Awesome GitHub RepositoriesDistributed Crawling Systems

Ce projet est une ressource éducative et un guide d'étude complet axé sur l'architecture des systèmes distribués et la conception d'infrastructures backend. Il fournit un programme structuré pour maîtriser les principes de scalabilité, de fiabilité et de performance requis pour concevoir des systèmes logiciels complexes. Le dépôt se distingue en offrant une approche méthodique de la préparation aux entretiens techniques, intégrant des modèles de conception, des compromis architecturaux et des outils de répétition espacée pour aider les utilisateurs à retenir des concepts complexes. Il met l'accent sur l'analyse axée sur les contraintes, enseignant aux utilisateurs comment évaluer des exigences concurrentes comme la latence, la cohérence et la disponibilité lors de l'élaboration de conceptions architecturales. Le contenu couvre un large spectre de capacités de conception de systèmes, notamment des stratégies pour la mise à l'échelle des bases de données, la gestion du trafic et l'optimisation de l'infrastructure. Il détaille des techniques pour la mise à l'échelle horizontale, la mise en cache multicouche, la communication asynchrone et la découverte de services, tout en fournissant des cadres pour effectuer des estimations de ressources et la planification de la capacité. La documentation est organisée comme un guide d'étude, offrant un chemin systématique à travers les fondamentaux de l'ingénierie backend et de la conception de systèmes à grande échelle.

Crawl4AI is an AI-powered web crawling and data extraction engine designed to transform complex web content into structured formats. It functions as a headless browser orchestrator, enabling the navigation of dynamic websites, the execution of custom scripts, and the capture of visual assets like screenshots and PDFs. By integrating language models directly into the extraction workflow, the system converts raw HTML into clean, structured data or Markdown files optimized for downstream ingestion. The platform distinguishes itself through a distributed, self-hosted infrastructure that manages l

Scrapy is a comprehensive framework designed for automated web data extraction and large-scale crawling. It operates on an asynchronous, event-driven engine that manages non-blocking network requests and data processing tasks, allowing for the efficient retrieval of structured information from web documents using path-based selectors. The system distinguishes itself through a highly modular architecture that supports complex data collection workflows. Users can implement custom middleware and signal handlers to intercept and modify request flows, while a priority-based scheduler manages concu

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

This project is a comprehensive educational guide and framework for building web scrapers using Python. It provides a course-based approach to data extraction, combining a Python crawler framework with tutorials on web reverse engineering and network traffic analysis. The project distinguishes itself by covering advanced extraction challenges, including the decryption of obfuscated JavaScript and the bypass of anti-scraping measures. It specifically addresses mobile application scraping through the simulation of user interactions and the interception of network traffic. The capability surfac

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

This project is a comprehensive knowledge base and study resource designed for mastering technical interviews. It provides structured guides, roadmaps, and curricula focused on data structures, algorithms, system design, and frontend engineering to help candidates prepare for software engineering screenings. The repository distinguishes itself by offering a holistic approach to professional advancement. Beyond technical drills, it includes a career development handbook covering resume optimization, salary benchmarking, and strategic negotiation coaching. It also provides detailed methodologie