Project Overview

This project is a comprehensive SEO toolkit consisting of two main components: a Python-based SEO crawler and a web-based SEO checker. The toolkit is designed to analyze websites, identify SEO issues, and generate detailed reports with optimization recommendations.

Main Technologies:

  • Python SEO Crawler (seo_auditor.py):
    • requests for making HTTP requests.
    • BeautifulSoup4 for parsing HTML content.
    • matplotlib for generating data visualizations (charts and graphs).
    • ThreadPoolExecutor for concurrent web crawling.
  • Web-based SEO Checker (seo-checker.html):
    • Tailwind CSS for styling the user interface.
    • Chart.js for rendering interactive charts.
    • Vanilla JavaScript for handling user interactions and simulating the SEO analysis process.

Architecture:

The project follows a modular architecture:

  1. seo_auditor.py: A command-line tool that takes a URL as input, crawls the website, performs a detailed SEO analysis, and generates a comprehensive HTML report, along with data files in JSON format and chart images.
  2. seo-checker.html: A single-page web application that provides a user-friendly interface for the SEO tools. It allows users to input a URL, select analysis options, and view the results in a visually appealing dashboard. The web interface simulates the functionality of the backend Python script.

Building and Running

Python SEO Crawler:

  • Prerequisites: Python 3.7+
  • Installation: 
    1

    pip install requests beautifulsoup4 matplotlib pillow
  • Running the tool: 
    1

    python seo_auditor.py
    The script can also be imported and used as a module in other Python applications.

Web-based SEO Checker:

  • No build process is required.
  • Simply open the seo-checker.html file in a web browser to use the tool.

Development Conventions

  • Python:
    • The code is well-documented with docstrings and comments.
    • It follows the PEP 8 style guide for Python code.
    • The use of ThreadPoolExecutor for concurrency suggests an emphasis on performance.
    • Error handling is implemented using try...except blocks.
    • Logging is used to provide detailed information about the crawling and analysis process.
  • HTML/JavaScript:
    • The web interface is built using modern web technologies, including Tailwind CSS and Chart.js.
    • The JavaScript code is embedded within the HTML file and is well-structured with functions for different functionalities.
    • The use of utility classes from Tailwind CSS indicates a focus on rapid UI development.