Improve the reliability and security of the Java class library data verification through the Bean Validation Scala framework
Improve the reliability and security of the Java class library data verification through the Bean Validation Scala framework
Overview:
Data verification is a vital link in software development.It can ensure that the input data meets expectations and effectively processes data.However, manual writing and management data verification logic may be very cumbersome and easy to make errors.To solve this problem, Java provides a flexible and powerful data verification framework -Bean Validation.This article will introduce how to improve the reliability and security of Java library data verification through the Bean Validation Scala framework.
Bean Validation Introduction:
Bean Validation is part of Java Ee, which provides a statement, a statement -based method to define and perform data verification rules.Through simply adding annotations to the fields, methods, or parameters of the Java class, developers can easily define data verification rules, such as non -air inspection, length check, regular expression matching, etc.The Bean Validation framework will automatically verify whether the attributes of the object meet the rules of these definitions and provide corresponding error messages.
Use Bean Validation Scala framework:
The Bean Validation framework was originally designed for Java language, but it can also be easily used in SCALA.SCALA is a powerful static type, functional programming language, which is highly compatible with Java language.Here are some example code that uses the Bean Validation Scala framework:
1. Add dependencies:
First of all, we need to add the following dependence on the construction document of the project:
scala
libraryDependencies += "org.hibernate.validator" % "hibernate-validator" % "6.0.20.Final"
libraryDependencies += "org.hibernate.validator" % "hibernate-validator-annotation-processor" % "6.0.20.Final"
2. Create a model class:
Define a simple User class as a data model, including username and age field.
scala
import javax.validation.constraints.{NotBlank, NotNull, Size}
case class User(
@NotBlank (Message = "Username cannot be empty")
@Size (min = 3, max = 20, message = "Username length must be between 3 and 20")
username: String,
@Notnull (Message = "Age cannot be empty")
@AGEVALID (Message = "Age must be between 18 and 99")
age: Integer
)
In the above examples, we use two built-in verification annotations-@notblank` and `@siZe.`@Notblank` Annotation is used to ensure that the user name segment is not empty.At the same time, the length of the user name is between 3 to 20 characters used to limit the username.In addition, we also define a customized verification annotation `@Agevalid` to verify whether the age is between 18 and 99.
3. Create custom verification annotations:
We need to create a custom annotation called `Agevalid` to verify whether the age field is legal.
scala
import javax.validation.Constraint
import javax.validation.Payload
import scala.annotation.StaticAnnotation
import scala.annotation.meta.{field, getter, param}
@Constraint(validatedBy = Array(classOf[AgeValidator]))
@Retention(RUNTIME)
@Target({FIELD, PARAMETER, METHOD})
annotation class AgeValid(
val message: String = "Invalid age",
val groups: Array<Class<*>> = Array(),
val payload: Array<Class<out Payload>> = Array()
) extends StaticAnnotation
In the above code, we use the scala method to define a custom annotation `Agevalid`.The annotation needs to specify that the verification logic is implemented by the `Agevalidator` class.We specify that the annotation can be applied to fields, methods and parameters in the annotation of `@target`.
4. Create a verification device:
Create a verification class called `Agevalidator` to achieve customized age verification logic.
scala
import javax.validation.ConstraintValidator
import javax.validation.ConstraintValidatorContext
class AgeValidator extends ConstraintValidator[AgeValid, Integer] {
override def isValid(value: Integer, context: ConstraintValidatorContext): Boolean = {
value >= 18 && value <= 99
}
}
In the above example, we implement the `ConstraintValidator` interface, and specify its generic parameters to the` Agevalid` annotation and age field type `Integer`.Then, we need to implement the `iSVALID` method to verify the inlet age values.In this example, we simply verify whether the age is between 18 and 99.
5. Perform data verification:
The following is an example code that uses Bean Validation Scala framework to verify:
scala
import javax.validation.Validation
import java.util.Set
val user = User("", 25)
val validatorFactory = Validation.buildDefaultValidatorFactory()
val validator = validatorFactory.getValidator()
val violations: Set[ConstraintViolation[User]] = validator.validate(user)
for (violation <- violations) {
println(violation.getMessage())
}
In the above examples, we first created an object of the `Validator", and then verified the `user` object using the` value method.The `validate` method will return a collection of` Constraintviolation` objects that contain all verification failure.We can obtain the detailed information of each verification failure by traversing the collection.
in conclusion:
By using the Bean Validation SCALA framework, we can simplify and unify the data verification logic and improve the data verification reliability and security of the Java library.Developers can declare data verification rules by annotating, and the framework will automatically execute verification.This makes us easier to write maintenance and robust code and reduce the risk of artificial errors.
