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DBIx::Class::Manual::Cookbook(3)     User Contributed Perl Documentation    DBIx::Class::Manual::Cookbook(3)



NAME
       DBIx::Class::Manual::Cookbook - Miscellaneous recipes

SEARCHING
   Paged results
       When you expect a large number of results, you can ask DBIx::Class for a paged resultset, which will
       fetch only a defined number of records at a time:

         my $rs = $schema->resultset('Artist')->search(
           undef,
           {
             page => 1,  # page to return (defaults to 1)
             rows => 10, # number of results per page
           },
         );

         return $rs->all(); # all records for page 1

         return $rs->page(2); # records for page 2

       You can get a Data::Page object for the resultset (suitable for use in e.g. a template) using the
       "pager" method:

         return $rs->pager();

   Complex WHERE clauses
       Sometimes you need to formulate a query using specific operators:

         my @albums = $schema->resultset('Album')->search({
           artist => { 'like', '%Lamb%' },
           title  => { 'like', '%Fear of Fours%' },
         });

       This results in something like the following "WHERE" clause:

         WHERE artist LIKE ? AND title LIKE ?

       And the following bind values for the placeholders: '%Lamb%', '%Fear of Fours%'.

       Other queries might require slightly more complex logic:

         my @albums = $schema->resultset('Album')->search({
           -or => [
             -and => [
               artist => { 'like', '%Smashing Pumpkins%' },
               title  => 'Siamese Dream',
             ],
             artist => 'Starchildren',
           ],
         });

       This results in the following "WHERE" clause:

         WHERE ( artist LIKE '%Smashing Pumpkins%' AND title = 'Siamese Dream' )
           OR artist = 'Starchildren'

       For more information on generating complex queries, see "WHERE CLAUSES" in SQL::Abstract.

   Retrieve one and only one row from a resultset
       Sometimes you need only the first "top" row of a resultset. While this can be easily done with
       $rs->first, it is suboptimal, as a full blown cursor for the resultset will be created and then
       immediately destroyed after fetching the first row object.  $rs->single is designed specifically for
       this case - it will grab the first returned result without even instantiating a cursor.

       Before replacing all your calls to "first()" with "single()" please observe the following CAVEATS:

       •   While single() takes a search condition just like search() does, it does _not_ accept search
           attributes. However one can always chain a single() to a search():

             my $top_cd = $cd_rs->search({}, { order_by => 'rating' })->single;

       •   Since single() is the engine behind find(), it is designed to fetch a single row per database
           query. Thus a warning will be issued when the underlying SELECT returns more than one row.
           Sometimes however this usage is valid: i.e. we have an arbitrary number of cd's but only one of
           them is at the top of the charts at any given time. If you know what you are doing, you can
           silence the warning by explicitly limiting the resultset size:

             my $top_cd = $cd_rs->search ({}, { order_by => 'rating', rows => 1 })->single;

   Arbitrary SQL through a custom ResultSource
       Sometimes you have to run arbitrary SQL because your query is too complex (e.g. it contains Unions,
       Sub-Selects, Stored Procedures, etc.) or has to be optimized for your database in a special way, but
       you still want to get the results as a DBIx::Class::ResultSet.

       This is accomplished by defining a ResultSource::View for your query, almost like you would define a
       regular ResultSource.

         package My::Schema::Result::UserFriendsComplex;
         use strict;
         use warnings;
         use base qw/DBIx::Class::Core/;

         __PACKAGE__->table_class('DBIx::Class::ResultSource::View');

         # ->table, ->add_columns, etc.

         # do not attempt to deploy() this view
         __PACKAGE__->result_source_instance->is_virtual(1);

         __PACKAGE__->result_source_instance->view_definition(q[
           SELECT u.* FROM user u
           INNER JOIN user_friends f ON u.id = f.user_id
           WHERE f.friend_user_id = ?
           UNION
           SELECT u.* FROM user u
           INNER JOIN user_friends f ON u.id = f.friend_user_id
           WHERE f.user_id = ?
         ]);

       Next, you can execute your complex query using bind parameters like this:

         my $friends = $schema->resultset( 'UserFriendsComplex' )->search( {},
           {
             bind  => [ 12345, 12345 ]
           }
         );

       ... and you'll get back a perfect DBIx::Class::ResultSet (except, of course, that you cannot modify
       the rows it contains, e.g. cannot call "update", "delete", ...  on it).

       Note that you cannot have bind parameters unless is_virtual is set to true.

