What is the fastest way to parse large XML docs in

问题:

I am currently running the following code based on Chapter 12.5 of the Python Cookbook:

from xml.parsers import expat

class Element(object):
    def __init__(self, name, attributes):
        self.name = name
        self.attributes = attributes
        self.cdata = ''
        self.children = []
    def addChild(self, element):
        self.children.append(element)
    def getAttribute(self,key):
        return self.attributes.get(key)
    def getData(self):
        return self.cdata
    def getElements(self, name=''):
        if name:
            return [c for c in self.children if c.name == name]
        else:
            return list(self.children)

class Xml2Obj(object):
    def __init__(self):
        self.root = None
        self.nodeStack = []
    def StartElement(self, name, attributes):
        element = Element(name.encode(), attributes)
        if self.nodeStack:
            parent = self.nodeStack[-1]
            parent.addChild(element)
        else:
            self.root = element
        self.nodeStack.append(element)
    def EndElement(self, name):
        self.nodeStack.pop()
    def CharacterData(self,data):
        if data.strip():
            data = data.encode()
            element = self.nodeStack[-1]
            element.cdata += data
    def Parse(self, filename):
        Parser = expat.ParserCreate()
        Parser.StartElementHandler = self.StartElement
        Parser.EndElementHandler = self.EndElement
        Parser.CharacterDataHandler = self.CharacterData
        ParserStatus = Parser.Parse(open(filename).read(),1)
        return self.root

I am working with XML documents of about 1 GB in size. Does anyone know a faster way to parse these?

回答1:

I looks to me as if you do not need any DOM capabilities from your program. I would second the use of the (c)ElementTree library. If you use the iterparse function of the cElementTree module, you can work your way through the xml and deal with the events as they occur.

Note however, Fredriks advice on using cElementTree iterparse function:

to parse large files, you can get rid of elements as soon as you’ve processed them:

for event, elem in iterparse(source):
    if elem.tag == "record":
        ... process record elements ...
        elem.clear()

The above pattern has one drawback; it does not clear the root element, so you will end up with a single element with lots of empty child elements. If your files are huge, rather than just large, this might be a problem. To work around this, you need to get your hands on the root element. The easiest way to do this is to enable start events, and save a reference to the first element in a variable:

# get an iterable
context = iterparse(source, events=("start", "end"))

# turn it into an iterator
context = iter(context)

# get the root element
event, root = context.next()

for event, elem in context:
    if event == "end" and elem.tag == "record":
        ... process record elements ...
        root.clear()

The lxml.iterparse() does not allow this.

The previous does not work on Python 3.7, consider the following way to get the first element.

# get an iterable
context = iterparse(source, events=("start", "end"))

is_first = True

for event, elem in context:
    # get the root element
    if is_first:
        root = elm
        is_first = False
    if event == "end" and elem.tag == "record":
        ... process record elements ...
        root.clear()

回答2:

Have you tried The cElementTree Module?

cElementTree is included with Python 2.5 and later, as xml.etree.cElementTree. Refer the benchmarks.

removed dead ImageShack link

回答3:

I recommend you to use lxml, it's a python binding for the libxml2 library which is really fast.

In my experience, libxml2 and expat have very similar performance. But I prefer libxml2 (and lxml for python) because it seems to be more actively developed and tested. Also libxml2 has more features.

lxml is mostly API compatible with xml.etree.ElementTree. And there is good documentation in its web site.

回答4:

Registering callbacks slows down the parsing tremendously. [EDIT]This is because the (fast) C code has to invoke the python interpreter which is just not as fast as C. Basically, you're using the C code to read the file (fast) and then build the DOM in Python (slow).[/EDIT]

Try to use xml.etree.ElementTree which is implemented 100% in C and which can parse XML without any callbacks to python code.

After the document has been parsed, you can filter it to get what you want.

If that's still too slow and you don't need a DOM another option is to read the file into a string and use simple string operations to process it.

回答5:

If your application is performance-sensitive and likely to encounter large files (like you said, > 1GB) then I'd strongly advise against using the code you're showing in your question for the simple reason that it loads the entire document into RAM. I would encourage you to rethink your design (if at all possible) to avoid holding the whole document tree in RAM at once. Not knowing what your application's requirements are, I can't properly suggest any specific approach, other than the generic piece of advice to try to use an "event-based" design.

回答6:

expat ParseFile works well if you don't need to store the entire tree in memory, which will sooner or later blow your RAM for large files:

import xml.parsers.expat
parser = xml.parsers.expat.ParserCreate()
parser.ParseFile(open('path.xml', 'r'))

It reads the files into chunks, and feeds them to the parser without exploding RAM.

Doc: https://docs.python.org/2/library/pyexpat.html#xml.parsers.expat.xmlparser.ParseFile

回答7:

I spent quite some time trying this out and it seems the fastest and the least memory intensive approach is using lxml and iterparse, but making sure to free unneeded memory. In my example, parsing arXiv dump:

from lxml import etree

context = etree.iterparse('path/to/file', events=('end',), tag='Record')

for event, element in context:
    record_id = element.findtext('.//{http://arxiv.org/OAI/arXiv/}id')
    created = element.findtext('.//{http://arxiv.org/OAI/arXiv/}created')

    print(record_id, created)

    # Free memory.
    element.clear()
    while element.getprevious() is not None:
        del element.getparent()[0]

So element.clear is not enough, but also the removal of any links to previous elements.

回答8:

Apparently PyRXP is really fast.

They claim it is the fastest parser - but cElementTree isn't in their stats list.