Hands on, part 2 Groovy, unlike Java, provides a relatively streamlined way to read and write XML documents. In the first part of my two-piece tutorial, I looked at how you can use Groovy's flexible strings, closures and iterators to quickly create XML fragments and files.

The emphasis was on making the most of Groovy as a scripting language rather than on making use of the heavyweight XML parsers and libraries that it can access due to its use of the Java Virtual Machine (JVM) and ability to access Java libraries.

Groovy can be used with the full range of Java XML parsers and libraries - so in addition to vanilla DOM and SAX, you can use JDOM, XOM, StAX and the whole alphabet soup of alternatives that are available for the Java platform.

What we're interested in here, though, is using Groovy for the kind of ad-hoc scripting tasks that have traditionally been the preserve of languages such as Perl. Instead of the heavyweights we are going to focus on Groovy's XmlSlurper class, which provides a very natural and intuitive interface to XML.

Our example data is the following simple XML file:

<?xml version="1.0"?>
<people>
  <person first_name='john' surname='smith'>
    <age>37</age>
    <gender>m</gender>
    <kids count='2' />
  </person>
  <person first_name='jill' surname='jones'>
    <age>28</age>
    <gender>f</gender>
    <kids count='0' />
  </person>
  <person first_name='clark' surname='kent'>
    <age>22</age>
    <gender>m</gender>
    <kids count='3' />
  </person>  
</people>

The first task is to parse the file - which we've called pers.xml and have placed in a /groovy/progs directory - from disk and make it available for processing. In Groovy this is a one-liner:

def pers=new XmlSlurper().parse(new File("/groovy/progs/pers.xml"))

Once we've got our XmlSlurper object we can use dot notation to access elements and attributes within it. Using dot notation is a very natural way of working for Java developers, and helps to bridge the gap between object notation and hierarchic XML structure. The top-level element in this case is people, but we can find that simply enough:

        println pers.name()

The above code will print people to the command-line or shell. Want to find out what the child elements are? Easy:

pers.children().each { println it.name() }

But why stop there? We can move up and down the tree easily enough. Say we want to find the children of each of the child elements in turn. Again, it's trivial:

pers.children().children().each {println it.name()}

That should print out three lots of age, gender and kids. Getting hold of attributes isn't much more difficult:

pers.children().each {println it.attributes()}

The output of that line of code is:

["first_name":"john", "surname":"smith"]
["first_name":"jill", "surname":"jones"]
["first_name":"clark", "surname":"kent"]

Note that the above is a map, with the attribute names acting as the keys.

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