What is the fastest XML parser in Python?

Feb 5, 2024 ยท 2 min read

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:

  • xml.etree.ElementTree - Python's built-in XML parsing library. Simple and familiar to use but slower than other options.
  • lxml - Very fast C-based XML parsing library. Requires separate installation.
  • xmltodict - Converts XML to Python dictionaries for easier processing. Fast but memory intensive.
  • 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:

    LibraryTime to Parse
    xml.etree.ElementTree2.15 sec
    lxml0.35 sec
    xmltodict1.12 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:

  • Processing large XML files
  • XML parsing is a bottleneck in your code
  • Fast performance is critical
  • 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.

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