The recent cElementTree release is causing some waves in the Python/XML community. It started when Uche Ugbuji posted The Python Community has too many deceptive XML benchmarks to his blog.
The effbot was not amused, as could be witnessed by his comment on it, and the blog entries:
http://online.effbot.org/2005_01_01_archive.htm#sigh http://online.effbot.org/2005_01_01_archive.htm#faking-it http://online.effbot.org/2005_01_01_archive.htm#faking-it-2 http://online.effbot.org/2005_01_01_archive.htm#faking-it-3
The problem is that Uche unwittingly introduced a benchmark that is rather.. deceptive. He has been testing the time taken by the whole program, including startup and shutdown of the Python interpreter, module importing, and the like, instead of the part where XML processing takes place. Unless you're writing command line scripts or classic CGI web applications, Python startup time is hardly relevant, and shouldn't be part of the measurement.
A while back while developing lxml.etree I was curious what benchmark Fredrik was using. I couldn't find the information on the web, but he told me when I mailed him about it. He was using the simple, obvious strategy which I myself had already been using:
.. imports .. start = time.time() # time.clock() on windows .. do the actual work .. end = time.time() print end - start
To measure approximate memory usage, he puts in a pause in the program before and after the processing, and checks the process overview on his machine manually.
I've replicated his results with cElementTree and ElementTree fairly well, though my machine is a bit different in its performance characteristics due to platform differences. See other blog entries for more info on this.
For fun, I thought I'd try Uche's benchmark against lxml.etree on this machine. I've also tested it against cElementTree (an older version, I can't keep up with Fredrik's releases; hm, no __version__ string I can find, so don't know what 0.9.x version it is.. reminds me to add one to lxml when the time comes for a release..).
Here's Uche's program adjusted for etree. As you can see, only the import statement needs to change:
import lxml.etree as ElementTree tree = ElementTree.parse("ot.xml") for v in tree.findall("//v"): text = v.text if text.find(u'begat') != -1: print text
I've also rewritten it to use xpath instead:
from lxml.import etree as ElementTree tree = ElementTree.parse("ot.xml") for text in tree.xpath("//v[contains(., 'begat')]/text()"): print text
Since this program is printing stuff, and printing overhead can be large, I've tried a number of tests:
- Unix 'time' command, print to stdout on Gnome terminal
- Unix 'time' command, redirect output to file
- time.time(), print to stdout on Gnome terminal
- time.time(), redirect output to file
Here are the results:
A B C D -------------------------- cElementTree 1.06s 0.32s 0.9s 0.23s lxml.etree 1.2s 0.43s 1.1s 0.36s lxml.etree xpath 0.53s 0.25s 0.42s 0.17s
As you can see from the results, the type of terminal you're printing to matters a lot. In case of the xpath tests, almost half of the time is spent printing to the terminal, and for the other tests the overhead seems to be even more.
Also note that at last I can claim a minor victory over cElementTree on my machine on this particular test! lxml.etree, when using xpath to do the task set, is faster than this version of cElementTree. Of course most of the credit here goes to libxml2's blazingly fast xpath implementation here.
All this shows benchmarks are nice as there are so many to choose from.