SEO Sentinel - Automated SEO Auditing Tool

A comprehensive SEO analysis tool that crawls websites, identifies SEO issues, and generates detailed HTML reports for website optimization.

[!CAUTION] SEO Sentinel is a helpful utility for SEO auditing but does not guarantee search engine ranking improvements. Please ensure your usage complies with the target site's policies. Always respect the robots.txt file of the websites you crawl. Use responsibly and ethically. The author is not responsible for any misuse or damage caused by the tool. Always test on your own sites or with permission from the site owner.

Features

• Website Crawling: Intelligent crawling with configurable depth and page limits
• SEO Analysis: Comprehensive analysis of metadata, links, and content
• Keyword Density: Track keyword usage and density across pages
• Broken Link Detection: Identify and report broken internal/external links
• Performance Metrics: Page load time and response code monitoring
• HTML Reports: Beautiful, detailed reports with actionable insights
• Auto Updates: Built-in update checker for latest features
• Configurable: Customizable crawling parameters and settings

Installation

Getting Started

Clone & Run Locally

# Clone the repository
git clone https://github.com/nayandas69/SEO-Sentinel
cd SEO-Sentinel

# Create a virtual environment
python3 -m venv venv

# Activate the environment
# Windows:
venv\Scripts\activate
# Linux/macOS:
source venv/bin/activate

# Install dependencies
pip3 install -r requirements.txt

# Run the project
python3 seose.py

Install via PyPI

pip3 install seo-sentinel

Then run via:

seo-sentinel

Programmatic Usage

from seose import SEOSentinel, SEOConfig

# Initialize with default config
sentinel = SEOSentinel()

# Or with custom configuration
config = SEOConfig(
    crawl_depth=2,
    max_pages=50,
    request_timeout=15
)
sentinel = SEOSentinel(config)

# Crawl and analyze a website
urls = sentinel.crawl_website("https://example.com")
results = {}

for url in urls:
    results[url] = sentinel.analyze_seo_issues(url, keywords=["seo", "optimization"])

# Generate HTML report
report_path = sentinel.generate_report(results, "https://example.com")
print(f"Report saved to: {report_path}")

Configuration

The SEOConfig class allows you to customize the analysis:

from seose import SEOConfig

config = SEOConfig(
    report_directory="reports",      # Directory for HTML reports
    log_directory="logs",           # Directory for log files
    crawl_depth=3,                  # Maximum crawling depth
    max_pages=100,                  # Maximum pages to crawl
    request_timeout=10,             # Request timeout in seconds
    max_workers=5,                  # Concurrent workers (future use)
    user_agent="SEO-Sentinel/1.0.2", # Custom user agent
    verify_ssl=True                 # SSL certificate verification
)

Requirements

Runtime Dependencies

• Python 3.8+
• beautifulsoup4 >= 4.12.0
• requests >= 2.31.0
• tqdm >= 4.65.0
• jinja2 >= 3.1.0

Development Dependencies

• pytest >= 7.0.0
• black >= 23.0.0
• flake8 >= 6.0.0
• mypy >= 1.0.0
• coverage >= 7.0.0

Usage Examples

Basic Website Analysis

from seose import SEOSentinel

sentinel = SEOSentinel()

# Analyze a single page
issues = sentinel.analyze_seo_issues("https://example.com")
print(f"Found {len(issues.missing_metadata)} metadata issues")

# Full website crawl and analysis
urls = sentinel.crawl_website("https://example.com")
results = {url: sentinel.analyze_seo_issues(url) for url in urls}
report_path = sentinel.generate_report(results, "https://example.com")

Keyword Analysis

keywords = ["seo", "optimization", "website", "ranking"]
issues = sentinel.analyze_seo_issues("https://example.com", keywords=keywords)

for keyword, data in issues.keyword_density.items():
    print(f"{keyword}: {data['count']} occurrences ({data['density']}%)")

Custom Configuration

from seose import SEOSentinel, SEOConfig

config = SEOConfig(
    crawl_depth=2,
    max_pages=25,
    request_timeout=15
)

sentinel = SEOSentinel(config)
urls = sentinel.crawl_website("https://example.com", max_depth=1, max_pages=10)

Report Features

The generated HTML reports include:

• Executive Summary: Total pages, issues, and performance metrics
• Page-by-Page Analysis: Detailed breakdown of each crawled page
• Performance Indicators: Load times and response codes
• Broken Link Detection: Complete list of broken internal/external links
• Metadata Analysis: Missing or problematic meta tags, titles, descriptions
• Keyword Density: Frequency and density analysis for target keywords

Testing

Run the test suite:

# Run all tests
pytest

# Run with coverage
pytest --cov=seose

# Run specific test file
pytest tests/test_seose.py

Contributing

1. Fork the repository
2. Create a feature branch (git checkout -b feature/amazing-feature)
3. Make your changes
4. Run tests (pytest)
5. Format code (black .)
6. Commit changes (git commit -m 'Add amazing feature')
7. Push to branch (git push origin feature/amazing-feature)
8. Open a Pull Request

License

This project is licensed under the MIT License - see the LICENSE file for details.

Author

Nayan Das

• Website: https://linkinbio-nextjs-ashen.vercel.app
• Email: nayanchandradas@hotmail.com
• GitHub: @nayandas69

Support

• 🐛 Bug Reports: GitHub Issues
• 💬 Community: Discord Server
• 📧 Email: nayanchandradas@hotmail.com

Roadmap

• Multi-threading support for faster crawling
• Additional SEO checks (schema markup, social meta tags)
• JSON/CSV export options
• Web interface
• Integration with popular CMS platforms
• Advanced keyword analysis and suggestions