mirror of
https://github.com/ZhuLinsen/daily_stock_analysis
synced 2026-09-20 02:43:35 +08:00
1011 lines
38 KiB
Python
1011 lines
38 KiB
Python
# -*- coding: utf-8 -*-
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"""
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===================================
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A股自选股智能分析系统 - 通知层
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===================================
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职责：
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1. 汇总分析结果生成日报
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2. 支持 Markdown 格式输出
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3. 推送到企业微信 Webhook
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"""
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import logging
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from datetime import datetime
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from typing import List, Dict, Any, Optional
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import requests
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from config import get_config
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from analyzer import AnalysisResult
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logger = logging.getLogger(__name__)
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class NotificationService:
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"""
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通知服务
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职责：
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1. 生成 Markdown 格式的分析日报
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2. 推送消息到企业微信机器人
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3. 支持本地保存日报
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"""
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def __init__(self, webhook_url: Optional[str] = None):
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"""
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初始化通知服务
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Args:
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webhook_url: 企业微信 Webhook URL（可选，默认从配置读取）
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"""
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self._webhook_url = webhook_url or get_config().wechat_webhook_url
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if not self._webhook_url:
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logger.warning("企业微信 Webhook URL 未配置，将不发送推送通知")
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def is_available(self) -> bool:
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"""检查通知服务是否可用"""
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return bool(self._webhook_url)
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def generate_daily_report(
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self,
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results: List[AnalysisResult],
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report_date: Optional[str] = None
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) -> str:
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"""
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生成 Markdown 格式的日报（详细版）
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Args:
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results: 分析结果列表
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report_date: 报告日期（默认今天）
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Returns:
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Markdown 格式的日报内容
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"""
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if report_date is None:
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report_date = datetime.now().strftime('%Y-%m-%d')
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# 标题
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report_lines = [
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f"# 📅 {report_date} A股自选股智能分析报告",
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"",
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f"> 共分析 **{len(results)}** 只股票 | 报告生成时间：{datetime.now().strftime('%H:%M:%S')}",
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"",
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"---",
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"",
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]
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# 按评分排序（高分在前）
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sorted_results = sorted(
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results,
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key=lambda x: x.sentiment_score,
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reverse=True
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)
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# 统计信息
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buy_count = sum(1 for r in results if r.operation_advice in ['买入', '加仓', '强烈买入'])
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sell_count = sum(1 for r in results if r.operation_advice in ['卖出', '减仓', '强烈卖出'])
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hold_count = sum(1 for r in results if r.operation_advice in ['持有', '观望'])
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avg_score = sum(r.sentiment_score for r in results) / len(results) if results else 0
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report_lines.extend([
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"## 📊 操作建议汇总",
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"",
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f"| 指标 | 数值 |",
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f"|------|------|",
