oficcejo
493 lines
18 KiB
Python
493 lines
18 KiB
Python
"""
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智瞰龙虎PDF报告生成模块
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"""
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from reportlab.lib import colors
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from reportlab.lib.pagesizes import A4
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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.platypus import SimpleDocTemplate, Paragraph, Spacer, Table, TableStyle, PageBreak
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from reportlab.pdfbase import pdfmetrics
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from reportlab.pdfbase.ttfonts import TTFont
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from reportlab.lib.enums import TA_CENTER, TA_LEFT, TA_JUSTIFY
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from datetime import datetime
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import os
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import tempfile
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class LonghubangPDFGenerator:
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"""龙虎榜PDF报告生成器"""
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def __init__(self):
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"""初始化PDF生成器"""
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self.setup_fonts()
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def setup_fonts(self):
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"""设置中文字体"""
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try:
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# 尝试注册常见的中文字体
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font_paths = [
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'C:/Windows/Fonts/msyh.ttc', # 微软雅黑
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'C:/Windows/Fonts/simsun.ttc', # 宋体
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'C:/Windows/Fonts/simhei.ttf', # 黑体
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]
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for font_path in font_paths:
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if os.path.exists(font_path):
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try:
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pdfmetrics.registerFont(TTFont('ChineseFont', font_path))
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self.chinese_font = 'ChineseFont'
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print(f"[PDF] 成功加载字体: {font_path}")
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return
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except:
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continue
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# 如果都失败，使用默认字体
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self.chinese_font = 'Helvetica'
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print("[PDF] 警告: 未找到中文字体，使用默认字体")
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except Exception as e:
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print(f"[PDF] 字体设置失败: {e}")
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self.chinese_font = 'Helvetica'
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def generate_pdf(self, result_data: dict, output_path: str = None) -> str:
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"""
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生成龙虎榜分析PDF报告
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Args:
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result_data: 分析结果数据
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output_path: 输出路径，如果为None则生成临时文件
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Returns:
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PDF文件路径
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"""
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try:
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# 如果没有指定输出路径，创建临时文件
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if output_path is None:
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temp_dir = tempfile.gettempdir()
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timestamp = datetime.now().strftime("%Y%m%d_%H%M%S")
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output_path = os.path.join(temp_dir, f"智瞰龙虎报告_{timestamp}.pdf")
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# 创建PDF文档
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doc = SimpleDocTemplate(
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output_path,
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pagesize=A4,
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rightMargin=0.5*inch,
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leftMargin=0.5*inch,
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topMargin=0.5*inch,
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bottomMargin=0.5*inch
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)
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# 构建内容
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story = []
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# 添加标题页
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story.extend(self._create_title_page(result_data))
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story.append(PageBreak())
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# 添加数据概况
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story.extend(self._create_data_overview(result_data))
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story.append(PageBreak())
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# 添加推荐股票
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story.extend(self._create_recommended_stocks(result_data))
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story.append(PageBreak())
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# 添加AI分析师报告
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story.extend(self._create_agents_analysis(result_data))
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# 生成PDF
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doc.build(story)
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print(f"[PDF] 龙虎榜报告生成成功: {output_path}")
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return output_path
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except Exception as e:
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print(f"[PDF] 生成失败: {e}")
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import traceback
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traceback.print_exc()
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raise
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def _get_styles(self) -> dict:
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"""获取样式"""
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styles = getSampleStyleSheet()
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# 自定义样式
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custom_styles = {
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'Title': ParagraphStyle(
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'CustomTitle',
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parent=styles['Heading1'],
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fontSize=24,
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textColor=colors.HexColor('#1f4788'),
