"Struggling with XML parsing in Python? What's your go-to python xml parser?"
Hey folks!
I’ve been wrestling with some massive XML files lately, and my usual python xml parser (ElementTree) is kinda choking on them.
Anyone got a better recommendation? I’ve heard mixed things about lxml being faster but also more complex.
Or is there some hidden gem I’m missing?
Also, how do y’all handle memory with huge files? Stream parsing? Or just throw more RAM at it? 😅
Thanks in advance!
I feel your pain! ElementTree is solid for small stuff, but for big XML files, lxml is a game-changer. Yeah, it’s a bit more complex, but the speed boost is worth it.
For memory, try `iterparse`—it streams the file instead of loading it all at once. Saved my bacon with a 2GB XML dump last week.
Also, check out `xmltodict` if you prefer working with dicts. Not as fast, but way easier for quick hacks.
lxml is my go-to python xml parser for sure. The XPath support alone makes it worth the learning curve.
If you’re dealing with *huge* files, streaming is the way. `iterparse` in lxml lets you process chunks and free memory as you go.
Pro tip: disable unnecessary features like DTD validation if you don’t need ’em. Speeds things up a ton.
Honestly, I just switched to `defusedxml` for security reasons—parsing untrusted XML with the usual python xml parser libs can be risky.
It’s a wrapper around ElementTree but safer. Not the fastest, but peace of mind > raw speed sometimes.
For big files, yeah, streaming or splitting the XML first might help.
If you’re open to non-Python tools, `xmllint` (from libxml2) is *blazing* fast for preprocessing. I often use it to split huge files before parsing in Python.
But for pure python xml parser work, lxml’s `iterparse` is the MVP. Just remember to clear nodes you’re done with to save memory!
ElementTree is fine, but lxml is *chef’s kiss* for big files. The C backend makes a huge diff.
Also, if you’re on Python 3.8+, check out the `xml.etree.ElementTree` improvements—they’ve added some optimizations.
For streaming, `iterparse` + `clear()` is your friend. Don’t just throw RAM at it—that’s a band-aid.
Try `untangle` if you want something stupid simple. It converts XML to Python objects, which is nice for small-to-medium files.
But yeah, for big stuff, lxml or streaming with `iterparse` is the way.
Side note: avoid `minidom` unless you hate yourself.
lxml is the best python xml parser for performance, but if you’re lazy like me, `xmltodict` is a nice middle ground.
For huge files, pre-process with `sax`—it’s event-based, so super memory-efficient. Steeper learning curve, though.
If you’re dealing with *massive* XML, consider `sax` or even a database like SQLite to chunk and query the data.
But for most cases, lxml’s `iterparse` is the sweet spot. The docs are kinda dense, but SO has great examples.
`lxml` is worth the hassle, I promise. The speed difference is night and day.
Also, if your XML is *really* big, maybe rethink the format? JSON or CSV might be easier to handle.
But if you’re stuck with XML, streaming is the only sane option.
