Why is elementtree.ElementTree.iterparse using so much memory?

I am using elementtree.ElementTree.iterparse to parse a large (371MB) xml file.

My code is basically like this:

outf = open('out.txt', 'w') 
context = iterparse('copyright.xml')
context = iter(context)
dummy, root = context.next()

for event, elem in context:
    if elem.tag == 'foo':
        author = elem.text

    elif elem.tag == 'bar':
        if elem.text is not None and 'bat' in elem.text.lower():
            outf.write(elem.text + '\n')
    elem.clear()   #line A
    root.clear()   #line B

      

        
        
        
      

    

My question is twofold:

First - Do I need A and B (see comments on the code snippet)? I was told that root.clear () cleans up unneeded children so it doesn’t gobble up memory, but here are my observations: using B, not A, is the same as using either in terms of memory consumption (built with the task manager). Using only A seems to be the same as using both.

Second, why is it still consuming so much memory? As the program runs, it uses about 100MB of RAM at the end.

I'm guessing it has something to do with outf, but why? Isn't that just writing to disk? And if it stores this data until it is closed, how can I avoid it?

Additional info: I am using Python 2.7.3 on Windows.