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spaceAfter=30,
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alignment=TA_CENTER,
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fontName=self.chinese_font
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),
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'Heading1': ParagraphStyle(
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'CustomHeading1',
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parent=styles['Heading1'],
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fontSize=16,
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textColor=colors.HexColor('#1f4788'),
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spaceAfter=12,
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spaceBefore=12,
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fontName=self.chinese_font
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),
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'Heading2': ParagraphStyle(
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'CustomHeading2',
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parent=styles['Heading2'],
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fontSize=14,
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textColor=colors.HexColor('#2c5aa0'),
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spaceAfter=10,
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spaceBefore=10,
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fontName=self.chinese_font
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),
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'Heading3': ParagraphStyle(
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'CustomHeading3',
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parent=styles['Heading3'],
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fontSize=12,
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textColor=colors.HexColor('#3d6db5'),
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spaceAfter=8,
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spaceBefore=8,
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fontName=self.chinese_font
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),
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'Normal': ParagraphStyle(
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'CustomNormal',
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parent=styles['Normal'],
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fontSize=10,
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leading=14,
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fontName=self.chinese_font,
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alignment=TA_JUSTIFY
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),
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'Small': ParagraphStyle(
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'CustomSmall',
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parent=styles['Normal'],
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fontSize=9,
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leading=12,
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fontName=self.chinese_font
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)
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}
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return custom_styles
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def _create_title_page(self, data: dict) -> list:
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"""创建标题页"""
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styles = self._get_styles()
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elements = []
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# 添加空白
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elements.append(Spacer(1, 2*inch))
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# 主标题
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title = Paragraph("智瞰龙虎榜分析报告", styles['Title'])
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elements.append(title)
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elements.append(Spacer(1, 0.5*inch))
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# 副标题
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subtitle = Paragraph("AI驱动的龙虎榜多维度分析系统", styles['Heading2'])
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elements.append(subtitle)
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elements.append(Spacer(1, 1*inch))
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# 报告信息
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timestamp = data.get('timestamp', datetime.now().strftime('%Y-%m-%d %H:%M:%S'))
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data_info = data.get('data_info', {})
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info_text = f"""
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<para align=center>
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<b>生成时间:</b> {timestamp}<br/>
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<b>数据记录:</b> {data_info.get('total_records', 0)} 条<br/>
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<b>涉及股票:</b> {data_info.get('total_stocks', 0)} 只<br/>
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<b>涉及游资:</b> {data_info.get('total_youzi', 0)} 个<br/>
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<b>AI分析师:</b> 5位专业分析师团队<br/>
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<b>分析模型:</b> DeepSeek AI Multi-Agent System
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</para>
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"""
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info = Paragraph(info_text, styles['Normal'])
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elements.append(info)
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elements.append(Spacer(1, 1*inch))
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# 免责声明
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disclaimer = Paragraph(
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"<para align=center><i>本报告由AI系统基于龙虎榜公开数据自动生成，仅供参考，不构成投资建议。<br/>"
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"市场有风险，投资需谨慎。请投资者独立判断并承担投资风险。</i></para>",
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styles['Normal']
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)
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elements.append(disclaimer)
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return elements
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def _create_data_overview(self, data: dict) -> list:
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"""创建数据概况部分"""
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styles = self._get_styles()
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elements = []
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# 标题
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elements.append(Paragraph("一、数据概况", styles['Heading1']))
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elements.append(Spacer(1, 0.2*inch))
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data_info = data.get('data_info', {})
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summary = data_info.get('summary', {})
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# 基本统计
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overview_text = f"""
