BREAKING CHANGE: Table extraction now uses Strategy Design Pattern
This epic commit introduces a game-changing approach to table extraction in Crawl4AI:
✨ NEW FEATURES:
- LLMTableExtraction: AI-powered extraction for complex HTML tables with rowspan/colspan
- Smart Chunking: Automatically splits massive tables into optimal chunks at row boundaries
- Parallel Processing: Processes multiple chunks simultaneously for blazing-fast extraction
- Intelligent Merging: Seamlessly combines chunk results into complete tables
- Header Preservation: Each chunk maintains context with original headers
- Auto-retry Logic: Built-in resilience with configurable retry attempts
🏗️ ARCHITECTURE:
- Strategy Design Pattern for pluggable table extraction strategies
- ThreadPoolExecutor for concurrent chunk processing
- Token-based chunking with configurable thresholds
- Handles tables without headers gracefully
⚡ PERFORMANCE:
- Process 1000+ row tables without timeout
- Parallel processing with up to 5 concurrent chunks
- Smart token estimation prevents LLM context overflow
- Optimized for providers like Groq for massive tables
🔧 CONFIGURATION:
- enable_chunking: Auto-handle large tables (default: True)
- chunk_token_threshold: When to split (default: 3000 tokens)
- min_rows_per_chunk: Meaningful chunk sizes (default: 10)
- max_parallel_chunks: Concurrent processing (default: 5)
📚 BACKWARD COMPATIBILITY:
- Existing code continues to work unchanged
- DefaultTableExtraction remains the default strategy
- Progressive enhancement approach
This is the future of web table extraction - handling everything from simple tables to massive, complex data grids with merged cells and nested structures. The chunking is completely transparent to users while providing unprecedented scalability.
- Extract base href from <head><base> tag using XPath in _process_element method
- Use base URL as the primary URL for link normalization when present
- Add error handling with logging for malformed or problematic base tags
- Maintain backward compatibility when no base tag is present
- Add test to verify the functionality of the base tag extraction.
commit 2def6524cdacb69c72760bf55a41089257c0bb07
Author: ntohidi <nasrin@kidocode.com>
Date: Mon Aug 4 18:59:10 2025 +0800
refactor: consolidate WebScrapingStrategy to use LXML implementation only
BREAKING CHANGE: None - full backward compatibility maintained
This commit simplifies the content scraping architecture by removing the
redundant BeautifulSoup-based WebScrapingStrategy implementation and making
it an alias for LXMLWebScrapingStrategy.
Changes:
- Remove ~1000 lines of BeautifulSoup-based WebScrapingStrategy code
- Make WebScrapingStrategy an alias for LXMLWebScrapingStrategy
- Update LXMLWebScrapingStrategy to inherit directly from ContentScrapingStrategy
- Add required methods (scrap, ascrap, process_element, _log) to LXMLWebScrapingStrategy
- Maintain 100% backward compatibility - existing code continues to work
Code changes:
- crawl4ai/content_scraping_strategy.py: Remove WebScrapingStrategy class, add alias
- crawl4ai/async_configs.py: Remove WebScrapingStrategy from imports
- crawl4ai/__init__.py: Update imports to show alias relationship
- crawl4ai/types.py: Update type definitions
- crawl4ai/legacy/web_crawler.py: Update import to use alias
- tests/async/test_content_scraper_strategy.py: Update to use LXMLWebScrapingStrategy
- docs/examples/scraping_strategies_performance.py: Update to use single strategy
Documentation updates:
- docs/md_v2/core/content-selection.md: Update scraping modes section
- docs/md_v2/migration/webscraping-strategy-migration.md: Add migration guide
- CHANGELOG.md: Document the refactoring under [Unreleased]
Benefits:
- 10-20x faster HTML parsing for large documents
- Reduced memory usage and simplified codebase
- Consistent parsing behavior
- No migration required for existing users
All existing code using WebScrapingStrategy continues to work without
modification, while benefiting from LXML's superior performance.
- Remove unused StealthConfig from browser_manager.py
- Update LinkPreviewConfig import path in __init__.py and examples
- Fix infinity handling in content_scraping_strategy.py (use 0 instead of float('inf'))
- Remove sanitize_json_data functions from API endpoints
- Add comprehensive C4A Script documentation to release notes
- Update v0.7.0 release notes with improved code examples
- Create v0.7.1 release notes focusing on cleanup and documentation improvements
- Update demo files with corrected import paths and examples
- Fix virtual scroll and adaptive crawling examples across documentation
🤖 Generated with Claude Code
Co-Authored-By: Claude <noreply@anthropic.com>
This change removes the link_extractor module and renames it to link_preview, streamlining the codebase. The removal of 395 lines of code reduces complexity and improves maintainability. Other files have been updated to reflect this change, ensuring consistency across the project.
BREAKING CHANGE: The link_extractor module has been deleted and replaced with link_preview. Update imports accordingly.
Squashed commit from feature/link-extractor branch implementing comprehensive link analysis:
- Extract HTML head content from discovered links with parallel processing
- Three-layer scoring: Intrinsic (URL quality), Contextual (BM25), and Total scores
- New LinkExtractionConfig class for type-safe configuration
- Pattern-based filtering for internal/external links
- Comprehensive documentation and examples
Add ability to capture web pages as MHTML format, which includes all page resources
in a single file. This enables complete page archival and offline viewing.
