Using Python Iterparse For Large XML Files

Question

I need to write a parser in Python that can process some extremely large files ( > 2 GB ) on a computer without much memory (only 2 GB). I wanted to use iterparse in lxml to do it.

My file is of the format:

<item>   <title>Item 1</title>   <desc>Description 1</desc> </item> <item>   <title>Item 2</title>   <desc>Description 2</desc> </item> 

and so far my solution is:

from lxml import etree  context = etree.iterparse( MYFILE, tag='item' )  for event, elem in context :       print elem.xpath( 'description/text( )' )  del context 

Unfortunately though, this solution is still eating up a lot of memory. I think the problem is that after dealing with each "ITEM" I need to do something to cleanup empty children. Can anyone offer some suggestions on what I might do after processing my data to properly cleanup?

Answer 1

Try Liza Daly's fast_iter. After processing an element, elem, it calls elem.clear() to remove descendants and also removes preceding siblings.

def fast_iter(context, func, *args, **kwargs):     """     http://lxml.de/parsing.html#modifying-the-tree     Based on Liza Daly's fast_iter     http://www.ibm.com/developerworks/xml/library/x-hiperfparse/     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         for ancestor in elem.xpath('ancestor-or-self::*'):             while ancestor.getprevious() is not None:                 del ancestor.getparent()[0]     del context   def process_element(elem):     print elem.xpath( 'description/text( )' )  context = etree.iterparse( MYFILE, tag='item' ) fast_iter(context,process_element) 

Daly's article is an excellent read, especially if you are processing large XML files.

---

Edit: The fast_iter posted above is a modified version of Daly's fast_iter. After processing an element, it is more aggressive at removing other elements that are no longer needed.

The script below shows the difference in behavior. Note in particular that orig_fast_iter does not delete the A1 element, while the mod_fast_iter does delete it, thus saving more memory.

import lxml.etree as ET import textwrap import io  def setup_ABC():     content = textwrap.dedent('''\       <root>         <A1>           <B1></B1>           <C>1<D1></D1></C>           <E1></E1>         </A1>         <A2>           <B2></B2>           <C>2<D></D></C>           <E2></E2>         </A2>       </root>         ''')     return content   def study_fast_iter():     def orig_fast_iter(context, func, *args, **kwargs):         for event, elem in context:             print('Processing {e}'.format(e=ET.tostring(elem)))             func(elem, *args, **kwargs)             print('Clearing {e}'.format(e=ET.tostring(elem)))             elem.clear()             while elem.getprevious() is not None:                 print('Deleting {p}'.format(                     p=(elem.getparent()[0]).tag))                 del elem.getparent()[0]         del context      def mod_fast_iter(context, func, *args, **kwargs):         """         http://www.ibm.com/developerworks/xml/library/x-hiperfparse/         Author: Liza Daly         See also http://effbot.org/zone/element-iterparse.htm         """         for event, elem in context:             print('Processing {e}'.format(e=ET.tostring(elem)))             func(elem, *args, **kwargs)             # It's safe to call clear() here because no descendants will be             # accessed             print('Clearing {e}'.format(e=ET.tostring(elem)))             elem.clear()             # Also eliminate now-empty references from the root node to elem             for ancestor in elem.xpath('ancestor-or-self::*'):                 print('Checking ancestor: {a}'.format(a=ancestor.tag))                 while ancestor.getprevious() is not None:                     print(                         'Deleting {p}'.format(p=(ancestor.getparent()[0]).tag))                     del ancestor.getparent()[0]         del context      content = setup_ABC()     context = ET.iterparse(io.BytesIO(content), events=('end', ), tag='C')     orig_fast_iter(context, lambda elem: None)     # Processing <C>1<D1/></C>     # Clearing <C>1<D1/></C>     # Deleting B1     # Processing <C>2<D/></C>     # Clearing <C>2<D/></C>     # Deleting B2      print('-' * 80)     """     The improved fast_iter deletes A1. The original fast_iter does not.     """     content = setup_ABC()     context = ET.iterparse(io.BytesIO(content), events=('end', ), tag='C')     mod_fast_iter(context, lambda elem: None)     # Processing <C>1<D1/></C>     # Clearing <C>1<D1/></C>     # Checking ancestor: root     # Checking ancestor: A1     # Checking ancestor: C     # Deleting B1     # Processing <C>2<D/></C>     # Clearing <C>2<D/></C>     # Checking ancestor: root     # Checking ancestor: A2     # Deleting A1     # Checking ancestor: C     # Deleting B2  study_fast_iter() 

Answer 2

iterparse() lets you do stuff while building the tree, that means that unless you remove what you don't need anymore, you'll still end up with the whole tree in the end.

For more information: read this by the author of the original ElementTree implementation (but it's also applicable to lxml)