backend/export.py

"""Export functionality for portfolio analyses.

Provides PDF and CSV export capabilities for analysis results.
"""

import io
from typing import Dict, Any, List, Optional
from decimal import Decimal
from datetime import datetime
import csv
import logging

from reportlab.lib import colors
from reportlab.lib.pagesizes import letter, A4
from reportlab.platypus import SimpleDocTemplate, Table, TableStyle, Paragraph, Spacer, PageBreak
from reportlab.lib.styles import getSampleStyleSheet, ParagraphStyle
from reportlab.lib.units import inch

logger = logging.getLogger(__name__)


def export_analysis_to_csv(analysis_results: Dict[str, Any]) -> str:
    """Export analysis results to CSV format.

    Args:
        analysis_results: Complete analysis results dictionary

    Returns:
        CSV string ready for download
    """
    output = io.StringIO()
    writer = csv.writer(output)

    # Headers
    writer.writerow(["Portfolio Analysis Export"])
    writer.writerow(["Generated:", datetime.now().isoformat()])
    writer.writerow([])

    # Holdings
    writer.writerow(["Portfolio Holdings"])
    writer.writerow(["Ticker", "Quantity", "Market Value", "Weight %"])

    holdings = analysis_results.get('holdings', [])
    for holding in holdings:
        ticker = holding.get('ticker', '')
        quantity = holding.get('quantity', 0)
        market_value = holding.get('market_value', 0)
        weight = holding.get('weight', 0) * 100

        writer.writerow([ticker, quantity, f"£{market_value:,.2f}", f"{weight:.2f}%"])

    writer.writerow([])

    # Key Metrics
    writer.writerow(["Key Metrics"])
    risk_analysis = analysis_results.get('risk_analysis', {})
    risk_metrics = risk_analysis.get('risk_metrics', {})

    writer.writerow(["Metric", "Value"])
    writer.writerow(["Sharpe Ratio", risk_metrics.get('sharpe_ratio', 'N/A')])

    volatility = risk_metrics.get('volatility_annual', 0)
    if isinstance(volatility, (int, float)):
        writer.writerow(["Volatility", f"{volatility*100:.2f}%"])
    else:
        writer.writerow(["Volatility", str(volatility)])

    var_95 = risk_analysis.get('var_95', {})
    var_value = var_95.get('var_percentage', 'N/A') if isinstance(var_95, dict) else var_95
    writer.writerow(["VaR (95%)", f"{var_value}%"])

    cvar_95 = risk_analysis.get('cvar_95', {})
    cvar_value = cvar_95.get('cvar_percentage', 'N/A') if isinstance(cvar_95, dict) else cvar_95
    writer.writerow(["CVaR (95%)", f"{cvar_value}%"])

    writer.writerow([])

    # AI Synthesis
    writer.writerow(["AI Analysis"])
    ai_synthesis = analysis_results.get('ai_synthesis', '')
    if ai_synthesis:
        # Split into lines for better CSV formatting
        for line in ai_synthesis.split('\n'):
            if line.strip():
                writer.writerow([line.strip()])

    writer.writerow([])

    # Recommendations
    writer.writerow(["Recommendations"])
    recommendations = analysis_results.get('recommendations', [])
    for i, rec in enumerate(recommendations, 1):
        writer.writerow([f"{i}.", rec])

    return output.getvalue()


def export_analysis_to_pdf(analysis_results: Dict[str, Any]) -> bytes:
    """Export analysis results to PDF format.

    Args:
        analysis_results: Complete analysis results dictionary

    Returns:
        PDF bytes ready for download
    """
    buffer = io.BytesIO()
    doc = SimpleDocTemplate(buffer, pagesize=letter)
    story = []
    styles = getSampleStyleSheet()

    # Title
    title_style = ParagraphStyle(
        'CustomTitle',
        parent=styles['Heading1'],
        fontSize=24,
        textColor=colors.HexColor('#05478A'),
        spaceAfter=30,
    )
    story.append(Paragraph("Portfolio Analysis Report", title_style))
    story.append(Paragraph(f"Generated: {datetime.now().strftime('%Y-%m-%d %H:%M')}", styles['Normal']))
    story.append(Spacer(1, 0.5*inch))

