396 lines
14 KiB
Python
396 lines
14 KiB
Python
#!/usr/bin/env python3
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"""
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实时新闻数据获取工具
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解决新闻滞后性问题
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"""
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import requests
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import json
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from datetime import datetime, timedelta
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from typing import List, Dict, Optional
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import time
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import os
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from dataclasses import dataclass
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@dataclass
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class NewsItem:
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"""新闻项目数据结构"""
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title: str
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content: str
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source: str
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publish_time: datetime
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url: str
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urgency: str # high, medium, low
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relevance_score: float
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class RealtimeNewsAggregator:
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"""实时新闻聚合器"""
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def __init__(self):
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self.headers = {
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'User-Agent': 'TradingAgents-CN/1.0'
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}
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# API密钥配置
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self.finnhub_key = os.getenv('FINNHUB_API_KEY')
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self.alpha_vantage_key = os.getenv('ALPHA_VANTAGE_API_KEY')
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self.newsapi_key = os.getenv('NEWSAPI_KEY')
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def get_realtime_stock_news(self, ticker: str, hours_back: int = 6) -> List[NewsItem]:
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"""
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获取实时股票新闻
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优先级：专业API > 新闻API > 搜索引擎
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"""
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all_news = []
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# 1. FinnHub实时新闻 (最高优先级)
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finnhub_news = self._get_finnhub_realtime_news(ticker, hours_back)
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all_news.extend(finnhub_news)
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# 2. Alpha Vantage新闻
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av_news = self._get_alpha_vantage_news(ticker, hours_back)
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all_news.extend(av_news)
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# 3. NewsAPI (如果配置了)
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if self.newsapi_key:
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newsapi_news = self._get_newsapi_news(ticker, hours_back)
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all_news.extend(newsapi_news)
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# 4. 中文财经新闻源
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chinese_news = self._get_chinese_finance_news(ticker, hours_back)
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all_news.extend(chinese_news)
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# 去重和排序
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unique_news = self._deduplicate_news(all_news)
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return sorted(unique_news, key=lambda x: x.publish_time, reverse=True)
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def _get_finnhub_realtime_news(self, ticker: str, hours_back: int) -> List[NewsItem]:
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"""获取FinnHub实时新闻"""
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if not self.finnhub_key:
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return []
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try:
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# 计算时间范围
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end_time = datetime.now()
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start_time = end_time - timedelta(hours=hours_back)
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# FinnHub API调用
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url = "https://finnhub.io/api/v1/company-news"
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params = {
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'symbol': ticker,
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'from': start_time.strftime('%Y-%m-%d'),
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'to': end_time.strftime('%Y-%m-%d'),
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'token': self.finnhub_key
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}
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response = requests.get(url, params=params, headers=self.headers)
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response.raise_for_status()
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news_data = response.json()
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news_items = []
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for item in news_data:
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# 检查新闻时效性
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publish_time = datetime.fromtimestamp(item.get('datetime', 0))
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if publish_time < start_time:
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continue
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# 评估紧急程度
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urgency = self._assess_news_urgency(item.get('headline', ''), item.get('summary', ''))
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news_items.append(NewsItem(
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title=item.get('headline', ''),
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content=item.get('summary', ''),
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source=item.get('source', 'FinnHub'),
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publish_time=publish_time,
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url=item.get('url', ''),
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urgency=urgency,
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relevance_score=self._calculate_relevance(item.get('headline', ''), ticker)
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))
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return news_items
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except Exception as e:
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print(f"FinnHub新闻获取失败: {e}")
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return []
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def _get_alpha_vantage_news(self, ticker: str, hours_back: int) -> List[NewsItem]:
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"""获取Alpha Vantage新闻"""
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if not self.alpha_vantage_key:
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return []
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try:
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url = "https://www.alphavantage.co/query"
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params = {
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'function': 'NEWS_SENTIMENT',
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'tickers': ticker,
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'apikey': self.alpha_vantage_key,
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'limit': 50
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}
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response = requests.get(url, params=params, headers=self.headers)
