# PODNAME: Validation::Class::Cookbook
# ABSTRACT: Recipes for Validation::Class
# VERSION
__END__
=pod
=head1 NAME
Validation::Class::Cookbook - Recipes for Validation::Class
=head1 VERSION
version 7.900056
=head1 GUIDED TOUR
The instructions contained in this documentation are also relevant for
configuring any class derived from L<Validation::Class>. The validation logic
that follows is not specific to a particular use-case.
=head2 Parameter Handling
There are three ways to declare parameters you wish to have validated. The first
and most common approach is to supply the target parameters to the validation
class constructor:
use Validation::Class::Simple;
my $rules = Validation::Class::Simple->new(params => $params);
All input parameters are wrapped by the L<Validation::Class::Params> container
which provides generic functionality for managing hashes. Additionally you can
declare parameters by using the params object directly:
use Validation::Class::Simple;
my $rules = Validation::Class::Simple->new;
$rules->params->clear;
$rules->params->add(user => 'admin', pass => 's3cret');
printf "%s parameters were submitted", $rules->params->count;
Finally, any parameter which has corresponding validation rules that has been
declared in a validation class derived from L<Validation::Class> will have an
accessor which can be used directly or as an argument to the constructor:
package MyApp::Person;
use Validation::Class;
field 'name' => {
required => 1
};
package main;
my $rules = MyApp::Person->new(name => 'Egon Spangler');
$rules->name('Egon Spengler');
=head2 Validation Rules
Validation::Class comes with a complete standard set of validation rules which
allows you to easily describe the constraints and operations that need to be
performed per parameter.
Validation rules are referred to as I<fields>, fields are named after the
parameters they expect to be matched against. A field is also a hashref whose
keys are called directives which correspond with the names of classes in the
directives namespace, and whose values are arguments which control how
directives carry-out their operations.
use Validation::Class::Simple;
my $rules = Validation::Class::Simple->new;
$rules->fields->clear;
$rules->fields->add(name => { required => 1, max_length => 255 });
Fields can be specified as an argument to the class constructor, or managed
directly using the L<Validation::Class::Fields> container. Every field is
wrapped by the L<Validation::Class::Field> container which provides accessors
for all core directives. Directives can be found under the directives namespace,
e.g. the required directive refers to L<Validation::Class::Directive::Required>.
Please see L<Validation::Class::Directives> for a list of all core directives.
=head2 Flow Control
A good data validation tool is not simply checking input against constraints,
its also providing a means to easily handle different and often complex data
input scenarios.
The queue method allows you to designate and defer fields to be validated. It
also allows you to set fields that must be validated regardless of what has been
passed to the validate method. Additionally it allows you to conditionally
specify constraints:
use Validation::Class::Simple;
my $rules = Validation::Class::Simple->new;
$rules->queue('name'); # always validate the name parameter
$rules->queue('email', 'email2') if $rules->param('change_email');
$rules->queue('login', 'login2') if $rules->param('change_login');
# validate name
# validate email and email confirmation if change_email is true
# validate login and login confirmation if change_login is true
$rules->validate('password'); # additionally, validate password
$rules->clear_queue; # reset the queue when finished
Akin to the queue method is the stash method. At-times it is necessary to break
out of the box in order to design constraints that fit your particular use-case.
The stash method allows you to share arbitrary objects with routines used by
validation classes.
use Validation::Class::Simple;
my $rules = Validation::Class::Simple->new;
$rules->fields->add(
email => {
# email validation relies on a stashed object
validation => sub {
my ($self, $field, $params) = @_;
return 0 if ! my $dbo = $self->stash('dbo');
return 0 if ! $dbo->email_exists($field->value);
return 1;
}
}
);
# elsewhere in the program
$rules->stash(dbo => $database_object); # stash the database object
=head2 Error Handling
When validation fails, and it will, you need to be able to report what failed
and why. L<Validation::Class> give you complete control over error handling and
messages. Errors can exist at the field-level and class-level (errors not
specific to a particular field). All errors are wrapped in a
L<Validation::Class::Errors> container.
