scraplingvsspidr
Scrapling is an adaptive web scraping framework for Python that introduces "self-healing" selectors — selectors that can track and find elements even when the website's DOM structure changes. This solves one of the biggest maintenance headaches in web scraping: broken selectors after website updates.
Key features include:
- Self-healing selectors Scrapling uses smart element matching that can identify target elements even after the page structure changes. It builds a fingerprint of the element based on multiple attributes (text, position, siblings, attributes) and uses fuzzy matching to relocate it.
- Multiple parsing backends Supports different parsing engines including lxml (fast) and a custom engine, allowing you to choose the right balance of speed and features.
- Scrapy-like Spider API Provides a familiar Spider class pattern for organizing crawling logic, similar to Scrapy but with the added benefit of adaptive selectors.
- CSS and XPath selectors Full support for CSS selectors and XPath, plus the adaptive matching system on top.
- Type hints and modern Python Built with full type annotations and 92% test coverage for reliability.
- Async support Supports asynchronous crawling for efficient concurrent scraping.
Scrapling gained massive traction in 2025 as one of the most starred new Python scraping libraries. It is particularly useful for scraping targets that frequently update their HTML structure, where traditional selector-based scrapers would break.
Spidr is a Ruby gem that provides a simple and flexible way to spider and scrape websites. It allows you to easily navigate through a website, following links and scraping data as you go. It is built on top of Nokogiri, a popular Ruby gem for parsing and searching HTML and XML documents, and it provides a simple and intuitive API for defining and running web scraping operations.
One of the main features of Spidr is its ability to spider a website, following all the links on a page and visiting all the pages of a website. This allows you to easily and quickly scrape large amounts of data from a website, without having to manually specify which pages to visit.
In addition to its spidering capabilities, Spidr also provides a variety of other features that can simplify the web scraping process. It can automatically filter which links to follow and which pages to visit, it can handle cookies and authentication, and it can automatically store the scraped data in a database or file. It also provides a built-in support for parallelism and queueing to speed up the scraping process.