       •   NOTE

           If you're using the old deprecated "$rsrc_instance->name(\'( SELECT ...')" method for custom SQL
           execution, you are highly encouraged to update your code to use a virtual view as above. If you
           do not want to change your code, and just want to suppress the deprecation warning when you call
           "deploy" in DBIx::Class::Schema, add this line to your source definition, so that "deploy" will
           exclude this "table":

             sub sqlt_deploy_hook { $_[1]->schema->drop_table ($_[1]) }

   Using specific columns
       When you only want specific columns from a table, you can use "columns" to specify which ones you
       need. This is useful to avoid loading columns with large amounts of data that you aren't about to use
       anyway:

         my $rs = $schema->resultset('Artist')->search(
           undef,
           {
             columns => [qw/ name /]
           }
         );

         # Equivalent SQL:
         # SELECT artist.name FROM artist

       This is a shortcut for "select" and "as", see below. "columns" cannot be used together with "select"
       and "as".

   Using database functions or stored procedures
       The combination of "select" and "as" can be used to return the result of a database function or
       stored procedure as a column value. You use "select" to specify the source for your column value
       (e.g. a column name, function, or stored procedure name). You then use "as" to set the column name
       you will use to access the returned value:

         my $rs = $schema->resultset('Artist')->search(
           {},
           {
             select => [ 'name', { LENGTH => 'name' } ],
             as     => [qw/ name name_length /],
           }
         );

         # Equivalent SQL:
         # SELECT name name, LENGTH( name )
         # FROM artist

       Note that the "as" attribute has absolutely nothing to do with the SQL syntax " SELECT foo AS bar "
       (see the documentation in "ATTRIBUTES" in DBIx::Class::ResultSet). You can control the "AS" part of
       the generated SQL via the "-as" field attribute as follows:

         my $rs = $schema->resultset('Artist')->search(
           {},
           {
             join => 'cds',
             distinct => 1,
             '+select' => [ { count => 'cds.cdid', -as => 'amount_of_cds' } ],
             '+as' => [qw/num_cds/],
             order_by => { -desc => 'amount_of_cds' },
           }
         );

         # Equivalent SQL
         # SELECT me.artistid, me.name, me.rank, me.charfield, COUNT( cds.cdid ) AS amount_of_cds
         #   FROM artist me LEFT JOIN cd cds ON cds.artist = me.artistid
         # GROUP BY me.artistid, me.name, me.rank, me.charfield
         # ORDER BY amount_of_cds DESC

       If your alias exists as a column in your base class (i.e. it was added with add_columns), you just
       access it as normal. Our "Artist" class has a "name" column, so we just use the "name" accessor:

         my $artist = $rs->first();
         my $name = $artist->name();

       If on the other hand the alias does not correspond to an existing column, you have to fetch the value
       using the "get_column" accessor:

         my $name_length = $artist->get_column('name_length');

       If you don't like using "get_column", you can always create an accessor for any of your aliases using
       either of these:

         # Define accessor manually:
         sub name_length { shift->get_column('name_length'); }

         # Or use DBIx::Class::AccessorGroup:
         __PACKAGE__->mk_group_accessors('column' => 'name_length');

       See also "Using SQL functions on the left hand side of a comparison".

   SELECT DISTINCT with multiple columns
         my $rs = $schema->resultset('Artist')->search(
           {},
           {
             columns => [ qw/artist_id name rank/ ],
             distinct => 1
           }
         );

         my $rs = $schema->resultset('Artist')->search(
           {},
           {
             columns => [ qw/artist_id name rank/ ],
             group_by => [ qw/artist_id name rank/ ],
           }
         );

         # Equivalent SQL:
         # SELECT me.artist_id, me.name, me.rank
         # FROM artist me
         # GROUP BY artist_id, name, rank

   SELECT COUNT(DISTINCT colname)
         my $rs = $schema->resultset('Artist')->search(
           {},
           {
             columns => [ qw/name/ ],
             distinct => 1
           }
         );

         my $rs = $schema->resultset('Artist')->search(
           {},
           {
             columns => [ qw/name/ ],
             group_by => [ qw/name/ ],
           }
         );

         my $count = $rs->count;

         # Equivalent SQL:
         # SELECT COUNT( * ) FROM (SELECT me.name FROM artist me GROUP BY me.name) me:

   Grouping results
       DBIx::Class supports "GROUP BY" as follows:

         my $rs = $schema->resultset('Artist')->search(
           {},
           {
             join     => [qw/ cds /],
             select   => [ 'name', { count => 'cds.id' } ],
             as       => [qw/ name cd_count /],
             group_by => [qw/ name /]
           }
         );

         # Equivalent SQL:
         # SELECT name, COUNT( cd.id ) FROM artist
         # LEFT JOIN cd ON artist.id = cd.artist
         # GROUP BY name

       Please see "ATTRIBUTES" in DBIx::Class::ResultSet documentation if you are in any way unsure about
       the use of the attributes above (" join ", " select ", " as " and " group_by ").