use Validation::Class::Simple;
my $rules = Validation::Class::Simple->new;
# print a comma separated list of class and field errors
print $rules->errors_to_string unless $rules->validate;
# print a newline separated list of class and field errors
print $rules->errors_to_string("\n") unless $rules->validate;
# print a comma separated list of class and upper-cased field errors
print $rules->errors_to_string(undef, sub{ ucfirst lc shift })
# print total number of errors at the class and field levels
print "Found %s errors", $rules->error_count;
# return a hashref of fields with errors
my $errors = $rules->error_fields;
# get errors for specific fields only
my @errors = $rules->get_errors('email', 'login');
=head2 Input Filtering
Filtering data is one fringe benefits of a good data validation framework. The
process is also known as scrubbing or sanitizing data. The process ensures that
the data being passed to the business logic will be clean and consistent.
Filtering data is not as simple and straight-forward as it may seem which is why
it is necessary to think-through your applications interactions before
implementation.
Filtering is the process of applying transformations to the incoming data. The
problem with filtering is that it permanently alters the data input and in the
event of a failure could report inconsistent error messages:
use Validation::Class::Simple;
my $rules = Validation::Class::Simple->new;
$rules->fields->add(
# even if the input is submitted as lowercase it will fail
# the filter is run as a pre-process by default
username => {
filters => ['uppercase'],
validation => sub {
return 0 if $_[1]->value =~ /[A-Z]/;
return 1;
}
}
);
When designing a system to filter data, it is always necessary to differentiate
pre-processing filters from post-processing filters. L<Validation::Class>
provides a filtering directive which designates certain fields to run filters in
post-processing:
$rules->fields->add(
# if the input is submitted as lowercase it will pass
username => {
filters => ['uppercase'],
filtering => 'post',
validation => sub {
return 0 if $_[1]->value =~ /[A-Z]/;
return 1;
}
}
);
=head2 Handling Failures
A data validation framework exists to handle failures, it is its main function
and purpose, in-fact, the difference between a validation framework and a
type-constraint system is how it responds to errors.
When a type-constraint system finds an error it raises an exception. Exception
handling is the process of responding to the occurrence, during computation, of
exceptions (anomalous or exceptional situations).
Typically the errors reported when an exception is raised includes a dump of the
program's state up until the point of the exception which is apropos as exceptions
are unexpected.
A data validation framework can also be thought-of as a type system but one that
is specifically designed to expect input errors and report user-friendly error
messages.
L<Validation::Class> may encounter exceptions as programmers defined validation
rules which remain mutable. L<Validation::Class> provides attributes for
determining how the validation engine reacts to exceptions and validation
failures:
use Validation::Class::Simple;
my $rules = Validation::Class::Simple->new(
ignore_failure => 1, # do not throw errors if validation fails
ignore_unknown => 0, # throw errors if unknown directives are found
report_failure => 0, # register errors if "method validations" fail
report_unknown => 0, # register errors if "unknown directives" are found
);
=head2 Data Validation
Once your fields are defined and you have your parameter rules configured as
desired you will like use the validate method to perform all required operations.
The validation operations occur in the following order:
normalization (resetting fields, clearing existing errors, etc)
pre-processing (applying filters, etc)
validation (processing directives, etc)
post-processing (applying filters, etc)
What gets validated is determined by the state and arguments passed to the
validate method. The validate method determines what to validate in the
following order:
checks the validation queue for fields
checks arguments for regular expression objects and adds matching fields
validates fields with matching parameters if no fields are specified
validates all fields if no parameters are specified
It is also important to under what it means to declare a field as being required.
A field is a data validation rule matching a specific parameter, A required
field simply means that if-and-when a parameter is submitted, it is required to
have a value. It does not mean that a field is always required to be validated.
