"""
Multi-format document processor for resumes and cover letters
Supports: Word, PDF, Text, PowerPoint for both input and output
"""

import os
import io
import logging
from pathlib import Path
from typing import Dict, Any, Optional, List, Tuple
from datetime import datetime
import json
import re
import zipfile

# Document processing libraries
try:
    from docx import Document
    from docx.shared import Pt, Inches, RGBColor
    from docx.enum.text import WD_ALIGN_PARAGRAPH
    DOCX_AVAILABLE = True
except ImportError:
    DOCX_AVAILABLE = False

try:
    from pptx import Presentation
    from pptx.util import Inches, Pt
    from pptx.enum.text import PP_ALIGN
    PPTX_AVAILABLE = True
except ImportError:
    PPTX_AVAILABLE = False

try:
    import PyPDF2
    from PyPDF2 import PdfReader
    PDF_READ_AVAILABLE = True
except ImportError:
    PDF_READ_AVAILABLE = False

try:
    from reportlab.lib.pagesizes import letter, A4
    from reportlab.lib.styles import getSampleStyleSheet, ParagraphStyle
    from reportlab.lib.units import inch
    from reportlab.platypus import SimpleDocTemplate, Paragraph, Spacer, Table, TableStyle
    from reportlab.lib import colors
    from reportlab.lib.enums import TA_CENTER, TA_LEFT, TA_JUSTIFY
    PDF_WRITE_AVAILABLE = True
except ImportError:
    PDF_WRITE_AVAILABLE = False

logger = logging.getLogger(__name__)

class DocumentProcessor:
    """Handles multiple document formats for resume/CV processing"""
    
    def __init__(self):
        self.supported_input_formats = []
        self.supported_output_formats = ['txt']  # Text always available
        
        if DOCX_AVAILABLE:
            self.supported_input_formats.append('docx')
            self.supported_output_formats.append('docx')
        if PPTX_AVAILABLE:
            self.supported_input_formats.append('pptx')
            self.supported_output_formats.append('pptx')
        if PDF_READ_AVAILABLE:
            self.supported_input_formats.append('pdf')
        if PDF_WRITE_AVAILABLE:
            self.supported_output_formats.append('pdf')
            
        logger.info(f"Document processor initialized - Input formats: {self.supported_input_formats}, Output formats: {self.supported_output_formats}")
    
    def extract_from_file(self, file_path: str) -> Dict[str, Any]:
        """Extract structured data from uploaded resume file"""
        file_ext = Path(file_path).suffix.lower().replace('.', '')
        
        if file_ext == 'docx':
            if DOCX_AVAILABLE:
                return self._extract_from_docx(file_path)
            else:
                # Fallback: parse DOCX as zip and extract XML text
                return self._extract_docx_zip_fallback(file_path)
        elif file_ext == 'pdf':
            if PDF_READ_AVAILABLE:
                return self._extract_from_pdf(file_path)
            else:
                logger.warning("PDF reader not available; returning empty parse")
                return {"full_text": "", "contact": {}, "summary": "", "experience": [], "education": [], "skills": []}
        elif file_ext == 'pptx':
            if PPTX_AVAILABLE:
                return self._extract_from_pptx(file_path)
            else:
                logger.warning("PPTX reader not available; returning empty parse")
                return {"full_text": "", "contact": {}, "summary": "", "experience": [], "education": [], "skills": []}
        elif file_ext in ['txt', 'text']:
            return self._extract_from_text(file_path)
        else:
            logger.warning(f"Unsupported file format: {file_ext}")
            # Don't try to read binary formats as text; return minimal structure
            return {"full_text": "", "contact": {}, "summary": "", "experience": [], "education": [], "skills": []}
    
    def _extract_from_docx(self, file_path: str) -> Dict[str, Any]:
        """Extract data from Word document"""
        try:
            doc = Document(file_path)
            full_text = []
            for paragraph in doc.paragraphs:
                if paragraph.text.strip():
                    full_text.append(paragraph.text.strip())
            
            # Also extract from tables
            for table in doc.tables:
                for row in table.rows:
                    for cell in row.cells:
                        if cell.text.strip():
                            full_text.append(cell.text.strip())
            
            text_content = '\n'.join(full_text)
            return self._parse_resume_text(text_content)
        except Exception as e:
            logger.error(f"Error extracting from DOCX: {e}")
            # Attempt zip fallback
            try:
                return self._extract_docx_zip_fallback(file_path)
            except Exception:
                return {}
    