   Subqueries
       You can write subqueries relatively easily in DBIC.

         my $inside_rs = $schema->resultset('Artist')->search({
           name => [ 'Billy Joel', 'Brittany Spears' ],
         });

         my $rs = $schema->resultset('CD')->search({
           artist_id => { -in => $inside_rs->get_column('id')->as_query },
         });

       The usual operators ( '=', '!=', -in, -not_in, etc.) are supported.

       NOTE: You have to explicitly use '=' when doing an equality comparison.  The following will not work:

         my $rs = $schema->resultset('CD')->search({
           artist_id => $inside_rs->get_column('id')->as_query,  # does NOT work
         });

       Support

       Subqueries are supported in the where clause (first hashref), and in the from, select, and +select
       attributes.

       Correlated subqueries

         my $cdrs = $schema->resultset('CD');
         my $rs = $cdrs->search({
           year => {
             '=' => $cdrs->search(
               { artist_id => { '=' => { -ident => 'me.artist_id' } } },
               { alias => 'inner' }
             )->get_column('year')->max_rs->as_query,
           },
         });

       That creates the following SQL:

         SELECT me.cdid, me.artist, me.title, me.year, me.genreid, me.single_track
           FROM cd me
          WHERE year = (
             SELECT MAX(inner.year)
               FROM cd inner
              WHERE artist_id = me.artist_id
             )

   Predefined searches
       You can define frequently used searches as methods by subclassing DBIx::Class::ResultSet:

         package My::DBIC::ResultSet::CD;
         use strict;
         use warnings;
         use base 'DBIx::Class::ResultSet';

         sub search_cds_ordered {
             my ($self) = @_;

             return $self->search(
                 {},
                 { order_by => 'name DESC' },
             );
         }

         1;

       If you're using "load_namespaces" in DBIx::Class::Schema, simply place the file into the "ResultSet"
       directory next to your "Result" directory, and it will be automatically loaded.

       If however you are still using "load_classes" in DBIx::Class::Schema, first tell DBIx::Class to
       create an instance of the ResultSet class for you, in your My::DBIC::Schema::CD class:

         # class definition as normal
         use base 'DBIx::Class::Core';
         __PACKAGE__->table('cd');

         # tell DBIC to use the custom ResultSet class
         __PACKAGE__->resultset_class('My::DBIC::ResultSet::CD');

       Note that "resultset_class" must be called after "load_components" and "table", or you will get
       errors about missing methods.

       Then call your new method in your code:

          my $ordered_cds = $schema->resultset('CD')->search_cds_ordered();

   Using SQL functions on the left hand side of a comparison
       Using SQL functions on the left hand side of a comparison is generally not a good idea since it
       requires a scan of the entire table. (Unless your RDBMS supports indexes on expressions - including
       return values of functions - and you create an index on the return value of the function in
       question.) However, it can be accomplished with "DBIx::Class" when necessary by resorting to literal
       SQL:

         $rs->search(\[ 'YEAR(date_of_birth) = ?', [ plain_value => 1979 ] ]);

         # Equivalent SQL:
         # SELECT * FROM employee WHERE YEAR(date_of_birth) = ?

         $rs->search({ -and => [
           name => 'Bob',
           \[ 'YEAR(date_of_birth) = ?', [ plain_value => 1979 ] ],
         ]});

         # Equivalent SQL:
         # SELECT * FROM employee WHERE name = ? AND YEAR(date_of_birth) = ?

       Note: the "plain_value" string in the "[ plain_value => 1979 ]" part should be either the same as the
       name of the column (do this if the type of the return value of the function is the same as the type
       of the column) or in the case of a function it's currently treated as a dummy string (it is a good
       idea to use "plain_value" or something similar to convey intent). The value is currently only
       significant when handling special column types (BLOBs, arrays, etc.), but this may change in the
       future.

       See also "Literal SQL with placeholders and bind values (subqueries)" in SQL::Abstract.