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response.raise_for_status()
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data = response.json()
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news_items = []
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if 'feed' in data:
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for item in data['feed']:
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# 解析时间
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time_str = item.get('time_published', '')
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try:
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publish_time = datetime.strptime(time_str, '%Y%m%dT%H%M%S')
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except:
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continue
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# 检查时效性
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if publish_time < datetime.now() - timedelta(hours=hours_back):
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continue
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urgency = self._assess_news_urgency(item.get('title', ''), item.get('summary', ''))
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news_items.append(NewsItem(
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title=item.get('title', ''),
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content=item.get('summary', ''),
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source=item.get('source', 'Alpha Vantage'),
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publish_time=publish_time,
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url=item.get('url', ''),
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urgency=urgency,
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relevance_score=self._calculate_relevance(item.get('title', ''), ticker)
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))
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return news_items
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except Exception as e:
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print(f"Alpha Vantage新闻获取失败: {e}")
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return []
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def _get_newsapi_news(self, ticker: str, hours_back: int) -> List[NewsItem]:
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"""获取NewsAPI新闻"""
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try:
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# 构建搜索查询
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company_names = {
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'AAPL': 'Apple',
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'TSLA': 'Tesla',
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'NVDA': 'NVIDIA',
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'MSFT': 'Microsoft',
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'GOOGL': 'Google'
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}
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query = f"{ticker} OR {company_names.get(ticker, ticker)}"
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url = "https://newsapi.org/v2/everything"
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params = {
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'q': query,
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'language': 'en',
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'sortBy': 'publishedAt',
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'from': (datetime.now() - timedelta(hours=hours_back)).isoformat(),
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'apiKey': self.newsapi_key
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}
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response = requests.get(url, params=params, headers=self.headers)
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response.raise_for_status()
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data = response.json()
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news_items = []
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for item in data.get('articles', []):
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# 解析时间
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time_str = item.get('publishedAt', '')
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try:
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publish_time = datetime.fromisoformat(time_str.replace('Z', '+00:00'))
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except:
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continue
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urgency = self._assess_news_urgency(item.get('title', ''), item.get('description', ''))
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news_items.append(NewsItem(
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title=item.get('title', ''),
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content=item.get('description', ''),
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source=item.get('source', {}).get('name', 'NewsAPI'),
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publish_time=publish_time,
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url=item.get('url', ''),
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urgency=urgency,
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relevance_score=self._calculate_relevance(item.get('title', ''), ticker)
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))
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return news_items
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except Exception as e:
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print(f"NewsAPI新闻获取失败: {e}")
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return []
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def _get_chinese_finance_news(self, ticker: str, hours_back: int) -> List[NewsItem]:
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"""获取中文财经新闻"""
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# 这里可以集成中文财经新闻API
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# 例如：财联社、新浪财经、东方财富等
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try:
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# 示例：集成财联社API (需要申请)
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# 或者使用RSS源
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news_items = []
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# 财联社RSS (如果可用)
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rss_sources = [
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"https://www.cls.cn/api/sw?app=CailianpressWeb&os=web&sv=7.7.5",
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# 可以添加更多RSS源
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]
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for rss_url in rss_sources:
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try:
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items = self._parse_rss_feed(rss_url, ticker, hours_back)
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news_items.extend(items)
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except:
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continue
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return news_items
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except Exception as e:
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print(f"中文财经新闻获取失败: {e}")
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return []
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def _parse_rss_feed(self, rss_url: str, ticker: str, hours_back: int) -> List[NewsItem]:
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"""解析RSS源"""
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# 简化实现，实际需要使用feedparser库
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return []
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def _assess_news_urgency(self, title: str, content: str) -> str:
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"""评估新闻紧急程度"""
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text = (title + ' ' + content).lower()
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# 高紧急度关键词
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high_urgency_keywords = [
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'breaking', 'urgent', 'alert', 'emergency', 'halt', 'suspend',
