本文介绍了Lxml element.lear()和访问子元素的处理方法,对大家解决问题具有一定的参考价值,需要的朋友们下面随着小编来一起学习吧!
问题描述
我使用lxml.iterparse来解析一个相当大的XML文件。在某个点上会引发内存不足异常。我知道有类似的问题,当您不再使用它时,通常应该使用element.lear()清除构建的树。
我的代码如下(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.lear(),则可以使用此方法。如果我使用的是element.lear,我会得到如下的键错误:
Traceback (most recent call last):
File "C:UsersNNDocumentsscriptsanalyseanalyse_all.py", line 289, in <module>
main()
File "C:UsersNNDocumentsscriptsanalyseanalyse_all.py", line 277, in main
join_characteristics_and_score(logpath, benchmarkscores)
File "C:UsersNNDocumentsscriptsanalyseanalyse_all.py", line 140, in join_characteristics_and_score
parsed_verbose_xml = parse_xml(verbose)
File "C:UsersNNDocumentsscriptsanalyseanalyze_g.py", line 62, in parse_xml
heapsize = filter(lambda x:x.attrib['name']=='maxHeapSize', attributes)[0].attrib['value']
File "C:UsersNNDocumentsscriptsanalyseanalyze_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__ (srclxmllxml.etree.c:54751)
KeyError: 'name'
当我打印元素时,它们是带有值的常规DICT,没有使用element.lear()。清除时,这些DICT为空。
编辑
说明该问题的最小运行的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)
xmlfile的内容如下:
<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>
推荐答案
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)
这篇关于Lxml element.lear()和访问子元素的文章就介绍到这了,希望我们推荐的答案对大家有所帮助,也希望大家多多支持!