Chapter 9. XML Processing

9.1. Diving in

These next two chapters are about XML processing in Python. It would be helpful if you already knew what an XML document looks like, that it's made up of structured tags to form a hierarchy of elements, and so on. If this doesn't make sense to you, there are many XML tutorials that can explain the basics.

If you're not particularly interested in XML, you should still read these chapters, which cover important topics like Python packages, Unicode, command line arguments, and how to use getattr for method dispatching.

Being a philosophy major is not required, although if you have ever had the misfortune of being subjected to the writings of Immanuel Kant, you will appreciate the example program a lot more than if you majored in something useful, like computer science.

There are two basic ways to work with XML. One is called SAX (“Simple API for XML”), and it works by reading the XML a little bit at a time and calling a method for each element it finds. (If you read Chapter 8, HTML Processing, this should sound familiar, because that's how the sgmllib module works.) The other is called DOM (“Document Object Model”), and it works by reading in the entire XML document at once and creating an internal representation of it using native Python classes linked in a tree structure. Python has standard modules for both kinds of parsing, but this chapter will only deal with using the DOM.

The following is a complete Python program which generates pseudo-random output based on a context-free grammar defined in an XML format. Don't worry yet if you don't understand what that means; you'll examine both the program's input and its output in more depth throughout these next two chapters.

Example 9.1.

If you have not already done so, you can download this and other examples used in this book.

"""Kant Generator for Python

Generates mock philosophy based on a context-free grammar

Usage: python [options] [source]

  -g ..., --grammar=...   use specified grammar file or URL
  -h, --help              show this help
  -d                      show debugging information while parsing

Examples:                  generates several paragraphs of Kantian philosophy -g husserl.xml   generates several paragraphs of Husserl "<xref id='paragraph'/>"  generates a paragraph of Kant template.xml     reads from template.xml to decide what to generate
from xml.dom import minidom
import random
import toolbox
import sys
import getopt

_debug = 0

class NoSourceError(Exception): pass

class KantGenerator:
    """generates mock philosophy based on a context-free grammar"""

    def __init__(self, grammar, source=None):
        self.loadSource(source and source or self.getDefaultSource())

    def _load(self, source):
        """load XML input source, return parsed XML document

        - a URL of a remote XML file ("")
        - a filename of a local XML file ("~/diveintopython/common/py/kant.xml")
        - standard input ("-")
        - the actual XML document, as a string
        sock = toolbox.openAnything(source)
        xmldoc = minidom.parse(sock).documentElement
        return xmldoc

    def loadGrammar(self, grammar):                         
        """load context-free grammar"""                     
        self.grammar = self._load(grammar)                  
        self.refs = {}                                      
        for ref in self.grammar.getElementsByTagName("ref"):
            self.refs[ref.attributes["id"].value] = ref     

    def loadSource(self, source):
        """load source"""
        self.source = self._load(source)

    def getDefaultSource(self):
        """guess default source of the current grammar
        The default source will be one of the <ref>s that is not
        cross-referenced.  This sounds complicated but it's not.
        Example: The default source for kant.xml is
        "<xref id='section'/>", because 'section' is the one <ref>
        that is not <xref>'d anywhere in the grammar.
        In most grammars, the default source will produce the
        longest (and most interesting) output.
        xrefs = {}
        for xref in self.grammar.getElementsByTagName("xref"):
            xrefs[xref.attributes["id"].value] = 1
        xrefs = xrefs.keys()
        standaloneXrefs = [e for e in self.refs.keys() if e not in xrefs]
        if not standaloneXrefs:
            raise NoSourceError, "can't guess source, and no source specified"
        return '<xref id="%s"/>' % random.choice(standaloneXrefs)
    def reset(self):
        """reset parser"""
        self.pieces = []
        self.capitalizeNextWord = 0

    def refresh(self):
        """reset output buffer, re-parse entire source file, and return output
        Since parsing involves a good deal of randomness, this is an
        easy way to get new output without having to reload a grammar file
        each time.
        return self.output()

