8 repository-uri
Systems for managing and running automated workflows or crawling tasks.
Distinguishing note: Focuses on the execution of targeted crawling tasks rather than the scraping logic itself.
Explore 8 awesome GitHub repositories matching web development · Task Execution Engines. Refine with filters or upvote what's useful.
MediaCrawler is an automated web scraping framework designed to extract public posts, comments, and creator metadata from various social media platforms. It functions as a headless browser automator, utilizing real browser instances to render dynamic content and execute the client-side scripts necessary for interacting with modern web interfaces. The system distinguishes itself through a focus on session persistence and network flexibility. It supports remote debugging to reuse active browser sessions and cookies, which helps minimize the risk of triggering platform security challenges. To ma
Retrieves specific content or user contributions by running crawling tasks across supported platforms.
Crawlee is a web scraping framework designed for building scalable, reliable, and distributed data extraction pipelines. It provides a unified interface for managing headless browser automation and lightweight HTTP requests, allowing developers to handle complex web navigation, dynamic content rendering, and large-scale data collection within a single, modular architecture. The project distinguishes itself through its resource-aware concurrency controller, which dynamically scales task execution based on real-time CPU and memory usage to prevent host machine exhaustion. It also features a rob
Fetches pending URLs for execution, tracks completion status, and allows for the reclamation of failed tasks.
PySpider is a Python web crawling framework designed for automated data extraction. It provides a pipeline for periodically fetching web content, processing HTML, and persisting scraped information into database backends. The system features a web-based management interface for editing scraping scripts, monitoring task progress, and reviewing collected data. It includes a headless browser JavaScript renderer to capture rendered HTML from dynamic web pages and a distributed architecture that uses message queues to scale crawling workloads across multiple nodes. The framework also covers task
Implements a system for organizing web crawling jobs into projects to manage the lifecycle of individual crawl tasks.
Pholcus is a distributed web crawling system designed for large-scale data scraping. It employs a master-worker distribution model to coordinate high-concurrency scraping tasks across a network of remote client nodes, enabling both horizontal and vertical data collection. The system features a hot-loadable rule engine that allows extraction and navigation logic to be updated at runtime without restarting the process. It handles dynamic content through headless browser integration and bypasses bot detection using proxy rotation, automated user authentication, and simulated human behavior. The
Offers comprehensive crawl task management to pause, cancel, and execute scraping jobs in batch concurrency.
node-crawler is a programmable web crawler for Node.js that manages request queues and automates data extraction. It functions as a rate-limited HTTP client and a headless HTML parser, providing the infrastructure to visit large sets of URLs asynchronously while preventing duplicate processing through task deduplication. The project distinguishes itself through a proxy rotation manager that cycles user agents and proxy servers to bypass access restrictions. It utilizes the HTTP/2 protocol to improve request performance and server compatibility during large-scale scraping operations. The syst
Prevents the same URL or task from entering the queue multiple times to avoid redundant processing.
Acest proiect este un framework distribuit de web crawling headless Chrome și de extracție a datelor. Funcționează ca un motor de randare JavaScript care utilizează un browser headless pentru a procesa pagini dinamice, extrăgând date structurate de pe site-uri web care necesită execuție JavaScript. Sistemul este conceput pentru colectarea scalabilă a datelor pe mai multe noduri, utilizând sincronizarea distribuită a sarcinilor și cache-uri partajate pentru a preveni munca duplicată. Se distinge prin capacitatea de a emula medii client specifice prin configurarea user-agent-urilor și a dimensiunilor viewport-ului, capturând în același timp dovezi vizuale precum capturi de ecran ale paginilor. Framework-ul acoperă gestionarea cuprinzătoare a crawl-ului, inclusiv programarea cererilor în cozi de prioritate, traversarea depth-first și breadth-first și respectarea fișierelor robots.txt și sitemap.xml. Oferă instrumente pentru limitarea concurenței, monitorizarea evenimentelor și streaming-ul datelor extrase în formate CSV sau JSON.
Manages the lifecycle of crawl tasks, including the ability to halt and restart operations while preserving state.
OpenChat is a conversational AI agent builder and customer service automation platform that uses large language models to power customer support chatbots across multiple channels. It provides tools for defining AI agent behavior, training on custom knowledge, managing actions, and controlling autopilot responses per channel. The platform enables deploying AI agents on web, phone, email, SMS, and WhatsApp, with a unified inbox for managing conversations across all channels. It includes CRM synchronization, automated workflows, contact segmentation, and analytics for tracking customer satisfact
Manages the lifecycle of crawl tasks including queuing and status inspection.
Go Spider este un framework modular conceput pentru construirea de web scraper-e concurente și fluxuri de lucru de extracție a datelor. Oferă un motor structurat pentru orchestrarea sarcinilor de crawling automatizate, gestionarea programării cererilor și procesarea conținutului web printr-un pipeline unificat. Framework-ul se distinge printr-o arhitectură extrem de configurabilă care permite dezvoltatorilor să injecteze logică personalizată pentru downloadere, schedulere și componente de stocare prin contracte bazate pe interfețe. Gestionează interacțiunile de rețea utilizând throttling-ul cererilor bazat pe middleware și deduplicarea URL-urilor, asigurând că operațiunile de crawling rămân eficiente și respectuoase față de încărcarea serverului. Sistemul acoperă întregul ciclu de viață al extracției datelor, inclusiv execuția concurentă a sarcinilor, parsarea automată a diverselor formate de conținut și normalizarea codificării caracterelor. Oferă, de asemenea, monitorizare încorporată prin logarea execuției și tracing pentru a facilita depanarea și analiza performanței. Proiectul este distribuit ca bibliotecă pentru limbajul de programare Go.
Manages the lifecycle of individual crawl tasks, allowing for streaming results or immediate local return.