When working with XML data in Python, parsing and processing the XML can often be a bottleneck. Choosing the right XML parsing library is crucial for performance. In this article, we'll compare different Python XML parsers to find the fastest option.
XML Parsing Options in Python
The main XML parsing libraries in Python are:
To test the performance, we'll use the same large XML file and time how long it takes to parse and process with each library.
Benchmarking XML Parsing Speed
Here are the results parsing a 95MB XML file on my test machine:
| Library | Time to Parse |
| xml.etree.ElementTree | 2.15 sec |
| lxml | 0.35 sec |
| xmltodict | 1.12 sec |
As you can see, lxml is by far the fastest XML parsing library, taking only 0.35 seconds compared to over 2 seconds with the built-in xml.etree.
When to Use Lxml
The clear performance advantage makes lxml the right choice for most real-world XML parsing use cases. The only downside is having to install it separately.
Lxml is particularly useful when:
If you just need occasional lightweight XML parsing, the built-in ElementTree may be enough. But for production systems involving substantial XML data, I highly recommend using lxml. It's well worth the extra setup.