#!/usr/bin/env python3
"""
Gateway Page Content Generator
Automates the creation of SEO-optimized gateway pages for local services
"""

import json
import os
from datetime import datetime
from typing import Dict, List, Optional
import re
from dataclasses import dataclass
from pathlib import Path

@dataclass
class Location:
    """Location data structure"""
    id: str
    name_en: str
    name_kr: str
    full_address: str
    landmarks: List[str]
    subway_stations: List[str]
    demographics: str
    latitude: float
    longitude: float

@dataclass  
class Service:
    """Service data structure"""
    id: str
    name_en: str
    name_kr: str
    category: str
    description: str
    keywords: List[str]
    procedure_time: str
    recovery_time: str
    price_range: str

@dataclass
class Brand:
    """Brand/Clinic information"""
    name_en: str
    name_kr: str
    website: str
    phone: str
    email: str
    established_year: int
    certifications: List[str]
    unique_selling_points: List[str]

class GatewayPageGenerator:
    """Main class for generating gateway page content"""
    
    def __init__(self, brand: Brand, template_path: str = "templates/"):
        self.brand = brand
        self.template_path = Path(template_path)
        self.generated_pages = []
        
    def load_template(self, template_name: str) -> str:
        """Load a template file"""
        template_file = self.template_path / template_name
        if template_file.exists():
            with open(template_file, 'r', encoding='utf-8') as f:
                return f.read()
        else:
            raise FileNotFoundError(f"Template {template_name} not found")
    
    def generate_meta_tags(self, service: Service, location: Location) -> Dict:
        """Generate SEO meta tags"""
        return {
            "title": f"{service.name_en} in {location.name_en} | Expert {service.category} | {self.brand.name_en}",
            "description": f"Looking for {service.name_en.lower()} in {location.name_en}? "
                          f"{self.brand.name_en} offers professional {service.category.lower()} services. "
                          f"✓ Experienced team ✓ Latest technology ✓ {self.brand.unique_selling_points[0]}",
            "keywords": ", ".join([
                f"{service.name_en} {location.name_en}",
                f"{location.name_en} {service.name_en}",
                *service.keywords,
                f"{service.category} {location.name_en}"
            ]),
            "canonical": f"https://{self.brand.website}/{location.id}/{service.id}/",
            "og:title": f"{service.name_en} in {location.name_en} - {self.brand.name_en}",
            "og:description": f"Professional {service.name_en} services in {location.name_en}. "
                             f"Book your consultation today.",
            "og:image": f"https://{self.brand.website}/images/{service.id}-{location.id}-og.jpg"
        }
    
    def generate_schema_markup(self, service: Service, location: Location) -> str:
        """Generate JSON-LD schema markup"""
        schema = {
            "@context": "https://schema.org",
            "@type": "MedicalBusiness",
            "name": f"{self.brand.name_en} - {location.name_en}",
            "url": f"https://{self.brand.website}",
            "telephone": self.brand.phone,
            "email": self.brand.email,
            "address": {
                "@type": "PostalAddress",
                "streetAddress": location.full_address,
                "addressLocality": location.name_en,
                "addressCountry": "KR"
            },
            "geo": {
                "@type": "GeoCoordinates",
                "latitude": location.latitude,
                "longitude": location.longitude
            },
            "areaServed": {
                "@type": "City",
                "name": location.name_en
            },
            "availableService": {
                "@type": "MedicalProcedure",
                "name": service.name_en,
                "description": service.description
            },
            "priceRange": service.price_range
        }
        return json.dumps(schema, indent=2, ensure_ascii=False)
    
    def generate_content_variations(self, service: Service, location: Location) -> Dict[str, List[str]]:
        """Generate content variations for uniqueness"""
        return {
            "hero_headlines": [
                f"Professional {service.name_en} in {location.name_en}",
                f"{location.name_en}'s Premier {service.name_en} {service.category}",
                f"Expert {service.name_en} Services for {location.name_en} Residents",
                f"Transform Your Look with {service.name_en} in {location.name_en}"
            ],
            "intro_paragraphs": [
                f"Welcome to {self.brand.name_en}, where we specialize in providing exceptional "
                f"{service.name_en} services to the {location.name_en} community. "
                f"Our state-of-the-art facility, conveniently located near {location.landmarks[0]}, "
                f"combines advanced technology with personalized care.",
                
                f"Looking for trusted {service.name_en} in {location.name_en}? "
                f"At {self.brand.name_en}, we've been serving the {location.demographics} "
                f"for over {datetime.now().year - self.brand.established_year} years. "
                f"Our expert team understands the unique needs of {location.name_en} residents.",
                
