧版) 获取实时行情失败 {stock_code}: {e}")
|
|
|
return None
|
|
|
|
|
|
def get_main_indices(self) -> Optional[List[dict]]:
|
|
|
"""
|
|
|
获取主要指数实时行情 (Tushare Pro)
|
|
|
"""
|
|
|
if self._api is None:
|
|
|
return None
|
|
|
|
|
|
from .realtime_types import safe_float
|
|
|
|
|
|
# 指数映射：Tushare代码 -> 名称
|
|
|
indices_map = {
|
|
|
'000001.SH': '上证指数',
|
|
|
'399001.SZ': '深证成指',
|
|
|
'399006.SZ': '创业板指',
|
|
|
'000688.SH': '科创50',
|
|
|
'000016.SH': '上证50',
|
|
|
'000300.SH': '沪深300',
|
|
|
}
|
|
|
|
|
|
try:
|
|
|
self._check_rate_limit()
|
|
|
|
|
|
# Tushare index_daily 获取历史数据，实时数据需用其他接口或估算
|
|
|
# 由于 Tushare 免费用户可能无法获取指数实时行情，这里作为备选
|
|
|
# 使用 index_daily 获取最近交易日数据
|
|
|
|
|
|
end_date = datetime.now().strftime('%Y%m%d')
|
|
|
start_date = (datetime.now() - pd.Timedelta(days=5)).strftime('%Y%m%d')
|
|
|
|
|
|
results = []
|
|
|
|
|
|
# 批量获取所有指数数据
|
|
|
for ts_code, name in indices_map.items():
|
|
|
try:
|
|
|
df = self._api.index_daily(ts_code=ts_code, start_date=start_date, end_date=end_date)
|
|
|
if df is not None and not df.empty:
|
|
|
row = df.iloc[0] # 最新一天
|
|
|
|
|
|
current = safe_float(row['close'])
|
|
|
prev_close = safe_float(row['pre_close'])
|
|
|
|
|
|
results.append({
|
|
|
'code': ts_code.split('.')[0], # 兼容 sh000001 格式需转换，这里保持纯数字
|
|
|
'name': name,
|
|
|
'current': current,
|
|
|
'change': safe_float(row['change']),
|
|
|
'change_pct': safe_float(row['pct_chg']),
|
|
|
'open': safe_float(row['open']),
|
|
|
'high': safe_float(row['high']),
|
|
|
'low': safe_float(row['low']),
|
|
|
'prev_close': prev_close,
|
|
|
'volume': safe_float(row['vol']),
|
|
|
'amount': safe_float(row['amount']) * 1000, # 千元转元
|
|
|
'amplitude': 0.0 # Tushare index_daily 不直接返回振幅
|
|
|
})
|
|
|
except Exception as e:
|
|
|
logger.debug(f"Tushare 获取指数 {name} 失败: {e}")
|
|
|
continue
|
|
|
|
|
|
if results:
|
|
|
return results
|
|
|
else:
|
|
|
logger.warning("[Tushare] 未获取到指数行情数据")
|
|
|
|
|
|
except Exception as e:
|
|
|
logger.error(f"[Tushare] 获取指数行情失败: {e}")
|
|
|
|
|
|
return None
|
|
|
|
|
|
def get_market_stats(self) -> Optional[dict]:
|
|
|
"""
|
|
|
获取市场涨跌统计 (Tushare Pro)
|
|
|
"""
|
|
|
if self._api is None:
|
|
|
return None
|
|
|
|
|
|
try:
|
|
|
self._check_rate_limit()
|
|
|
|
|
|
# 获取最近交易日 (获取过去20天，确保有足够历史)
|
|
|
start_date = (datetime.now() - pd.Timedelta(days=20)).strftime('%Y%m%d')
|
|
|
trade_cal = self._api.trade_cal(exchange='', start_date=start_date, end_date=datetime.now().strftime('%Y%m%d'), is_open='1')
|
|
|
|
|
|
if trade_cal is None or trade_cal.empty:
|
|
|
