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rolando avatar

rolando/scrapy-redis

0
View on GitHub↗
5,639 stars·1,581 forks·Python·MIT·15 viewsscrapy-redis.readthedocs.io↗

Scrapy Redis

This project is a distributed web crawling framework that enables the horizontal scaling of scraping tasks. It uses Redis as a centralized request queue manager and state store to coordinate crawl progress and request metadata across multiple server instances.

The system distributes crawling workloads by sharing a single request queue and utilizes a distributed duplicate filter to prevent multiple workers from visiting the same page. It persists complex request state and metadata as JSON strings within the shared remote store.

The framework also provides capabilities for distributed data processing by pushing scraped items into a shared queue for parallel consumption by separate processing workers.

Features

  • Crawl Request Queues - Provides a centralized Redis-backed queue to coordinate HTTP crawl requests across distributed worker instances.
  • Distributed Crawl State Stores - Provides a shared Redis storage backend for tracking visited URLs and crawl progress across server instances.
  • Distributed Web Crawling - Provides a framework for scaling Scrapy crawlers across multiple servers using Redis for coordination.
  • Horizontal Crawler Scaling - Increases crawling throughput by running multiple Scrapy instances pulling from a single centralized Redis queue.
  • Visited URL Sets - Implements shared visited URL sets in Redis to ensure collaborative deduplication across a crawler cluster.
  • Distributed Crawl Workload Distribution - Distributes crawling tasks across several server instances by sharing a single centralized request queue.
  • URL Duplicate Filters - Implements a shared Redis set to prevent multiple distributed workers from crawling the same URL.
  • Crawl Request Deduplications - Prevents redundant crawling of the same page by tracking visited URLs in a shared Redis set.
  • Scrapy-Framework-Based Crawlers - Extends the Scrapy framework to support distributed crawling using Redis for queue and deduplication coordination.
  • Web Crawling Frameworks - Serves as a comprehensive framework for scaling web scraping tasks horizontally via shared state.
  • Distributed Data Processing - Facilitates distributed data processing by pushing scraped items into shared queues for parallel worker consumption.
  • Redis Item Queues - Pushes scraped items into a shared Redis queue for parallel consumption by separate processing workers.
  • Python Crawling Frameworks - Redis-based components for distributed Scrapy projects.

Star history

Star history chart for rolando/scrapy-redisStar history chart for rolando/scrapy-redis

How this analysis was created: This summary and feature list are AI-generated from collected project material and can contain mistakes. Stars, license and language are imported from GitHub. Inclusion does not mean that we have tested or audited this project. Check the source documentation for any feature you depend on. Learn more on our About page.

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Projects sharing features with Scrapy Redis

These projects share indexed features with Scrapy Redis. Shared tags can include platform or build tooling; verify the primary use case before treating a result as a replacement.
  • rmax/scrapy-redisrmax avatar

    rmax/scrapy-redis

    5,639View on GitHub↗

    Scrapy-Redis is a library that transforms Scrapy into a distributed web crawling framework by replacing its in-memory scheduler with a Redis-backed component. This allows multiple Scrapy spider workers to coordinate through a shared request queue, enabling them to consume URLs concurrently while a Redis set tracks seen URLs across all workers to prevent duplicate crawls. The system persists crawl state—including pending requests and already-crawled URLs—in Redis, so a paused or crashed spider can resume from where it left off without losing progress. The library provides a Redis-based duplica

    Pythoncrawlerdistributedredis
    View on GitHub↗5,639
  • yujiosaka/headless-chrome-crawleryujiosaka avatar

    yujiosaka/headless-chrome-crawler

    5,643View on GitHub↗

    This project is a distributed headless Chrome web crawler and data extraction framework. It functions as a JavaScript rendering engine that uses a headless browser to process dynamic pages, extracting structured data from websites that require JavaScript execution. The system is designed for scalable data collection across multiple nodes, using distributed task synchronization and shared caches to prevent duplicate work. It distinguishes itself through the ability to emulate specific client environments by configuring user agents and viewport dimensions, while capturing visual evidence such a

    JavaScript
    View on GitHub↗5,643
  • gnemoug/distribute_crawlergnemoug avatar

    gnemoug/distribute_crawler

    3,243View on GitHub↗

    Distribute crawler is a distributed web scraping framework that integrates with Scrapy to coordinate multiple crawler instances across clusters. It utilizes a centralized task queue to manage and scale concurrent data collection operations, enabling horizontal scaling of scraping tasks across multiple worker nodes. The framework distinguishes itself through its focus on large-scale data management and traffic control. It persists scraped items and binary assets into document-oriented database clusters, utilizing deduplication logic to optimize bandwidth and storage. To maintain consistent dat

    Python
    View on GitHub↗3,243
  • boris-code/feapderBoris-code avatar

    Boris-code/feapder

    3,709View on GitHub↗

    Feapder is a Python web crawling framework designed for building scalable data extraction systems. It features a distributed spider engine and a headless browser renderer to execute JavaScript and extract content from dynamic web pages. The system includes a scalable data deduplicator to filter duplicate URLs and records during large-scale operations. A crawler monitoring system tracks the health of active scraping jobs and triggers alerts when system anomalies occur. The framework provides capabilities for task scheduling, web data extraction, and resilient workflows that allow crawling tas

    Pythoncrawlerfeapderfeaplat
    View on GitHub↗3,709
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Frequently asked questions

What does rolando/scrapy-redis do?

This project is a distributed web crawling framework that enables the horizontal scaling of scraping tasks. It uses Redis as a centralized request queue manager and state store to coordinate crawl progress and request metadata across multiple server instances.

What are the main features of rolando/scrapy-redis?

The main features of rolando/scrapy-redis are: Crawl Request Queues, Distributed Crawl State Stores, Distributed Web Crawling, Horizontal Crawler Scaling, Visited URL Sets, Distributed Crawl Workload Distribution, URL Duplicate Filters, Crawl Request Deduplications.

Which projects share features with rolando/scrapy-redis?

Projects with overlapping indexed features include: rmax/scrapy-redis — Scrapy-Redis is a library that transforms Scrapy into a distributed web crawling framework by replacing its in-memory… yujiosaka/headless-chrome-crawler — This project is a distributed headless Chrome web crawler and data extraction framework. It functions as a JavaScript… gnemoug/distribute_crawler — Distribute crawler is a distributed web scraping framework that integrates with Scrapy to coordinate multiple crawler… boris-code/feapder — Feapder is a Python web crawling framework designed for building scalable data extraction systems. It features a… binux/pyspider — PySpider is a Python web crawling framework designed for automated data extraction. It provides a pipeline for… scrapinghub/portia — Portia is a containerized scraping platform and visual web scraper that enables no-code data extraction. It serves as…