CellProcessor for MapEntry - supercsv

Question

I have a simple POJO that has a Map inside it.
public class Product {
public Map map;
}
then my csv looks like this:
"mapEntry1","mapEntry2","mapEntry3"
So I created a custom cell processor for parsing those:
public class MapEntryCellProcessor {
public Object execute(Object val, CsvContext context) {
return next.execute(new AbstractMap.SimpleEntry<>("somekey", val), context);
}
}
and then I add an entry setter method in my Product:
public void setName(Entry<String, String> entry) {
if (getName() == null) {
name = new HashMap<>();
}
name.put(entry.getKey(), entry.getValue());
}
Unfortunately this means I have 2 setter methods: one that accepts a map and another one that accepts an entry which doesn't really work for me (I have no control on how the POJOs are generated). Is there any other way I can parse such a CSV and have only setter that accepts a Map in my Product?

Answer 1

It's possible to write a cell processor that collects each column into a map. For example, the following processor allows you to specify the key and the map to add to.
package org.supercsv.example;
import java.util.Map;
import org.supercsv.cellprocessor.CellProcessorAdaptor;
import org.supercsv.cellprocessor.ift.CellProcessor;
import org.supercsv.util.CsvContext;
public class MapCollector extends CellProcessorAdaptor {
private String key;
private Map<String, String> map;
public MapCollector(String key, Map<String, String> map){
this.key = key;
this.map = map;
}
public MapCollector(String key, Map<String, String> map,
CellProcessor next){
super(next);
this.key = key;
this.map = map;
}
public Object execute(Object value, CsvContext context) {
validateInputNotNull(value, context);
map.put(key, String.valueOf(value));
return next.execute(map, context);
}
}
Then assuming your Product bean has a field name of type Map<String,String>, you can use the processor as follows.
package org.supercsv.example;
import java.io.IOException;
import java.io.StringReader;
import java.util.HashMap;
import java.util.Map;
import junit.framework.TestCase;
import org.supercsv.cellprocessor.ift.CellProcessor;
import org.supercsv.io.CsvBeanReader;
import org.supercsv.io.ICsvBeanReader;
import org.supercsv.prefs.CsvPreference;
public class MapCollectorTest extends TestCase {
private static final String CSV = "John,L,Smith\n" +
"Sally,P,Jones";
public void testMapCollector() throws IOException{
ICsvBeanReader reader = new CsvBeanReader(
new StringReader(CSV),
CsvPreference.STANDARD_PREFERENCE);
// only need to map the field once, so use nulls
String[] nameMapping = new String[]{"name", null, null};
// create processors for each row (otherwise every bean
// will contain the same map!)
Product product;
while ((product = reader.read(Product.class,
nameMapping, createProcessors())) != null){
System.out.println(product.getName());
}
}
private static CellProcessor[] createProcessors() {
Map<String, String> nameMap = new HashMap<String, String>();
final CellProcessor[] processors = new CellProcessor[]{
new MapCollector("name1", nameMap),
new MapCollector("name2", nameMap),
new MapCollector("name3", nameMap)};
return processors;
}
}
This outputs:
{name3=Smith, name2=L, name1=John}
{name3=Jones, name2=P, name1=Sally}
You'll notice that while the processors execute on all 3 columns, it's only mapped to the bean once (hence the nulls in the nameMapping array).
I've also created the processors each time a row is read, otherwise every bean will be using the same map...which probably isn't what you want ;)