Last modified: Jan 10, 2026 By Alexander Williams
BeautifulSoup vs lxml: Which Python Parser to Use
Python web scraping needs a good parsing library. Two top choices are BeautifulSoup and lxml. This guide compares them.
We will look at speed, ease of use, and features. You will learn which tool fits your project best.
What is BeautifulSoup?
BeautifulSoup is a Python library. It creates parse trees from HTML and XML. It is very popular for web scraping.
It provides simple methods to navigate and search the tree. You can use it with different parsers like lxml or html.parser.
For a smooth start, see our Install BeautifulSoup in Python Step by Step guide.
What is lxml?
lxml is a powerful library for processing XML and HTML. It is very fast and feature-rich. It uses the libxml2 and libxslt C libraries.
lxml supports XPath and XSLT. It is known for its high performance. It can handle large documents efficiently.
Key Differences: A Head-to-Head Comparison
Let's break down the main differences between these two tools.
Parsing Speed and Performance
lxml is significantly faster. It is written in C. This makes it ideal for large-scale scraping.
BeautifulSoup is slower. Its speed depends on the underlying parser you choose. Using lxml as the parser makes BeautifulSoup faster.
Ease of Use and Syntax
BeautifulSoup is easier for beginners. Its API is intuitive. Methods like find_all() are simple to learn.
lxml has a steeper learning curve. Its XPath syntax is powerful but more complex. It is great for developers needing precise control.
Error Handling and Fault Tolerance
BeautifulSoup is very forgiving. It can parse messy, broken HTML commonly found on the web. It creates a valid tree from bad markup.
lxml is stricter by default. It expects well-formed documents. You can configure it to be more lenient, but it's not its default mode.
Feature Set and Flexibility
lxml has a broader native feature set. It includes full XPath 1.0 support, XSLT, and validation against schemas.
BeautifulSoup focuses on HTML/XML navigation and search. It excels at the core tasks of web scraping. For complex nested structures, our Parse Nested HTML with BeautifulSoup Guide can help.
Code Examples: Side-by-Side Comparison
Let's see how to extract all links from a page with both libraries.
Example with BeautifulSoup
from bs4 import BeautifulSoup
html_doc = """
<html>
<body>
<a href="https://example.com/page1">Link 1</a>
<p>Some text.</p>
<a href="https://example.com/page2">Link 2</a>
</body>
</html>
"""
# Parse the HTML
soup = BeautifulSoup(html_doc, 'html.parser')
# Find all anchor tags
links = soup.find_all('a')
# Print the href attribute for each link
for link in links:
print(link.get('href'))
https://example.com/page1
https://example.com/page2
Example with lxml
from lxml import html
html_doc = """
<html>
<body>
<a href="https://example.com/page1">Link 1</a>
<p>Some text.</p>
<a href="https://example.com/page2">Link 2</a>
</body>
</html>
"""
# Parse the HTML
tree = html.fromstring(html_doc)
# Use XPath to find all anchor tags
links = tree.xpath('//a/@href')
# Print each link
for link in links:
print(link)
https://example.com/page1
https://example.com/page2
Both get the job done. BeautifulSoup uses find_all(). lxml uses an XPath expression.
When to Use BeautifulSoup
Choose BeautifulSoup for quick scraping tasks. It is perfect for beginners.
Use it when HTML is messy or malformed. Its fault tolerance is a major strength.
Pick it for projects where developer speed is more critical than execution speed. Its simple API gets you results fast.
If you need to scrape modern JavaScript-heavy sites, pair it with a tool like requests-html. Learn more in our guide on Scrape Dynamic Content with BeautifulSoup & Requests-HTML.
When to Use lxml
Choose lxml for processing large volumes of data. Its speed is unmatched in Python.
Use it when you need XPath or XSLT. These are powerful query languages for complex documents.
Pick it for applications where performance is the top priority. This includes production scrapers and data pipelines.
Can You Use Them Together?
Yes! This is a common and powerful pattern. You can use lxml as the parser engine for BeautifulSoup.
This combines lxml's speed with BeautifulSoup's simple API. Here is how:
from bs4 import BeautifulSoup
# Parse using the lxml parser for speed
soup = BeautifulSoup(html_doc, 'lxml')
# Now use BeautifulSoup's easy methods
You get the best of both worlds. Fast parsing with an easy-to-use interface.
Conclusion: Which One Wins?
There is no single winner. The best choice depends on your project's needs.
Use BeautifulSoup if you are new to web scraping. Use it for small to medium projects. Use it when HTML quality is poor.
Use lxml if you need maximum speed. Use it for large-scale data extraction. Use it if you require XPath.
For many developers, using BeautifulSoup with the lxml parser is the ideal compromise. It offers great speed and a gentle learning curve.
Start with BeautifulSoup to learn the basics. Move to lxml as your projects grow in scale and complexity. Happy scraping!