    def _extract_docx_zip_fallback(self, file_path: str) -> Dict[str, Any]:
        """Extract text from a DOCX by reading the zipped XML (no python-docx)."""
        try:
            with zipfile.ZipFile(file_path) as z:
                with z.open('word/document.xml') as f:
                    xml_bytes = f.read()
            # crude tag strip
            xml_text = xml_bytes.decode('utf-8', errors='ignore')
            # Replace common tags with newlines/spaces
            xml_text = re.sub(r'<w:p[^>]*>', '\n', xml_text)
            xml_text = re.sub(r'<[^>]+>', ' ', xml_text)
            text_content = re.sub(r'\s+', ' ', xml_text)
            return self._parse_resume_text(text_content)
        except Exception as e:
            logger.error(f"DOCX zip fallback failed: {e}")
            return {}

    def _extract_from_pdf(self, file_path: str) -> Dict[str, Any]:
        """Extract data from PDF"""
        try:
            with open(file_path, 'rb') as file:
                reader = PdfReader(file)
                full_text = []
                for page in reader.pages:
                    text = page.extract_text()
                    if text:
                        full_text.append(text)
                
                text_content = '\n'.join(full_text)
                return self._parse_resume_text(text_content)
        except Exception as e:
            logger.error(f"Error extracting from PDF: {e}")
            return {}
    
    def _extract_from_pptx(self, file_path: str) -> Dict[str, Any]:
        """Extract data from PowerPoint"""
        try:
            prs = Presentation(file_path)
            full_text = []
            
            for slide in prs.slides:
                for shape in slide.shapes:
                    if hasattr(shape, "text") and shape.text:
                        full_text.append(shape.text.strip())
            
            text_content = '\n'.join(full_text)
            return self._parse_resume_text(text_content)
        except Exception as e:
            logger.error(f"Error extracting from PPTX: {e}")
            return {}
    
    def _extract_from_text(self, file_path: str) -> Dict[str, Any]:
        """Extract data from text file"""
        try:
            # try multiple encodings safely
            try:
                with open(file_path, 'r', encoding='utf-8') as file:
                    text_content = file.read()
            except Exception:
                try:
                    with open(file_path, 'r', encoding='utf-16') as file:
                        text_content = file.read()
                except Exception:
                    with open(file_path, 'rb') as file:
                        text_content = file.read().decode('cp1252', errors='ignore')
            return self._parse_resume_text(text_content)
        except Exception as e:
            logger.error(f"Error extracting from text: {e}")
            return {}
    
    def _parse_resume_text(self, text: str) -> Dict[str, Any]:
        """Parse resume text into structured data"""
        data = {
            'full_text': text,
            'contact': {},
            'summary': '',
            'experience': [],
            'education': [],
            'skills': [],
            'certifications': [],
            'projects': [],
            'languages': []
        }
        
        lines = text.split('\n')
        
        # Extract email
        email_pattern = r'\b[A-Za-z0-9._%+-]+@[A-Za-z0-9.-]+\.[A-Z|a-z]{2,}\b'
        emails = re.findall(email_pattern, text)
        if emails:
            data['contact']['email'] = emails[0]
        
        # Extract phone
        phone_pattern = r'[\+]?[()]?[0-9]{1,4}[)]?[-\s\.]?[()]?[0-9]{1,4}[)]?[-\s\.]?[0-9]{1,5}[-\s\.]?[0-9]{1,5}'
        phones = re.findall(phone_pattern, text)
        if phones:
            data['contact']['phone'] = phones[0]
        
        # Extract LinkedIn URL
        linkedin_pattern = r'linkedin\.com/in/[\w-]+'
        linkedin = re.findall(linkedin_pattern, text.lower())
        if linkedin:
            data['contact']['linkedin'] = f"https://{linkedin[0]}"
        
        # Extract name (usually first non-empty line)
        for line in lines:
            if line.strip() and not any(char.isdigit() for char in line[:5]):
                data['contact']['name'] = line.strip()
                break
        
        # Extract sections
        current_section = None
        section_content = []
        
        section_keywords = {
            'experience': ['experience', 'work history', 'employment', 'professional experience'],
            'education': ['education', 'academic', 'qualification'],
            'skills': ['skills', 'technical skills', 'competencies', 'expertise'],
            'summary': ['summary', 'objective', 'profile', 'about'],
            'projects': ['projects', 'portfolio'],
            'certifications': ['certifications', 'certificates', 'credentials'],
            'languages': ['languages', 'language skills']
        }
        
        for line in lines:
            line_lower = line.lower().strip()
            
            # Check if this line is a section header
            for section, keywords in section_keywords.items():
                if any(keyword in line_lower for keyword in keywords):
                    # Save previous section
                    if current_section and section_content:
                        if current_section in ['experience', 'education', 'projects']:
                            data[current_section] = self._parse_list_section(section_content)
                        elif current_section == 'skills':
                            data[current_section] = self._parse_skills(section_content)
                        else:
                            data[current_section] = '\n'.join(section_content)
                    
                    current_section = section
                    section_content = []
                    break
            else:
                if current_section:
                    section_content.append(line)
        
