425 lines
17 KiB
Python
425 lines
17 KiB
Python
"""
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报告生成器 - 生成综合分析报告
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"""
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import pandas as pd
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import matplotlib.pyplot as plt
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import seaborn as sns
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import plotly.graph_objects as go
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import plotly.express as px
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from plotly.subplots import make_subplots
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from reportlab.lib.pagesizes import letter, A4
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from reportlab.platypus import SimpleDocTemplate, Paragraph, Spacer, Table, TableStyle, Image
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from reportlab.lib.styles import getSampleStyleSheet, ParagraphStyle
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from reportlab.lib.units import inch
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from reportlab.lib import colors
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from reportlab.lib.enums import TA_CENTER, TA_LEFT, TA_RIGHT
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import os
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from datetime import datetime
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from typing import Dict, List
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import logging
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logger = logging.getLogger(__name__)
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class ReportGenerator:
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def __init__(self, output_dir: str = "reports"):
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self.output_dir = output_dir
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self.chart_dir = os.path.join(output_dir, "charts")
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# 创建输出目录
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os.makedirs(self.output_dir, exist_ok=True)
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os.makedirs(self.chart_dir, exist_ok=True)
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# 设置中文字体
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plt.rcParams['font.sans-serif'] = ['SimHei', 'Arial Unicode MS', 'DejaVu Sans']
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plt.rcParams['axes.unicode_minus'] = False
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def generate_comprehensive_report(self, symbol: str, data: Dict, analysis_results: Dict) -> str:
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"""生成综合分析报告"""
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try:
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# 生成图表
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chart_files = self._generate_charts(symbol, data, analysis_results)
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# 生成PDF报告
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report_file = self._generate_pdf_report(symbol, data, analysis_results, chart_files)
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logger.info(f"报告生成完成: {report_file}")
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return report_file
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except Exception as e:
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logger.error(f"生成报告失败: {e}")
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return ""
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def _generate_charts(self, symbol: str, data: Dict, analysis_results: Dict) -> List[str]:
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"""生成图表"""
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chart_files = []
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try:
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# 股价走势图
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price_chart = self._create_price_chart(symbol, data)
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if price_chart:
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chart_files.append(price_chart)
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# 财务指标雷达图
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radar_chart = self._create_radar_chart(symbol, analysis_results)
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if radar_chart:
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chart_files.append(radar_chart)
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# 估值对比图
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valuation_chart = self._create_valuation_chart(symbol, analysis_results)
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if valuation_chart:
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chart_files.append(valuation_chart)
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# 财务健康度仪表盘
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health_gauge = self._create_health_gauge(symbol, analysis_results)
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if health_gauge:
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chart_files.append(health_gauge)
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except Exception as e:
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logger.error(f"生成图表失败: {e}")
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return chart_files
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def _create_price_chart(self, symbol: str, data: Dict) -> str:
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"""创建股价走势图"""
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try:
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stock_prices = data.get('stock_prices', pd.DataFrame())
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if stock_prices.empty:
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return ""
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fig = go.Figure()
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# 添加收盘价线
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fig.add_trace(go.Scatter(
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x=stock_prices['date'],
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y=stock_prices['close'],
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mode='lines',
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name='收盘价',
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line=dict(color='#1f77b4', width=2)
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))
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# 添加移动平均线
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if len(stock_prices) >= 20:
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stock_prices['MA20'] = stock_prices['close'].rolling(window=20).mean()
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fig.add_trace(go.Scatter(
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x=stock_prices['date'],
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y=stock_prices['MA20'],
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mode='lines',
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name='20日均线',
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line=dict(color='orange', width=1, dash='dash')
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))