Occasionally you may need to temporarily set a field as required or
not-required for a specific validation operation. This requirement is referred
to as the toggle function. The toggle function is enacted by prefixing a field
name with a plus or minus sign (+|-) when passed to the validate method:
use Validation::Class::Simple;
my $rules = Validation::Class::Simple->new(fields => {...});
# meaning, email is always required to have a value
# however password and password2 can be submitted as empty strings
# but if password and password2 have values they will be validated
$rules->validate('+email', '-password', '-password2');
Here are a few examples and explanations of using the validate method:
use Validation::Class::Simple;
my $rules = Validation::Class::Simple->new(fields => {...});
unless ($rules->validate) {
# validate all fields with matching parameters
}
unless ($rules->validate) {
# validate all fields because no parameters were submitted
}
unless ($rules->validate(qr/^email/)) {
# validate all fields whose name being with email
# e.g. email, email2, email_update
}
unless ($rules->validate('login', 'password')) {
# validate the login and password specifically
# regardless of what parameters have been set
}
unless ($rules->validate({ user => 'login', pass => 'password' })) {
# map user and pass parameters to the appropriate fields as aliases
# and validate login and password fields using the aliases
}
=head1 BUILDING CLASSES
This recipe displays the usage of keywords to configure a validation class.
=head2 Problem
You want to know how to use the L<Validation::Class> keywords to define a
validation class.
=head2 Solution
Use the keywords exported by L<Validation::Class> to register validation rules,
templates, profiles, methods and filters.
=head2 Discussion
Your validation class can be thought of as your data-model/input-firewall. The
benefits this approach provides might require you to change your perspective
on parameter handling and workflow. Typically when designing an application we
tend to name parameters arbitrarily and validate the same data at various stages
during a program's execution in various places in the application stack. This
approach is inefficient and prone to bugs and security problems.
To get the most out of Validation::Class you should consider each parameter
hitting your application (individually) as a transmission fitting a very specific
criteria, yes, like a field in a data model.
Your validation rules will act as filters which will reject or accept and
format the transmission for use within your application, yes, almost exactly
like a firewall.
A validation class is defined as follows:
package MyApp::Person;
use Validation::Class;
# a validation rule template
mixin 'basic' => {
required => 1,
min_length => 1,
max_length => 255,
filters => ['lowercase', 'alphanumeric']
};
# a validation rule
field 'login' => {
mixin => 'basic',
label => 'user login',
error => 'login invalid',
validation => sub {
my ($self, $field, $params) = @_;
return $field->value eq 'admin' ? 1 : 0;
}
};
# a validation rule
field 'password' => {
mixin => 'basic',
label => 'user password',
error => 'password invalid',
validation => sub {
my ($self, $field, $params) = @_;
return $field->value eq 'pass' ? 1 : 0;
}
};
# a validation profile
profile 'registration' => sub {
my ($self, @args) = @_;
return $self->validate(qw(login password));
};
# an auto-validating method
method 'registers' => {
input => 'registration',
using => sub {
my ($self, @args) = shift;
# ... do something
}
};
1;
The fields defined will be used to validate the specified input parameters.
You specify the input parameters at/after instantiation, parameters should take
the form of a hashref of key/value pairs passed to the params attribute, or
attribute/value pairs. The following is an example on using your validate class
to validate input in various scenarios:
# web app
package MyApp;
use MyApp::User;
use Misc::WebAppFramework;
get '/auth' => sub {
# get user input parameters
my $params = shift;
# initialize validation class and set input parameters
my $user = MyApp::User->new(params => $params);
unless ($user->registers) {
# print errors to browser unless validation is successful
return $user->errors_to_string;
}
return 'you have authenticated';
};
A field can have aliases, parameter names that if detected will be mapped to
the parameter name matching the field definition. Multiple fields cannot have
the same alias defined, such a configuration would result in a runtime error.
use MyApp::User;
my $user = MyApp::User->new(params => $params);
unless ($user->validate) {
return $input->errors_to_string;
}
package MyApp::User;
field 'email' => {
...,
alias => [
'emails',
'email_address',
'email_addresses'
]
};
package main;
use MyApp::User;
my $user = MyApp::User->new(params => { email_address => '...' });
unless ($user->validate('email'){
return $user->errors_to_string;
}
# valid because email_address is an alias on the email field
=head1 INTEGRATING CLASSES AND FRAMEWORKS
This recipe displays methods of configuring your validation class to cooperate
with your pre-existing classes and object-system.
=head2 Problem
You want to know how to configure L<Validation::Class> to cooperate with
pre-existing classes or object systems like L<Mo>, L<Moo>, L<Mouse>, and L<Moose>.
