NAME¶
MooseX::Types::Structured - Structured Type Constraints for Moose
VERSION¶
version 0.30
SYNOPSIS¶
The following is example usage for this module.
package Person;
use Moose;
use MooseX::Types::Moose qw(Str Int HashRef);
use MooseX::Types::Structured qw(Dict Tuple Optional);
## A name has a first and last part, but middle names are not required
has name => (
isa=>Dict[
first => Str,
last => Str,
middle => Optional[Str],
],
);
## description is a string field followed by a HashRef of tagged data.
has description => (
isa=>Tuple[
Str,
Optional[HashRef],
],
);
## Remainder of your class attributes and methods
Then you can instantiate this class with something like:
my $john = Person->new(
name => {
first => 'John',
middle => 'James'
last => 'Napiorkowski',
},
description => [
'A cool guy who loves Perl and Moose.', {
married_to => 'Vanessa Li',
born_in => 'USA',
};
]
);
Or with:
my $vanessa = Person->new(
name => {
first => 'Vanessa',
last => 'Li'
},
description => ['A great student!'],
);
But all of these would cause a constraint error for the "name"
attribute:
## Value for 'name' not a HashRef
Person->new( name => 'John' );
## Value for 'name' has incorrect hash key and missing required keys
Person->new( name => {
first_name => 'John'
});
## Also incorrect keys
Person->new( name => {
first_name => 'John',
age => 39,
});
## key 'middle' incorrect type, should be a Str not a ArrayRef
Person->new( name => {
first => 'Vanessa',
middle => [1,2],
last => 'Li',
});
And these would cause a constraint error for the "description"
attribute:
## Should be an ArrayRef
Person->new( description => 'Hello I am a String' );
## First element must be a string not a HashRef.
Person->new (description => [{
tag1 => 'value1',
tag2 => 'value2'
}]);
Please see the test cases for more examples.
DESCRIPTION¶
A structured type constraint is a standard container Moose type constraint, such
as an "ArrayRef" or "HashRef", which has been enhanced to
allow you to explicitly name all the allowed type constraints inside the
structure. The generalized form is:
TypeConstraint[@TypeParameters or %TypeParameters]
Where "TypeParameters" is an array reference or hash references of
Moose::Meta::TypeConstraint objects.
This type library enables structured type constraints. It is built on top of the
MooseX::Types library system, so you should review the documentation for that
if you are not familiar with it.
Comparing Parameterized types to Structured types¶
Parameterized constraints are built into core Moose and you are probably already
familiar with the type constraints "HashRef" and
"ArrayRef". Structured types have similar functionality, so their
syntax is likewise similar. For example, you could define a parameterized
constraint like:
subtype ArrayOfInts,
as ArrayRef[Int];
which would constrain a value to something like [1,2,3,...] and so on. On the
other hand, a structured type constraint explicitly names all it's allowed
'internal' type parameter constraints. For the example:
subtype StringFollowedByInt,
as Tuple[Str,Int];
would constrain its value to things like "['hello', 111]" but
"['hello', 'world']" would fail, as well as "['hello', 111,
'world']" and so on. Here's another example:
package MyApp::Types;
use MooseX::Types -declare [qw(StringIntOptionalHashRef)];
use MooseX::Types::Moose qw(Str Int);
use MooseX::Types::Structured qw(Tuple Optional);
subtype StringIntOptionalHashRef,
as Tuple[
Str, Int,
Optional[HashRef]
];
This defines a type constraint that validates values like:
['Hello', 100, {key1 => 'value1', key2 => 'value2'}];
['World', 200];
Notice that the last type constraint in the structure is optional. This is
enabled via the helper "Optional" type constraint, which is a
variation of the core Moose type constraint "Maybe". The main
difference is that "Optional" type constraints are required to
validate if they exist, while "Maybe" permits undefined values. So
the following example would not validate:
StringIntOptionalHashRef->validate(['Hello Undefined', 1000, undef]);
Please note the subtle difference between undefined and null. If you wish to
allow both null and undefined, you should use the core Moose "Maybe"
type constraint instead:
package MyApp::Types;
use MooseX::Types -declare [qw(StringIntMaybeHashRef)];
use MooseX::Types::Moose qw(Str Int Maybe);
use MooseX::Types::Structured qw(Tuple);
subtype StringIntMaybeHashRef,
as Tuple[
Str, Int, Maybe[HashRef]
];
This would validate the following:
['Hello', 100, {key1 => 'value1', key2 => 'value2'}];
['World', 200, undef];
['World', 200];
Structured constraints are not limited to arrays. You can define a structure
against a "HashRef" with the "Dict" type constraint as in
this example:
subtype FirstNameLastName,
as Dict[
firstname => Str,
lastname => Str,
];
This would constrain a "HashRef" that validates something like:
{firstname => 'Christopher', lastname => 'Parsons'};
but all the following would fail validation:
## Incorrect keys
{first => 'Christopher', last => 'Parsons'};
## Too many keys
{firstname => 'Christopher', lastname => 'Parsons', middlename => 'Allen'};
## Not a HashRef
['Christopher', 'Parsons'];
These structures can be as simple or elaborate as you wish. You can even combine
various structured, parameterized and simple constraints all together:
subtype Crazy,
as Tuple[
Int,
Dict[name=>Str, age=>Int],
ArrayRef[Int]
];
Which would match:
[1, {name=>'John', age=>25},[10,11,12]];
Please notice how the type parameters can be visually arranged to your liking
and to improve the clarity of your meaning. You don't need to run then
altogether onto a single line. Additionally, since the "Dict" type
constraint defines a hash constraint, the key order is not meaningful. For
example:
subtype AnyKeyOrder,
as Dict[
key1=>Int,
key2=>Str,
key3=>Int,
];
Would validate both:
{key1 => 1, key2 => "Hi!", key3 => 2};
{key2 => "Hi!", key1 => 100, key3 => 300};
As you would expect, since underneath it's just a plain old Perl hash at work.
