The Super CSV Dozer extension integrates Super CSV with Dozer, a powerful Javabean mapping library. Typically, Dozer requires lots of XML configuration but the addition of API mapping allows Super CSV to set up Dozer mappings dynamically.
The use of Dozer allows CsvDozerBeanReader and CsvDozerBeanWriter to map simple fields (the same as CsvBeanReader and CsvBeanWriter), but to also perform deep mapping and index-based mapping as well!
Check out the examples, or read on for more information.
Deep mapping allows you to make use of the relationships between your classes.
For example, if your class had an address field, you could utilize deep mapping as follows (assuming there are valid getters/setters defined for address, city and name in the 3 involved classes):
address.city.name
Index-based mapping allows you to access elements of arrays and Collections by their index.
For example, if your class had a collection of Addresses, you could utilize index-based mapping to access the first one as follows:
addresses[0]
You can even combine index-based mapping with deep mapping:
addresses[0].city.name
Dozer uses SLF4J for logging. By default it will use a no-operation implementation (i.e. no logging), but you can use any of the supported implementations (logback, log4j, slf4j-simple) by placing the appropriate binding jar on the classpath.
See the SLF4J manual for more details.
Most of the time you'll want to let Super CSV take care of the dozer configuration by simply calling the configureBeanMapping() method. However, you might want to make use of the advanced features of Dozer (such as custom converters, bean factories, etc). In this case, you can supply Super CSV with a pre-configured DozerBeanMapper.
The following XML is provided as a reference - it's the XML configuration used in the project's unit tests. The CsvDozerBeanData class is used internally as the input/output of any Dozer mapping (each indexed column represents a column of CSV). At a minimum, you should replace the org.supercsv.mock.dozer.SurveyResponse with the class you're mapping, and update the field mappings as appropriate (but try not to change the XML attributes, as they're important!).
<mappings xmlns="http://dozer.sourceforge.net" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance"
xsi:schemaLocation="http://dozer.sourceforge.net
http://dozer.sourceforge.net/schema/beanmapping.xsd">
<!-- configuration for CsvDozerBeanReader -->
<mapping type="one-way" wildcard="false" map-null="true">
<class-a>org.supercsv.io.dozer.CsvDozerBeanData</class-a>
<class-b>org.supercsv.mock.dozer.SurveyResponse</class-b>
<field>
<a>columns[0]</a>
<b>age</b>
</field>
<field>
<a>columns[1]</a>
<b>consentGiven</b>
</field>
<field>
<a>columns[2]</a>
<b>answers[0].questionNo</b>
</field>
<field>
<a>columns[3]</a>
<b>answers[0].answer</b>
</field>
<field>
<a>columns[4]</a>
<b>answers[1].questionNo</b>
</field>
<field>
<a>columns[5]</a>
<b>answers[1].answer</b>
</field>
<field>
<a>columns[6]</a>
<b>answers[2].questionNo</b>
</field>
<field>
<a>columns[7]</a>
<b>answers[2].answer</b>
</field>
</mapping>
<!-- configuration for CsvDozerBeanWriter -->
<mapping type="one-way" wildcard="false" map-null="true">
<class-a>org.supercsv.mock.dozer.SurveyResponse</class-a>
<class-b>org.supercsv.io.dozer.CsvDozerBeanData</class-b>
<field copy-by-reference="true">
<a>age</a>
<b>columns[0]</b>
</field>
<field copy-by-reference="true">
<a>consentGiven</a>
<b>columns[1]</b>
</field>
<field copy-by-reference="true">
<a>answers[0].questionNo</a>
<b>columns[2]</b>
</field>
<field copy-by-reference="true">
<a>answers[0].answer</a>
<b>columns[3]</b>
</field>
<field copy-by-reference="true">
<a>answers[1].questionNo</a>
<b>columns[4]</b>
</field>
<field copy-by-reference="true">
<a>answers[1].answer</a>
<b>columns[5]</b>
</field>
<field copy-by-reference="true">
<a>answers[2].questionNo</a>
<b>columns[6]</b>
</field>
<field copy-by-reference="true">
<a>answers[2].answer</a>
<b>columns[7]</b>
</field>
</mapping>
</mappings>