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<para>
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本次分析共涵盖 <b>{data_info.get('total_records', 0)}</b> 条龙虎榜记录，
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涉及 <b>{data_info.get('total_stocks', 0)}</b> 只股票和
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<b>{data_info.get('total_youzi', 0)}</b> 个游资席位。<br/><br/>
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<b>资金概况:</b><br/>
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• 总买入金额: {summary.get('total_buy_amount', 0):,.2f} 元<br/>
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• 总卖出金额: {summary.get('total_sell_amount', 0):,.2f} 元<br/>
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• 净流入金额: {summary.get('total_net_inflow', 0):,.2f} 元
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</para>
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"""
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elements.append(Paragraph(overview_text, styles['Normal']))
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elements.append(Spacer(1, 0.3*inch))
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# TOP游资
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if summary.get('top_youzi'):
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elements.append(Paragraph("1.1 活跃游资 TOP10", styles['Heading2']))
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elements.append(Spacer(1, 0.1*inch))
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table_data = [['排名', '游资名称', '净流入金额(元)']]
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for idx, (name, amount) in enumerate(list(summary['top_youzi'].items())[:10], 1):
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table_data.append([str(idx), name, f"{amount:,.2f}"])
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table = Table(table_data, colWidths=[0.8*inch, 3.5*inch, 2*inch])
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table.setStyle(TableStyle([
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('BACKGROUND', (0, 0), (-1, 0), colors.HexColor('#1f4788')),
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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, -1), self.chinese_font),
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('FONTSIZE', (0, 0), (-1, 0), 10),
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('FONTSIZE', (0, 1), (-1, -1), 9),
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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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elements.append(table)
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elements.append(Spacer(1, 0.3*inch))
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# TOP股票
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if summary.get('top_stocks'):
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elements.append(Paragraph("1.2 资金净流入 TOP20 股票", styles['Heading2']))
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elements.append(Spacer(1, 0.1*inch))
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table_data = [['排名', '股票代码', '股票名称', '净流入金额(元)']]
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for idx, stock in enumerate(summary['top_stocks'][:20], 1):
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table_data.append([
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str(idx),
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stock['code'],
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stock['name'],
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f"{stock['net_inflow']:,.2f}"
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])
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table = Table(table_data, colWidths=[0.8*inch, 1.2*inch, 2*inch, 2.3*inch])
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table.setStyle(TableStyle([
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('BACKGROUND', (0, 0), (-1, 0), colors.HexColor('#1f4788')),
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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, -1), self.chinese_font),
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('FONTSIZE', (0, 0), (-1, 0), 10),
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('FONTSIZE', (0, 1), (-1, -1), 8),
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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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elements.append(table)
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elements.append(Spacer(1, 0.3*inch))
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# 热门概念
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if summary.get('hot_concepts'):
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elements.append(Paragraph("1.3 热门概念 TOP15", styles['Heading2']))
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elements.append(Spacer(1, 0.1*inch))
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concepts_text = ""
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for idx, (concept, count) in enumerate(list(summary['hot_concepts'].items())[:15], 1):
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concepts_text += f"{idx}. {concept} ({count}次) "
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if idx % 3 == 0:
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concepts_text += "<br/>"
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elements.append(Paragraph(concepts_text, styles['Normal']))
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return elements
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def _create_recommended_stocks(self, data: dict) -> list:
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"""创建推荐股票部分"""
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styles = self._get_styles()
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elements = []
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# 标题
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elements.append(Paragraph("二、AI推荐股票", styles['Heading1']))
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elements.append(Spacer(1, 0.2*inch))
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recommended = data.get('recommended_stocks', [])
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if not recommended:
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elements.append(Paragraph("暂无推荐股票", styles['Normal']))
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return elements
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# 说明
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intro_text = f"""
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<para>
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基于5位AI分析师的综合分析，系统识别出以下 <b>{len(recommended)}</b> 只潜力股票，
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这些股票在资金流向、游资关注度、题材热度等多个维度表现突出。
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</para>
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"""
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elements.append(Paragraph(intro_text, styles['Normal']))
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elements.append(Spacer(1, 0.2*inch))
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# 推荐股票表格
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table_data = [['排名', '股票代码', '股票名称', '净流入金额', '确定性', '持有周期']]
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for stock in recommended[:10]:
