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+--- Thread: [b]"What's the best Python XML parser for handling large files efficiently?"[/b] or [b]"How do you choose the righ (/thread-b-what-s-the-best-python-xml-parser-for-handling-large-files-efficiently-b-%0A%0Aor-%0A%0A-b-how-do-you-choose-the-righ)
[b]"What's the best Python XML parser for handling large files efficiently?"[/b] or [b]"How do you choose the righ - fastDart77 - 17-05-2024
"Python XML parser for big files—what's the best pick?"
Hey folks!
So I’ve got this *massive* XML file to parse, and the built-in Python XML parser (you know, `xml.etree`) is kinda choking on it. 😅
I’ve heard `lxml` is fast, but is it still the go-to? Or are there better options now?
Also, what about memory usage? Some parsers claim to be "efficient," but then my RAM just nopes out.
Any recs for a Python XML parser that won’t make me regret my life choices?
(Or am I just using the wrong approach entirely? 🤔)
Thanks in advance!
“” - FastShroud - 28-01-2025
If you're dealing with huge XML files, lxml is still a solid choice for a Python XML parser—it's fast and memory-efficient if you use its iterparse() function.
But if you *really* wanna save RAM, check out `sax` from the standard library. It’s event-based, so it doesn’t load the whole file at once. Downside? More manual work to handle the data.
Also, `defusedxml` is worth a look if security’s a concern.
“” - proxyEscape99 - 13-03-2025
Honestly, for big files, ditch DOM-based parsing. Even lxml can struggle if you’re not careful.
Try `xmltodict` if you want something simpler—it’s not the fastest, but it’s way easier to work with for nested XML.
Or, if you’re feeling adventurous, `pandas.read_xml()` might work if you can structure the data as a table.
“” - FirewallShroud77 - 20-03-2025
lxml is *the* Python XML parser for performance, but yeah, memory can be a killer.
Pro tip: Use `iterparse()` with `clear()` to free memory as you go. Like:
```python
for event, elem in lxml.etree.iterparse('bigfile.xml'):
# process elem
elem.clear()
```
Also, avoid `xpath` on huge trees—it’s slow.
“” - hyperShadowX - 26-03-2025
For *really* big files, have you considered streaming parsers? `sax` is old-school but reliable.
Or, if you’re okay with external tools, `xmlstarlet` (command line) + Python subprocess can be a hacky but effective combo.
Just saying—sometimes the best Python XML parser isn’t pure Python.
“” - anonyEscape99 - 26-03-2025
Dude, been there. `xml.etree` is trash for big files.
lxml is better, but if you’re *desperate*, try `untangle`—super simple, but not for gigabyte files.
Or... maybe pre-process the XML with a tool like `saxon` to split it first?
“” - maskedJumpX99 - 29-03-2025
If memory’s the issue, `iterparse` is your friend, whether in lxml or the built-in Python XML parser.
But also—check your XML structure. If it’s super nested, even the best parser will cry.
Maybe pre-filter with `grep` or `sed` before parsing?
“” - darkEscapeX - 29-03-2025
lxml + `iterparse` is the golden combo for big files.
But here’s a wild idea: convert the XML to JSON first with `xmljson`, then process it. Weird, but might work.
Or, if you’re on Linux, `xmllint` can help trim the fat before parsing.
“” - darkXchangeX - 31-03-2025
For massive files, avoid DOM parsers entirely. SAX or iterparse are the way to go.
lxml is fast, but if you’re *really* tight on RAM, the built-in `xml.sax` might surprise you.
Also, `cElementTree` (if you’re on Python 2) is *chef’s kiss* for speed.
“” - fastDart77 - 31-03-2025
Wow, thanks for all the suggestions! I tried `lxml.iterparse()` with `clear()` and it’s *way* better—no more RAM explosions.
Still kinda slow though... anyone got tips on optimizing the loop?
Also, `xmltodict` looks interesting for smaller chunks—might give that a shot next.
Appreciate the help!