        # Save last section
        if current_section and section_content:
            if current_section in ['experience', 'education', 'projects']:
                data[current_section] = self._parse_list_section(section_content)
            elif current_section == 'skills':
                data[current_section] = self._parse_skills(section_content)
            else:
                data[current_section] = '\n'.join(section_content)
        
        return data
    
    def _parse_list_section(self, lines: List[str]) -> List[Dict[str, str]]:
        """Parse experience/education/projects sections"""
        items = []
        current_item = {}
        
        for line in lines:
            if line.strip():
                # Simple heuristic: lines with dates might be titles
                if re.search(r'\d{4}', line):
                    if current_item:
                        items.append(current_item)
                    current_item = {'title': line.strip(), 'description': ''}
                elif current_item:
                    current_item['description'] += line.strip() + ' '
                else:
                    current_item = {'title': line.strip(), 'description': ''}
        
        if current_item:
            items.append(current_item)
        
        return items
    
    def _parse_skills(self, lines: List[str]) -> List[str]:
        """Parse skills section"""
        skills = []
        for line in lines:
            # Split by common delimiters
            parts = re.split(r'[,;|•·]', line)
            for part in parts:
                skill = part.strip()
                if skill and len(skill) > 1:
                    skills.append(skill)
        return skills
    
    def export_to_format(self, data: Dict[str, Any], format: str, template: Optional[str] = None) -> bytes:
        """Export resume data to specified format"""
        format = format.lower()
        
        if format == 'docx' and DOCX_AVAILABLE:
            return self._export_to_docx(data, template)
        elif format == 'pdf' and PDF_WRITE_AVAILABLE:
            return self._export_to_pdf(data, template)
        elif format == 'pptx' and PPTX_AVAILABLE:
            return self._export_to_pptx(data, template)
        else:
            return self._export_to_text(data).encode('utf-8')
    
    def _export_to_docx(self, data: Dict[str, Any], template: Optional[str] = None) -> bytes:
        """Export to Word document"""
        doc = Document()
        
        # Add title (name)
        if data.get('contact', {}).get('name'):
            title = doc.add_heading(data['contact']['name'], 0)
            title.alignment = WD_ALIGN_PARAGRAPH.CENTER
        
        # Add contact info
        if data.get('contact'):
            contact_para = doc.add_paragraph()
            contact_para.alignment = WD_ALIGN_PARAGRAPH.CENTER
            contact_items = []
            if data['contact'].get('email'):
                contact_items.append(data['contact']['email'])
            if data['contact'].get('phone'):
                contact_items.append(data['contact']['phone'])
            if data['contact'].get('linkedin'):
                contact_items.append(data['contact']['linkedin'])
            contact_para.add_run(' | '.join(contact_items))
        
        # Add summary
        if data.get('summary'):
            doc.add_heading('Professional Summary', 1)
            doc.add_paragraph(data['summary'])
        
        # Add experience
        if data.get('experience'):
            doc.add_heading('Professional Experience', 1)
            for exp in data['experience']:
                if isinstance(exp, dict):
                    doc.add_heading(exp.get('title', ''), 2)
                    doc.add_paragraph(exp.get('description', ''))
                else:
                    doc.add_paragraph(str(exp))
        
        # Add education
        if data.get('education'):
            doc.add_heading('Education', 1)
            for edu in data['education']:
                if isinstance(edu, dict):
                    doc.add_heading(edu.get('title', ''), 2)
                    doc.add_paragraph(edu.get('description', ''))
                else:
                    doc.add_paragraph(str(edu))
        
        # Add skills
        if data.get('skills'):
            doc.add_heading('Skills', 1)
            skills_para = doc.add_paragraph()
            if isinstance(data['skills'], list):
                for skill in data['skills']:
                    skills_para.add_run(f'• {skill}\n')
            else:
                skills_para.add_run(str(data['skills']))
        
        # Save to bytes
        buffer = io.BytesIO()
        doc.save(buffer)
        buffer.seek(0)
        return buffer.getvalue()
    
    def _export_to_pdf(self, data: Dict[str, Any], template: Optional[str] = None) -> bytes:
        """Export to PDF"""
        buffer = io.BytesIO()
        doc = SimpleDocTemplate(buffer, pagesize=letter)
        styles = getSampleStyleSheet()
        story = []
        
        # Title style
        title_style = ParagraphStyle(
            'CustomTitle',
            parent=styles['Heading1'],
            fontSize=24,
            textColor=colors.HexColor('#2E4057'),
            alignment=TA_CENTER,
            spaceAfter=12
        )
        
        # Add name
        if data.get('contact', {}).get('name'):
            story.append(Paragraph(data['contact']['name'], title_style))
            story.append(Spacer(1, 12))
        
