lxmlvsscrapling
lxml is a low-level XML and HTML tree processor. It's used by many other libraries such as parsel or beautifulsoup for higher level HTML parsing.
One of the main features of lxml is its speed and efficiency.
It is built on top of the libxml2 and libxslt C libraries, which are known for their high performance and low memory footprint.
This makes lxml well-suited for processing large and complex XML and HTML documents.
One of the key components of lxml is the ElementTree API, which is modeled after the ElementTree API from the Python standard library's xml module. This API provides a simple and intuitive way to access and manipulate the elements and attributes of an XML or HTML document. It also provides a powerful and flexible Xpath engine that allows you to select elements based on their names, attributes, and contents.
Another feature of lxml is its support for parsing and creating XML documents using the XSLT standard. The lxml library provides a powerful and easy-to-use interface for applying XSLT stylesheets to XML documents, which can be used to transform and convert XML documents into other formats, such as HTML, PDF, or even other XML formats.
For web scraping it's best to use other higher level libraries that use lxml like parsel or beautifulsoup
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.
Highlights
Example Use
Product Title
paragraph 1
paragraph2
$10