Alternatives¶
You should exercise some care as to whether or not your complex structured
constraints would be better off contained by a real object as in the following
example:
package MyApp::MyStruct;
use Moose;
## lazy way to make a bunch of attributes
has $_ for qw(full_name age_in_years);
package MyApp::MyClass;
use Moose;
has person => (isa => 'MyApp::MyStruct');
my $instance = MyApp::MyClass->new(
person=>MyApp::MyStruct->new(
full_name => 'John',
age_in_years => 39,
),
);
This method may take some additional time to set up but will give you more
flexibility. However, structured constraints are highly compatible with this
method, granting some interesting possibilities for coercion. Try:
package MyApp::MyClass;
use Moose;
use MyApp::MyStruct;
## It's recommended your type declarations live in a separate class in order
## to promote reusability and clarity. Inlined here for brevity.
use MooseX::Types::DateTime qw(DateTime);
use MooseX::Types -declare [qw(MyStruct)];
use MooseX::Types::Moose qw(Str Int);
use MooseX::Types::Structured qw(Dict);
## Use class_type to create an ISA type constraint if your object doesn't
## inherit from Moose::Object.
class_type 'MyApp::MyStruct';
## Just a shorter version really.
subtype MyStruct,
as 'MyApp::MyStruct';
## Add the coercions.
coerce MyStruct,
from Dict[
full_name=>Str,
age_in_years=>Int
], via {
MyApp::MyStruct->new(%$_);
},
from Dict[
lastname=>Str,
firstname=>Str,
dob=>DateTime
], via {
my $name = $_->{firstname} .' '. $_->{lastname};
my $age = DateTime->now - $_->{dob};
MyApp::MyStruct->new(
full_name=>$name,
age_in_years=>$age->years,
);
};
has person => (isa=>MyStruct);
This would allow you to instantiate with something like:
my $obj = MyApp::MyClass->new( person => {
full_name=>'John Napiorkowski',
age_in_years=>39,
});
Or even:
my $obj = MyApp::MyClass->new( person => {
lastname=>'John',
firstname=>'Napiorkowski',
dob=>DateTime->new(year=>1969),
});
If you are not familiar with how coercions work, check out the Moose cookbook
entry Moose::Cookbook::Recipe5 for an explanation. The section
"Coercions" has additional examples and discussion.
Subtyping a Structured type constraint¶
You need to exercise some care when you try to subtype a structured type as in
this example:
subtype Person,
as Dict[name => Str];
subtype FriendlyPerson,
as Person[
name => Str,
total_friends => Int,
];
This will actually work BUT you have to take care that the subtype has a
structure that does not contradict the structure of it's parent. For now the
above works, but I will clarify the syntax for this at a future point, so it's
recommended to avoid (should not really be needed so much anyway). For now
this is supported in an EXPERIMENTAL way. Your thoughts, test cases and
patches are welcomed for discussion. If you find a good use for this, please
let me know.
Coercions¶
Coercions currently work for 'one level' deep. That is you can do:
subtype Person,
as Dict[
name => Str,
age => Int
];
subtype Fullname,
as Dict[
first => Str,
last => Str
];
coerce Person,
## Coerce an object of a particular class
from BlessedPersonObject, via {
+{
name=>$_->name,
age=>$_->age,
};
},
## Coerce from [$name, $age]
from ArrayRef, via {
+{
name=>$_->[0],
age=>$_->[1],
},
},
## Coerce from {fullname=>{first=>...,last=>...}, dob=>$DateTimeObject}
from Dict[fullname=>Fullname, dob=>DateTime], via {
my $age = $_->dob - DateTime->now;
my $firstn = $_->{fullname}->{first};
my $lastn = $_->{fullname}->{last}
+{
name => $_->{fullname}->{first} .' '. ,
age =>$age->years
}
};
And that should just work as expected. However, if there are any 'inner'
coercions, such as a coercion on "Fullname" or on
"DateTime", that coercion won't currently get activated.