JOINS AND PREFETCHING
   Using joins and prefetch
       You can use the "join" attribute to allow searching on, or sorting your results by, one or more
       columns in a related table.

       This requires that you have defined the DBIx::Class::Relationship. For example :

         My::Schema::CD->has_many( artists => 'My::Schema::Artist', 'artist_id');

       To return all CDs matching a particular artist name, you specify the name of the relationship
       ('artists'):

         my $rs = $schema->resultset('CD')->search(
           {
             'artists.name' => 'Bob Marley'
           },
           {
             join => 'artists', # join the artist table
           }
         );

         # Equivalent SQL:
         # SELECT cd.* FROM cd
         # JOIN artist ON cd.artist = artist.id
         # WHERE artist.name = 'Bob Marley'

       In that example both the join, and the condition use the relationship name rather than the table name
       (see DBIx::Class::Manual::Joining for more details on aliasing ).

       If required, you can now sort on any column in the related tables by including it in your "order_by"
       attribute, (again using the aliased relation name rather than table name) :

         my $rs = $schema->resultset('CD')->search(
           {
             'artists.name' => 'Bob Marley'
           },
           {
             join     => 'artists',
             order_by => [qw/ artists.name /]
           }
         );

         # Equivalent SQL:
         # SELECT cd.* FROM cd
         # JOIN artist ON cd.artist = artist.id
         # WHERE artist.name = 'Bob Marley'
         # ORDER BY artist.name

       Note that the "join" attribute should only be used when you need to search or sort using columns in a
       related table. Joining related tables when you only need columns from the main table will make
       performance worse!

       Now let's say you want to display a list of CDs, each with the name of the artist. The following will
       work fine:

         while (my $cd = $rs->next) {
           print "CD: " . $cd->title . ", Artist: " . $cd->artist->name;
         }

       There is a problem however. We have searched both the "cd" and "artist" tables in our main query, but
       we have only returned data from the "cd" table. To get the artist name for any of the CD objects
       returned, DBIx::Class will go back to the database:

         SELECT artist.* FROM artist WHERE artist.id = ?

       A statement like the one above will run for each and every CD returned by our main query. Five CDs,
       five extra queries. A hundred CDs, one hundred extra queries!

       Thankfully, DBIx::Class has a "prefetch" attribute to solve this problem.  This allows you to fetch
       results from related tables in advance:

         my $rs = $schema->resultset('CD')->search(
           {
             'artists.name' => 'Bob Marley'
           },
           {
             join     => 'artists',
             order_by => [qw/ artists.name /],
             prefetch => 'artists' # return artist data too!
           }
         );

         # Equivalent SQL (note SELECT from both "cd" and "artist"):
         # SELECT cd.*, artist.* FROM cd
         # JOIN artist ON cd.artist = artist.id
         # WHERE artist.name = 'Bob Marley'
         # ORDER BY artist.name

       The code to print the CD list remains the same:

         while (my $cd = $rs->next) {
           print "CD: " . $cd->title . ", Artist: " . $cd->artist->name;
         }

       DBIx::Class has now prefetched all matching data from the "artist" table, so no additional SQL
       statements are executed. You now have a much more efficient query.

       Also note that "prefetch" should only be used when you know you will definitely use data from a
       related table. Pre-fetching related tables when you only need columns from the main table will make
       performance worse!

   Multiple joins
       In the examples above, the "join" attribute was a scalar.  If you pass an array reference instead,
       you can join to multiple tables.  In this example, we want to limit the search further, using
       "LinerNotes":

         # Relationships defined elsewhere:
         # CD->belongs_to('artist' => 'Artist');
         # CD->has_one('liner_notes' => 'LinerNotes', 'cd');
         my $rs = $schema->resultset('CD')->search(
           {
             'artist.name' => 'Bob Marley'
             'liner_notes.notes' => { 'like', '%some text%' },
           },
           {
             join     => [qw/ artist liner_notes /],
             order_by => [qw/ artist.name /],
           }
         );

         # Equivalent SQL:
         # SELECT cd.*, artist.*, liner_notes.* FROM cd
         # JOIN artist ON cd.artist = artist.id
         # JOIN liner_notes ON cd.id = liner_notes.cd
         # WHERE artist.name = 'Bob Marley'
         # ORDER BY artist.name

   Multi-step joins
       Sometimes you want to join more than one relationship deep. In this example, we want to find all
       "Artist" objects who have "CD"s whose "LinerNotes" contain a specific string:

