import javax.swing.text.MaskFormatter;JFormattedTextField customerId = new JFormattedTextField(new MaskFormatter("UUU_UUU"));testImplementation 'org.junit-pioneer:junit-pioneer:1.7.0'
@Test
@ClearSystemProperty(key = "some key")
@SetSystemProperty(key = "another key", value = "new value")
void test() {
assertNull(System.getProperty("some key"));
assertEquals("new value", System.getProperty("another key"));
}Helidon is a set of libraries for microservices. It is created and maintained by Oracle. To run it, we need at least Java 11. The latest release introduces support for Java 17. We can write code with Java and Kotlin as well. Interestingly, it comes in two flavors: Helidon SE and Helidon MP.
...
Both may be compiled into native images using GraalVM, resulting in a faster startup time and lower memory consumption. However, the SE profile consumes fewer resources than MP.
Helidon SE is a small toolkit that supports the most recent Java SE features, including reactive streams, asynchronous and functional programming, and APIs with a fluid design. Helidon SE offers GraalVM native files for low storage use and flash -like launch. Helidon SE’s REST framework is based on Netty and provides a simplistic API for session handling.
Helidon SE is a toolkit providing reactive streams, asynchronous and functional programming, and fluent-style APIs. It offers a reactive API for streams, messaging, and databases. You may create web endpoints based on GraphQL, gRPC, WebSockets, and HTTP server technologies. Next, we can secure them using a dedicated security add-on. And, at the end, we can spice it with a pinch of metrics, health checks, tracing, and documentation with OpenAPI.
On the other hand, Helidon MP is an implementation of MicroProfile specification. Among the features mentioned for the SE profile, you can find here support for JPA, RESTful services, security with JWT, and long-running actions based on SAGA patterns. Furthermore, this version is meant to run in the cloud; we can deploy an application on OCI or Kubernetes.
Both may be compiled into native images using GraalVM, resulting in a faster startup time and lower memory consumption. However, the SE profile consumes fewer resources than MP.
import com.rabbitmq.client.Channel;
import com.rabbitmq.client.Channel;
import com.rabbitmq.client.Connection;
import com.rabbitmq.client.ConnectionFactory;
ConnectionFactory factory = new ConnectionFactory();
factory.setHost("localhost");
Connection connection = factory.newConnection();
Channel channel = connection.createChannel();DeliverCallback deliverCallbackDlx = (consumerTag, delivery) -> {
String routingKey = delivery.getEnvelope().getRoutingKey();
String message = new String(delivery.getBody(), StandardCharsets.UTF_8);
System.out.println(" [x] Received WITH DLX! '" + routingKey + "':'" + message + "'");
channel.basicAck(delivery.getEnvelope().getDeliveryTag(), false);
};
channel.basicConsume("tickets_dlx", false, deliverCallbackDlx, consumerTag -> {});The following shows how RabbitMQ’s Java publisher sets the TTL of a message which can reside in the queue for at most 60 seconds:
byte[] messageBodyBytes = "Hello, world!".getBytes();
AMQP.BasicProperties properties = new AMQP.BasicProperties.Builder()
.expiration("60000")
.build();
channel.basicPublish("my-exchange", "routing-key", properties, messageBodyBytes);channel.basicPublish("tickets", "payment_is_done", null,
paymentInfo.toString().getBytes(StandardCharsets.UTF_8));Map<String, args = new HashMap<>()
{
{
put("x-max-length", 10);
put("x-message-ttl", 5000);
put("x-dead-letter-exchange", "tickets_dlx";
put("x-dead-letter-routing-key", "payment_is_done");
}
};
channel.queueDeclare("TICKETS_AFTER_APPROVING_PAYMENT",
true, //Durable
false,//Exclusive
false, //Auto delete
args);
channel.queueBind("TICKETS_AFTER_APPROVING_PAYMENT", "tickets", "payment_is_done");