Please see the test
07-coerce.t for a more detailed example. Discussion
on extending coercions to support this welcome on the Moose development
channel or mailing list.
Recursion¶
Newer versions of MooseX::Types support recursive type constraints. That is you
can include a type constraint as a contained type constraint of itself. For
example:
subtype Person,
as Dict[
name=>Str,
friends=>Optional[
ArrayRef[Person]
],
];
This would declare a "Person" subtype that contains a name and an
optional "ArrayRef" of "Person"s who are friends as in:
{
name => 'Mike',
friends => [
{ name => 'John' },
{ name => 'Vincent' },
{
name => 'Tracey',
friends => [
{ name => 'Stephenie' },
{ name => 'Ilya' },
],
},
],
};
Please take care to make sure the recursion node is either "Optional",
or declare a union with an non-recursive option such as:
subtype Value
as Tuple[
Str,
Str|Tuple,
];
Which validates:
[
'Hello', [
'World', [
'Is', [
'Getting',
'Old',
],
],
],
];
Otherwise you will define a subtype that is impossible to validate since it is
infinitely recursive. For more information about defining recursive types,
please see the documentation in MooseX::Types and the test cases.
TYPE CONSTRAINTS¶
This type library defines the following constraints.
Tuple[@constraints]¶
This defines an ArrayRef based constraint which allows you to validate a
specific list of contained constraints. For example:
Tuple[Int,Str]; ## Validates [1,'hello']
Tuple[Str|Object, Int]; ## Validates ['hello', 1] or [$object, 2]
The Values of @constraints should ideally be MooseX::Types declared type
constraints. We do support 'old style' Moose string based constraints to a
limited degree but these string type constraints are considered deprecated.
There will be limited support for bugs resulting from mixing string and
MooseX::Types in your structures. If you encounter such a bug and really need
it fixed, we will required a detailed test case at the minimum.
Dict[%constraints]¶
This defines a HashRef based constraint which allowed you to validate a specific
hashref. For example:
Dict[name=>Str, age=>Int]; ## Validates {name=>'John', age=>39}
The keys in %constraints follow the same rules as @constraints in the above
section.
Map[ $key_constraint, $value_constraint ]¶
This defines a "HashRef"-based constraint in which both the keys and
values are required to meet certain constraints. For example, to map hostnames
to IP addresses, you might say:
Map[ HostName, IPAddress ]
The type constraint would only be met if every key was a valid
"HostName" and every value was a valid "IPAddress".
Optional[$constraint]¶
This is primarily a helper constraint for "Dict" and "Tuple"
type constraints. What this allows is for you to assert that a given type
constraint is allowed to be null (but NOT undefined). If the value is null,
then the type constraint passes but if the value is defined it must validate
against the type constraint. This makes it easy to make a Dict where one or
more of the keys doesn't have to exist or a tuple where some of the values are
not required. For example:
subtype Name() => as Dict[
first=>Str,
last=>Str,
middle=>Optional[Str],
];
...creates a constraint that validates against a hashref with the keys 'first'
and 'last' being strings and required while an optional key 'middle' is must
be a string if it appears but doesn't have to appear. So in this case both the
following are valid:
{first=>'John', middle=>'James', last=>'Napiorkowski'}
{first=>'Vanessa', last=>'Li'}
If you use the "Maybe" type constraint instead, your values will also
validate against "undef", which may be incorrect for you.
EXPORTABLE SUBROUTINES¶
This type library makes available for export the following subroutines
slurpy¶
Structured type constraints by their nature are closed; that is validation will
depend on an exact match between your structure definition and the arguments
to be checked. Sometimes you might wish for a slightly looser amount of
validation. For example, you may wish to validate the first 3 elements of an
array reference and allow for an arbitrary number of additional elements. At
first thought you might think you could do it this way:
# I want to validate stuff like: [1,"hello", $obj, 2,3,4,5,6,...]
subtype AllowTailingArgs,
as Tuple[
Int,
Str,
Object,
ArrayRef[Int],
];
However what this will actually validate are structures like this:
[10,"Hello", $obj, [11,12,13,...] ]; # Notice element 4 is an ArrayRef
In order to allow structured validation of, "and then some",
arguments, you can use the "slurpy" method against a type
constraint. For example:
use MooseX::Types::Structured qw(Tuple slurpy);
subtype AllowTailingArgs,
as Tuple[
Int,
Str,
Object,
slurpy ArrayRef[Int],
];
This will now work as expected, validating ArrayRef structures such as:
[1,"hello", $obj, 2,3,4,5,6,...]