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fig.update_layout(
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title=f'{symbol} 股价走势图',
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xaxis_title='日期',
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yaxis_title='价格 (USD)',
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template='plotly_white',
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height=400
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)
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chart_file = os.path.join(self.chart_dir, f'{symbol}_price_chart.html')
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fig.write_html(chart_file)
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return chart_file
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except Exception as e:
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logger.error(f"创建股价图表失败: {e}")
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return ""
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def _create_radar_chart(self, symbol: str, analysis_results: Dict) -> str:
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"""创建雷达图"""
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try:
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categories = ['估值吸引力', '财务健康度', '成长性', '风险控制']
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values = [
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analysis_results.get('valuation_score', 0),
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analysis_results.get('financial_health_score', 0),
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analysis_results.get('growth_score', 0),
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analysis_results.get('risk_score', 0)
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]
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fig = go.Figure()
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fig.add_trace(go.Scatterpolar(
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r=values,
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theta=categories,
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fill='toself',
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name=symbol,
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line_color='blue'
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))
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fig.update_layout(
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polar=dict(
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radialaxis=dict(
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visible=True,
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range=[0, 100]
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)),
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showlegend=True,
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title=f'{symbol} 综合评分雷达图',
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height=400
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)
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chart_file = os.path.join(self.chart_dir, f'{symbol}_radar_chart.html')
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fig.write_html(chart_file)
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return chart_file
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except Exception as e:
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logger.error(f"创建雷达图失败: {e}")
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return ""
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def _create_valuation_chart(self, symbol: str, analysis_results: Dict) -> str:
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"""创建估值对比图"""
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try:
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valuation_data = analysis_results.get('valuation_metrics', {})
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metrics = ['PE比率', 'PB比率', 'PS比率', 'PEG比率']
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values = [
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valuation_data.get('pe_ratio', 0),
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valuation_data.get('pb_ratio', 0),
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valuation_data.get('ps_ratio', 0),
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valuation_data.get('peg_ratio', 0)
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]
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# 行业平均值（示例数据）
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industry_avg = [15, 2.5, 3.0, 1.2]
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fig = go.Figure()
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fig.add_trace(go.Bar(
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name=symbol,
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x=metrics,
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y=values,
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marker_color='lightblue'
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))
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fig.add_trace(go.Bar(
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name='行业平均',
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x=metrics,
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y=industry_avg,
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marker_color='lightcoral'
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))
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fig.update_layout(
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title=f'{symbol} 估值指标对比',
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xaxis_title='指标',
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yaxis_title='数值',
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barmode='group',
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height=400
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)
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chart_file = os.path.join(self.chart_dir, f'{symbol}_valuation_chart.html')
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fig.write_html(chart_file)
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return chart_file
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except Exception as e:
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logger.error(f"创建估值图表失败: {e}")
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return ""
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def _create_health_gauge(self, symbol: str, analysis_results: Dict) -> str:
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"""创建财务健康度仪表盘"""
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try:
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health_score = analysis_results.get('financial_health_score', 0)
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fig = go.Figure(go.Indicator(
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mode = "gauge+number+delta",
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value = health_score,
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domain = {'x': [0, 1], 'y': [0, 1]},
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title = {'text': f"{symbol} 财务健康度"},
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delta = {'reference': 50},
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gauge = {
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'axis': {'range': [None, 100]},
