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The Athena::Validator component provides a robust object/value validation framework.


First, install the component by adding the following to your shard.yml, then running shards install:

    github: athena-framework/validator
    version: ~> 0.3.0


Athena::Validator comes with a set of common AVD::Constraints built-in that any project could find useful. When used on its own, the Athena::Validator.validator method can be used to obtain an AVD::Validator::ValidatorInterface instance to validate a given value/object.


A validator accepts a value, and one or more AVD::Constraint to validate the value against. The validator then returns an AVD::Violation::ConstraintViolationListInterface that includes all the violations, if any.

# Obtain a validator instance.
validator = AVD.validator

# Use the validator to validate a value.
violations = validator.validate "foo",

# The validator returns an empty list of violations, indicating the value is valid.
violations.inspect # => Athena::Validator::Violation::ConstraintViolationList(@violations=[])

In this case it returns an empty list of violations, meaning the value is valid.

# Using the validator instance from the previous example
violations = validator.validate "",

violations.inspect # =>
# Athena::Validator::Violation::ConstraintViolationList(
#   @violations=[
#     Athena::Validator::Violation::ConstraintViolation(
#       @cause=nil,
#       @code="0d0c3254-3642-4cb0-9882-46ee5918e6e3",
#       @constraint=#<Athena::Validator::Constraints::NotBlank:0x7f8a7291fed0
#         @allow_nil=false,
#         @groups=["default"],
#         @message="This value should not be blank.",
#         @payload=nil>,
#       @invalid_value_container=Athena::Validator::ValueContainer(String)(@value=""),
#       @message="This value should not be blank.",
#       @message_template="This value should not be blank.",
#       @parameters={"{{ value }}" => ""},
#       @plural=nil,
#       @property_path="",
#       @root_container=Athena::Validator::ValueContainer(String)(@value="")
#     )
#   ]

# Both the ConstraintViolationList and ConstraintViolation implement a `#to_s` method.
puts violations # =>
# :
#   This value should not be blank. (code: 0d0c3254-3642-4cb0-9882-46ee5918e6e3)

However in the case of the value NOT being valid, the list includes all of the AVD::Violation::ConstraintViolationInterfaces produced during this run. Each violation includes some metadata; such as the related constraint that failed, a machine readable code, a human readable message, any parameters that should be used to render that message, etc. The extra context allows for a lot of flexibility; both in terms of how the error could be rendered or handled.

By default, in addition to any constraint specific arguments, the majority of the constraints have three optional arguments: message, groups, and payload.

  • The message argument represents the message that should be used if the value is found to not be valid. The message can also include placeholders, in the form of {{ key }}, that will be replaced when the message is rendered. Most commonly this includes the invalid value itself, but some constraints have additional placeholders.
  • The payload argument can be used to attach any domain specific data to the constraint; such as attaching a severity with each constraint to have more serious violations be handled differently.
  • The groups argument can be used to run a subset of the defined constraints. More on this in the Validation Groups section.

validator = AVD.validator

# Instantiate a constraint with a custom message, using a placeholder.
violations = validator.validate -4, message: "{{ value }} is not a valid age.  A user cannot have a negative age."

puts violations # =>
# -4:
#   -4 is not a valid age.  A user cannot have a negative age. (code: e09e52d0-b549-4ba1-8b4e-420aad76f0de)
Customizing the message can be a good way for those consuming the errors to determine WHY a given value is not valid.

Validating Objects#

Validating arbitrary values against a set of arbitrary constraints can be useful in smaller applications and/or for one off use cases. However to keep in line with our Object Oriented Programming (OOP) principles, we can also validate objects. The object could be either a struct or a class. The only requirements are that the object includes a specific module, AVD::Validatable, and specifies which properties should be validated and against what constraints. The easiest/most common way to do this is via annotations and the Assert alias.