- Add capture_mhtml parameter to CrawlerRunConfig
- Implement MHTML capture using CDP in AsyncPlaywrightCrawlerStrategy
- Add mhtml field to CrawlResult and AsyncCrawlResponse models
- Add comprehensive tests for MHTML capture functionality
- Update documentation with MHTML capture details
- Add exclude_all_images option for better memory management
Breaking changes: None
Adds new target_elements parameter to CrawlerRunConfig that allows more flexible content selection than css_selector. This enables focusing markdown generation and data extraction on specific elements while still processing the entire page for links and media.
Key changes:
- Added target_elements list parameter to CrawlerRunConfig
- Modified WebScrapingStrategy and LXMLWebScrapingStrategy to handle target_elements
- Updated documentation with examples and comparison between css_selector and target_elements
- Fixed table extraction in content_scraping_strategy.py
BREAKING CHANGE: Table extraction logic has been modified to better handle thead/tbody structures
Add comprehensive table detection and extraction functionality to the web scraping system:
- Implement intelligent table detection algorithm with scoring system
- Add table extraction with support for headers, rows, captions
- Update models to include tables in Media class
- Add table_score_threshold configuration option
- Add documentation and examples for table extraction
- Include crypto analysis example demonstrating table usage
This change enables users to extract structured data from HTML tables while intelligently filtering out layout tables.
Adds a new 'reverse' parameter to URLPatternFilter that allows inverting the filter's logic. When reverse=True, URLs that would normally match are rejected and vice versa.
Also removes unused 'scraped_html' from WebScrapingStrategy output to reduce memory usage.
BREAKING CHANGE: WebScrapingStrategy no longer returns 'scraped_html' in its output dictionary
Moves ProxyConfig from configs/ directory into proxy_strategy.py to improve code organization and reduce fragmentation. Updates all imports and type hints to reflect the new location.
Key changes:
- Moved ProxyConfig class from configs/proxy_config.py to proxy_strategy.py
- Updated type hints in async_configs.py to support ProxyConfig
- Fixed proxy configuration handling in browser_manager.py
- Updated documentation and examples to use new import path
BREAKING CHANGE: ProxyConfig import path has changed from crawl4ai.configs to crawl4ai.proxy_strategy
Add new PDF processing module with the following features:
- PDF text extraction and formatting to HTML/Markdown
- Image extraction with multiple format support (JPEG, PNG, TIFF)
- Link extraction from PDF documents
- Metadata extraction including title, author, dates
- Support for both local and remote PDF files
Also includes:
- New configuration options for HTML attribute handling
- Internal/external link filtering improvements
- Version bump to 0.4.300b4
Replace the ScrapingMode enum with a proper strategy pattern implementation for content scraping.
This change introduces:
- New ContentScrapingStrategy abstract base class
- Concrete WebScrapingStrategy and LXMLWebScrapingStrategy implementations
- New Pydantic models for structured scraping results
- Updated documentation reflecting the new strategy-based approach
BREAKING CHANGE: ScrapingMode enum has been removed. Users should now use ContentScrapingStrategy implementations instead.
Adds a new ScrapingMode enum to allow switching between BeautifulSoup and LXML parsing.
LXML mode offers 10-20x better performance for large HTML documents.
Key changes:
- Added ScrapingMode enum with BEAUTIFULSOUP and LXML options
- Implemented LXMLWebScrapingStrategy class
- Added LXML-based metadata extraction
- Updated documentation with scraping mode usage and performance considerations
- Added cssselect dependency
BREAKING CHANGE: None
- Fix JsonCssExtractionStrategy._get_elements to return all matching elements instead of just one
- Add robust error handling to page_need_scroll with default fallback
- Improve JSON extraction strategies documentation
- Refactor content scraping strategy
- Update version to 0.4.247
- Added examples for Amazon product data extraction methods
- Updated configuration options and enhance documentation
- Minor refactoring for improved performance and readability
- Cleaned up version control settings.
- Add llm.txt generator
- Added SSL certificate extraction in AsyncWebCrawler.
- Introduced new content filters and chunking strategies for more robust data extraction.
- Updated documentation.
- Fix crawler text mode for improved performance; cover missing `srcset` and `data_srcset` attributes in image tags.
- Introduced Managed Browsers for enhanced crawling experience.
- Updated documentation for clearer navigation on configuration.
- Changed 'text_only' to 'text_mode' in configuration and methods.
- Improved performance and relevance in content filtering strategies.
- Added markdown generator parameter to CrawlerRunConfig in `async_configs.py`.
- Implemented logic for Markdown generation in content scraping in `async_webcrawler.py`.
- Updated version number to 0.4.21 in `__version__.py`.
- Introduced new async crawl strategy with session management.
- Added BrowserManager for improved browser management.
- Enhanced documentation, focusing on storage state and usage examples.
- Improved error handling and logging for sessions.
- Added JavaScript snippets for customizing navigator properties.
- Enhanced the web scraping strategy with new methods for optimized media handling.
- Added new utility functions for better content processing.
- Refined existing features for improved accuracy and efficiency in scraping tasks.
- Introduced more robust filtering criteria for media elements.
- Introduced the PruningContentFilter for better content relevance.
- Implemented comprehensive unit tests for verification of functionality.
- Enhanced existing BM25ContentFilter tests for edge case coverage.
- Updated documentation to include usage examples for new filter.
- Updated version to 0.3.743
- Improved ManagedBrowser configuration with dynamic host/port
- Implemented fast HTML formatting in web crawler
- Enhanced markdown generation with a new generator class
- Improved sanitization and utility functions
- Added contributor details and pull request acknowledgments
- Updated documentation for clearer usage scenarios
- Adjusted tests to reflect class name changes