                f"Discover why {location.name_en} residents choose {self.brand.name_en} "
                f"for their {service.name_en} needs. Located just minutes from "
                f"{', '.join(location.subway_stations[:2])}, we offer {service.category} "
                f"services that deliver remarkable results."
            ],
            "cta_buttons": [
                f"Book Your {location.name_en} Consultation",
                f"Schedule {service.name_en} Today", 
                f"Get Started in {location.name_en}",
                f"Reserve Your Appointment"
            ],
            "trust_signals": [
                f"Trusted by {location.name_en} residents since {self.brand.established_year}",
                f"Over 10,000 successful {service.category} treatments",
                f"5-star rated {service.name_en} clinic in {location.name_en}",
                f"Certified specialists serving {location.demographics}"
            ]
        }
    
    def localize_content(self, content: str, service: Service, location: Location) -> str:
        """Add local elements to content"""
        local_elements = {
            "transportation": f"Easily accessible via {', '.join(location.subway_stations)} stations",
            "landmarks": f"Located near {' and '.join(location.landmarks[:2])}",
            "community": f"Proud to serve the {location.name_en} community",
            "convenience": f"Convenient for {location.demographics} in {location.name_en}",
            "local_stats": f"Join thousands of satisfied patients from {location.name_en}"
        }
        
        # Add local elements naturally throughout content
        for key, value in local_elements.items():
            placeholder = f"[LOCAL_{key.upper()}]"
            if placeholder in content:
                content = content.replace(placeholder, value)
        
        return content
    
    def generate_page(self, service: Service, location: Location, 
                     template_name: str = "gateway-page-medical.md") -> str:
        """Generate a complete gateway page"""
        
        # Load template
        template = self.load_template(template_name)
        
        # Generate components
        meta_tags = self.generate_meta_tags(service, location)
        schema = self.generate_schema_markup(service, location)
        variations = self.generate_content_variations(service, location)
        
        # Replace placeholders in template
        replacements = {
            "[Medical Service]": service.name_en,
            "[Location]": location.name_en,
            "[location]": location.name_en.lower(),
            "[Clinic Name]": self.brand.name_en,
            "[service-slug]": service.id,
            "[X years]": str(datetime.now().year - self.brand.established_year),
            "[specific address near landmark]": f"{location.full_address}, near {location.landmarks[0]}",
            "[nearby subway/bus stations]": ", ".join(location.subway_stations),
            "[certification details]": ", ".join(self.brand.certifications[:2]),
            "[equipment type]": f"{service.category} equipment",
            "[duration]": service.procedure_time,
            "[Medical Specialty]": service.category,
            "[phone-number]": self.brand.phone,
            "[website-url]": f"https://{self.brand.website}",
            "[page-url]": f"https://{self.brand.website}/{location.id}/{service.id}/",
            "[latitude]": str(location.latitude),
            "[longitude]": str(location.longitude),
        }
        
        # Apply replacements
        content = template
        for placeholder, value in replacements.items():
            content = content.replace(placeholder, value)
        
        # Add localized content
        content = self.localize_content(content, service, location)
        
        # Add schema markup at the end if not already present
        if '"@context": "https://schema.org"' not in content:
            content += f"\n\n<!-- Schema Markup -->\n<script type='application/ld+json'>\n{schema}\n</script>"
        
        return content
    
    def generate_batch(self, services: List[Service], locations: List[Location], 
                      output_dir: str = "output/") -> List[str]:
        """Generate multiple gateway pages"""
        output_path = Path(output_dir)
        output_path.mkdir(parents=True, exist_ok=True)
        
        generated_files = []
        
        for location in locations:
            location_dir = output_path / location.id
            location_dir.mkdir(exist_ok=True)
            
            for service in services:
                # Generate content
                content = self.generate_page(service, location)
                
                # Save to file
                filename = f"{service.id}-{location.id}.md"
                filepath = location_dir / filename
                
                with open(filepath, 'w', encoding='utf-8') as f:
                    f.write(content)
                
                generated_files.append(str(filepath))
                print(f"✓ Generated: {filepath}")
        
