Validations
Validation in Azu is support by the Schema shards and is already included with every Crystal Application
Self validating Schemas are beneficial, and in my opinion, ideal, for when defining API Requests, Web Forms, JSON. Schema-Validation Takes a different approach and focuses a lot on explicitness, clarity, and precision of validation logic. It is designed to work with any data input, whether it’s a simple hash, an array or a complex object with deeply nested data.
Each validation is encapsulated by a simple, stateless predicate that receives some input and returns either true or false. Those predicates are encapsulated by rules which can be composed together using predicate logic, meaning you can use the familiar logic operators to build up a validation schema.
Usage
Schema instance methods
Validations
You can also perform validations for existing objects without the use of Schemas.
Custom Validations
Simply create a class {Name}Validator
with the following signature:
Defining Predicates
You can define your custom predicates by simply creating a custom validator or creating methods in the Schema::Predicates
module ending with ?
and it should return a boolean
. For example:
Differences: Custom Validator vs Predicates
The differences between a custom validator and a method predicate are:
Custom Validators
Must be inherited from
Schema::Validator
abstractReceives an instance of the object as a
record
instance var.Must have a
:field
and:message
defined.Must implement a
def valid? : Array(Schema::Error)
method.
Predicates
Assertions of the property value against an expected value.
Predicates are light weight boolean methods.
Predicates methods must be defined as
def {predicate}?(property_value, expected_value) : Bool
.
Built in Predicates
These are the current available predicates.
CONTRIBUTE - Add more predicates to this shards by contributing a Pull Request.
Additional Parameters
Last updated