    def output(self):
        """output generated text"""
        return "".join(self.pieces)

    def randomChildElement(self, node):
        """choose a random child element of a node
        This is a utility method used by do_xref and do_choice.
        choices = [e for e in node.childNodes
                   if e.nodeType == e.ELEMENT_NODE]
        chosen = random.choice(choices)            
        if _debug:                                 
            sys.stderr.write('%s available choices: %s\n' % \
                (len(choices), [e.toxml() for e in choices]))
            sys.stderr.write('Chosen: %s\n' % chosen.toxml())
        return chosen                              

    def parse(self, node):         
        """parse a single XML node
        A parsed XML document (from minidom.parse) is a tree of nodes
        of various types.  Each node is represented by an instance of the
        corresponding Python class (Element for a tag, Text for
        text data, Document for the top-level document).  The following
        statement constructs the name of a class method based on the type
        of node we're parsing ("parse_Element" for an Element node,
        "parse_Text" for a Text node, etc.) and then calls the method.
        parseMethod = getattr(self, "parse_%s" % node.__class__.__name__)

    def parse_Document(self, node):
        """parse the document node
        The document node by itself isn't interesting (to us), but
        its only child, node.documentElement, is: it's the root node
        of the grammar.

    def parse_Text(self, node):    
        """parse a text node
        The text of a text node is usually added to the output buffer
        verbatim.  The one exception is that <p class='sentence'> sets
        a flag to capitalize the first letter of the next word.  If
        that flag is set, we capitalize the text and reset the flag.
        text =
        if self.capitalizeNextWord:
            self.capitalizeNextWord = 0

    def parse_Element(self, node): 
        """parse an element
        An XML element corresponds to an actual tag in the source:
        <xref id='...'>, <p chance='...'>, <choice>, etc.
        Each element type is handled in its own method.  Like we did in
        parse(), we construct a method name based on the name of the
        element ("do_xref" for an <xref> tag, etc.) and
        call the method.
        handlerMethod = getattr(self, "do_%s" % node.tagName)

    def parse_Comment(self, node):
        """parse a comment
        The grammar can contain XML comments, but we ignore them
    def do_xref(self, node):
        """handle <xref id='...'> tag
        An <xref id='...'> tag is a cross-reference to a <ref id='...'>
        tag.  <xref id='sentence'/> evaluates to a randomly chosen child of
        <ref id='sentence'>.
        id = node.attributes["id"].value

    def do_p(self, node):
        """handle <p> tag
        The <p> tag is the core of the grammar.  It can contain almost
        anything: freeform text, <choice> tags, <xref> tags, even other
        <p> tags.  If a "class='sentence'" attribute is found, a flag
        is set and the next word will be capitalized.  If a "chance='X'"
        attribute is found, there is an X% chance that the tag will be
        evaluated (and therefore a (100-X)% chance that it will be
        completely ignored)
        keys = node.attributes.keys()
        if "class" in keys:
            if node.attributes["class"].value == "sentence":
                self.capitalizeNextWord = 1
        if "chance" in keys:
            chance = int(node.attributes["chance"].value)
            doit = (chance > random.randrange(100))
            doit = 1
        if doit:
            for child in node.childNodes: self.parse(child)

    def do_choice(self, node):
        """handle <choice> tag
        A <choice> tag contains one or more <p> tags.  One <p> tag
        is chosen at random and evaluated; the rest are ignored.

def usage():
    print __doc__

def main(argv):                         
    grammar = "kant.xml"                
        opts, args = getopt.getopt(argv, "hg:d", ["help", "grammar="])
    except getopt.GetoptError:          
    for opt, arg in opts:               
        if opt in ("-h", "--help"):     
        elif opt == '-d':               
            global _debug               
            _debug = 1                  
        elif opt in ("-g", "--grammar"):
            grammar = arg               
    source = "".join(args)              

    k = KantGenerator(grammar, source)
    print k.output()

if __name__ == "__main__":

Example 9.2.

