jaypyles/ScraperrArchived
Scraperr
Scraperr is a self-hosted web scraping and crawling platform designed for extracting structured data from websites using XPath selectors. It functions as a containerized system for managing scraping jobs through a queue and analyzing the resulting content using artificial intelligence.
The project differentiates itself through its Kubernetes-native architecture, allowing for scalable deployment and management via package managers. It includes a crawling engine capable of domain-level spidering to discover linked pages and a data analyzer that uses artificial intelligence to query extracted web content.
The platform covers a broad range of capabilities, including automated data extraction, bulk web crawling, and media file downloading. It provides tools for visualizing scraped data in tables, configuring custom request headers to mimic browser identities, and exporting results into CSV or Markdown formats.
The application supports customizable installation parameters and version updates through Kubernetes deployment configurations.
Features
- XPath Data Extractors - Uses XPath selectors to precisely target and extract specific data elements from web pages.
- Web Scraping and Extraction - Provides a self-hosted platform for extracting structured data from websites using XPath selectors.
- Automated Web Scraping - Provides a self-hosted platform for automatically extracting structured information from websites.
- CSS and XPath Query Engines - Utilizes XPath expressions to locate and extract specific nodes from parsed HTML documents.
- Domain-Restricted Crawling - Includes a crawling engine that limits link discovery to a specific root domain for focused data collection.
- Kubernetes Application Deployments - Utilizes a Kubernetes-native architecture for scalable deployment and automated application management.
- Job Queues - Manages bulk scraping tasks through a sequential job queue to ensure reliable data collection.
- Data Extractions - Uses XPath selectors and DOM traversal to pull structured data from multiple URLs.
- Domain Spidering - Implements a crawler that visits all linked pages within a domain to discover wide-ranging content.
- Scraping Infrastructure Management - Provides infrastructure to submit and track multiple scraping tasks via a centralized job queue.
- Web Crawling - Systematically discovers and indexes web content across entire domains for large-scale data collection.
- Web Scrapers - Ships an automated system for navigating websites and extracting structured data via a job queue.
- Selector Mappings - Enables precise data extraction by mapping target URLs to specific XPath selectors.
- Content Query Analyzers - Integrates AI to allow users to query and analyze the extracted web content using natural language.
- Web Content AI Analysis - Implements AI-driven analysis to query and retrieve information from extracted web content.
- AI-Powered Intelligence - Leverages artificial intelligence to query and extract insights from large volumes of scraped web content.
- CSV Data Exports - Exports scraped data into CSV and Markdown files for external analysis in spreadsheet applications.
- AI Data Analysis Tools - Provides a capability to answer questions based on scraped web data using AI model APIs.
- Kubernetes-Native Data Platforms - Implements a containerized scraping platform designed specifically for scalable orchestration on Kubernetes.
- File-Based Data Exports - Serializes collected web data into structured formats such as CSV and Markdown for external use.
- Scraped Data Exporters - Converts results from completed scraping jobs into structured CSV files.
- Kubernetes Application Deployments - Provides a Kubernetes-native architecture for scalable deployment and management of the scraping platform.