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'bar': {'color': "darkblue"},
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'steps': [
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{'range': [0, 40], 'color': "lightgray"},
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{'range': [40, 70], 'color': "yellow"},
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{'range': [70, 100], 'color': "green"}
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],
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'threshold': {
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'line': {'color': "red", 'width': 4},
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'thickness': 0.75,
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'value': 90
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}
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}
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))
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fig.update_layout(height=300)
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chart_file = os.path.join(self.chart_dir, f'{symbol}_health_gauge.html')
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fig.write_html(chart_file)
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return chart_file
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except Exception as e:
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logger.error(f"创建健康度仪表盘失败: {e}")
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return ""
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def _generate_pdf_report(self, symbol: str, data: Dict, analysis_results: Dict, chart_files: List[str]) -> str:
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"""生成PDF报告"""
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try:
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report_file = os.path.join(self.output_dir, f'{symbol}_analysis_report.pdf')
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doc = SimpleDocTemplate(report_file, pagesize=A4)
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styles = getSampleStyleSheet()
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story = []
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# 标题样式
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title_style = ParagraphStyle(
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'CustomTitle',
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parent=styles['Heading1'],
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fontSize=18,
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spaceAfter=30,
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alignment=TA_CENTER,
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textColor=colors.darkblue
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)
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# 添加标题
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story.append(Paragraph(f"{symbol} 股票分析报告", title_style))
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story.append(Spacer(1, 20))
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# 基本信息
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company_info = data.get('company_info', {})
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story.append(Paragraph("基本信息", styles['Heading2']))
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basic_info_data = [
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['公司名称', company_info.get('name', 'N/A')],
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['行业', company_info.get('industry', 'N/A')],
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['市值', f"${company_info.get('market_cap', 0):,.0f}"],
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['员工数', f"{company_info.get('employees', 0):,}"],
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['分析日期', datetime.now().strftime('%Y-%m-%d %H:%M:%S')]
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]
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basic_info_table = Table(basic_info_data, colWidths=[2*inch, 4*inch])
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basic_info_table.setStyle(TableStyle([
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('BACKGROUND', (0, 0), (-1, 0), colors.grey),
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('TEXTCOLOR', (0, 0), (-1, 0), colors.whitesmoke),
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('ALIGN', (0, 0), (-1, -1), 'LEFT'),
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('FONTNAME', (0, 0), (-1, 0), 'Helvetica-Bold'),
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('FONTSIZE', (0, 0), (-1, 0), 12),
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('BOTTOMPADDING', (0, 0), (-1, 0), 12),
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('BACKGROUND', (0, 1), (-1, -1), colors.beige),
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('GRID', (0, 0), (-1, -1), 1, colors.black)
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]))
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story.append(basic_info_table)
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story.append(Spacer(1, 20))
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# 分析结果
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story.append(Paragraph("分析结果", styles['Heading2']))
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# 评分表格
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scores_data = [
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['分析维度', '评分', '评级'],
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['估值吸引力', f"{analysis_results.get('valuation_score', 0):.1f}/100", self._get_rating(analysis_results.get('valuation_score', 0))],
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['财务健康度', f"{analysis_results.get('financial_health_score', 0):.1f}/100", self._get_rating(analysis_results.get('financial_health_score', 0))],
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['成长性', f"{analysis_results.get('growth_score', 0):.1f}/100", self._get_rating(analysis_results.get('growth_score', 0))],
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['风险控制', f"{analysis_results.get('risk_score', 0):.1f}/100", self._get_rating(analysis_results.get('risk_score', 0))],
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['综合评分', f"{analysis_results.get('overall_score', 0):.1f}/100", self._get_rating(analysis_results.get('overall_score', 0))]
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]
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scores_table = Table(scores_data, colWidths=[2*inch, 1.5*inch, 1.5*inch])
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scores_table.setStyle(TableStyle([
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('BACKGROUND', (0, 0), (-1, 0), colors.grey),
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('TEXTCOLOR', (0, 0), (-1, 0), colors.whitesmoke),
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('ALIGN', (0, 0), (-1, -1), 'CENTER'),
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('FONTNAME', (0, 0), (-1, 0), 'Helvetica-Bold'),
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('FONTSIZE', (0, 0), (-1, 0), 12),
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('BOTTOMPADDING', (0, 0), (-1, 0), 12),
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('BACKGROUND', (0, 1), (-1, -1), colors.beige),
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('GRID', (0, 0), (-1, -1), 1, colors.black)
