How to Parse XML Fast in 2026 (Python)

JSON won the internet. We all know that. But XML never left — it just moved into the places where reliability matters more than trendiness . If you work with Maven configs, Android manifests, Office Open XML ( .docx / .xlsx ), SVG, RSS feeds, DocBook, SOAP services, or any enterprise integration layer, you're still parsing XML. And in 2026, there's no excuse for it being slow. The Problem with XML Parsing in Python Python's standard library ships with xml.etree.ElementTree . It works. It's fine for small files. But the moment your XML grows beyond a few hundred elements, ElementTree becomes a bottleneck — because it builds a full Python object for every single node, attribute, and text node in the tree. The usual answer is lxml , which wraps libxml2 in C. It's fast and feature-rich. But it's also a 5.5 MB install with a heavy dependency chain, and its Python bindings add overhead on every call. So what if you want the fastest possible parse, a tiny footprint, and a clean Python API? Th