Experienced SEO professionals know that there’s much more to it than just copying and pasting some data into Google.
Since some of the information might be outdated or inaccurate, it’s considered wise to rely on a legit source while scraping so that you can derive accurate data.
Of course, finding a good library for web scraping is not easy. Still, when you find one, you are assured that your information is reliable, saving you loads of time.
With that said, here are the four most powerful libraries for web scraping.
Using libxslt for parsing HTML is a general-purpose solution for reading XML and HTML files. The libxslt library provides a set of functions for transforming documents with XML syntax, supporting many of the standard constructs found in such documents. It also offers some support for HTML documents.
- XPath is used to find nodes in an XML document, and libxslt provides a function that allows an easy way of parsing HTML documents using XPath syntax.
- A lot of the complicated work of figuring out how to traverse the DOM is done by libxslt so you can focus on what you want to extract from the web page instead of how to get your data.
- As long as you have the correct system libraries installed, you can use libxslt on pretty much any platform.
- It is a complex library, and to use it properly, you need to be familiar with basic XSLT and XPath.
- Given its complexity, it can be hard to debug libxslt-based stylesheets.
- libxslt is a C library which means that you have to compile your stylesheet into a binary form before it can run.
LXML is a Python binding for the libxslt and libxml2 libraries. It’s designed to be small, portable, and efficient. LXML can be a good choice for heavyweight XML processing tasks, such as validating or transforming large XML documents.
- It uses the Expat parser to parse XML into an object tree, giving it general support for processing XML with XPath expressions.
- It is easy to find an lxml tutorial online to guide you through. To get started with lxml, check here.
- Lxml is a complex library that makes it challenging to diagnose simple parsing problems.
- Lxml does not provide you with any help when validating documents. So it’s up to you to ensure your XML documents aren’t malformed or invalid before trying to parse them.
- Lxml uses libxml2 and libxslt, which means that it can take longer to parse XML files on some systems.
Beautiful Soup is a Python library initially created by Ian Bicking and maintained by Daniel Moth. It helps you parse HTML and XML documents using regular expressions.
Beautiful Soup offers several simple methods and Pythonic idioms for searching, navigating, and modifying a parse tree: a toolkit for dissecting a document and fetching the data required.
Although Beautiful Soup provides some support for XML parsing, its real strength is in HTML parsing, which it does with the help of html5lib, an alternative HTML parser.
Using Beautiful Soup You can use Beautiful Soup to pull out parts of a document by their structure rather than manually inspecting the document’s markup.
This speeds up parsing operations and makes them more robust against real-world HTML that often contains invalid tags or attributes.
- It’s fast, both in terms of parsing and generation. I find my pages load faster because they’re smaller.
- It’s more compact than other similar libraries. There is no separate DOM object in BeautifulSoup; the parser doesn’t generate one behind the scenes; it just parses the HTML into a generic Python object. That leaves less to throw away when you’re done with it.
- It’s powerful, flexible, and well-documented.
- Beautiful Soup has no direct way to select a particular XML tag by its name.
- It doesn’t do well with mistakes in your HTML or XML markup.
- It has some problems dealing with namespaces.
PyQuery is a jQuery-like library written in Python that makes it easy to find and manipulate HTML documents using an API similar to jQuery.
- It’s written in Python, which is an elegant language.
- It can use XPath expressions in CSS selectors if you want more precision in selecting nodes on a page.
- It does not have full support for all major browsers.
- Since it is a Python library, you must have Python installed on your server to use it on your website or project.
- There aren’t as many tutorials and resources available on using PyQuery, unlike lxml tutorials.
The Bottom Line
While the process of web scraping might be complicated, it can undoubtedly be rewarding if you have the right tools. These libraries are a place to start if you want to make your life easier with web scraping.
Overall, these four libraries are easy to use and learn. While none of them is perfect, they’re all still quite good. Of course, there are many more libraries out there that work just as well, so you should look out for more if experimenting is your thing.