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ferretvskimurai

Apache-2.0 34 8 5,964
58.1 thousand (month) Oct 28 2020 v2.0.0-alpha.7(2026-04-07 15:33:51 ago)
1,098 1 14 MIT
Aug 23 2018 2.4 thousand (month) 2.2.0(2026-01-27 17:36:19 ago)

Ferret is a web scraping system. It aims to simplify data extraction from the web for UI testing, machine learning, analytics and more. ferret allows users to focus on the data. It abstracts away the technical details and complexity of underlying technologies using its own declarative language. It is extremely portable, extensible, and fast.

Features

  • Declarative language
  • Support of both static and dynamic web pages
  • Embeddable
  • Extensible

Ferret is always implemented in Python through pyfer

Kimurai is a modern web scraping framework for Ruby, inspired by Python's Scrapy. It provides a structured approach to building web scrapers with built-in support for multiple browser engines, session management, and data pipelines.

Key features include:

  • Multiple engine support Can use different backends depending on the scraping needs: Mechanize for simple HTTP requests, Selenium with headless Chrome/Firefox for JavaScript-rendered pages, and Poltergeist (PhantomJS) for lightweight rendering.
  • Scrapy-like architecture Follows the spider pattern: define a spider class with start URLs and parsing methods, and the framework handles crawling, scheduling, and data collection.
  • Built-in data pipelines Save scraped data to JSON, CSV, or custom formats with configurable output pipelines.
  • Session management Maintains browser sessions with automatic cookie handling and configurable delays between requests.
  • Request scheduling Built-in request queue with configurable concurrency, delays, and retry logic.
  • CLI tools Command-line tools for generating new spiders, running individual spiders, and managing scraping projects.

Kimurai is the closest Ruby equivalent to Scrapy. It's well-suited for structured scraping projects that need organization, multiple spiders, and data pipeline processing.

Note: Kimurai has not seen active development recently, but it remains a useful framework for Ruby scraping projects and is included as the most complete Ruby scraping framework available.

Highlights


middlewaresoutput-pipelines

Example Use


```go // Example scraper for Google in Ferret: LET google = DOCUMENT("https://www.google.com/", { driver: "cdp", userAgent: "Mozilla/5.0 (Macintosh; Intel Mac OS X 10_14_6) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/76.0.3809.87 Safari/537.36" }) HOVER(google, 'input[name="q"]') WAIT(RAND(100)) INPUT(google, 'input[name="q"]', @criteria, 30) WAIT(RAND(100)) CLICK(google, 'input[name="btnK"]') WAITFOR EVENT "navigation" IN google WAIT_ELEMENT(google, "#res") LET results = ELEMENTS(google, X("//*[text() = 'Search Results']/following-sibling::*/*")) FOR el IN results RETURN { title: INNER_TEXT(el, 'h3')?, description: INNER_TEXT(el, X("//em/parent::*")), url: ELEMENT(el, 'a')?.attributes.href } ```
```ruby require 'kimurai' class ProductSpider < Kimurai::Base @name = 'product_spider' @engine = :selenium_chrome # or :mechanize for simple pages @start_urls = ['https://example.com/products'] def parse(response, url:, data: {}) # Extract product data from current page response.css('.product').each do |product| item = { name: product.css('.name').text.strip, price: product.css('.price').text.strip, url: absolute_url(product.at_css('a')['href'], base: url), } # Send item to the pipeline save_to "products.json", item, format: :json end # Follow pagination links if next_page = response.at_css('a.next-page') request_to :parse, url: absolute_url(next_page['href'], base: url) end end end # Run the spider ProductSpider.crawl! ```

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