         # Relationships defined elsewhere:
         # Artist->has_many('cds' => 'CD', 'artist');
         # CD->has_one('liner_notes' => 'LinerNotes', 'cd');

         my $rs = $schema->resultset('Artist')->search(
           {
             'liner_notes.notes' => { 'like', '%some text%' },
           },
           {
             join => {
               'cds' => 'liner_notes'
             }
           }
         );

         # Equivalent SQL:
         # SELECT artist.* FROM artist
         # LEFT JOIN cd ON artist.id = cd.artist
         # LEFT JOIN liner_notes ON cd.id = liner_notes.cd
         # WHERE liner_notes.notes LIKE '%some text%'

       Joins can be nested to an arbitrary level. So if we decide later that we want to reduce the number of
       Artists returned based on who wrote the liner notes:

         # Relationship defined elsewhere:
         # LinerNotes->belongs_to('author' => 'Person');

         my $rs = $schema->resultset('Artist')->search(
           {
             'liner_notes.notes' => { 'like', '%some text%' },
             'author.name' => 'A. Writer'
           },
           {
             join => {
               'cds' => {
                 'liner_notes' => 'author'
               }
             }
           }
         );

         # Equivalent SQL:
         # SELECT artist.* FROM artist
         # LEFT JOIN cd ON artist.id = cd.artist
         # LEFT JOIN liner_notes ON cd.id = liner_notes.cd
         # LEFT JOIN author ON author.id = liner_notes.author
         # WHERE liner_notes.notes LIKE '%some text%'
         # AND author.name = 'A. Writer'

   Multi-step and multiple joins
       With various combinations of array and hash references, you can join tables in any combination you
       desire.  For example, to join Artist to CD and Concert, and join CD to LinerNotes:

         # Relationships defined elsewhere:
         # Artist->has_many('concerts' => 'Concert', 'artist');

         my $rs = $schema->resultset('Artist')->search(
           { },
           {
             join => [
               {
                 cds => 'liner_notes'
               },
               'concerts'
             ],
           }
         );

         # Equivalent SQL:
         # SELECT artist.* FROM artist
         # LEFT JOIN cd ON artist.id = cd.artist
         # LEFT JOIN liner_notes ON cd.id = liner_notes.cd
         # LEFT JOIN concert ON artist.id = concert.artist

   Multi-step prefetch
       "prefetch" can be nested more than one relationship deep using the same syntax as a multi-step join:

         my $rs = $schema->resultset('Tag')->search(
           {},
           {
             prefetch => {
               cd => 'artist'
             }
           }
         );

         # Equivalent SQL:
         # SELECT tag.*, cd.*, artist.* FROM tag
         # JOIN cd ON tag.cd = cd.id
         # JOIN artist ON cd.artist = artist.id

       Now accessing our "cd" and "artist" relationships does not need additional SQL statements:

         my $tag = $rs->first;
         print $tag->cd->artist->name;

ROW-LEVEL OPERATIONS
   Retrieving a row object's Schema
       It is possible to get a Schema object from a row object like so:

         my $schema = $cd->result_source->schema;
         # use the schema as normal:
         my $artist_rs = $schema->resultset('Artist');

       This can be useful when you don't want to pass around a Schema object to every method.

   Getting the value of the primary key for the last database insert
       AKA getting last_insert_id

       Thanks to the core component PK::Auto, this is straightforward:

         my $foo = $rs->create(\%blah);
         # do more stuff
         my $id = $foo->id; # foo->my_primary_key_field will also work.

       If you are not using autoincrementing primary keys, this will probably not work, but then you already
       know the value of the last primary key anyway.

   Stringification
       Employ the standard stringification technique by using the overload module.

       To make an object stringify itself as a single column, use something like this (replace "name" with
       the column/method of your choice):

         use overload '""' => sub { shift->name}, fallback => 1;

       For more complex stringification, you can use an anonymous subroutine:

         use overload '""' => sub { $_[0]->name . ", " .
                                    $_[0]->address }, fallback => 1;

       Stringification Example

       Suppose we have two tables: "Product" and "Category". The table specifications are:

         Product(id, Description, category)
         Category(id, Description)

       "category" is a foreign key into the Category table.

       If you have a Product object $obj and write something like

         print $obj->category

       things will not work as expected.