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f"| 🟢 建议买入/加仓 | **{buy_count}** 只 |",
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f"| 🟡 建议持有/观望 | **{hold_count}** 只 |",
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f"| 🔴 建议减仓/卖出 | **{sell_count}** 只 |",
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f"| 📈 平均看多评分 | **{avg_score:.1f}** 分 |",
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"",
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"---",
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"",
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"## 📈 个股详细分析",
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"",
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])
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# 逐个股票的详细分析
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for result in sorted_results:
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emoji = result.get_emoji()
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confidence_stars = result.get_confidence_stars() if hasattr(result, 'get_confidence_stars') else '⭐⭐'
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report_lines.extend([
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f"### {emoji} {result.name} ({result.code})",
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"",
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f"**操作建议：{result.operation_advice}** | **综合评分：{result.sentiment_score}分** | **趋势预测：{result.trend_prediction}** | **置信度：{confidence_stars}**",
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"",
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])
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# 核心看点
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if hasattr(result, 'key_points') and result.key_points:
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report_lines.extend([
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f"**🎯 核心看点**：{result.key_points}",
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"",
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])
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# 买入/卖出理由
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if hasattr(result, 'buy_reason') and result.buy_reason:
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report_lines.extend([
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f"**💡 操作理由**：{result.buy_reason}",
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"",
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])
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# 走势分析
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if hasattr(result, 'trend_analysis') and result.trend_analysis:
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report_lines.extend([
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"#### 📉 走势分析",
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f"{result.trend_analysis}",
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"",
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])
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# 短期/中期展望
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outlook_lines = []
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if hasattr(result, 'short_term_outlook') and result.short_term_outlook:
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outlook_lines.append(f"- **短期（1-3日）**：{result.short_term_outlook}")
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if hasattr(result, 'medium_term_outlook') and result.medium_term_outlook:
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outlook_lines.append(f"- **中期（1-2周）**：{result.medium_term_outlook}")
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if outlook_lines:
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report_lines.extend([
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"#### 🔮 市场展望",
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*outlook_lines,
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"",
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])
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# 技术面分析
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tech_lines = []
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if result.technical_analysis:
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tech_lines.append(f"**综合**：{result.technical_analysis}")
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if hasattr(result, 'ma_analysis') and result.ma_analysis:
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tech_lines.append(f"**均线**：{result.ma_analysis}")
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if hasattr(result, 'volume_analysis') and result.volume_analysis:
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tech_lines.append(f"**量能**：{result.volume_analysis}")
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if hasattr(result, 'pattern_analysis') and result.pattern_analysis:
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tech_lines.append(f"**形态**：{result.pattern_analysis}")
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if tech_lines:
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report_lines.extend([
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"#### 📊 技术面分析",
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*tech_lines,
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"",
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])
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# 基本面分析
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fund_lines = []
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if hasattr(result, 'fundamental_analysis') and result.fundamental_analysis:
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fund_lines.append(result.fundamental_analysis)
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if hasattr(result, 'sector_position') and result.sector_position:
