What's the best way to parse HTML/XML with lxml in Python? or How do you handle large XML files effic

"Is lxml python still the fastest HTML/XML parser? Or am I wasting my time?"

Seriously tho, I’ve been using lxml python for ages, and it’s *blazing* fast compared to the built-in stuff. But I keep hearing about newer libs popping up.

Anyone done recent benchmarks? Or is lxml still king for speed + features?

Also, why *is* it so much faster? Magic? Cython? Black magic?

(And yeah, I know BeautifulSoup is easier, but come on—speed matters when you’re scraping 10k pages.)

Thoughts? Hot takes? Or am I just old-school?

lxml python is still a beast for parsing, no doubt. But if you're curious about alternatives, check out `selectolax`—it's a newer parser that's stupid fast because it's written in Rust.

Did some quick benchmarks last month, and for raw speed on *clean* HTML, selectolax sometimes edges out lxml. But lxml still wins for messy HTML and XPath support.

And yeah, the speed comes from Cython + tight integration with libxml2. No black magic, just good ol' optimized C.

Honestly, if you're scraping 10k pages, lxml python is still the way to go. The overhead of switching libs isn't worth it unless you're *really* squeezing for milliseconds.

But if you wanna nerd out, try `pyppeteer` or `playwright` for JS-heavy sites. They're slower but handle dynamic content better.

Also, BeautifulSoup with `lxml` as the backend is a nice middle ground—almost as fast but way easier to write.

lxml is fast because it's basically a Python wrapper around libxml2, which is a battle-tested C library. No surprises there.

But have you tried `parsel`? It's what Scrapy uses, and it's *almost* as fast as lxml python but with a nicer API. Plus, it plays well with Scrapy if you're into large-scale scraping.

For benchmarks, check out this repo: [github.com/lorien/html_parser_benchmark](https://github.com/lorien/html_parser_benchmark). It's a bit outdated but still useful.

Hot take: lxml python is overkill for most people. Unless you're parsing *massive* files or need XPath, something like `html5lib` or even the built-in `html.parser` is fine.

But yeah, if speed is your thing, lxml is still king. The Cython stuff makes it scream compared to pure-Python parsers.

Fun fact: lxml's XPath is *way* faster than BeautifulSoup's find_all(). That's where it really shines.

Dude, lxml python is *not* old-school—it's just *that* good. I’ve tried newer libs, and they either match lxml or are worse.

The only thing faster is maybe writing your own C extension, but who has time for that?

If you're worried, just profile your script with `cProfile`. Chances are, the bottleneck isn’t lxml but your network requests or something else.

Thanks for all the insights! Definitely gonna check out selectolax and parsel—sounds like they might be worth testing for my use case.

But yeah, after skimming that benchmark repo, lxml python still seems like the safest bet. The XPath support alone is a killer feature.

Quick follow-up: anyone tried combining lxml with multiprocessing for *really* large scrapes? Wondering if it’s worth the hassle.

For raw speed, lxml python is hard to beat. But if you're dealing with malformed HTML, `html5-parser` is worth a look. It's slower but way more forgiving.

Also, if you're *really* into benchmarks, this article compares lxml to a bunch of others: [medium.com/some-benchmark-post](https://medium.com/some-benchmark-post). Spoiler: lxml wins most of the time.

The Cython + libxml2 combo is just unfair. It’s like bringing a rocket to a knife fight.