       To obtain, for example, the category description, you should add this method to the class defining
       the Category table:

         use overload "" => sub {
             my $self = shift;

             return $self->Description;
         }, fallback => 1;

   Want to know if find_or_create found or created a row?
       Just use "find_or_new" instead, then check "in_storage":

         my $obj = $rs->find_or_new({ blah => 'blarg' });
         unless ($obj->in_storage) {
           $obj->insert;
           # do whatever else you wanted if it was a new row
         }

   Static sub-classing DBIx::Class result classes
       AKA adding additional relationships/methods/etc. to a model for a specific usage of the (shared)
       model.

       Schema definition

           package My::App::Schema;

           use base 'DBIx::Class::Schema';

           # load subclassed classes from My::App::Schema::Result/ResultSet
           __PACKAGE__->load_namespaces;

           # load classes from shared model
           load_classes({
               'My::Shared::Model::Result' => [qw/
                   Foo
                   Bar
               /]});

           1;

       Result-Subclass definition

           package My::App::Schema::Result::Baz;

           use strict;
           use warnings;
           use base 'My::Shared::Model::Result::Baz';

           # WARNING: Make sure you call table() again in your subclass,
           # otherwise DBIx::Class::ResultSourceProxy::Table will not be called
           # and the class name is not correctly registered as a source
           __PACKAGE__->table('baz');

           sub additional_method {
               return "I'm an additional method only needed by this app";
           }

           1;

   Dynamic Sub-classing DBIx::Class proxy classes
       AKA multi-class object inflation from one table

       DBIx::Class classes are proxy classes, therefore some different techniques need to be employed for
       more than basic subclassing.  In this example we have a single user table that carries a boolean bit
       for admin.  We would like like to give the admin users objects (DBIx::Class::Row) the same methods as
       a regular user but also special admin only methods.  It doesn't make sense to create two separate
       proxy-class files for this.  We would be copying all the user methods into the Admin class.  There is
       a cleaner way to accomplish this.

       Overriding the "inflate_result" method within the User proxy-class gives us the effect we want.  This
       method is called by DBIx::Class::ResultSet when inflating a result from storage.  So we grab the
       object being returned, inspect the values we are looking for, bless it if it's an admin object, and
       then return it.  See the example below:

       Schema Definition

           package My::Schema;

           use base qw/DBIx::Class::Schema/;

           __PACKAGE__->load_namespaces;

           1;

       Proxy-Class definitions

           package My::Schema::Result::User;

           use strict;
           use warnings;
           use base qw/DBIx::Class::Core/;

           ### Define what our admin class is, for ensure_class_loaded()
           my $admin_class = __PACKAGE__ . '::Admin';

           __PACKAGE__->table('users');

           __PACKAGE__->add_columns(qw/user_id   email    password
                                       firstname lastname active
                                       admin/);

           __PACKAGE__->set_primary_key('user_id');

           sub inflate_result {
               my $self = shift;
               my $ret = $self->next::method(@_);
               if( $ret->admin ) {### If this is an admin, rebless for extra functions
                   $self->ensure_class_loaded( $admin_class );
                   bless $ret, $admin_class;
               }
               return $ret;
           }

           sub hello {
               print "I am a regular user.\n";
               return ;
           }

           1;


           package My::Schema::Result::User::Admin;

           use strict;
           use warnings;
           use base qw/My::Schema::Result::User/;

           # This line is important
           __PACKAGE__->table('users');

           sub hello
           {
               print "I am an admin.\n";
               return;
           }

           sub do_admin_stuff
           {
               print "I am doing admin stuff\n";
               return ;
           }

           1;

       Test File test.pl

           use warnings;
           use strict;
           use My::Schema;

           my $user_data = { email    => 'someguy@place.com',
                             password => 'pass1',
                             admin    => 0 };

           my $admin_data = { email    => 'someadmin@adminplace.com',
                              password => 'pass2',
                              admin    => 1 };

           my $schema = My::Schema->connection('dbi:Pg:dbname=test');

           $schema->resultset('User')->create( $user_data );
           $schema->resultset('User')->create( $admin_data );

           ### Now we search for them
           my $user = $schema->resultset('User')->single( $user_data );
           my $admin = $schema->resultset('User')->single( $admin_data );

           print ref $user, "\n";
           print ref $admin, "\n";

           print $user->password , "\n"; # pass1
           print $admin->password , "\n";# pass2; inherited from User
           print $user->hello , "\n";# I am a regular user.
           print $admin->hello, "\n";# I am an admin.

           ### The statement below will NOT print
           print "I can do admin stuff\n" if $user->can('do_admin_stuff');
           ### The statement below will print
           print "I can do admin stuff\n" if $admin->can('do_admin_stuff');

       Alternatively you can use DBIx::Class::DynamicSubclass that implements exactly the above
       functionality.