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fund_lines.append(f"**板块地位**：{result.sector_position}")
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if hasattr(result, 'company_highlights') and result.company_highlights:
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fund_lines.append(f"**公司亮点**：{result.company_highlights}")
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if fund_lines:
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report_lines.extend([
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"#### 🏢 基本面分析",
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*fund_lines,
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"",
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])
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# 消息面/情绪面
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news_lines = []
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if result.news_summary:
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news_lines.append(f"**新闻摘要**：{result.news_summary}")
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if hasattr(result, 'market_sentiment') and result.market_sentiment:
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news_lines.append(f"**市场情绪**：{result.market_sentiment}")
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if hasattr(result, 'hot_topics') and result.hot_topics:
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news_lines.append(f"**相关热点**：{result.hot_topics}")
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if news_lines:
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report_lines.extend([
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"#### 📰 消息面/情绪面",
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*news_lines,
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"",
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])
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# 综合分析
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if result.analysis_summary:
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report_lines.extend([
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"#### 📝 综合分析",
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result.analysis_summary,
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"",
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])
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# 风险提示
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if hasattr(result, 'risk_warning') and result.risk_warning:
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report_lines.extend([
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f"⚠️ **风险提示**：{result.risk_warning}",
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"",
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])
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# 数据来源说明
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if hasattr(result, 'search_performed') and result.search_performed:
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report_lines.append(f"*🔍 已执行联网搜索*")
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if hasattr(result, 'data_sources') and result.data_sources:
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report_lines.append(f"*📋 数据来源：{result.data_sources}*")
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# 错误信息（如果有）
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if not result.success and result.error_message:
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report_lines.extend([
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"",
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f"❌ **分析异常**：{result.error_message[:100]}",
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])
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report_lines.extend([
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"",
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"---",
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"",
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])
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# 底部信息（去除免责声明）
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report_lines.extend([
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"",
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f"*报告生成时间：{datetime.now().strftime('%Y-%m-%d %H:%M:%S')}*",
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])
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return "\n".join(report_lines)
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def _get_signal_level(self, result: AnalysisResult) -> tuple:
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"""
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根据操作建议获取信号等级和颜色
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Returns:
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(信号文字, emoji, 颜色标记)
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"""
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advice = result.operation_advice
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score = result.sentiment_score
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if advice in ['强烈买入'] or score >= 80:
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return ('强烈买入', '💚', '强买')
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elif advice in ['买入', '加仓'] or score >= 65:
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return ('买入', '🟢', '买入')
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elif advice in ['持有'] or 55 <= score < 65:
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return ('持有', '🟡', '持有')
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elif advice in ['观望'] or 45 <= score < 55:
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return ('观望', '⚪', '观望')
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elif advice in ['减仓'] or 35 <= score < 45:
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return ('减仓', '🟠', '减仓')
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elif advice in ['卖出', '强烈卖出'] or score < 35:
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return ('卖出', '🔴', '卖出')
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else:
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return ('观望', '⚪', '观望')
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def generate_dashboard_report(
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self,
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results: List[AnalysisResult],
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report_date: Optional[str] = None
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) -> str:
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"""
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生成决策仪表盘格式的日报（详细版）
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格式：市场概览 + 重要信息 + 核心结论 + 数据透视 + 作战计划
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Args:
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results: 分析结果列表
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report_date: 报告日期（默认今天）
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Returns:
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Markdown 格式的决策仪表盘日报
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"""
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if report_date is None:
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report_date = datetime.now().strftime('%Y-%m-%d')
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# 按评分排序（高分在前）
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sorted_results = sorted(results, key=lambda x: x.sentiment_score, reverse=True)
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# 统计信息
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buy_count = sum(1 for r in results if r.operation_advice in ['买入', '加仓', '强烈买入'])
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sell_count = sum(1 for r in results if r.operation_advice in ['卖出', '减仓', '强烈卖出'])
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hold_count = sum(1 for r in results if r.operation_advice in ['持有', '观望'])
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report_lines = [
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f"# 🎯 {report_date} 决策仪表盘",
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"",
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f"> 共分析 **{len(results)}** 只股票 | 🟢买入:{buy_count} 🟡观望:{hold_count} 🔴卖出:{sell_count}",
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"",
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"---",
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"",
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]
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# 逐个股票的决策仪表盘
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for result in sorted_results:
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signal_text, signal_emoji, signal_tag = self._get_signal_level(result)
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dashboard = result.dashboard if hasattr(result, 'dashboard') and result.dashboard else {}
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# 股票名称（优先使用 dashboard 或 result 中的名称）
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stock_name = result.name if result.name and not result.name.startswith('股票') else f'股票{result.code}'
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report_lines.extend([
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f"## {signal_emoji} {stock_name} ({result.code})",
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"",
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])
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# ========== 舆情与基本面概览（放在最前面）==========
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intel = dashboard.get('intelligence', {}) if dashboard else {}
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if intel:
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report_lines.extend([
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"### 📰 重要信息速览",
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"",
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])
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# 舆情情绪总结
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if intel.get('sentiment_summary'):
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report_lines.append(f"**💭 舆情情绪**: {intel['sentiment_summary']}")
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# 业绩预期
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if intel.get('earnings_outlook'):
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report_lines.append(f"**📊 业绩预期**: {intel['earnings_outlook']}")
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# 风险警报（醒目显示）
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risk_alerts = intel.get('risk_alerts', [])
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if risk_alerts:
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report_lines.append("")
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report_lines.append("**🚨 风险警报**:")
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for alert in risk_alerts:
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report_lines.append(f"- {alert}")
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# 利好催化
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catalysts = intel.get('positive_catalysts', [])
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if catalysts:
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report_lines.append("")
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report_lines.append("**✨ 利好催化**:")
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for cat in catalysts:
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report_lines.append(f"- {cat}")