return None
|
|
|
|
|
|
# 确保按日期升序排列 (Tushare有时返回降序)
|
|
|
trade_cal = trade_cal.sort_values('cal_date')
|
|
|
|
|
|
# 尝试获取最新一天的数据
|
|
|
last_date = trade_cal.iloc[-1]['cal_date']
|
|
|
logger.info(f"[Tushare] Calendar suggests last trading date: {last_date}")
|
|
|
|
|
|
# 注意：每日指标接口 daily 可能数据量较大
|
|
|
# 如果是在盘中调用，当天的数据可能还未生成，导致返回空或极少数据
|
|
|
df = self._api.daily(trade_date=last_date)
|
|
|
|
|
|
current_len = len(df) if df is not None else 0
|
|
|
logger.info(f"[Tushare] Initial fetch for {last_date} returned {current_len} records")
|
|
|
|
|
|
# 如果数据过少（<100条），说明当天数据未就绪，尝试使用前一交易日
|
|
|
if df is None or len(df) < 100:
|
|
|
if len(trade_cal) > 1:
|
|
|
prev_date = trade_cal.iloc[-2]['cal_date']
|
|
|
logger.warning(f"Data for {last_date} is incomplete (count={current_len}), falling back to {prev_date}")
|
|
|
last_date = prev_date
|
|
|
df = self._api.daily(trade_date=last_date)
|
|
|
else:
|
|
|
logger.warning(f"[Tushare] {last_date} 数据不足且无可用历史交易日")
|
|
|
|
|
|
logger.info(f"Calculating stats using data from date: {last_date}")
|
|
|
|
|
|
if df is not None and not df.empty:
|
|
|
logger.info(f"[Tushare] 使用交易日 {last_date} 进行市场统计分析")
|
|
|
up_count = len(df[df['pct_chg'] > 0])
|
|
|
down_count = len(df[df['pct_chg'] < 0])
|
|
|
flat_count = len(df[df['pct_chg'] == 0])
|
|
|
|
|
|
# 涨停跌停估算 (9.9%阈值)
|
|
|
limit_up = len(df[df['pct_chg'] >= 9.9])
|
|
|
limit_down = len(df[df['pct_chg'] <= -9.9])
|
|
|
|
|
|
total_amount = df['amount'].sum() * 1000 / 1e8 # 千元 -> 元 -> 亿元
|
|
|
|
|
|
return {
|
|
|
'up_count': up_count,
|
|
|
'down_count': down_count,
|
|
|
'flat_count': flat_count,
|
|
|
'limit_up_count': limit_up,
|
|
|
'limit_down_count': limit_down,
|
|
|
'total_amount': total_amount
|
|
|
}
|
|
|
else:
|
|
|
logger.warning("[Tushare] 获取市场统计数据为空")
|
|
|
|
|
|
except Exception as e:
|
|
|
logger.error(f"[Tushare] 获取市场统计失败: {e}")
|
|
|
|
|
|
return None
|
|
|
|
|
|
def get_sector_rankings(self, n: int = 5) -> Optional[Tuple[list, list]]:
|
|
|
"""
|
|
|
获取板块涨跌榜 (Tushare Pro)
|
|
|
"""
|
|
|
# Tushare 获取板块数据较复杂，暂时返回 None，让 AkShare 处理
|
|
|
return None
|
|
|
|
|
|
|
|
|
if __name__ == "__main__":
|
|
|
# 测试代码
|
|
|
logging.basicConfig(level=logging.DEBUG)
|
|
|
|
|
|
fetcher = TushareFetcher()
|
|
|
|
|
|
try:
|
|
|
# 测试历史数据
|
|
|
df = fetcher.get_daily_data('600519') # 茅台
|
|
|
print(f"获取成功，共 {len(df)} 条数据")
|
|
|
print(df.tail())
|
|
|
|
|
|
# 测试股票名称
|
|
|
name = fetcher.get_stock_name('600519')
|
|
|
print(f"股票名称: {name}")
|
|
|
|
|
|
except Exception as e:
|
|
|
print(f"获取失败: {e}")
|
