helper.setProperty(bean, "name", String.class, config);
        assertEquals("testValue", bean.getName());

        // Clear caches and verify it still works
        EnhancedCompositeBeanHelper.clearCaches();

        TestBean bean2 = new TestBean();
        helper.setProperty(bean2, "name", String.class, config);
        assertEquals("testValue", bean2.getName());

		t.Errorf("Hamster's preferred toy should be cleared with Clear")
	}

	if DB.Model(&hamster2).Association("OtherToy").Count() != 1 {
		t.Errorf("Hamster's other toy should be still available")
	}

	DB.Model(&hamster).Association("OtherToy").Clear()
	if DB.Model(&hamster).Association("OtherToy").Count() != 0 {
		t.Errorf("Hamster's other toy should be cleared with Clear")
	}

  }

  @Override
  public final boolean equals(@Nullable Object obj) {
    if (obj instanceof Subscriber) {
      Subscriber that = (Subscriber) obj;
      // Use == so that different equal instances will still receive events.
      // We only guard against the case that the same object is registered
      // multiple times
      return target == that.target && method.equals(that.method);
    }
    return false;
  }

However, this does not fully remove the prerequisite, as the Wrapper itself would still need an installed Java runtime to execute.

Gradle needs a solution that covers the use-case of starting the Wrapper itself as well given its importance.

### Running Gradle on multiple Java versions

// Here you should declare versions which should be shared by the different modules of buildSrc itself
val javaParserVersion = "3.18.0"
// Note: this currently still contains 3/4 logic as we will temporarily have Groovy 3 for the build itself until we move to a Gradle built with Groovy 4
// It can be removed or changed to 4/5 logic (if necessary) at that point.

 *
 * <p>Lookups by row key are often faster than lookups by column key, because the data is stored in
 * a {@code Map<R, Map<C, V>>}. A method call like {@code column(columnKey).get(rowKey)} still runs
 * quickly, since the row key is provided. However, {@code column(columnKey).size()} takes longer,
 * since an iteration across all row keys occurs.
 *

 *
 * <p>Lookups by row key are often faster than lookups by column key, because the data is stored in
 * a {@code Map<R, Map<C, V>>}. A method call like {@code column(columnKey).get(rowKey)} still runs
 * quickly, since the row key is provided. However, {@code column(columnKey).size()} takes longer,
 * since an iteration across all row keys occurs.
 *

   * next} field is lazily initialized. The type of that field would be {@code @Nullable T}, and the
   * code would be responsible for populating a "real" {@code T} (which might still be the value
   * {@code null}!) before returning it to callers. Depending on how the code is structured, a
   * nullness analysis might not understand that the field has been populated. To avoid that problem

   * next} field is lazily initialized. The type of that field would be {@code @Nullable T}, and the
   * code would be responsible for populating a "real" {@code T} (which might still be the value
   * {@code null}!) before returning it to callers. Depending on how the code is structured, a
   * nullness analysis might not understand that the field has been populated. To avoid that problem

```

////

## Recap { #recap }

Apart from all the fancy words used here, the **Dependency Injection** system is quite simple.

Just functions that look the same as the *path operation functions*.

But still, it is very powerful, and allows you to declare arbitrarily deeply nested dependency "graphs" (trees).

/// tip

All this might not seem as useful with these simple examples.