# Define a class that can be validated.
class User
  include AVD::Validatable

  def initialize(@name : String, @age : Int32? = nil); end

  # Specify that we want to assert that the user's name is not blank.
  # Multiple constraints can be defined on a single property.
  getter name : String

  # Arguments to the constraint can be used normally as well.
  # The constraint's default argument can also be supplied positionally: `@[Assert::GreaterThan(0)]`.
  @[Assert::NotNil(message: "A user's age cannot be null")]
  getter age : Int32?

# Obtain a validator instance.
validator = AVD.validator

# Validate a user instance, notice we're not passing in any constraints.
validator.validate("Jim", 10)).empty? # => true
validator.validate "", 10             # =>
# Object(User).name:
#   This value should not be blank. (code: 0d0c3254-3642-4cb0-9882-46ee5918e6e3)

Notice that in this case we do not need to supply the constraints to the #validate method. This is because the validator is able to extract them from the annotations on the properties. An array of constraints can still be supplied, and will take precedence over the constraints defined within the type.


By default if a property's value is another object, the sub object will not be validated. use the AVD::Constraints::Valid constraint if you wish to also validate the sub object. This also applies to arrays of objects.

Another important thing to point out is that no custom DSL is required to define these constraints. Athena::Validator is intended to be a generic validation solution that could be used outside of the Athena ecosystem. However, in order to be able to use the annotation based approach, you need to be able to apply the annotations to the underlying properties. If this is not possible due to how a specific type is implemented, or if you just don't like the annotation syntax, the type can also be configured via code.

# Define a class that can be validated.
class User
  include AVD::Validatable

  # This class method is invoked when building the metadata associated with a type,
  # and can be used to manually wire up the constraints.
  def self.load_metadata(metadata : AVD::Metadata::ClassMetadata) : Nil
    metadata.add_property_constraint "name",

  def initialize(@name : String); end

  getter name : String

# Obtain a validator instance.
validator = AVD.validator

# Validate a user instance, notice we're not passing in any constraints.
validator.validate("Jim")).empty? # => true
validator.validate ""             # =>
# Object(User).name:
#   This value should not be blank. (code: 0d0c3254-3642-4cb0-9882-46ee5918e6e3)

The metadata for each type is lazily loaded when an instance of that type is validated, and is only built once. See AVD::Metadata::ClassMetadata for some additional ways to register property constraints.


Constraints can also be applied to getter methods of an object. This allows for dynamic validations based on the return value of the method. For example, say we wanted to assert that a user's name is not the same as their password.

class User
  include AVD::Validatable

  property name : String
  property password : String

  def initialize(@name : String, @password : String); end

  @[Assert::IsTrue(message: "Your password cannot be the same as your name.")]
  def is_safe_password? : Bool
    @name != @password

validator = AVD.validator

user = "foo", "foo"

validator.validate(user).empty? # => false

user.password = "bar"

validator.validate(user).empty? # => true

Custom Constraints#

If the built in AVD::Constraints are not sufficient to handle validating a given value/object; custom ones can be defined. Let's make a new constraint that asserts a string contains only alphanumeric characters.

This is accomplished by first defining a new class within the AVD::Constraints namespace that inherits from AVD::Constraint. Then define a Validator struct within our constraint that inherits from AVD::ConstraintValidator that actually implements the validation logic.

class AVD::Constraints::AlphaNumeric < AVD::Constraint
  # (Optional) A unique error code can also be defined to provide a machine readable identifier for a specific error.
  NOT_ALPHANUMERIC_ERROR = "1a83a8bd-ff79-4d5c-96e7-86d0b25b8a09"

  # (Optional) Allows using the `.error_message(code : String) : String` method with this constraint.
  @@error_names = {

  # Define an initializer with our default message, and any additional arguments specific to this constraint.
  def initialize(
    message : String = "This value should contain only alphanumeric characters.",
    groups : Array(String) | String | Nil = nil,
    payload : Hash(String, String)? = nil
    super message, groups, payload

  # Define the validator within our constraint that'll contain our validation logic.
  class Validator < AVD::ConstraintValidator
    # Define our validate method that accepts the value to be validated, and the constraint.
    # Overloads can be used to filter values of specific types.
    def validate(value : _, constraint : AVD::Constraints::AlphaNumeric) : Nil
      # Custom constraints should ignore nil and empty values to allow
      # other constraints (NotBlank, NotNil, etc.) take care of that
      return if value.nil? || value == ""

      # We'll cast the value to a string,
      # alternatively we could just ignore non `String?` values.
      value = value.to_s

      # If all the characters of this string are alphanumeric, then it is valid
      return if value.each_char.all? &.alphanumeric?

