This file is indexed.

/usr/share/perl5/Validation/Class/Cookbook.pod is in libvalidation-class-perl 7.900054-1.

This file is owned by root:root, with mode 0o644.

The actual contents of the file can be viewed below.

  1
  2
  3
  4
  5
  6
  7
  8
  9
 10
 11
 12
 13
 14
 15
 16
 17
 18
 19
 20
 21
 22
 23
 24
 25
 26
 27
 28
 29
 30
 31
 32
 33
 34
 35
 36
 37
 38
 39
 40
 41
 42
 43
 44
 45
 46
 47
 48
 49
 50
 51
 52
 53
 54
 55
 56
 57
 58
 59
 60
 61
 62
 63
 64
 65
 66
 67
 68
 69
 70
 71
 72
 73
 74
 75
 76
 77
 78
 79
 80
 81
 82
 83
 84
 85
 86
 87
 88
 89
 90
 91
 92
 93
 94
 95
 96
 97
 98
 99
100
101
102
103
104
105
106
107
108
109
110
111
112
113
114
115
116
117
118
119
120
121
122
123
124
125
126
127
128
129
130
131
132
133
134
135
136
137
138
139
140
141
142
143
144
145
146
147
148
149
150
151
152
153
154
155
156
157
158
159
160
161
162
163
164
165
166
167
168
169
170
171
172
173
174
175
176
177
178
179
180
181
182
183
184
185
186
187
188
189
190
191
192
193
194
195
196
197
198
199
200
201
202
203
204
205
206
207
208
209
210
211
212
213
214
215
216
217
218
219
220
221
222
223
224
225
226
227
228
229
230
231
232
233
234
235
236
237
238
239
240
241
242
243
244
245
246
247
248
249
250
251
252
253
254
255
256
257
258
259
260
261
262
263
264
265
266
267
268
269
270
271
272
273
274
275
276
277
278
279
280
281
282
283
284
285
286
287
288
289
290
291
292
293
294
295
296
297
298
299
300
301
302
303
304
305
306
307
308
309
310
311
312
313
314
315
316
317
318
319
320
321
322
323
324
325
326
327
328
329
330
331
332
333
334
335
336
337
338
339
340
341
342
343
344
345
346
347
348
349
350
351
352
353
354
355
356
357
358
359
360
361
362
363
364
365
366
367
368
369
370
371
372
373
374
375
376
377
378
379
380
381
382
383
384
385
386
387
388
389
390
391
392
393
394
395
396
397
398
399
400
401
402
403
404
405
406
407
408
409
410
411
412
413
414
415
416
417
418
419
420
421
422
423
424
425
426
427
428
429
430
431
432
433
434
435
436
437
438
439
440
441
442
443
444
445
446
447
448
449
450
451
452
453
454
455
456
457
458
459
460
461
462
463
464
465
466
467
468
469
470
471
472
473
474
475
476
477
478
479
480
481
482
483
484
485
486
487
488
489
490
491
492
493
494
495
496
497
498
499
500
501
502
503
504
505
506
507
508
509
510
511
512
513
514
515
516
517
518
519
520
521
522
523
524
525
526
527
528
529
530
531
532
533
534
535
536
537
538
539
540
541
542
543
544
545
546
547
548
549
550
551
552
553
554
555
556
557
558
559
560
561
562
563
564
565
566
567
568
569
570
571
572
573
574
575
576
577
578
579
580
581
582
583
584
585
586
587
588
589
590
591
592
593
594
595
596
597
598
599
600
601
602
603
604
605
606
607
608
609
610
611
612
613
614
615
616
617
618
619
620
621
622
623
624
625
626
627
628
629
630
631
632
633
634
635
636
637
638
639
640
641
642
643
644
645
646
647
648
649
650
651
652
653
654
655
656
657
658
659
660
661
662
663
664
665
666
667
668
669
670
671
672
673
674
675
676
677
678
679
680
681
682
683
684
685
686
687
688
689
690
691
692
693
694
695
696
697
698
699
700
701
702
703
704
705
706
707
708
709
710
711
712
713
714
715
716
717
718
719
720
721
722
723
724
725
726
727
728
729
730
731
732
733
734
735
736
737
738
739
740
741
742
743
744
745
746
747
748
749
750
751
752
753
754
755
756
757
758
759
760
761
762
763
764
765
766
767
768
769
770
771
772
773
774
775
776
777
778
779
780
781
782
783
784
785
786
787
788
789
790
791
792
793
794
795
796
797
798
799
800
801
802
803
804
805
806
807
808
809
810
811
812
813
814
815
816
817
818
819
820
821
822
823
824
825
826
827
828
829
830
831
832
833
834
835
836
837
838
839
840
841
842
843
844
845
846
847
848
849
850
851
852
853
854
855
856
857
858
859
860
861
862
863
864
865
866
867
868
# PODNAME: Validation::Class::Cookbook
# ABSTRACT: Recipes for Validation::Class

# VERSION

__END__

=pod

=head1 NAME

Validation::Class::Cookbook - Recipes for Validation::Class

=head1 VERSION

version 7.900054

=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 precedence

    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