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# 最新消息
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if intel.get('latest_news'):
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report_lines.append("")
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report_lines.append(f"**📢 最新动态**: {intel['latest_news']}")
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report_lines.append("")
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# ========== 核心结论 ==========
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core = dashboard.get('core_conclusion', {}) if dashboard else {}
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one_sentence = core.get('one_sentence', result.analysis_summary)
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time_sense = core.get('time_sensitivity', '本周内')
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pos_advice = core.get('position_advice', {})
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report_lines.extend([
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"### 📌 核心结论",
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"",
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f"**{signal_emoji} {signal_text}** | {result.trend_prediction}",
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"",
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f"> **一句话决策**: {one_sentence}",
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"",
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f"⏰ **时效性**: {time_sense}",
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"",
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])
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# 持仓分类建议
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if pos_advice:
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report_lines.extend([
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"| 持仓情况 | 操作建议 |",
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"|---------|---------|",
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f"| 🆕 **空仓者** | {pos_advice.get('no_position', result.operation_advice)} |",
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f"| 💼 **持仓者** | {pos_advice.get('has_position', '继续持有')} |",
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"",
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])
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# ========== 数据透视 ==========
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data_persp = dashboard.get('data_perspective', {}) if dashboard else {}
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if data_persp:
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trend_data = data_persp.get('trend_status', {})
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price_data = data_persp.get('price_position', {})
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vol_data = data_persp.get('volume_analysis', {})
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chip_data = data_persp.get('chip_structure', {})
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report_lines.extend([
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"### 📊 数据透视",
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"",
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])
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# 趋势状态
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if trend_data:
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is_bullish = "✅ 是" if trend_data.get('is_bullish', False) else "❌ 否"
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report_lines.extend([
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f"**均线排列**: {trend_data.get('ma_alignment', 'N/A')} | 多头排列: {is_bullish} | 趋势强度: {trend_data.get('trend_score', 'N/A')}/100",
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"",
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])
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# 价格位置
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if price_data:
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bias_status = price_data.get('bias_status', 'N/A')
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bias_emoji = "✅" if bias_status == "安全" else ("⚠️" if bias_status == "警戒" else "🚨")
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report_lines.extend([
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"| 价格指标 | 数值 |",
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"|---------|------|",
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f"| 当前价 | {price_data.get('current_price', 'N/A')} |",
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f"| MA5 | {price_data.get('ma5', 'N/A')} |",
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f"| MA10 | {price_data.get('ma10', 'N/A')} |",
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f"| MA20 | {price_data.get('ma20', 'N/A')} |",
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f"| 乖离率(MA5) | {price_data.get('bias_ma5', 'N/A')}% {bias_emoji}{bias_status} |",
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f"| 支撑位 | {price_data.get('support_level', 'N/A')} |",
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f"| 压力位 | {price_data.get('resistance_level', 'N/A')} |",
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"",
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])
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# 量能分析
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if vol_data:
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report_lines.extend([
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f"**量能**: 量比 {vol_data.get('volume_ratio', 'N/A')} ({vol_data.get('volume_status', '')}) | 换手率 {vol_data.get('turnover_rate', 'N/A')}%",
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f"💡 *{vol_data.get('volume_meaning', '')}*",
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"",
