"""
LinkedIn Profile Scraper API Integration
Uses the Relevance API to scrape LinkedIn profile data
"""

import requests
import json
from typing import Dict, Any, Optional
from urllib.parse import urlparse
import time

class LinkedInScraper:
    """
    A Python wrapper for the Relevance LinkedIn scraping API
    """
    
    def __init__(self):
        # Primary API (original)
        self.primary_api = {
            "url": "https://api-f1db6c.stack.tryrelevance.com/latest/studios/11116e42-9be9-4837-8753-c46a80458318/trigger_webhook",
            "project_id": "f56ec267-8285-4bef-b8ab-4dce36204e5d"
        }
        
        # Fallback API (new account)
        self.fallback_api = {
            "url": "https://api-f1db6c.stack.tryrelevance.com/latest/studios/a1a00cf9-4102-4d76-99e5-8ce9b922b51c/trigger_webhook",
            "project_id": "e5f9ef92-aa24-4626-a145-3fb746186504"
        }
        
        self.headers = {
            "Content-Type": "application/json"
        }
    
    def is_valid_linkedin_url(self, url: str) -> bool:
        """
        Validate if the URL is a LinkedIn profile URL
        """
        try:
            parsed = urlparse(url)
            return (
                parsed.netloc in ['www.linkedin.com', 'linkedin.com'] and
                '/in/' in parsed.path
            )
        except:
            return False
    
    def _try_api(self, api_config: Dict[str, str], linkedin_url: str, api_name: str) -> Dict[str, Any]:
        """
        Try scraping with a specific API configuration
        """
        try:
            payload = {"url": linkedin_url}
            full_url = f"{api_config['url']}?project={api_config['project_id']}"
            
            print(f"[{api_name}] Trying to scrape: {linkedin_url}")
            start_time = time.time()
            
            response = requests.post(
                full_url,
                headers=self.headers,
                data=json.dumps(payload),
                timeout=60
            )
            
            end_time = time.time()
            duration = round(end_time - start_time, 2)
            
            if response.status_code == 200:
                data = response.json()
                
                # Handle different response formats from different APIs
                profile_data = None
                if 'linkedin_full_data' in data:
                    profile_data = data['linkedin_full_data']
                elif 'data' in data:
                    profile_data = data['data']
                
                if profile_data:
                    print(f"[{api_name}] SUCCESS in {duration}s")
                    print(f"   Name: {profile_data.get('full_name', 'N/A')}")
                    print(f"   Headline: {profile_data.get('headline', 'N/A')}")
                    print(f"   Location: {profile_data.get('location', 'N/A')}")
                    
                    return {
                        "success": True,
                        "data": profile_data,
                        "scrape_time": duration,
                        "url": linkedin_url,
                        "api_used": api_name
                    }
                else:
                    return {
                        "success": False,
                        "error": f"{api_name}: No profile data returned",
                        "raw_response": data,
                        "url": linkedin_url
                    }
            else:
                return {
                    "success": False,
                    "error": f"{api_name}: API returned status {response.status_code}",
                    "response_text": response.text,
                    "url": linkedin_url
                }
                
        except requests.exceptions.Timeout:
            return {
                "success": False,
                "error": f"{api_name}: Request timed out after 60 seconds",
                "url": linkedin_url
            }
        except Exception as e:
            return {
                "success": False,
                "error": f"{api_name}: {str(e)}",
                "url": linkedin_url
            }

    def scrape_profile(self, linkedin_url: str) -> Dict[str, Any]:
        """
        Scrape a LinkedIn profile using primary API with fallback
        
        Args:
            linkedin_url (str): LinkedIn profile URL
            
        Returns:
            Dict containing profile data or error information
        """
        
        # Validate URL
        if not self.is_valid_linkedin_url(linkedin_url):
            return {
                "success": False,
                "error": "Invalid LinkedIn URL format",
                "url": linkedin_url
            }
        
        print(f"[SCRAPING] LinkedIn profile: {linkedin_url}")
        
        # Try primary API first
        result = self._try_api(self.primary_api, linkedin_url, "PRIMARY")
        
        if result["success"]:
            return result
        
        print(f"[FALLBACK] Primary API failed: {result['error']}")
        print(f"[FALLBACK] Trying secondary API...")
        
        # Try fallback API
        result = self._try_api(self.fallback_api, linkedin_url, "FALLBACK")
        
        if result["success"]:
            return result
        
        # Both APIs failed
        print(f"[FAILED] Both APIs failed!")
        return {
            "success": False,
            "error": "Both primary and fallback APIs failed",
            "primary_error": result.get('error', 'Unknown error'),
            "url": linkedin_url
        }
    
    def extract_key_info(self, profile_data: Dict[str, Any]) -> Dict[str, Any]:
        """
        Extract key information from the scraped profile data
        
        Args:
            profile_data: Raw profile data from the API
            
        Returns:
            Simplified profile data with key fields
        """
        
        if not profile_data.get('success', False):
            return profile_data
        
        data = profile_data['data']
        
        # Extract education info
        educations = []
        for edu in data.get('educations', []):
            educations.append({
                'school': edu.get('school', ''),
                'degree': edu.get('degree', ''),
                'field': edu.get('field_of_study', ''),
                'date_range': edu.get('date_range', ''),
                'grade': edu.get('activities', '')  # Grade is often in activities
            })
        
        # Extract experience info
        experiences = []
        for exp in data.get('experiences', []):
            experiences.append({
                'title': exp.get('title', ''),
                'company': exp.get('company', ''),
                'date_range': exp.get('date_range', ''),
                'description': exp.get('description', '')
            })
        
        return {
            'success': True,
            'profile': {
                'name': data.get('full_name', ''),
                'headline': data.get('headline', ''),
                'location': data.get('location', ''),
                'about': data.get('about', ''),
                'profile_url': data.get('linkedin_url', ''),
                'profile_image': data.get('profile_image_url', ''),
                'connections': data.get('connection_count', 0),
                'is_verified': data.get('is_verified', False),
                'current_company': data.get('company', ''),
                'current_title': data.get('job_title', ''),
                'educations': educations,
                'experiences': experiences
            },
            'scrape_time': profile_data.get('scrape_time', 0),
            'url': profile_data.get('url', '')
        }

# This module is integrated with the Enhance LinkedIn application
# No standalone test code needed