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]))
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story.append(scores_table)
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story.append(Spacer(1, 20))
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# 投资建议
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recommendation = analysis_results.get('investment_recommendation', {})
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story.append(Paragraph("投资建议", styles['Heading2']))
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story.append(Paragraph(f"<b>建议:</b> {recommendation.get('recommendation', 'N/A')}", styles['Normal']))
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story.append(Paragraph(f"<b>信心度:</b> {recommendation.get('confidence', 'N/A')}", styles['Normal']))
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story.append(Paragraph(f"<b>综合评分:</b> {recommendation.get('overall_score', 0):.1f}/100", styles['Normal']))
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# 关键优势
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strengths = recommendation.get('key_strengths', [])
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if strengths:
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story.append(Spacer(1, 10))
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story.append(Paragraph("关键优势:", styles['Heading3']))
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for strength in strengths:
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story.append(Paragraph(f"• {strength}", styles['Normal']))
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# 关键担忧
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concerns = recommendation.get('key_concerns', [])
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if concerns:
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story.append(Spacer(1, 10))
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story.append(Paragraph("关键担忧:", styles['Heading3']))
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for concern in concerns:
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story.append(Paragraph(f"• {concern}", styles['Normal']))
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# 风险提示
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risk_warnings = recommendation.get('risk_warnings', [])
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if risk_warnings:
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story.append(Spacer(1, 10))
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story.append(Paragraph("风险提示:", styles['Heading3']))
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for warning in risk_warnings:
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story.append(Paragraph(f"⚠️ {warning}", styles['Normal']))
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story.append(Spacer(1, 20))
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# 免责声明
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story.append(Paragraph("免责声明", styles['Heading2']))
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disclaimer = """
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本报告仅供投资参考，不构成投资建议。投资有风险，入市需谨慎。
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投资者应根据自身情况做出投资决策，并承担相应风险。
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本报告基于公开信息分析，可能存在信息滞后或不准确的情况。
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"""
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story.append(Paragraph(disclaimer, styles['Normal']))
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# 构建PDF
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doc.build(story)
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return report_file
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except Exception as e:
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logger.error(f"生成PDF报告失败: {e}")
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return ""
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def _get_rating(self, score: float) -> str:
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"""根据分数获取评级"""
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if score >= 90:
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return "优秀"
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elif score >= 80:
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return "良好"
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elif score >= 70:
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return "中等"
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elif score >= 60:
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return "一般"
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else:
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return "较差"
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def generate_summary_report(self, symbol: str, analysis_results: Dict) -> str:
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"""生成简要报告（文本格式）"""
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try:
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recommendation = analysis_results.get('investment_recommendation', {})
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summary = f"""
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=== {symbol} 股票分析摘要 ===
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📊 综合评分: {analysis_results.get('overall_score', 0):.1f}/100
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💡 投资建议: {recommendation.get('recommendation', 'N/A')}
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🎯 信心度: {recommendation.get('confidence', 'N/A')}
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📈 各维度评分:
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• 估值吸引力: {analysis_results.get('valuation_score', 0):.1f}/100
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• 财务健康度: {analysis_results.get('financial_health_score', 0):.1f}/100
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• 成长性: {analysis_results.get('growth_score', 0):.1f}/100
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• 风险控制: {analysis_results.get('risk_score', 0):.1f}/100
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✅ 关键优势:
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{chr(10).join([f"• {s}" for s in recommendation.get('key_strengths', [])])}
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⚠️ 关键担忧:
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{chr(10).join([f"• {c}" for c in recommendation.get('key_concerns', [])])}
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🚨 风险提示:
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{chr(10).join([f"• {w}" for w in recommendation.get('risk_warnings', [])])}
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分析时间: {datetime.now().strftime('%Y-%m-%d %H:%M:%S')}
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"""
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# 保存简要报告
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summary_file = os.path.join(self.output_dir, f'{symbol}_summary.txt')
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with open(summary_file, 'w', encoding='utf-8') as f:
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f.write(summary)
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return summary_file
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except Exception as e:
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logger.error(f"生成简要报告失败: {e}")
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return "" |