webtable2json v1.1.0 - Enhanced Features & Performance

✨ New Features Added:
Image Support - Extract images with src and alt attributes
URL Normalization - Automatic relative to absolute URL conversion
Session Support - Connection pooling for better performance
Built-in Logging - Debug and monitoring capabilities
File Operations - save_tables_to_file() function
Table Filtering - filter_tables_by_size() utility
Enhanced Metadata - Table ID, class, and source URL tracking
Better Error Handling - More detailed error messages

Description: Major feature update with image support, URL normalization, session management, and new utility functions. Improved performance and better error handling make this release more robust for production use.

The package is fully tested, validated, and ready for release! All files have been updated with the new version number and comprehensive documentation.

webtable2json v1.0.0 - Initial Release

🎉 Initial Release
A powerful Python library for extracting HTML tables from webpages and converting them to structured JSON format.

✨ Features
Universal Table Extraction: Extract tables from any URL or HTML content
Smart Data Cleaning: Automatically cleans and normalizes table data
Complex Table Support: Handles thead, tbody, colspan, rowspan, and nested structures
Link Preservation: Maintains links and metadata from table cells
Flexible Output: Get all tables or target specific ones by index
Type Safety: Full type hints for better development experience
Error Handling: Comprehensive error handling with meaningful messages

🚀 Key Functions
convert_url_to_json() - Extract tables directly from URLs
convert_html_to_json() - Process HTML content
get_main_table() - Get the largest/main table automatically
get_clean_ranking_data() - Specialized function for ranking websites
WebTableToJSON class - Full control with custom headers and options

📊 Perfect For
Web scraping projects
Data extraction from ranking websites (NIRF, university rankings, etc.)
Converting tabular web data to structured formats
Research and data analysis
API development requiring table data

🛠 Requirements
Python 3.7+
requests >= 2.25.0
beautifulsoup4 >= 4.9.0

📦 Installation
pip install webtable2json
🔧 Quick Start
from webtable2json import convert_url_to_json

Extract all tables from a webpage

tables = convert_url_to_json("https://example.com/data")
print(f"Found {len(tables)} tables")

This initial release provides a solid foundation for HTML table extraction with clean, intuitive APIs and robust error handling.