=head2 Solution
Use a combination of techniques such as excluding keywords exported by
L<Validation::Class> and utilizing the initialize_validator method.
=head2 Discussion
L<Validation::Class> will atuomatically inject a method name
`initialize_validator` if a pre-existing `new` method is dicovered which allows
you to execute certain validation class normalization routines. When, the
initialize_validator method is called is not important, it is only important
that it is called before your object is used as a validation class object.
A validation class using Moose as an object system could be configured as follows:
package MyApp::Person;
use Moose;
use Validation::Class qw(fld mxn);
# the order in which these frameworks are used is important
# loading Moose first ensures that the Moose::Object constructor
# has precendence
sub BUILD {
my ($self, $params) = @_;
$self->initialize_validator($params);
}
mxn 'basic' => {
required => 1,
min_length => 1,
max_length => 255,
filters => ['lowercase', 'alphanumeric']
};
fld 'login' => {
mixin => 'basic',
label => 'user login',
error => 'login invalid'
};
fld 'password' => {
mixin => 'basic',
label => 'user password',
error => 'password invalid'
};
has 'profile' => (
is => 'rw',
isa => 'MyApp::Person::Profile'
);
1;
=head1 FILTERING DATA
This recipe describes how to define filtering in your validation class rules.
=head2 Problem
You want to know how to define filters to sanatize and transform your data
although some transformations may need to occur after a successful validation.
=head2 Solution
Data validation rules can be configured to apply filtering as both pre-and-post
processing operations.
=head2 Discussion
Validation::Class supports pre/post filtering but is configured to pre-filter
incoming data by default. This means that based upon the filtering options
supplied within the individual fields, filtering will happen before validation
(technically at instantiation and again just before validation). As expected,
this is configurable via the filtering attribute.
A WORD OF CAUTION: Validation::Class is configured to pre-filter incoming data
which boosts application security and is best used with passive filtering
(e.g. converting character case - filtering which only alters the input in
predictable ways), versus aggressive filtering (e.g. formatting a telephone
number) which completely and permanently changes the incoming data ... so much
so that if the validation still fails ... errors that are reported may not
match the data that was submitted.
If you're sure you'd rather employ aggressive filtering, I suggest setting
the filtering attribute to 'post' for post-filtering or setting it to null
and applying the filters manually by calling the apply_filters() method.
=head1 DELEGATING VALIDATION
This recipe describes how to separate validation logic between multiple related
classes.
=head2 Problem
You want to know how to define multiple validation classes and pass input
data and input parameters between them.
=head2 Solution
Use classes as validation domains, as a space to logically group related
validation rules, then use built-in methods to have multiple validation classes
validate in-concert.
=head2 Discussion
For larger applications where a single validation class might become cluttered
and inefficient, Validation::Class comes equipped to help you separate your
validation rules into separate classes.
The idea is that you'll end up with a main validation class (most likely empty)
that will simply serve as your point of entry into your relative (child)
classes. The following is an example of this:
package MyApp::User;
use Validation::Class;
field name => { ... };
field email => { ... };
field login => { ... };
field password => { ... };
package MyApp::Profile;
use Validation::Class;
field age => { ... };
field sex => { ... };
field birthday => { ... };
package MyApp;
use Validation::Class;
set classes => 1;
package main;
my $input = MyApp->new(params => $params);
my $user = $input->class('user');
my $profile = $input->class('profile');
1;
=head1 INTROSPECT AND EXTEND
This recipe describes how to peek under the curtain and leverage the framework
for other purposes.
=head2 Problem
You want to know how to use your data validation classes to perform other tasks
programatically (e.g. generate documentation, etc).
=head2 Solution
By using the prototype class associated with your validation class you can
introspect it's configuration and perform additional tasks programatically.
=head2 Discussion
Most users will never venture beyond the public API, but powerful abilities
await the more adventureous developer and this section was written specifically
for you. To assist you on along your journey, let me explain exactly what
happens when you define and instantiate a validation class.
