JarCastingdata-factory
Test framework for generating rich objects with dummy data
Inspired and leverages java-faker
Usage
In your pom.xml, add the following:
<dependency>
<groupId>com.github.srang</groupId>
<artifactId>data-factory</artifactId>
<version>1.0.3</version>
</dependency>
In your Java code define a class you want to generate for example:
public class Fruit {
public String name;
public String description;
public Fruit(String name, String description) {
this.name = name;
this.description = description;
}
}
Then to start generating Fruit instances, you'll need to instantiate a DataFactory:
DataFactory<Fruit> fruitFactory = new BaseFactory<>(Fruit.class);
Then you can start generating objects:
// generate one fruit
Fruit fruit = fruitFactory.generate();
// or generate a list of fruits
List<Fruit> fruits = fruitFactory.generate(6);
Factory Customization
There are a number of ways to customize a DataFactory:
// inline field filter
fruitFilter.addFilter(
(Field field) -> field.getType().equals(String.class)
&& field.getName().toLowerCase().contains("name"),
() -> "Apple");
Fruit apple = fruitFactory.generate();
apple.getName(); // the name is "Apple"
// add custom language/locale
Locale bos = new Locale("eng","boston"); // colloquialisms
DataFactory<Fruit> bostonFruitFactory = new BaseFactory<>(Fruit.class, bos);
bostonFruitFactory.generate().getName(); // wahtamelon
Nesting and Inheritance
A DataFactory can be used with complex objects that have List fields, nested objects, and/or inherit fields from parent objects. Going back to the Fruit example, let's create a couple supporting objects:
public class FruitBasket {
public String material;
public List<Fruit> contents;
public Fruit(String material, List<Fruit> contents) {
this.material = material;
this.contents = contents;
}
}
public class Berry extends Fruit {
public Integer seedCount;
public Berry(String name, String description, Integer seedCount) {
super(name, description);
this.seedCount = seedCount;
}
}