- Quarkus - Validation with Hibernate Validator
Quarkus - Validation with Hibernate Validator
This guide covers how to use Hibernate Validator/Bean Validation for:
validating the input/output of your REST services;
validating the parameters and return values of the methods of your business services.
Prerequisites
To complete this guide, you need:
less than 15 minutes
an IDE
JDK 1.8+ installed with
JAVA_HOME
configured appropriatelyApache Maven 3.6.2+
Architecture
The application built in this guide is quite simple. The user fills a form on a web page. The web page sends the form content to the BookResource
as JSON (using Ajax). The BookResource
validates the user input and returns the result as JSON.
Solution
We recommend that you follow the instructions in the next sections and create the application step by step. However, you can go right to the completed example.
Clone the Git repository: git clone [https://github.com/quarkusio/quarkus-quickstarts.git](https://github.com/quarkusio/quarkus-quickstarts.git)
, or download an archive.
The solution is located in the validation-quickstart
directory.
Creating the Maven project
First, we need a new project. Create a new project with the following command:
mvn io.quarkus:quarkus-maven-plugin:1.7.6.Final:create \
-DprojectGroupId=org.acme \
-DprojectArtifactId=validation-quickstart \
-DclassName="org.acme.validation.BookResource" \
-Dpath="/books" \
-Dextensions="resteasy-jsonb, hibernate-validator"
cd validation-quickstart
This command generates a Maven structure importing the RESTEasy/JAX-RS, JSON-B and Hibernate Validator/Bean Validation extensions.
If you already have your Quarkus project configured, you can add the hibernate-validator
extension to your project by running the following command in your project base directory:
./mvnw quarkus:add-extension -Dextensions="hibernate-validator"
This will add the following to your pom.xml
:
<dependency>
<groupId>io.quarkus</groupId>
<artifactId>quarkus-hibernate-validator</artifactId>
</dependency>
Accessing the Validator
Edit the org.acme.validation.BookResource
class, and inject the Validator
object as follows:
@Inject
Validator validator;
The Validator
allows checking constraints on a specific object.
Constraints
In this application, we are going to test an elementary object, but we support complicated constraints and can validate graphs of objects. Create the org.acme.validation.Book
class with the following content:
package org.acme.validation;
import javax.validation.constraints.NotBlank;
import javax.validation.constraints.Min;
public class Book {
@NotBlank(message="Title may not be blank")
public String title;
@NotBlank(message="Author may not be blank")
public String author;
@Min(message="Author has been very lazy", value=1)
public double pages;
}
Constraints are added on fields, and when an object is validated, the values are checked. The getter and setter methods are also used for JSON mapping.
JSON mapping and validation
Back to the BookResource
class. Add the following method:
@Path("/manual-validation")
@POST
@Produces(MediaType.APPLICATION_JSON)
@Consumes(MediaType.APPLICATION_JSON)
public Result tryMeManualValidation(Book book) {
Set<ConstraintViolation<Book>> violations = validator.validate(book);
if (violations.isEmpty()) {
return new Result("Book is valid! It was validated by manual validation.");
} else {
return new Result(violations);
}
}
Yes it does not compile, Result
is missing, but we will add it very soon.
The method parameter (book
) is created from the JSON payload automatically.
The method uses the Validator
to check the payload. It returns a set of violations. If this set is empty, it means the object is valid. In case of failures, the messages are concatenated and sent back to the browser.
Let’s now create the Result
class as an inner class:
public static class Result {
Result(String message) {
this.success = true;
this.message = message;
}
Result(Set<? extends ConstraintViolation<?>> violations) {
this.success = false;
this.message = violations.stream()
.map(cv -> cv.getMessage())
.collect(Collectors.joining(", "));
}
private String message;
private boolean success;
public String getMessage() {
return message;
}
public boolean isSuccess() {
return success;
}
}
The class is very simple and only contains 2 fields and the associated getters and setters. Because we indicate that we produce JSON, the mapping to JSON is made automatically.
REST end point validation
While using the Validator
manually might be useful for some advanced usage, if you simply want to validate the parameters or the return value or your REST end point, you can annotate it directly, either with constraints (@NotNull
, @Digits
…) or with @Valid
(which will cascade the validation to the bean).