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])
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# 筹码结构
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if chip_data:
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chip_health = chip_data.get('chip_health', 'N/A')
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chip_emoji = "✅" if chip_health == "健康" else ("⚠️" if chip_health == "一般" else "🚨")
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report_lines.extend([
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f"**筹码**: 获利比例 {chip_data.get('profit_ratio', 'N/A')} | 平均成本 {chip_data.get('avg_cost', 'N/A')} | 集中度 {chip_data.get('concentration', 'N/A')} {chip_emoji}{chip_health}",
|
||
"",
|
||
])
|
||
|
||
# 舆情情报已移至顶部显示
|
||
|
||
# ========== 作战计划 ==========
|
||
battle = dashboard.get('battle_plan', {}) if dashboard else {}
|
||
if battle:
|
||
report_lines.extend([
|
||
"### 🎯 作战计划",
|
||
"",
|
||
])
|
||
|
||
# 狙击点位
|
||
sniper = battle.get('sniper_points', {})
|
||
if sniper:
|
||
report_lines.extend([
|
||
"**📍 狙击点位**",
|
||
"",
|
||
"| 点位类型 | 价格 |",
|
||
"|---------|------|",
|
||
f"| 🎯 理想买入点 | {sniper.get('ideal_buy', 'N/A')} |",
|
||
f"| 🔵 次优买入点 | {sniper.get('secondary_buy', 'N/A')} |",
|
||
f"| 🛑 止损位 | {sniper.get('stop_loss', 'N/A')} |",
|
||
f"| 🎊 目标位 | {sniper.get('take_profit', 'N/A')} |",
|
||
"",
|
||
])
|
||
|
||
# 仓位策略
|
||
position = battle.get('position_strategy', {})
|
||
if position:
|
||
report_lines.extend([
|
||
f"**💰 仓位建议**: {position.get('suggested_position', 'N/A')}",
|
||
f"- 建仓策略: {position.get('entry_plan', 'N/A')}",
|
||
f"- 风控策略: {position.get('risk_control', 'N/A')}",
|
||
"",
|
||
])
|
||
|
||
# 检查清单
|
||
checklist = battle.get('action_checklist', [])
|
||
if checklist:
|
||
report_lines.extend([
|
||
"**✅ 检查清单**",
|
||
"",
|
||
])
|
||
for item in checklist:
|
||
report_lines.append(f"- {item}")
|
||
report_lines.append("")
|
||
|
||
# 如果没有 dashboard，显示传统格式
|
||
if not dashboard:
|
||
# 操作理由
|
||
if result.buy_reason:
|
||
report_lines.extend([
|
||
f"**💡 操作理由**: {result.buy_reason}",
|
||
"",
|
||
])
|
||
|
||
# 风险提示
|
||
if result.risk_warning:
|
||
report_lines.extend([
|
||
f"**⚠️ 风险提示**: {result.risk_warning}",
|
||
"",
|
||
])
|
||
|
||
# 技术面分析
|
||
if result.ma_analysis or result.volume_analysis:
|
||
report_lines.extend([
|
||
"### 📊 技术面",
|
||
"",
|
||
])
|
||
if result.ma_analysis:
|
||
report_lines.append(f"**均线**: {result.ma_analysis}")
|
||
if result.volume_analysis:
|
||
report_lines.append(f"**量能**: {result.volume_analysis}")
|
||
report_lines.append("")
|
||
|
||
# 消息面
|
||
if result.news_summary:
|
||
report_lines.extend([
|
||
"### 📰 消息面",
|
||
f"{result.news_summary}",
|
||
"",
|
||
])
|
||
|
||
report_lines.extend([
|
||
"---",
|
||
"",
|
||
])
|
||
|
||
# 底部（去除免责声明）
|
||
report_lines.extend([
|
||
"",
|
||
f"*报告生成时间：{datetime.now().strftime('%Y-%m-%d %H:%M:%S')}*",
|
||
])
|
||
|
||
return "\n".join(report_lines)
|
||
|
||
def generate_wechat_dashboard(self, results: List[AnalysisResult]) -> str:
|
||
"""
|
||
生成企业微信决策仪表盘精简版（控制在4000字符内）
|
||
|
||
只保留核心结论和狙击点位
|
||
|
||
Args:
|
||
results: 分析结果列表
|
||
|
||
Returns:
|
||
精简版决策仪表盘
|
||
"""
|
||
report_date = datetime.now().strftime('%Y-%m-%d')
|
||
|
||
# 按评分排序
|
||
sorted_results = sorted(results, key=lambda x: x.sentiment_score, reverse=True)
|
||
|
||
# 统计
|
||
buy_count = sum(1 for r in results if r.operation_advice in ['买入', '加仓', '强烈买入'])
|
||
sell_count = sum(1 for r in results if r.operation_advice in ['卖出', '减仓', '强烈卖出'])
|
||
hold_count = sum(1 for r in results if r.operation_advice in ['持有', '观望'])
|
||
|
||
lines = [
|
||
f"## 🎯 {report_date} 决策仪表盘",
|
||
"",
|
||
f"> {len(results)}只股票 | 🟢买入:{buy_count} 🟡观望:{hold_count} 🔴卖出:{sell_count}",
|
||
"",
|
||
]
|
||
|
||
for result in sorted_results:
|
||
signal_text, signal_emoji, _ = self._get_signal_level(result)
|
||
dashboard = result.dashboard if hasattr(result, 'dashboard') and result.dashboard else {}
|
||
core = dashboard.get('core_conclusion', {}) if dashboard else {}
|
||
battle = dashboard.get('battle_plan', {}) if dashboard else {}
|
||
intel = dashboard.get('intelligence', {}) if dashboard else {}
|
||
|
||
# 股票名称
|
||
stock_name = result.name if result.name and not result.name.startswith('股票') else f'股票{result.code}'
|
||
|
||
# 标题行：信号等级 + 股票名称
|
||
lines.append(f"### {signal_emoji} **{signal_text}** | {stock_name}({result.code})")
|
||
lines.append("")
|
||
|
||
# 核心决策（一句话）
|
||
one_sentence = core.get('one_sentence', result.analysis_summary) if core else result.analysis_summary
|
||
if one_sentence:
|
||
lines.append(f"📌 **{one_sentence[:80]}**")
|
||
lines.append("")
|
||
|
||
# 重要信息区（舆情+基本面）
|
||
info_lines = []
|
||
|
||
# 业绩预期
|
||
if intel.get('earnings_outlook'):
|
||
outlook = intel['earnings_outlook'][:60]
|
||
info_lines.append(f"📊 业绩: {outlook}")
|
||
|
||
# 舆情情绪
|
||
if intel.get('sentiment_summary'):
|
||
sentiment = intel['sentiment_summary'][:50]
|
||
info_lines.append(f"💭 舆情: {sentiment}")
|
||
|
||
if info_lines:
|
||
lines.extend(info_lines)
|
||
lines.append("")
|
||
|
||
# 风险警报（最重要，醒目显示）
|
||
risks = intel.get('risk_alerts', []) if intel else []
|
||
if risks:
|
||
lines.append("🚨 **风险**:")
|
||
for risk in risks[:2]: # 最多显示2条
|
||
risk_text = risk[:50] + "..." if len(risk) > 50 else risk
|
||
lines.append(f" • {risk_text}")
|
||
lines.append("")
|
||
|
||
# 利好催化
|
||
catalysts = intel.get('positive_catalysts', []) if intel else []
|
||
if catalysts:
|
||
lines.append("✨ **利好**:")
|
||
for cat in catalysts[:2]: # 最多显示2条
|
||
cat_text = cat[:50] + "..." if len(cat) > 50 else cat
|
||
lines.append(f" • {cat_text}")
|
||
lines.append("")
|
||
|
||
# 狙击点位
|
||
sniper = battle.get('sniper_points', {}) if battle else {}
|
||
if sniper:
|
||
ideal_buy = sniper.get('ideal_buy', '')
|
||
stop_loss = sniper.get('stop_loss', '')
|
||
take_profit = sniper.get('take_profit', '')
|
||
|
||
points = []
