Data extraction is the process of retrieving data from various sources for further processing or storage. In web context, it involves: - Identifying relevant data points - Parsing structured and unstructured content - Converting data into desired formats - Cleaning and validating extracted information
Data parsing is the process of converting raw data into a structured format that can be easily analyzed and processed. In web data extraction context, it includes: - Converting HTML/XML structures into organized data - Identifying and extracting specific data patterns - Handling different data types (text, numbers, dates) - Managing nested data structures - Cleaning and normalizing extracted data
Data transformation is the process of converting extracted data from one format to another, making it suitable for specific use cases. This includes: - Format conversion (JSON, CSV, Excel) - Data structure reorganization - Field mapping and normalization - Data cleaning and validation - Custom template application
Data validation tools ensure the quality and accuracy of extracted data. Essential functions include: - Data format verification - Field type checking - Required field validation - Custom validation rules - Error reporting - Data cleaning automation
Dynamic content extraction refers to the ability to capture data from websites that load content dynamically through JavaScript or AJAX. Key aspects include: - JavaScript rendered content handling - Single Page Application (SPA) support - Real-time data capture - Infinite scroll handling - Dynamic state management
Extraction monitoring provides real-time oversight of data extraction processes. Key features include: - Progress tracking - Performance metrics - Error detection - Resource usage monitoring - Status reporting - Alert systems
Extraction rules define how data should be identified and captured from web pages. Important components include: - Selection patterns - Data validation rules - Extraction conditions - Field mappings - Error handling logic - Filter criteria
Extraction workflow describes the end-to-end process of web data extraction. Key stages include: - Target identification - Rule configuration - Data extraction - Validation and cleaning - Export and storage - Result verification
A template system in data extraction provides reusable patterns for consistent data collection and output formatting. Key features include: - Predefined extraction patterns - Custom output formatting - Variable substitution - Conditional logic handling - Template sharing and reuse - Version control support
Tool configuration refers to the customization and setup of extraction tools. Important aspects include: - User preferences - Extraction settings - Performance tuning - Proxy configuration - Rate limiting - Authentication setup