Let’s create an end point validating the Book
provided in the request:
@Path("/end-point-method-validation")
@POST
@Produces(MediaType.APPLICATION_JSON)
@Consumes(MediaType.APPLICATION_JSON)
public Result tryMeEndPointMethodValidation(@Valid Book book) {
return new Result("Book is valid! It was validated by end point method validation.");
}
As you can see, we don’t have to manually validate the provided Book
anymore as it is automatically validated.
If a validation error is triggered, a violation report is generated and serialized as JSON as our end point produces a JSON output. It can be extracted and manipulated to display a proper error message.
Service method validation
It might not always be handy to have the validation rules declared at the end point level as it could duplicate some business validation.
The best option is then to annotate a method of your business service with your constraints (or in our particular case with @Valid
):
package org.acme.validation;
import javax.enterprise.context.ApplicationScoped;
import javax.validation.Valid;
@ApplicationScoped
public class BookService {
public void validateBook(@Valid Book book) {
// your business logic here
}
}
Calling the service in your rest end point triggers the Book
validation automatically:
@Inject BookService bookService;
@Path("/service-method-validation")
@POST
@Produces(MediaType.APPLICATION_JSON)
@Consumes(MediaType.APPLICATION_JSON)
public Result tryMeServiceMethodValidation(Book book) {
try {
bookService.validateBook(book);
return new Result("Book is valid! It was validated by service method validation.");
} catch (ConstraintViolationException e) {
return new Result(e.getConstraintViolations());
}
}
Note that, if you want to push the validation errors to the frontend, you have to catch the exception and push the information yourselves as they will not be automatically pushed to the JSON output.
Keep in mind that you usually don’t want to expose to the public the internals of your services - and especially not the validated value contained in the violation object.
A frontend
Now let’s add the simple web page to interact with our BookResource
. Quarkus automatically serves static resources contained in the META-INF/resources
directory. In the src/main/resources/META-INF/resources
directory, replace the index.html
file with the content from this index.html file in it.
Run the application
Now, let’s see our application in action. Run it with:
./mvnw compile quarkus:dev
Then, open your browser to http://localhost:8080/:
Enter the book details (valid or invalid)
Click on the Try me… buttons to check if your data is valid using one of the methods we presented above.
As usual, the application can be packaged using ./mvnw clean package
and executed using the -runner.jar
file. You can also build the native executable using ./mvnw package -Pnative
.
Going further
Hibernate Validator extension and CDI
The Hibernate Validator extension is tightly integrated with CDI.
Configuring the ValidatorFactory
Sometimes, you might need to configure the behavior of the ValidatorFactory
, for instance to use a specific ParameterNameProvider
.
While the ValidatorFactory
is instantiated by Quarkus itself, you can very easily tweak it by declaring replacement beans that will be injected in the configuration.
If you create a bean of the following types in your application, it will automatically be injected into the ValidatorFactory
configuration:
javax.validation.ClockProvider
javax.validation.ConstraintValidator
javax.validation.ConstraintValidatorFactory
javax.validation.MessageInterpolator
javax.validation.ParameterNameProvider
javax.validation.TraversableResolver
org.hibernate.validator.spi.properties.GetterPropertySelectionStrategy
org.hibernate.validator.spi.scripting.ScriptEvaluatorFactory
You don’t have to wire anything.
Obviously, for each listed type, you can declare only one bean. These beans should be declared as |
Constraint validators as beans
You can declare your constraint validators as CDI beans:
@ApplicationScoped
public class MyConstraintValidator implements ConstraintValidator<MyConstraint, String> {
@Inject
MyService service;
@Override
public boolean isValid(String value, ConstraintValidatorContext context) {
if (value == null) {
return true;
}
return service.validate(value);
}
}
When initializing a constraint validator of a given type, Quarkus will check if a bean of this type is available and, if so, it will use it instead of instantiating one.
Thus, as demonstrated in our example, you can fully use injection in your constraint validator beans.
Except in very specific situations, it is recommended to make the said beans |
Validation and localization
By default, constraint violation messages will be returned in the build system locale.
You can configure this behavior by adding the following configuration in your application.properties
:
# The default locale to use
quarkus.default-locale=fr-FR
If you are using RESTEasy, in the context of a JAX-RS endpoint, Hibernate Validator will automatically resolve the optimal locale to use from the Accept-Language
HTTP header, provided the supported locales have been properly specified in the application.properties
:
# The list of all the supported locales
quarkus.locales=en-US,es-ES,fr-FR