Classes are defined using keywords (field, mixin, filter, etc) which register
rule definitions on a cached class profile (of-sorts) associated with the class
which is being constructed. On instantiation, the cached class profile is cloned
then merged with any arguments provided to the constructor, this means that even
in a persistent environment the original class profile is never altered.
To begin introspection, simply look into the attributes attached to the class
prototype, e.g. fields, mixins, filters, etc., the following examples will give
you an idea of how to use introspection to extend your application code using
Validation::Class.
Please keep in mind that Validation::Class is likely to already have most of the
functionalty you would need to introspect your codebase. The following is an
introspection design template that will work in most cases:
package MyApp::Introspect;
use Validation::Class;
load classes => 'MyApp'; # load MyApp and all child classes
sub per_class {
my ($self, $code) = @_;
my %relatives = %{$self->proto->settings->{relatives}};
while (my($parent, $children) = each(%relatives)) {
while (my($nickname, $namespace) = each(%{$children})) {
# do something with each class
$code->($namespace);
}
}
}
sub per_field_per_class {
my ($self, $code) = @_;
$self->per_class(sub{
my $namespace = shift;
my $class = $namespace->new;
foreach my $field ($class->fields->values) {
# do something with each field in each class
$code->($class, $class->fields->{$field});
}
});
}
=head1 CLIENT-SIDE VALIDATION
This recipe describes how to generate JSON objects which can be used to validate
user input in the web-browser (client-side).
=head2 Problem
You want to know how to make the most out of your data validation rules by
making your configuration available as JSON objects in the browser.
=head2 Solution
Using introspection, you can leverage the prototype class associated with your
validation class to generate JSON objects based on your validation class
configuration.
=head2 Discussion
In the context of a web-application, it is often best to perform the initial
input validation on the client (web-browser) before submitting data to the
server for further validation and processing. In the following code we will
generate javascript objects that match our Validation::Class data models which
we will then use with some js library to validate form data, etc.
... example validation class
package MyApp::Model;
use Validation::Class;
use Validation::Class::Plugin::JavascriptObjects;
mxn scrub => {
filters => ['trim', 'strip']
};
fld login => {
mixin => 'scrub'
email => 1,
required => 1,
alias => 'user',
};
fld password => {
mixin => 'scrub',
required => 1,
alias => 'pass',
min_length => 5,
min_symbols => 1,
min_alpha => 1,
min_digits => 1
};
... in your webapp controller
get '/js/model' => sub {
my $model = MyApp::Model->new;
# generate the JS object
my $data = $model->plugin('javascript_objects')->render(
namespace => 'validate.model',
fields => [qw/email password/],
include => [qw/required email minlength maxlength/]
)
return print $data;
};
The output of the /js/model route should generate a javascript object which
looks similar to the following:
var validate = {
"model" : {
"email" : {
"minlength" : 3,
"required" : 1,
"maxlength" : 255
},
"password" : {
"minlength" : 5,
"required" : 1,
"maxlength" : 255
}
}
};
If its not obvious yet, we can now easily use this generated javascript API with
jQuery (or other client-side library) to validate form data, etc.
<!DOCTYPE html>
<html>
<head>
<title>AUTH REQUIRED</title>
<script type="text/javascript" src="/js/jquery.js"></script>
<script type="text/javascript" src="/js/jquery.validate.js"></script>
<script type="text/javascript" src="/js/model"></script>
<script type="text/javascript">
$(document).ready(function() {
$("#form").validate({rules:validate.model});
});
</script>
</head>
<body>
<div>[% input.errors_to_string %]</div>
<form id="form" autocomplete="off" method="post" action="/">
<fieldset>
<legend><h2><strong>Halt</strong>, who goes there?</h2></legend>
<label for="email">Email</label><br/>
<input id="email" name="email" value="" /><br/>
<label for="password">Password</label><br/>
<input id="password" name="password" type="password" /><br/>
<br/><input type="submit" value="Submit" />
</fieldset>
</form>
</body>
</html>
=head1 AUTHOR
Al Newkirk <anewkirk@ana.io>
=head1 COPYRIGHT AND LICENSE
This software is copyright (c) 2011 by Al Newkirk.
This is free software; you can redistribute it and/or modify it under
the same terms as the Perl 5 programming language system itself.
=cut