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crawleevsrvest

Apache-2.0 175 26 22,720
341.9 thousand (month) Apr 22 2022 3.16.0(2026-04-09 07:36:53 ago)
1,517 1 38 MIT
Nov 22 2014 534.7 thousand (month) 1.0.5(2024-02-12 21:10:00 ago)

Crawlee is a modern web scraping and browser automation framework for JavaScript and TypeScript, built by Apify. It is the successor to the Apify SDK and provides a unified interface for building reliable web scrapers and crawlers that can scale from simple scripts to large-scale data extraction projects.

Crawlee supports multiple crawling strategies through different crawler classes:

  • CheerioCrawler For fast, lightweight HTML scraping using Cheerio (no browser needed). Best for static pages.
  • PlaywrightCrawler Uses Playwright for full browser automation. Handles JavaScript-rendered pages, SPAs, and complex interactions.
  • PuppeteerCrawler Similar to PlaywrightCrawler but uses Puppeteer as the browser automation backend.
  • HttpCrawler Minimal crawler for raw HTTP requests without HTML parsing.

Key features include:

  • Automatic request queue management with configurable concurrency and rate limiting
  • Built-in proxy rotation with session management
  • Persistent request queue and dataset storage (local or cloud via Apify)
  • Automatic retry and error handling with configurable strategies
  • TypeScript-first design with full type safety
  • Middleware-like request/response hooks (preNavigationHooks, postNavigationHooks)
  • Output pipelines for storing extracted data
  • Easy deployment to Apify cloud platform

Crawlee is considered the most feature-complete web scraping framework in the JavaScript/TypeScript ecosystem, comparable to Python's Scrapy but with native browser automation support.

rvest is a popular R library for web scraping and parsing HTML and XML documents. It is built on top of the xml2 and httr libraries and provides a simple and consistent API for interacting with web pages.

One of the main advantages of using rvest is its simplicity and ease of use. It provides a number of functions that make it easy to extract information from web pages, even for those who are not familiar with web scraping. The html_nodes and html_node functions allow you to select elements from an HTML document using CSS selectors, similar to how you would select elements in JavaScript.

rvest also provides functions for interacting with forms, including html_form, set_values, and submit_form functions. These functions make it easy to navigate through forms and submit data to the server, which can be useful when scraping sites that require authentication or when interacting with dynamic web pages.

rvest also provides functions for parsing XML documents. It includes xml_nodes and xml_node functions, which also use CSS selectors to select elements from an XML document, as well as xml_attrs and xml_attr functions to extract attributes from elements.

Another advantage of rvest is that it provides a way to handle cookies, so you can keep the session alive while scraping a website, and also you can handle redirections with handle_redirects

Highlights


populartypescriptextendiblemiddlewaresoutput-pipelineslarge-scaleproxy

Example Use


```javascript import { PlaywrightCrawler, Dataset } from 'crawlee'; // Create a crawler with Playwright for JS rendering const crawler = new PlaywrightCrawler({ // Limit concurrency to avoid overwhelming the target maxConcurrency: 5, // This function is called for each URL async requestHandler({ request, page, enqueueLinks }) { const title = await page.title(); // Extract data from the page const products = await page.$$eval('.product', (els) => els.map((el) => ({ name: el.querySelector('.name')?.textContent, price: el.querySelector('.price')?.textContent, })) ); // Store extracted data await Dataset.pushData({ url: request.url, title, products, }); // Follow links to crawl more pages await enqueueLinks({ globs: ['https://example.com/products/**'], }); }, }); // Start crawling await crawler.run(['https://example.com/products']); ```
```r library("rvest") # Rvest can use basic HTTP client to download remote HTML: tree <- read_html("http://webscraping.fyi/lib/r/rvest") # or read from string: tree <- read_html(' ') # to parse HTML trees with rvest we use r pipes (the %>% symbol) and html_element function: # we can use css selectors: print(tree %>% html_element(".products>a") %>% html_text()) # "[1] "\nCat Food\nDog Food\n"" # or XPath: print(tree %>% html_element(xpath="//div[@class='products']/a") %>% html_text()) # "[1] "\nCat Food\nDog Food\n"" # Additionally rvest offers many quality of life functions: # html_text2 - removes trailing and leading spaces and joins values print(tree %>% html_element("div") %>% html_text2()) # "[1] "Cat Food Dog Food"" # html_attr - selects element's attribute: print(tree %>% html_element("div") %>% html_attr('class')) # "products" ```

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