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'突发', '紧急', '暂停', '停牌', '重大'
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]
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# 中等紧急度关键词
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medium_urgency_keywords = [
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'earnings', 'report', 'announce', 'launch', 'merger', 'acquisition',
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'财报', '发布', '宣布', '并购', '收购'
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]
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if any(keyword in text for keyword in high_urgency_keywords):
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return 'high'
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elif any(keyword in text for keyword in medium_urgency_keywords):
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return 'medium'
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else:
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return 'low'
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def _calculate_relevance(self, title: str, ticker: str) -> float:
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"""计算新闻相关性分数"""
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text = title.lower()
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ticker_lower = ticker.lower()
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# 基础相关性
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if ticker_lower in text:
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return 1.0
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# 公司名称匹配
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company_names = {
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'aapl': ['apple', 'iphone', 'ipad', 'mac'],
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'tsla': ['tesla', 'elon musk', 'electric vehicle'],
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'nvda': ['nvidia', 'gpu', 'ai chip'],
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'msft': ['microsoft', 'windows', 'azure'],
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'googl': ['google', 'alphabet', 'search']
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}
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if ticker_lower in company_names:
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for name in company_names[ticker_lower]:
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if name in text:
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return 0.8
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return 0.3 # 默认相关性
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def _deduplicate_news(self, news_items: List[NewsItem]) -> List[NewsItem]:
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"""去重新闻"""
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seen_titles = set()
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unique_news = []
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for item in news_items:
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# 简单的标题去重
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title_key = item.title.lower().strip()
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if title_key not in seen_titles and len(title_key) > 10:
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seen_titles.add(title_key)
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unique_news.append(item)
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return unique_news
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def format_news_report(self, news_items: List[NewsItem], ticker: str) -> str:
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"""格式化新闻报告"""
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if not news_items:
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return f"未获取到{ticker}的实时新闻数据。"
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# 按紧急程度分组
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high_urgency = [n for n in news_items if n.urgency == 'high']
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medium_urgency = [n for n in news_items if n.urgency == 'medium']
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low_urgency = [n for n in news_items if n.urgency == 'low']
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report = f"# {ticker} 实时新闻分析报告\n\n"
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report += f"📅 生成时间: {datetime.now().strftime('%Y-%m-%d %H:%M:%S')}\n"
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report += f"📊 新闻总数: {len(news_items)}条\n\n"
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if high_urgency:
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report += "## 🚨 紧急新闻\n\n"
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for news in high_urgency[:3]: # 最多显示3条
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report += f"### {news.title}\n"
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report += f"**来源**: {news.source} | **时间**: {news.publish_time.strftime('%H:%M')}\n"
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report += f"{news.content}\n\n"
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if medium_urgency:
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report += "## 📢 重要新闻\n\n"
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for news in medium_urgency[:5]: # 最多显示5条
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report += f"### {news.title}\n"
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report += f"**来源**: {news.source} | **时间**: {news.publish_time.strftime('%H:%M')}\n"
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report += f"{news.content}\n\n"
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# 添加时效性说明
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latest_news = max(news_items, key=lambda x: x.publish_time)
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time_diff = datetime.now() - latest_news.publish_time
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report += f"\n## ⏰ 数据时效性\n"
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report += f"最新新闻发布于: {time_diff.total_seconds() / 60:.0f}分钟前\n"
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if time_diff.total_seconds() < 1800: # 30分钟内
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report += "🟢 数据时效性: 优秀 (30分钟内)\n"
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elif time_diff.total_seconds() < 3600: # 1小时内
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report += "🟡 数据时效性: 良好 (1小时内)\n"
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else:
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report += "🔴 数据时效性: 一般 (超过1小时)\n"
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return report
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def get_realtime_stock_news(ticker: str, curr_date: str, hours_back: int = 6) -> str:
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"""
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获取实时股票新闻的主要接口函数
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"""
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aggregator = RealtimeNewsAggregator()
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try:
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# 获取实时新闻
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news_items = aggregator.get_realtime_stock_news(ticker, hours_back)
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# 格式化报告
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report = aggregator.format_news_report(news_items, ticker)
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return report
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except Exception as e:
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return f"""
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实时新闻获取失败 - {ticker}
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分析日期: {curr_date}
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❌ 错误信息: {str(e)}
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💡 备用建议:
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1. 检查API密钥配置 (FINNHUB_API_KEY, NEWSAPI_KEY)
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2. 使用基础新闻分析作为备选
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3. 关注官方财经媒体的最新报道
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4. 考虑使用专业金融终端获取实时新闻
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注: 实时新闻获取依赖外部API服务的可用性。
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"""
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