|
||
if ideal_buy:
|
||
points.append(f"🎯买点:{ideal_buy[:15]}")
|
||
if stop_loss:
|
||
points.append(f"🛑止损:{stop_loss[:15]}")
|
||
if take_profit:
|
||
points.append(f"🎊目标:{take_profit[:15]}")
|
||
|
||
if points:
|
||
lines.append(" | ".join(points))
|
||
lines.append("")
|
||
|
||
# 持仓建议
|
||
pos_advice = core.get('position_advice', {}) if core else {}
|
||
if pos_advice:
|
||
no_pos = pos_advice.get('no_position', '')
|
||
has_pos = pos_advice.get('has_position', '')
|
||
if no_pos:
|
||
lines.append(f"🆕 空仓者: {no_pos[:50]}")
|
||
if has_pos:
|
||
lines.append(f"💼 持仓者: {has_pos[:50]}")
|
||
lines.append("")
|
||
|
||
# 检查清单简化版
|
||
checklist = battle.get('action_checklist', []) if battle else []
|
||
if checklist:
|
||
# 只显示不通过的项目
|
||
failed_checks = [c for c in checklist if c.startswith('❌') or c.startswith('⚠️')]
|
||
if failed_checks:
|
||
lines.append("**检查未通过项**:")
|
||
for check in failed_checks[:3]:
|
||
lines.append(f" {check[:40]}")
|
||
lines.append("")
|
||
|
||
lines.append("---")
|
||
lines.append("")
|
||
|
||
# 底部
|
||
lines.append(f"*生成时间: {datetime.now().strftime('%H:%M')}*")
|
||
|
||
content = "\n".join(lines)
|
||
|
||
# 检查长度
|
||
if len(content) > 3800:
|
||
logger.warning(f"仪表盘超长({len(content)}字符)，截断")
|
||
content = content[:3800] + "\n...(已截断)"
|
||
|
||
return content
|
||
|
||
def generate_wechat_summary(self, results: List[AnalysisResult]) -> str:
|
||
"""
|
||
生成企业微信精简版日报（控制在4000字符内）
|
||
|
||
Args:
|
||
results: 分析结果列表
|
||
|
||
Returns:
|
||
精简版 Markdown 内容
|
||
"""
|
||
report_date = datetime.now().strftime('%Y-%m-%d')
|
||
|
||
# 按评分排序
|
||
sorted_results = sorted(results, key=lambda x: x.sentiment_score, reverse=True)
|
||
|
||
# 统计
|
||
buy_count = sum(1 for r in results if r.operation_advice in ['买入', '加仓', '强烈买入'])
|
||
sell_count = sum(1 for r in results if r.operation_advice in ['卖出', '减仓', '强烈卖出'])
|
||
hold_count = sum(1 for r in results if r.operation_advice in ['持有', '观望'])
|
||
avg_score = sum(r.sentiment_score for r in results) / len(results) if results else 0
|
||
|
||
lines = [
|
||
f"## 📅 {report_date} A股分析报告",
|
||
"",
|
||
f"> 共 **{len(results)}** 只 | 🟢买入:{buy_count} 🟡持有:{hold_count} 🔴卖出:{sell_count} | 均分:{avg_score:.0f}",
|
||
"",
|
||
]
|
||
|
||
# 每只股票精简信息（控制长度）
|
||
for result in sorted_results:
|
||
emoji = result.get_emoji()
|
||
|
||
# 核心信息行
|
||
lines.append(f"### {emoji} {result.name}({result.code})")
|
||
lines.append(f"**{result.operation_advice}** | 评分:{result.sentiment_score} | {result.trend_prediction}")
|
||
|
||
# 操作理由（截断）
|
||
if hasattr(result, 'buy_reason') and result.buy_reason:
|
||
reason = result.buy_reason[:80] + "..." if len(result.buy_reason) > 80 else result.buy_reason
|
||
lines.append(f"💡 {reason}")
|
||
|
||
# 核心看点
|
||
if hasattr(result, 'key_points') and result.key_points:
|
||
points = result.key_points[:60] + "..." if len(result.key_points) > 60 else result.key_points
|
||
lines.append(f"🎯 {points}")
|
||
|
||
# 风险提示（截断）
|
||
if hasattr(result, 'risk_warning') and result.risk_warning:
|
||
risk = result.risk_warning[:50] + "..." if len(result.risk_warning) > 50 else result.risk_warning
|
||
lines.append(f"⚠️ {risk}")
|
||
|
||
lines.append("")
|
||
|
||
# 底部
|
||
lines.extend([
|
||
"---",
|
||
"*AI生成，仅供参考，不构成投资建议*",
|
||
f"*详细报告见 reports/report_{report_date.replace('-', '')}.md*"
|
||
])
|
||
|
||
content = "\n".join(lines)
|
||
|
||
# 最终检查长度
|
||
if len(content) > 3800:
|
||
logger.warning(f"精简报告仍超长({len(content)}字符)，进行截断")
|
||
content = content[:3800] + "\n\n...(内容过长已截断)"
|
||
|
||
return content
|
||
|
||
def send_to_wechat(self, content: str) -> bool:
|
||
"""
|
||
推送消息到企业微信机器人
|
||
|
||
企业微信 Webhook 消息格式：
|
||
{
|
||
"msgtype": "markdown",
|
||
"markdown": {
|
||
"content": "Markdown 内容"
|
||
}
|
||
}
|
||
|
||
注意：企业微信 Markdown 限制 4096 字符
|
||
|
||
Args:
|
||
content: Markdown 格式的消息内容
|
||
|
||
Returns:
|
||
是否发送成功
|
||
"""
|
||
if not self.is_available():
|
||
logger.warning("企业微信 Webhook 未配置，跳过推送")
|
||
return False
|
||
|
||
# 检查长度
|
||
if len(content) > 4000:
|
||
logger.warning(f"消息内容超长({len(content)}字符)，将截断至4000字符")
|
||
content = content[:3950] + "\n\n...(内容过长已截断，详见完整报告)"
|
||
|
||
try:
|
||
return self._send_single_message(content)
|
||
except Exception as e:
|
||
logger.error(f"发送企业微信消息失败: {e}")
|
||
return False
|
||
|
||
def _send_single_message(self, content: str) -> bool:
|
||
"""发送单条消息"""
|
||
payload = {
|
||
"msgtype": "markdown",
|
||
"markdown": {
|
||
"content": content
|
||
}
|
||
}
|
||
|
||
response = requests.post(
|
||
self._webhook_url,
|
||
json=payload,
|
||
timeout=10
|
||
)
|
||
|
||
if response.status_code == 200:
|
||
result = response.json()
|
||
if result.get('errcode') == 0:
|
||
logger.info("企业微信消息发送成功")
|
||
return True
|
||
else:
|
||
logger.error(f"企业微信返回错误: {result}")
|
||
return False
|
||
else:
|
||
logger.error(f"企业微信请求失败: {response.status_code}")
|
||
return False
|
||
|
||
def _send_chunked_messages(self, content: str, max_length: int) -> bool:
|
||
"""
|
||
分段发送长消息
|
||
|
||
按段落（---）分割，确保每段不超过最大长度
|
||
"""
|
||
# 按分隔线分割
|
||
sections = content.split("\n---\n")
|
||
|
||
current_chunk = []
|
||
current_length = 0
|
||
all_success = True
|
||
chunk_index = 1
|
||
|
||
for section in sections:
|
||
section_with_divider = section + "\n---\n"
|
||
section_length = len(section_with_divider)
|
||
|
||
if current_length + section_length > max_length:
|
||
# 发送当前块
|
||
if current_chunk:
|
||
chunk_content = "\n---\n".join(current_chunk)
|
||
logger.info(f"发送消息块 {chunk_index}...")
|
||
if not self._send_single_message(chunk_content):
|
||
all_success = False
|
||
chunk_index += 1
|
||
|
||
# 重置
|
||
current_chunk = [section]
|
||
current_length = section_length
|
||
else:
|
||
current_chunk.append(section)
|
||
current_length += section_length
|
||
|
||
# 发送最后一块
|
||
if current_chunk:
|
||
chunk_content = "\n---\n".join(current_chunk)
|
||
logger.info(f"发送消息块 {chunk_index}（最后）...")