        # Add contact info
        if data.get('contact'):
            contact_items = []
            if data['contact'].get('email'):
                contact_items.append(data['contact']['email'])
            if data['contact'].get('phone'):
                contact_items.append(data['contact']['phone'])
            if data['contact'].get('linkedin'):
                contact_items.append(data['contact']['linkedin'])
            
            contact_style = ParagraphStyle(
                'Contact',
                parent=styles['Normal'],
                alignment=TA_CENTER
            )
            story.append(Paragraph(' | '.join(contact_items), contact_style))
            story.append(Spacer(1, 20))
        
        # Add sections
        for section, heading in [
            ('summary', 'Professional Summary'),
            ('experience', 'Professional Experience'),
            ('education', 'Education'),
            ('skills', 'Skills')
        ]:
            if data.get(section):
                story.append(Paragraph(heading, styles['Heading2']))
                story.append(Spacer(1, 12))
                
                if isinstance(data[section], list):
                    for item in data[section]:
                        if isinstance(item, dict):
                            story.append(Paragraph(item.get('title', ''), styles['Heading3']))
                            story.append(Paragraph(item.get('description', ''), styles['Normal']))
                        else:
                            story.append(Paragraph(f'• {item}', styles['Normal']))
                        story.append(Spacer(1, 6))
                else:
                    story.append(Paragraph(str(data[section]), styles['Normal']))
                    story.append(Spacer(1, 12))
        
        doc.build(story)
        buffer.seek(0)
        return buffer.getvalue()
    
    def _export_to_pptx(self, data: Dict[str, Any], template: Optional[str] = None) -> bytes:
        """Export to PowerPoint"""
        prs = Presentation()
        
        # Title slide
        slide = prs.slides.add_slide(prs.slide_layouts[0])
        title = slide.shapes.title
        subtitle = slide.placeholders[1]
        
        if data.get('contact', {}).get('name'):
            title.text = data['contact']['name']
        
        contact_items = []
        if data.get('contact'):
            if data['contact'].get('email'):
                contact_items.append(data['contact']['email'])
            if data['contact'].get('phone'):
                contact_items.append(data['contact']['phone'])
        subtitle.text = ' | '.join(contact_items)
        
        # Summary slide
        if data.get('summary'):
            slide = prs.slides.add_slide(prs.slide_layouts[1])
            slide.shapes.title.text = "Professional Summary"
            slide.placeholders[1].text = data['summary']
        
        # Experience slides
        if data.get('experience'):
            for exp in data['experience'][:3]:  # Limit to 3 for brevity
                slide = prs.slides.add_slide(prs.slide_layouts[1])
                slide.shapes.title.text = "Professional Experience"
                if isinstance(exp, dict):
                    content = f"{exp.get('title', '')}\n\n{exp.get('description', '')}"
                else:
                    content = str(exp)
                slide.placeholders[1].text = content
        
        # Skills slide
        if data.get('skills'):
            slide = prs.slides.add_slide(prs.slide_layouts[1])
            slide.shapes.title.text = "Skills"
            if isinstance(data['skills'], list):
                slide.placeholders[1].text = '\n'.join([f'• {skill}' for skill in data['skills']])
            else:
                slide.placeholders[1].text = str(data['skills'])
        
        # Save to bytes
        buffer = io.BytesIO()
        prs.save(buffer)
        buffer.seek(0)
        return buffer.getvalue()
    
    def _export_to_text(self, data: Dict[str, Any]) -> str:
        """Export to plain text"""
        lines = []
        
        # Name and contact
        if data.get('contact', {}).get('name'):
            lines.append(data['contact']['name'])
            lines.append('=' * len(data['contact']['name']))
        
        if data.get('contact'):
            contact_items = []
            for field in ['email', 'phone', 'linkedin']:
                if data['contact'].get(field):
                    contact_items.append(data['contact'][field])
            if contact_items:
                lines.append(' | '.join(contact_items))
                lines.append('')
        
        # Sections
        for section, heading in [
            ('summary', 'PROFESSIONAL SUMMARY'),
            ('experience', 'PROFESSIONAL EXPERIENCE'),
            ('education', 'EDUCATION'),
            ('skills', 'SKILLS'),
            ('certifications', 'CERTIFICATIONS'),
            ('projects', 'PROJECTS')
        ]:
            if data.get(section):
                lines.append(heading)
                lines.append('-' * len(heading))
                
                if isinstance(data[section], list):
                    for item in data[section]:
                        if isinstance(item, dict):
                            lines.append(f"\n{item.get('title', '')}")
                            lines.append(item.get('description', ''))
                        else:
                            lines.append(f"• {item}")
                else:
                    lines.append(str(data[section]))
                lines.append('')
        
        return '\n'.join(lines)

# Singleton instance
document_processor = DocumentProcessor()