    # Holdings Table
    story.append(Paragraph("Portfolio Holdings", styles['Heading2']))

    holdings = analysis_results.get('holdings', [])
    holdings_data = [["Ticker", "Quantity", "Market Value", "Weight %"]]

    for holding in holdings:
        ticker = holding.get('ticker', '')
        quantity = holding.get('quantity', 0)
        market_value = holding.get('market_value', 0)
        weight = holding.get('weight', 0) * 100

        holdings_data.append([
            ticker,
            f"{quantity:.2f}",
            f"£{market_value:,.2f}",
            f"{weight:.2f}%"
        ])

    holdings_table = Table(holdings_data)
    holdings_table.setStyle(TableStyle([
        ('BACKGROUND', (0, 0), (-1, 0), colors.HexColor('#05478A')),
        ('TEXTCOLOR', (0, 0), (-1, 0), colors.whitesmoke),
        ('ALIGN', (0, 0), (-1, -1), 'CENTER'),
        ('FONTNAME', (0, 0), (-1, 0), 'Helvetica-Bold'),
        ('FONTSIZE', (0, 0), (-1, 0), 12),
        ('BOTTOMPADDING', (0, 0), (-1, 0), 12),
        ('BACKGROUND', (0, 1), (-1, -1), colors.beige),
        ('GRID', (0, 0), (-1, -1), 1, colors.black)
    ]))

    story.append(holdings_table)
    story.append(Spacer(1, 0.5*inch))

    # Key Metrics
    story.append(Paragraph("Key Metrics", styles['Heading2']))

    risk_analysis = analysis_results.get('risk_analysis', {})
    risk_metrics = risk_analysis.get('risk_metrics', {})

    metrics_data = [["Metric", "Value"]]
    metrics_data.append(["Sharpe Ratio", f"{risk_metrics.get('sharpe_ratio', 0):.3f}"])

    volatility = risk_metrics.get('volatility_annual', 0)
    if isinstance(volatility, (int, float)):
        metrics_data.append(["Volatility", f"{volatility*100:.2f}%"])
    else:
        metrics_data.append(["Volatility", str(volatility)])

    var_95 = risk_analysis.get('var_95', {})
    var_value = var_95.get('var_percentage', 0) if isinstance(var_95, dict) else var_95
    metrics_data.append(["VaR (95%)", f"{var_value:.2f}%"])

    cvar_95 = risk_analysis.get('cvar_95', {})
    cvar_value = cvar_95.get('cvar_percentage', 0) if isinstance(cvar_95, dict) else cvar_95
    metrics_data.append(["CVaR (95%)", f"{cvar_value:.2f}%"])

    metrics_table = Table(metrics_data)
    metrics_table.setStyle(TableStyle([
        ('BACKGROUND', (0, 0), (-1, 0), colors.HexColor('#048CFC')),
        ('TEXTCOLOR', (0, 0), (-1, 0), colors.whitesmoke),
        ('ALIGN', (0, 0), (-1, -1), 'LEFT'),
        ('FONTNAME', (0, 0), (-1, 0), 'Helvetica-Bold'),
        ('FONTSIZE', (0, 0), (-1, 0), 12),
        ('BOTTOMPADDING', (0, 0), (-1, 0), 12),
        ('BACKGROUND', (0, 1), (-1, -1), colors.lightblue),
        ('GRID', (0, 0), (-1, -1), 1, colors.black)
    ]))

    story.append(metrics_table)
    story.append(Spacer(1, 0.5*inch))

    # AI Synthesis
    story.append(Paragraph("AI Analysis", styles['Heading2']))
    ai_synthesis = analysis_results.get('ai_synthesis', '')
    if ai_synthesis:
        # Clean and format the text
        paragraphs = ai_synthesis.split('\n\n')
        for para in paragraphs:
            if para.strip():
                story.append(Paragraph(para.strip(), styles['Normal']))
                story.append(Spacer(1, 0.1*inch))

    # Recommendations
    story.append(Spacer(1, 0.3*inch))
    story.append(Paragraph("Recommendations", styles['Heading2']))
    recommendations = analysis_results.get('recommendations', [])
    for i, rec in enumerate(recommendations, 1):
        story.append(Paragraph(f"{i}. {rec}", styles['Normal']))
        story.append(Spacer(1, 0.1*inch))

    # Build PDF
    try:
        doc.build(story)
    except Exception as e:
        logger.error(f"Failed to build PDF: {e}")
        raise

    buffer.seek(0)
    return buffer.getvalue()