"""Miscellaneous utility functions"""

def openAnything(source):            
    """URI, filename, or string --> stream

    This function lets you define parsers that take any input source
    (URL, pathname to local or network file, or actual data as a string)
    and deal with it in a uniform manner.  Returned object is guaranteed
    to have all the basic stdio read methods (read, readline, readlines).
    Just .close() the object when you're done with it.
    >>> from xml.dom import minidom
    >>> sock = openAnything("http://localhost/kant.xml")
    >>> doc = minidom.parse(sock)
    >>> sock.close()
    >>> sock = openAnything("c:\\inetpub\\wwwroot\\kant.xml")
    >>> doc = minidom.parse(sock)
    >>> sock.close()
    >>> sock = openAnything("<ref id='conjunction'><text>and</text><text>or</text></ref>")
    >>> doc = minidom.parse(sock)
    >>> sock.close()
    if hasattr(source, "read"):
        return source

    if source == '-':
        import sys
        return sys.stdin

    # try to open with urllib (if source is http, ftp, or file URL)
    import urllib                         
        return urllib.urlopen(source)     
    except (IOError, OSError):            
    # try to open with native open function (if source is pathname)
        return open(source)               
    except (IOError, OSError):            
    # treat source as string
    import StringIO                       
    return StringIO.StringIO(str(source)) 

Run the program by itself, and it will parse the default XML-based grammar, in kant.xml, and print several paragraphs worth of philosophy in the style of Immanuel Kant.

Example 9.3. Sample output of

[you@localhost kgp]$ python
     As is shown in the writings of Hume, our a priori concepts, in
reference to ends, abstract from all content of knowledge; in the study
of space, the discipline of human reason, in accordance with the
principles of philosophy, is the clue to the discovery of the
Transcendental Deduction.  The transcendental aesthetic, in all
theoretical sciences, occupies part of the sphere of human reason
concerning the existence of our ideas in general; still, the
never-ending regress in the series of empirical conditions constitutes
the whole content for the transcendental unity of apperception.  What
we have alone been able to show is that, even as this relates to the
architectonic of human reason, the Ideal may not contradict itself, but
it is still possible that it may be in contradictions with the
employment of the pure employment of our hypothetical judgements, but
natural causes (and I assert that this is the case) prove the validity
of the discipline of pure reason.  As we have already seen, time (and
it is obvious that this is true) proves the validity of time, and the
architectonic of human reason, in the full sense of these terms,
abstracts from all content of knowledge.  I assert, in the case of the
discipline of practical reason, that the Antinomies are just as
necessary as natural causes, since knowledge of the phenomena is a
    The discipline of human reason, as I have elsewhere shown, is by
its very nature contradictory, but our ideas exclude the possibility of
the Antinomies.  We can deduce that, on the contrary, the pure
employment of philosophy, on the contrary, is by its very nature
contradictory, but our sense perceptions are a representation of, in
the case of space, metaphysics.  The thing in itself is a
representation of philosophy.  Applied logic is the clue to the
discovery of natural causes.  However, what we have alone been able to
show is that our ideas, in other words, should only be used as a canon
for the Ideal, because of our necessary ignorance of the conditions.


This is, of course, complete gibberish. Well, not complete gibberish. It is syntactically and grammatically correct (although very verbose -- Kant wasn't what you would call a get-to-the-point kind of guy). Some of it may actually be true (or at least the sort of thing that Kant would have agreed with), some of it is blatantly false, and most of it is simply incoherent. But all of it is in the style of Immanuel Kant.

Let me repeat that this is much, much funnier if you are now or have ever been a philosophy major.

The interesting thing about this program is that there is nothing Kant-specific about it. All the content in the previous example was derived from the grammar file, kant.xml. If you tell the program to use a different grammar file (which you can specify on the command line), the output will be completely different.

Example 9.4. Simpler output from

[you@localhost kgp]$ python -g binary.xml
[you@localhost kgp]$ python -g binary.xml

You will take a closer look at the structure of the grammar file later in this chapter. For now, all you need to know is that the grammar file defines the structure of the output, and the program reads through the grammar and makes random decisions about which words to plug in where.