""" Web Scraping Example This example demonstrates how to scrape web content and build knowledge bases using Semantica. Key Features Demonstrated: - Web content scraping and crawling - HTML content parsing and cleaning - Web content normalization - Entity extraction from web content - Relationship detection in web content - Knowledge base construction from web data Use Cases: - News article processing - Blog post analysis - Website content extraction - Social media content processing - E-commerce product information extraction """ class WebScrapingExample: """ Web scraping example implementation. This example shows how to: • Scrape web content from various sources • Parse HTML content and extract text • Normalize and clean web content • Extract entities and relationships • Build knowledge bases from web data • Handle different web content types """ def __init__(self): """ Initialize web scraping example. • Setup Semantica framework • Configure web scraping tools • Initialize content parsing • Setup knowledge extraction • Configure export handlers """ # TODO: Initialize Semantica framework # TODO: Setup WebIngestor for web scraping # TODO: Configure HTML parsing # TODO: Setup content normalization # TODO: Initialize entity extraction # TODO: Setup relationship detection pass def scrape_website(self, website_url, **options): """ Scrape content from a website. • Scrape web content from specified URL • Parse HTML content and extract text • Normalize and clean content • Extract entities and relationships • Build knowledge base • Export results Args: website_url: URL of website to scrape **options: Scraping options Returns: dict: Scraping results including knowledge base """ # TODO: Use WebIngestor to scrape website # TODO: Parse HTML content using WebParser # TODO: Normalize content using TextNormalizer # TODO: Extract entities using NamedEntityRecognizer # TODO: Extract relationships using RelationExtractor # TODO: Build knowledge base # TODO: Return scraping results pass def scrape_multiple_pages(self, page_urls, **options): """ Scrape content from multiple web pages. • Scrape multiple pages concurrently • Process each page individually • Aggregate results from all pages • Build comprehensive knowledge base Args: page_urls: List of page URLs to scrape **options: Scraping options Returns: dict: Aggregated scraping results """ # TODO: Use WebIngestor to scrape multiple pages # TODO: Process each page concurrently # TODO: Aggregate results from all pages # TODO: Build comprehensive knowledge base # TODO: Return aggregated results pass def scrape_with_sitemap(self, sitemap_url, **options): """ Scrape website using sitemap. • Parse sitemap to get page URLs • Scrape all pages in sitemap • Process sitemap structure • Build comprehensive knowledge base Args: sitemap_url: URL of website sitemap **options: Scraping options Returns: dict: Sitemap-based scraping results """ # TODO: Use SitemapCrawler to parse sitemap # TODO: Extract page URLs from sitemap # TODO: Scrape all pages in sitemap # TODO: Process sitemap structure # TODO: Build comprehensive knowledge base # TODO: Return sitemap-based results pass def process_news_articles(self, news_urls, **options): """ Process news articles from web sources. • Scrape news article content • Extract article metadata • Process article text content • Extract entities and relationships • Build news knowledge base Args: news_urls: List of news article URLs **options: News processing options Returns: dict: News processing results """ # TODO: Scrape news article content # TODO: Extract article metadata (title, date, author) # TODO: Process article text content # TODO: Extract entities and relationships # TODO: Build news knowledge base # TODO: Return news processing results pass def process_blog_posts(self, blog_urls, **options): """ Process blog posts from web sources. • Scrape blog post content • Extract post metadata • Process post text content • Extract entities and relationships • Build blog knowledge base Args: blog_urls: List of blog post URLs **options: Blog processing options Returns: dict: Blog processing results """ # TODO: Scrape blog post content # TODO: Extract post metadata (title, date, author, tags) # TODO: Process post text content # TODO: Extract entities and relationships # TODO: Build blog knowledge base # TODO: Return blog processing results pass def extract_web_entities(self, web_content, **options): """ Extract entities from web content. • Process web content for entity extraction • Extract named entities • Classify entity types • Handle entity disambiguation Args: web_content: Web content to process **options: Entity extraction options Returns: dict: Entity extraction results """ # TODO: Use NamedEntityRecognizer to extract entities # TODO: Classify entity types # TODO: Handle entity disambiguation # TODO: Return entity extraction results pass def extract_web_relationships(self, web_content, entities, **options): """ Extract relationships from web content. • Process web content for relationship extraction • Extract relationships between entities • Classify relationship types • Handle relationship disambiguation Args: web_content: Web content to process entities: Extracted entities **options: Relationship extraction options Returns: dict: Relationship extraction results """ # TODO: Use RelationExtractor to extract relationships # TODO: Classify relationship types # TODO: Handle relationship disambiguation # TODO: Return relationship extraction results pass def run_web_scraping_example(): """ Run the web scraping example. This function demonstrates the complete web scraping workflow. """ # TODO: Create WebScrapingExample instance # TODO: Define website URLs to scrape # TODO: Scrape website content # TODO: Extract knowledge from web content # TODO: Export results # TODO: Display results pass def run_news_scraping_example(): """ Run news article scraping example. This function demonstrates news article processing. """ # TODO: Create WebScrapingExample instance # TODO: Define news article URLs # TODO: Scrape news articles # TODO: Extract knowledge from news # TODO: Export news processing results # TODO: Display results pass def run_blog_scraping_example(): """ Run blog post scraping example. This function demonstrates blog post processing. """ # TODO: Create WebScrapingExample instance # TODO: Define blog post URLs # TODO: Scrape blog posts # TODO: Extract knowledge from blog posts # TODO: Export blog processing results # TODO: Display results pass