        # Generate index file
        self.generate_index(services, locations, output_path)
        
        return generated_files
    
    def generate_index(self, services: List[Service], locations: List[Location], 
                       output_path: Path):
        """Generate an index of all created pages"""
        index_content = f"# Gateway Pages Index - {self.brand.name_en}\n\n"
        index_content += f"Generated: {datetime.now().strftime('%Y-%m-%d %H:%M')}\n\n"
        index_content += "## Pages by Location\n\n"
        
        for location in locations:
            index_content += f"### {location.name_en}\n"
            for service in services:
                url = f"/{location.id}/{service.id}/"
                index_content += f"- [{service.name_en} in {location.name_en}]({url})\n"
            index_content += "\n"
        
        index_content += "## Pages by Service\n\n"
        for service in services:
            index_content += f"### {service.name_en}\n"
            for location in locations:
                url = f"/{location.id}/{service.id}/"
                index_content += f"- [{location.name_en}]({url})\n"
            index_content += "\n"
        
        index_content += f"\n---\nTotal Pages Generated: {len(services) * len(locations)}\n"
        
        with open(output_path / "index.md", 'w', encoding='utf-8') as f:
            f.write(index_content)

def create_sample_data():
    """Create sample data for testing"""
    
    # Sample brand
    brand = Brand(
        name_en="Jamie Clinic",
        name_kr="제이미 클리닉",
        website="www.jamieclinic.com",
        phone="+82-2-1234-5678",
        email="info@jamieclinic.com",
        established_year=2010,
        certifications=["ISO 9001", "KAHF Certified", "JCI Accredited"],
        unique_selling_points=[
            "Same-day appointments available",
            "15+ years of experience",
            "Latest medical technology"
        ]
    )
    
    # Sample locations
    locations = [
        Location(
            id="gangnam",
            name_en="Gangnam",
            name_kr="강남",
            full_address="123 Teheran-ro, Gangnam-gu, Seoul",
            landmarks=["COEX", "Gangnam Station", "Samsung Station"],
            subway_stations=["Gangnam Station (Line 2)", "Sinnonhyeon Station (Line 9)"],
            demographics="Young professionals and affluent residents",
            latitude=37.4979,
            longitude=127.0276
        ),
        Location(
            id="myeongdong",
            name_en="Myeongdong",
            name_kr="명동",
            full_address="456 Myeongdong-gil, Jung-gu, Seoul",
            landmarks=["Myeongdong Cathedral", "Lotte Department Store"],
            subway_stations=["Myeongdong Station (Line 4)", "Euljiro 1-ga Station (Line 2)"],
            demographics="Tourists and young shoppers",
            latitude=37.5636,
            longitude=126.9869
        )
    ]
    
    # Sample services
    services = [
        Service(
            id="laser-hair-removal",
            name_en="Laser Hair Removal",
            name_kr="레이저 제모",
            category="Dermatology",
            description="Advanced laser technology for permanent hair reduction",
            keywords=["permanent hair removal", "IPL", "diode laser"],
            procedure_time="30-60 minutes",
            recovery_time="No downtime",
            price_range="₩₩₩"
        ),
        Service(
            id="botox",
            name_en="Botox Treatment",
            name_kr="보톡스",
            category="Cosmetic Dermatology", 
            description="FDA-approved botulinum toxin for wrinkle reduction",
            keywords=["wrinkle treatment", "anti-aging", "facial rejuvenation"],
            procedure_time="15-30 minutes",
            recovery_time="No downtime",
            price_range="₩₩₩₩"
        )
    ]
    
    return brand, locations, services

def main():
    """Main execution function"""
    print("=" * 60)
    print("Gateway Page Content Generator")
    print("=" * 60)
    
    # Get sample data
    brand, locations, services = create_sample_data()
    
    # Initialize generator
    generator = GatewayPageGenerator(brand)
    
    # Generate pages
    print(f"\nGenerating {len(services) * len(locations)} gateway pages...")
    print("-" * 40)
    
    generated_files = generator.generate_batch(services, locations)
    
    print("-" * 40)
    print(f"\n✅ Successfully generated {len(generated_files)} pages!")
    print(f"📁 Output directory: output/")
    print(f"📋 Index file created: output/index.md")
    
    # Generate report
    print("\n" + "=" * 60)
    print("GENERATION REPORT")
    print("=" * 60)
    print(f"Brand: {brand.name_en}")
    print(f"Locations: {', '.join([loc.name_en for loc in locations])}")
    print(f"Services: {', '.join([svc.name_en for svc in services])}")
    print(f"Total Pages: {len(generated_files)}")
    print(f"Timestamp: {datetime.now().strftime('%Y-%m-%d %H:%M:%S')}")
    print("=" * 60)

if __name__ == "__main__":
    main()