ALwrity Version 0.5.0 (Fastapi + React )
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ajaysi
208
backend/services/seo_analyzer/core.py
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208
backend/services/seo_analyzer/core.py
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"""
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Core SEO Analyzer Module
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Contains the main ComprehensiveSEOAnalyzer class and data structures.
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"""
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from datetime import datetime
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from dataclasses import dataclass
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from typing import Dict, List, Any, Optional
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from loguru import logger
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from .analyzers import (
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URLStructureAnalyzer,
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MetaDataAnalyzer,
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ContentAnalyzer,
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TechnicalSEOAnalyzer,
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PerformanceAnalyzer,
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AccessibilityAnalyzer,
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UserExperienceAnalyzer,
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SecurityHeadersAnalyzer,
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KeywordAnalyzer
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)
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from .utils import HTMLFetcher, AIInsightGenerator
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@dataclass
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class SEOAnalysisResult:
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"""Data class for SEO analysis results"""
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url: str
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timestamp: datetime
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overall_score: int
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health_status: str
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critical_issues: List[Dict[str, Any]]
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warnings: List[Dict[str, Any]]
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recommendations: List[Dict[str, Any]]
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data: Dict[str, Any]
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class ComprehensiveSEOAnalyzer:
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"""
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Comprehensive SEO Analyzer
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Orchestrates all individual analyzers to provide complete SEO analysis.
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"""
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def __init__(self):
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"""Initialize the comprehensive SEO analyzer with all sub-analyzers"""
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self.html_fetcher = HTMLFetcher()
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self.ai_insight_generator = AIInsightGenerator()
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# Initialize all analyzers
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self.url_analyzer = URLStructureAnalyzer()
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self.meta_analyzer = MetaDataAnalyzer()
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self.content_analyzer = ContentAnalyzer()
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self.technical_analyzer = TechnicalSEOAnalyzer()
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self.performance_analyzer = PerformanceAnalyzer()
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self.accessibility_analyzer = AccessibilityAnalyzer()
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self.ux_analyzer = UserExperienceAnalyzer()
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self.security_analyzer = SecurityHeadersAnalyzer()
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self.keyword_analyzer = KeywordAnalyzer()
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def analyze_url_progressive(self, url: str, target_keywords: Optional[List[str]] = None) -> SEOAnalysisResult:
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"""
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Progressive analysis method that runs all analyses with enhanced AI insights
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"""
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try:
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logger.info(f"Starting enhanced SEO analysis for URL: {url}")
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# Fetch HTML content
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html_content = self.html_fetcher.fetch_html(url)
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if not html_content:
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return self._create_error_result(url, "Failed to fetch HTML content")
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# Run all analyzers
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analysis_data = {}
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logger.info("Running enhanced analyses...")
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analysis_data.update({
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'url_structure': self.url_analyzer.analyze(url),
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'meta_data': self.meta_analyzer.analyze(html_content, url),
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'content_analysis': self.content_analyzer.analyze(html_content, url),
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'keyword_analysis': self.keyword_analyzer.analyze(html_content, target_keywords) if target_keywords else {},
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'technical_seo': self.technical_analyzer.analyze(html_content, url),
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'accessibility': self.accessibility_analyzer.analyze(html_content),
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'user_experience': self.ux_analyzer.analyze(html_content, url)
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})
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# Run potentially slower analyses with error handling
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logger.info("Running security headers analysis...")
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try:
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analysis_data['security_headers'] = self.security_analyzer.analyze(url)
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except Exception as e:
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logger.warning(f"Security headers analysis failed: {e}")
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analysis_data['security_headers'] = self._create_fallback_result('security_headers', str(e))
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logger.info("Running performance analysis...")
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try:
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analysis_data['performance'] = self.performance_analyzer.analyze(url)
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except Exception as e:
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logger.warning(f"Performance analysis failed: {e}")
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analysis_data['performance'] = self._create_fallback_result('performance', str(e))
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# Generate AI-powered insights
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ai_insights = self.ai_insight_generator.generate_insights(analysis_data, url)
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# Calculate overall health
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overall_score, health_status, critical_issues, warnings, recommendations = self._calculate_overall_health(analysis_data, ai_insights)
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result = SEOAnalysisResult(
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url=url,
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timestamp=datetime.now(),
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overall_score=overall_score,
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health_status=health_status,
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critical_issues=critical_issues,
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warnings=warnings,
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recommendations=recommendations,
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data=analysis_data
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)
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logger.info(f"Enhanced SEO analysis completed for {url}. Overall score: {overall_score}")
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return result
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except Exception as e:
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logger.error(f"Error in enhanced SEO analysis for {url}: {str(e)}")
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return self._create_error_result(url, str(e))
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def _calculate_overall_health(self, analysis_data: Dict[str, Any], ai_insights: List[Dict[str, Any]]) -> tuple:
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"""Calculate overall health with enhanced scoring"""
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scores = []
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all_critical_issues = []
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all_warnings = []
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all_recommendations = []
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for category, data in analysis_data.items():
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if isinstance(data, dict) and 'score' in data:
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scores.append(data['score'])
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all_critical_issues.extend(data.get('issues', []))
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all_warnings.extend(data.get('warnings', []))
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all_recommendations.extend(data.get('recommendations', []))
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# Calculate overall score
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overall_score = sum(scores) // len(scores) if scores else 0
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# Determine health status
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if overall_score >= 80:
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health_status = 'excellent'
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elif overall_score >= 60:
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health_status = 'good'
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elif overall_score >= 40:
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health_status = 'needs_improvement'
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else:
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health_status = 'poor'
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# Add AI insights to recommendations
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for insight in ai_insights:
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all_recommendations.append({
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'type': 'ai_insight',
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'message': insight['message'],
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'priority': insight['priority'],
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'action': insight['action'],
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'description': insight['description']
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})
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return overall_score, health_status, all_critical_issues, all_warnings, all_recommendations
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def _create_fallback_result(self, category: str, error_message: str) -> Dict[str, Any]:
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"""Create a fallback result when analysis fails"""
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return {
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'score': 0,
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'error': f'{category} analysis failed: {error_message}',
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'issues': [{
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'type': 'critical',
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'message': f'{category} analysis timed out',
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'location': 'System',
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'fix': f'Check {category} manually',
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'action': 'manual_check'
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}],
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'warnings': [{
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'type': 'warning',
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'message': f'Could not analyze {category}',
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'location': 'System',
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'fix': f'Verify {category} manually',
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'action': 'manual_check'
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}],
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'recommendations': [{
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'type': 'recommendation',
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'message': f'Check {category} manually',
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'priority': 'medium',
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'action': 'manual_check'
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}]
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}
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def _create_error_result(self, url: str, error_message: str) -> SEOAnalysisResult:
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"""Create error result with enhanced structure"""
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return SEOAnalysisResult(
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url=url,
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timestamp=datetime.now(),
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overall_score=0,
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health_status='error',
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critical_issues=[{
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'type': 'critical',
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'message': f'Analysis failed: {error_message}',
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'location': 'System',
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'fix': 'Check URL accessibility and try again',
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'action': 'retry_analysis'
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}],
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warnings=[],
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recommendations=[],
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data={}
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)
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