      # Otherwise, it is invalid and we need to add a violation,
      # see `AVD::ExecutionContextInterface` for additional information.
      self.context.add_violation constraint.message, NOT_ALPHANUMERIC_ERROR, value

puts AVD.validator.validate "$", # =>
# $:
#   This value should contain only alphanumeric characters. (code: 1a83a8bd-ff79-4d5c-96e7-86d0b25b8a09)


The constraint MUST be defined within the AVD::Constraints namespace for implementation reasons. This may change in the future.

We are now able to use this constraint as we would one of the built in ones; either by manually instantiating it, or applying an @[Assert::AlphaNumeric] annotation to a property.

See AVD::ConstraintValidatorInterface for more information on custom validators.

Validation Groups#

By default when validating an object, all constraints defined on that type will be checked. However, in some cases you may only want to validate the object against some of those constraints. This can be accomplished via assigning each constraint to a validation group, then apply validation against one specific group of constraints.

For example, using our User class from earlier, say we only want to validate certain properties when the user is first created. To do this we can utilize the groups argument that all constraints have.

class User
  include AVD::Validatable

  def initialize(@email : String, @password : String, @city : String); end

  @[Assert::Email(groups: "create")]
  getter email : String

  @[Assert::NotBlank(groups: "create")]
  @[Assert::Size(7.., groups: "create")]
  getter password : String

  getter city : String

user = "[email protected]", "monkey123", ""

# Validate the user object, but only for those in the "create" group,
# if no groups are supplied, then all constraints in the "default" group will be used.
violations = AVD.validator.validate user, groups: "create"

# There are no violations since the city's size is not validated since it's not in the "create" group.
violations.empty? # => true

See AVD::Constraint@validation-groups for some expanded information.

Sequential Validation#

By default, all constraints are validated in a single "batch". I.e. all constraints within the provided group(s) are validated, without regard to if the previous/next constraint is/was (in)valid. However, an AVD::Constraints::GroupSequence can be used to validate batches of constraints in steps. I.e. validate the first "batch" of constraints, and only advance to the next batch if all constraints in that step are valid.

@[Assert::GroupSequence("User", "Secondary")]
class User
  include AVD::Validatable

  getter username : String

  @[Assert::NotBlank(groups: "Secondary")]
  getter password : String

  def initialize(@username : String, @password : String); end

# Instantiate a new `User` object where both properties are invalid.
user = "", ""

# Notice there is only one violation since there was a violation in the `User` group,
# it did not advance to the `Secondary` group.
AVD.validator.validate user # =>
# Object(User).username:
#   This value should not be blank. (code: 0d0c3254-3642-4cb0-9882-46ee5918e6e3)

Group Sequence Providers#

The AVD::Constraints::GroupSequence can be a useful tool for creating efficient validations, but it is quite limiting since the sequence is static on the type. If more flexibility is required the AVD::Constraints::GroupSequence::Provider module can be included into a type. The module allows the object to return the sequence it should use dynamically at runtime.

class User
  include AVD::Validatable
  include AVD::Constraints::GroupSequence::Provider

  # ...

  def group_sequence : Array(Array(String) | String) | AVD::Constraints::GroupSequence
    # Build out and return the sequence `self` should use.

Alternatively, if you only want to apply constraints sequentially on a single property, the AVD::Constraints::Sequentially constraint can be used to do this in a simpler way.