python - lxml element.clear() 和访问子元素

Question

我正在使用 lxml.iterparse 来解析一个相当大的 xml 文件。在某个时刻抛出内存不足异常。我知道类似的问题，并且有一个构建的树，当您不再使用它时，您通常应该使用 element.clear() 清除它。

我的代码看起来像这样(缩短):

for  event,element in context :
    if element.tag == xmlns + 'initialized':        
        attributes = element.findall(xmlns+'attribute')         
        heapsize = filter(lambda x:x.attrib['name']=='maxHeapSize', attributes)[0].attrib['value']
        characteristics['max_heap_size_MB'] = bytes_to_MB(int(heapsize, 16))

    #clear up the built tree to avoid mem alloc fails
    element.clear()
del context

如果我注释掉 element.clear()，这会起作用。如果我使用的是 element.clear，我会得到这样的 Keyerrors:

Traceback (most recent call last):
  File "C:\Users\NN\Documents\scripts\analyse\analyse_all.py", line 289, in <module>
    main()
  File "C:\Users\NN\Documents\scripts\analyse\analyse_all.py", line 277, in main
    join_characteristics_and_score(logpath, benchmarkscores)
  File "C:\Users\NN\Documents\scripts\analyse\analyse_all.py", line 140, in join_characteristics_and_score
    parsed_verbose_xml  = parse_xml(verbose)
  File "C:\Users\NN\Documents\scripts\analyse\analyze_g.py", line 62, in parse_xml
    heapsize = filter(lambda x:x.attrib['name']=='maxHeapSize', attributes)[0].attrib['value']
  File "C:\Users\NN\Documents\scripts\analyse\analyze_g.py", line 62, in <lambda>
    heapsize = filter(lambda x:x.attrib['name']=='maxHeapSize', attributes)[0].attrib['value']
  File "lxml.etree.pyx", line 2272, in lxml.etree._Attrib.__getitem__ (src\lxml\lxml.etree.c:54751)
KeyError: 'name'

当我打印元素时，它们是带有值的常规字典，无需使用 element.clear()。清除时，那些字典是空的。

编辑

说明问题的最小运行 python 程序:

#!/usr/bin/python

from lxml import etree
from pprint import pprint

def fast_iter(context, func, *args, **kwargs):
        # http://www.ibm.com/developerworks/xml/library/x-hiperfparse/
        # Author: Liza Daly
        for event, elem in context:
            func(elem, *args, **kwargs) 
            elem.clear()
            while elem.getprevious() is not None:
                del elem.getparent()[0]
        del context

def process_element(elem):
        xmlns = "{http://www.ibm.com/j9/verbosegc}"

        if elem.tag == xmlns + "gc-start":
            memelements = elem.findall('.//root:mem', namespaces = {'root':xmlns[1:-1]})
            pprint(memelements)

if __name__ == '__main__':
    with open('small.xml', "r+") as xmlf:
                context = etree.iterparse(xmlf)
                fast_iter(context, process_element)

xml文件内容如下:

<verbosegc xmlns="http://www.ibm.com/j9/verbosegc">
<gc-start id="5" type="scavenge" contextid="4" timestamp="2013-06-14T15:48:46.815">
  <mem-info id="6" free="3048240" total="4194304" percent="72">
    <mem type="nursery" free="0" total="1048576" percent="0">
      <mem type="allocate" free="0" total="524288" percent="0" />
      <mem type="survivor" free="0" total="524288" percent="0" />
    </mem>
    <mem type="tenure" free="3048240" total="3145728" percent="96">
      <mem type="soa" free="2891568" total="2989056" percent="96" />
      <mem type="loa" free="156672" total="156672" percent="100" />
    </mem>
    <remembered-set count="1593" />
  </mem-info>
</gc-start>
</verbosegc>

Answer 1

Liza Daly 写了一篇关于 processing large XML using lxml 的精彩文章.尝试此处提供的 fast_iter 代码:

import lxml.etree as ET
import pprint


def fast_iter(context, func, *args, **kwargs):
    """
    http://www.ibm.com/developerworks/xml/library/x-hiperfparse/ (Liza Daly)
    See also http://effbot.org/zone/element-iterparse.htm
    """
    for event, elem in context:
        func(elem, *args, **kwargs)
        # It's safe to call clear() here because no descendants will be
        # accessed
        elem.clear()
        # Also eliminate now-empty references from the root node to elem
        # (ancestor loop added by unutbu)
        for ancestor in elem.xpath('ancestor-or-self::*'):
            while ancestor.getprevious() is not None:
                del ancestor.getparent()[0]
    del context


def process_element(elem, namespaces):
    memelements = elem.findall('.//root:mem', namespaces=namespaces)
    pprint.pprint(memelements)

if __name__ == '__main__':
    xmlns = "http://www.ibm.com/j9/verbosegc"
    namespaces = {'root': xmlns}
    with open('small.xml', "r+") as xmlf:
        context = ET.iterparse(xmlf, events=('end', ),
                               tag='{{{}}}gc-start'.format(xmlns))
        fast_iter(context, process_element, namespaces)