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table_data.append([
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str(stock.get('rank', '-')),
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stock.get('code', '-'),
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stock.get('name', '-'),
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f"{stock.get('net_inflow', 0):,.0f}",
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stock.get('confidence', '-'),
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stock.get('hold_period', '-')
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])
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table = Table(table_data, colWidths=[0.7*inch, 1.2*inch, 1.5*inch, 1.5*inch, 0.9*inch, 1*inch])
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table.setStyle(TableStyle([
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('BACKGROUND', (0, 0), (-1, 0), colors.HexColor('#1f4788')),
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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, -1), self.chinese_font),
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('FONTSIZE', (0, 0), (-1, 0), 9),
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('FONTSIZE', (0, 1), (-1, -1), 8),
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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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elements.append(table)
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elements.append(Spacer(1, 0.3*inch))
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# 详细推荐理由
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elements.append(Paragraph("2.1 推荐理由详解", styles['Heading2']))
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elements.append(Spacer(1, 0.1*inch))
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for stock in recommended[:5]: # 只详细展示前5只
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stock_text = f"""
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<para>
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<b>{stock.get('rank', '-')}. {stock.get('name', '-')} ({stock.get('code', '-')})</b><br/>
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推荐理由: {stock.get('reason', '暂无')}<br/>
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确定性: {stock.get('confidence', '-')} | 持有周期: {stock.get('hold_period', '-')}
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</para>
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"""
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elements.append(Paragraph(stock_text, styles['Small']))
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elements.append(Spacer(1, 0.1*inch))
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return elements
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def _create_agents_analysis(self, data: dict) -> list:
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"""创建AI分析师报告部分"""
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styles = self._get_styles()
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elements = []
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agents_analysis = data.get('agents_analysis', {})
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if not agents_analysis:
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return elements
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# 标题
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elements.append(Paragraph("三、AI分析师报告", styles['Heading1']))
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elements.append(Spacer(1, 0.2*inch))
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# 分析师介绍
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intro_text = """
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<para>
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本报告由5位AI专业分析师从不同维度进行分析，综合形成投资建议：<br/>
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• <b>游资行为分析师</b> - 分析游资操作特征和意图<br/>
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• <b>个股潜力分析师</b> - 挖掘次日大概率上涨的股票<br/>
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• <b>题材追踪分析师</b> - 识别热点题材和轮动机会<br/>
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• <b>风险控制专家</b> - 识别高风险股票和市场陷阱<br/>
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• <b>首席策略师</b> - 综合研判并给出最终建议
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</para>
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"""
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elements.append(Paragraph(intro_text, styles['Normal']))
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elements.append(Spacer(1, 0.3*inch))
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# 各分析师报告
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agent_titles = {
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'youzi': '3.1 游资行为分析师',
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'stock': '3.2 个股潜力分析师',
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'theme': '3.3 题材追踪分析师',
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'risk': '3.4 风险控制专家',
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'chief': '3.5 首席策略师综合研判'
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}
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for agent_key, agent_title in agent_titles.items():
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agent_data = agents_analysis.get(agent_key, {})
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if agent_data:
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elements.append(Paragraph(agent_title, styles['Heading2']))
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elements.append(Spacer(1, 0.1*inch))
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analysis_text = agent_data.get('analysis', '暂无分析')
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# 截断过长的文本
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if len(analysis_text) > 3000:
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analysis_text = analysis_text[:3000] + "\n...(内容过长，已截断)"
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elements.append(Paragraph(analysis_text, styles['Small']))
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elements.append(Spacer(1, 0.2*inch))
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if agent_key != 'chief':
|
||
elements.append(PageBreak())
|
||
|
||
return elements
|
||
|
||
|
||
# 测试函数
|
||
if __name__ == "__main__":
|
||
print("=" * 60)
|
||
print("测试智瞰龙虎PDF生成模块")
|
||
print("=" * 60)
|
||
|
||
# 创建测试数据
|
||
test_data = {
|
||
'timestamp': '2024-01-15 18:30:00',
|
||
'data_info': {
|
||
'total_records': 150,
|
||
'total_stocks': 50,
|
||
'total_youzi': 30,
|
||
'summary': {
|
||
'total_buy_amount': 500000000,
|
||
'total_sell_amount': 200000000,
|
||
'total_net_inflow': 300000000,
|
||
'top_youzi': {
|
||
'92科比': 14455321,
|
||
'赵老哥': 12000000
|
||
},
|
||
'top_stocks': [
|
||
{'code': '001337', 'name': '四川黄金', 'net_inflow': 14455321}
|
||
],
|
||
'hot_concepts': {
|
||
'黄金概念': 10,
|
||
'新能源': 8
|
||
}
|
||
}
|
||
},
|
||
'recommended_stocks': [
|
||
{
|
||
'rank': 1,
|
||
'code': '001337',
|
||
'name': '四川黄金',
|
||
'net_inflow': 14455321,
|
||
'reason': '游资大幅买入',
|
||
'confidence': '高',
|
||
'hold_period': '短线'
|
||
}
|
||
],
|
||
'agents_analysis': {
|
||
'chief': {
|
||
'analysis': '综合分析显示...'
|
||
}
|
||
}
|
||
}
|
||
|
||
# 生成PDF
|
||
generator = LonghubangPDFGenerator()
|
||
pdf_path = generator.generate_pdf(test_data)
|
||
print(f"\nPDF已生成: {pdf_path}")
|
||
|