A few caveats apply. First, the slurpy type constraint must be the last one in
the list of type constraint parameters. Second, the parent type of the slurpy
type constraint must match that of the containing type constraint. That means
that a "Tuple" can allow a slurpy "ArrayRef" (or children
of "ArrayRef"s, including another "Tuple") and a
"Dict" can allow a slurpy "HashRef" (or children/subtypes
of HashRef, also including other "Dict" constraints).
Please note the technical way this works 'under the hood' is that the slurpy
keyword transforms the target type constraint into a coderef. Please do not
try to create your own custom coderefs; always use the slurpy method. The
underlying technology may change in the future but the slurpy keyword will be
supported.
ERROR MESSAGES¶
Error reporting has been improved to return more useful debugging messages. Now
I will stringify the incoming check value with Devel::PartialDump so that you
can see the actual structure that is tripping up validation. Also, I report
the 'internal' validation error, so that if a particular element inside the
Structured Type is failing validation, you will see that. There's a limit to
how deep this internal reporting goes, but you shouldn't see any of the
"failed with ARRAY(XXXXXX)" that we got with earlier versions of
this module.
This support is continuing to expand, so it's best to use these messages for
debugging purposes and not for creating messages that 'escape into the wild'
such as error messages sent to the user.
Please see the test '12-error.t' for a more lengthy example. Your thoughts and
preferable tests or code patches very welcome!
EXAMPLES¶
Here are some additional example usage for structured types. All examples can be
found also in the 't/examples.t' test. Your contributions are also welcomed.
Normalize a HashRef¶
You need a hashref to conform to a canonical structure but are required accept a
bunch of different incoming structures. You can normalize using the
"Dict" type constraint and coercions. This example also shows
structured types mixed which other MooseX::Types libraries.
package Test::MooseX::Meta::TypeConstraint::Structured::Examples::Normalize;
use Moose;
use DateTime;
use MooseX::Types::Structured qw(Dict Tuple);
use MooseX::Types::DateTime qw(DateTime);
use MooseX::Types::Moose qw(Int Str Object);
use MooseX::Types -declare => [qw(Name Age Person)];
subtype Person,
as Dict[
name=>Str,
age=>Int,
];
coerce Person,
from Dict[
first=>Str,
last=>Str,
years=>Int,
], via { +{
name => "$_->{first} $_->{last}",
age => $_->{years},
}},
from Dict[
fullname=>Dict[
last=>Str,
first=>Str,
],
dob=>DateTime,
],
## DateTime needs to be inside of single quotes here to disambiguate the
## class package from the DataTime type constraint imported via the
## line "use MooseX::Types::DateTime qw(DateTime);"
via { +{
name => "$_->{fullname}{first} $_->{fullname}{last}",
age => ($_->{dob} - 'DateTime'->now)->years,
}};
has person => (is=>'rw', isa=>Person, coerce=>1);
And now you can instantiate with all the following:
__PACKAGE__->new(
person=>{
name=>'John Napiorkowski',
age=>39,
},
);
__PACKAGE__->new(
person=>{
first=>'John',
last=>'Napiorkowski',
years=>39,
},
);
__PACKAGE__->new(
person=>{
fullname => {
first=>'John',
last=>'Napiorkowski'
},
dob => 'DateTime'->new(
year=>1969,
month=>2,
day=>13
),
},
);
This technique is a way to support various ways to instantiate your class in a
clean and declarative way.
SEE ALSO¶
The following modules or resources may be of interest.
Moose, MooseX::Types, Moose::Meta::TypeConstraint,
MooseX::Meta::TypeConstraint::Structured
AUTHORS¶
- •
- John Napiorkowski <jjnapiork@cpan.org>
- •
- Florian Ragwitz <rafl@debian.org>
- •
- XXXX XXX'XX (Yuval Kogman) <nothingmuch@woobling.org>
- •
- Tomas (t0m) Doran <bobtfish@bobtfish.net>
- •
- Robert Sedlacek <rs@474.at>
COPYRIGHT AND LICENSE¶
This software is copyright (c) 2008 by John Napiorkowski.
This is free software; you can redistribute it and/or modify it under the same
terms as the Perl 5 programming language system itself.
CONTRIBUTORS¶
- •
- Ansgar Burchardt <ansgar@43-1.org>
- •
- Dave Rolsky <autarch@urth.org>
- •
- Jesse Luehrs <doy@tozt.net>
- •
- Karen Etheridge <ether@cpan.org>
- •
- Ricardo Signes <rjbs@cpan.org>
- •
- Robert 'phaylon' Sedlacek <rs@474.at>
- •
- Stevan Little <stevan.little@iinteractive.com>
- •
- arcanez <justin.d.hunter@gmail.com>