|
||
if not self._send_single_message(chunk_content):
|
||
all_success = False
|
||
|
||
return all_success
|
||
|
||
def save_report_to_file(
|
||
self,
|
||
content: str,
|
||
filename: Optional[str] = None
|
||
) -> str:
|
||
"""
|
||
保存日报到本地文件
|
||
|
||
Args:
|
||
content: 日报内容
|
||
filename: 文件名（可选，默认按日期生成）
|
||
|
||
Returns:
|
||
保存的文件路径
|
||
"""
|
||
from pathlib import Path
|
||
|
||
if filename is None:
|
||
date_str = datetime.now().strftime('%Y%m%d')
|
||
filename = f"report_{date_str}.md"
|
||
|
||
# 确保 reports 目录存在
|
||
reports_dir = Path(__file__).parent / 'reports'
|
||
reports_dir.mkdir(parents=True, exist_ok=True)
|
||
|
||
filepath = reports_dir / filename
|
||
|
||
with open(filepath, 'w', encoding='utf-8') as f:
|
||
f.write(content)
|
||
|
||
logger.info(f"日报已保存到: {filepath}")
|
||
return str(filepath)
|
||
|
||
|
||
class NotificationBuilder:
|
||
"""
|
||
通知消息构建器
|
||
|
||
提供便捷的消息构建方法
|
||
"""
|
||
|
||
@staticmethod
|
||
def build_simple_alert(
|
||
title: str,
|
||
content: str,
|
||
alert_type: str = "info"
|
||
) -> str:
|
||
"""
|
||
构建简单的提醒消息
|
||
|
||
Args:
|
||
title: 标题
|
||
content: 内容
|
||
alert_type: 类型（info, warning, error, success）
|
||
"""
|
||
emoji_map = {
|
||
"info": "ℹ️",
|
||
"warning": "⚠️",
|
||
"error": "❌",
|
||
"success": "✅",
|
||
}
|
||
emoji = emoji_map.get(alert_type, "📢")
|
||
|
||
return f"{emoji} **{title}**\n\n{content}"
|
||
|
||
@staticmethod
|
||
def build_stock_summary(results: List[AnalysisResult]) -> str:
|
||
"""
|
||
构建股票摘要（简短版）
|
||
|
||
适用于快速通知
|
||
"""
|
||
lines = ["📊 **今日自选股摘要**", ""]
|
||
|
||
for r in sorted(results, key=lambda x: x.sentiment_score, reverse=True):
|
||
emoji = r.get_emoji()
|
||
lines.append(f"{emoji} {r.name}({r.code}): {r.operation_advice} | 评分 {r.sentiment_score}")
|
||
|
||
return "\n".join(lines)
|
||
|
||
|
||
# 便捷函数
|
||
def get_notification_service() -> NotificationService:
|
||
"""获取通知服务实例"""
|
||
return NotificationService()
|
||
|
||
|
||
def send_daily_report(results: List[AnalysisResult]) -> bool:
|
||
"""
|
||
发送每日报告的快捷方式
|
||
|
||
自动生成报告并推送到企业微信
|
||
"""
|
||
service = get_notification_service()
|
||
|
||
# 生成报告
|
||
report = service.generate_daily_report(results)
|
||
|
||
# 保存到本地
|
||
service.save_report_to_file(report)
|
||
|
||
# 推送到企业微信
|
||
return service.send_to_wechat(report)
|
||
|
||
|
||
if __name__ == "__main__":
|
||
# 测试代码
|
||
logging.basicConfig(level=logging.DEBUG)
|
||
|
||
# 模拟分析结果
|
||
test_results = [
|
||
AnalysisResult(
|
||
code='600519',
|
||
name='贵州茅台',
|
||
sentiment_score=75,
|
||
trend_prediction='看多',
|
||
analysis_summary='技术面强势，消息面利好',
|
||
operation_advice='买入',
|
||
technical_analysis='放量突破 MA20，MACD 金叉',
|
||
news_summary='公司发布分红公告，业绩超预期',
|
||
),
|
||
AnalysisResult(
|
||
code='000001',
|
||
name='平安银行',
|
||
sentiment_score=45,
|
||
trend_prediction='震荡',
|
||
analysis_summary='横盘整理，等待方向',
|
||
operation_advice='持有',
|
||
technical_analysis='均线粘合，成交量萎缩',
|
||
news_summary='近期无重大消息',
|
||
),
|
||
AnalysisResult(
|
||
code='300750',
|
||
name='宁德时代',
|
||
sentiment_score=35,
|
||
trend_prediction='看空',
|
||
analysis_summary='技术面走弱，注意风险',
|
||
operation_advice='卖出',
|
||
technical_analysis='跌破 MA10 支撑，量能不足',
|
||
news_summary='行业竞争加剧，毛利率承压',
|
||
),
|
||
]
|
||
|
||
service = NotificationService()
|
||
|
||
# 生成日报
|
||
print("=== 生成日报测试 ===")
|
||
report = service.generate_daily_report(test_results)
|
||
print(report)
|
||
|
||
# 保存到文件
|
||
print("\n=== 保存日报 ===")
|
||
filepath = service.save_report_to_file(report)
|
||
print(f"保存成功: {filepath}")
|
||
|
||
# 推送测试（仅当配置了 Webhook 时）
|
||
if service.is_available():
|
||
print("\n=== 推送测试 ===")
|
||
success = service.send_to_wechat(report)
|
||
print(f"推送结果: {'成功' if success else '失败'}")
|
||
else:
|
||
print("\n企业微信 Webhook 未配置，跳过推送测试")
|