   Skip row object creation for faster results
       DBIx::Class is not built for speed, it's built for convenience and ease of use, but sometimes you
       just need to get the data, and skip the fancy objects.

       To do this simply use DBIx::Class::ResultClass::HashRefInflator.

        my $rs = $schema->resultset('CD');

        $rs->result_class('DBIx::Class::ResultClass::HashRefInflator');

        my $hash_ref = $rs->find(1);

       Wasn't that easy?

       Beware, changing the Result class using "result_class" in DBIx::Class::ResultSet will replace any
       existing class completely including any special components loaded using load_components, eg
       DBIx::Class::InflateColumn::DateTime.

   Get raw data for blindingly fast results
       If the HashRefInflator solution above is not fast enough for you, you can use a DBIx::Class to return
       values exactly as they come out of the database with none of the convenience methods wrapped round
       them.

       This is used like so:

         my $cursor = $rs->cursor
         while (my @vals = $cursor->next) {
             # use $val[0..n] here
         }

       You will need to map the array offsets to particular columns (you can use the "select" in
       DBIx::Class::ResultSet attribute of "search" in DBIx::Class::ResultSet to force ordering).

RESULTSET OPERATIONS
   Getting Schema from a ResultSet
       To get the DBIx::Class::Schema object from a ResultSet, do the following:

        $rs->result_source->schema

   Getting Columns Of Data
       AKA Aggregating Data

       If you want to find the sum of a particular column there are several ways, the obvious one is to use
       search:

         my $rs = $schema->resultset('Items')->search(
           {},
           {
              select => [ { sum => 'Cost' } ],
              as     => [ 'total_cost' ], # remember this 'as' is for DBIx::Class::ResultSet not SQL
           }
         );
         my $tc = $rs->first->get_column('total_cost');

       Or, you can use the DBIx::Class::ResultSetColumn, which gets returned when you ask the "ResultSet"
       for a column using "get_column":

         my $cost = $schema->resultset('Items')->get_column('Cost');
         my $tc = $cost->sum;

       With this you can also do:

         my $minvalue = $cost->min;
         my $maxvalue = $cost->max;

       Or just iterate through the values of this column only:

         while ( my $c = $cost->next ) {
           print $c;
         }

         foreach my $c ($cost->all) {
           print $c;
         }

       "ResultSetColumn" only has a limited number of built-in functions. If you need one that it doesn't
       have, then you can use the "func" method instead:

         my $avg = $cost->func('AVERAGE');

       This will cause the following SQL statement to be run:

         SELECT AVERAGE(Cost) FROM Items me

       Which will of course only work if your database supports this function.  See
       DBIx::Class::ResultSetColumn for more documentation.

   Creating a result set from a set of rows
       Sometimes you have a (set of) row objects that you want to put into a resultset without the need to
       hit the DB again. You can do that by using the set_cache method:

        my @uploadable_groups;
        while (my $group = $groups->next) {
          if ($group->can_upload($self)) {
            push @uploadable_groups, $group;
          }
        }
        my $new_rs = $self->result_source->resultset;
        $new_rs->set_cache(\@uploadable_groups);
        return $new_rs;

USING RELATIONSHIPS
   Create a new row in a related table
         my $author = $book->create_related('author', { name => 'Fred'});

   Search in a related table
       Only searches for books named 'Titanic' by the author in $author.

         my $books_rs = $author->search_related('books', { name => 'Titanic' });

   Delete data in a related table
       Deletes only the book named Titanic by the author in $author.

         $author->delete_related('books', { name => 'Titanic' });

   Ordering a relationship result set
       If you always want a relation to be ordered, you can specify this when you create the relationship.

       To order "$book->pages" by descending page_number, create the relation as follows:

         __PACKAGE__->has_many('pages' => 'Page', 'book', { order_by => { -desc => 'page_number'} } );

   Filtering a relationship result set
       If you want to get a filtered result set, you can just add add to $attr as follows:

        __PACKAGE__->has_many('pages' => 'Page', 'book', { where => { scrap => 0 } } );

   Many-to-many relationship bridges
       This is straightforward using ManyToMany:

         package My::User;
         use base 'DBIx::Class::Core';
         __PACKAGE__->table('user');
         __PACKAGE__->add_columns(qw/id name/);
         __PACKAGE__->set_primary_key('id');
         __PACKAGE__->has_many('user_address' => 'My::UserAddress', 'user');
         __PACKAGE__->many_to_many('addresses' => 'user_address', 'address');

         package My::UserAddress;
         use base 'DBIx::Class::Core';
         __PACKAGE__->table('user_address');
         __PACKAGE__->add_columns(qw/user address/);
         __PACKAGE__->set_primary_key(qw/user address/);
         __PACKAGE__->belongs_to('user' => 'My::User');
         __PACKAGE__->belongs_to('address' => 'My::Address');

         package My::Address;
         use base 'DBIx::Class::Core';
         __PACKAGE__->table('address');
         __PACKAGE__->add_columns(qw/id street town area_code country/);
         __PACKAGE__->set_primary_key('id');
         __PACKAGE__->has_many('user_address' => 'My::UserAddress', 'address');
         __PACKAGE__->many_to_many('users' => 'user_address', 'user');

         $rs = $user->addresses(); # get all addresses for a user
         $rs = $address->users(); # get all users for an address

         my $address = $user->add_to_addresses(    # returns a My::Address instance,
                                                   # NOT a My::UserAddress instance!
           {
             country => 'United Kingdom',
             area_code => 'XYZ',
             town => 'London',
             street => 'Sesame',
           }
         );

   Relationships across DB schemas
       Mapping relationships across DB schemas is easy as long as the schemas themselves are all accessible
       via the same DBI connection. In most cases, this means that they are on the same database host as
       each other and your connecting database user has the proper permissions to them.

       To accomplish this one only needs to specify the DB schema name in the table declaration, like so...

         package MyDatabase::Main::Artist;
         use base qw/DBIx::Class::Core/;

         __PACKAGE__->table('database1.artist'); # will use "database1.artist" in FROM clause

         __PACKAGE__->add_columns(qw/ artist_id name /);
         __PACKAGE__->set_primary_key('artist_id');
         __PACKAGE__->has_many('cds' => 'MyDatabase::Main::Cd');

         1;

       Whatever string you specify there will be used to build the "FROM" clause in SQL queries.

       The big drawback to this is you now have DB schema names hardcoded in your class files. This becomes
       especially troublesome if you have multiple instances of your application to support a change
       lifecycle (e.g. DEV, TEST, PROD) and the DB schemas are named based on the environment (e.g.
       database1_dev).

       However, one can dynamically "map" to the proper DB schema by overriding the connection method in
       your Schema class and building a renaming facility, like so:

         package MyDatabase::Schema;
         use Moose;

         extends 'DBIx::Class::Schema';

         around connection => sub {
           my ( $inner, $self, $dsn, $username, $pass, $attr ) = ( shift, @_ );

           my $postfix = delete $attr->{schema_name_postfix};

           $inner->(@_);

           if ( $postfix ) {
               $self->append_db_name($postfix);
           }
         };

         sub append_db_name {
           my ( $self, $postfix ) = @_;

           my @sources_with_db
               = grep
                   { $_->name =~ /^\w+\./mx }
                   map
                       { $self->source($_) }
                       $self->sources;

           foreach my $source (@sources_with_db) {
               my $name = $source->name;
               $name =~ s{^(\w+)\.}{${1}${postfix}\.}mx;

               $source->name($name);
           }
         }

         1;

       By overridding the connection method and extracting a custom option from the provided \%attr hashref
       one can then simply iterate over all the Schema's ResultSources, renaming them as needed.

       To use this facility, simply add or modify the \%attr hashref that is passed to connection, as
       follows:

         my $schema
           = MyDatabase::Schema->connect(
             $dsn,
             $user,
             $pass,
             {
               schema_name_postfix => '_dev'
               # ... Other options as desired ...
             })

       Obviously, one could accomplish even more advanced mapping via a hash map or a callback routine.

TRANSACTIONS
   Transactions with txn_do
       As of version 0.04001, there is improved transaction support in DBIx::Class::Storage and
       DBIx::Class::Schema.  Here is an example of the recommended way to use it:

         my $genus = $schema->resultset('Genus')->find(12);

         my $coderef2 = sub {
           $genus->extinct(1);
           $genus->update;
         };

         my $coderef1 = sub {
           $genus->add_to_species({ name => 'troglodyte' });
           $genus->wings(2);
           $genus->update;
           $schema->txn_do($coderef2); # Can have a nested transaction. Only the outer will actualy commit
           return $genus->species;
         };

         use Try::Tiny;
         my $rs;
         try {
           $rs = $schema->txn_do($coderef1);
         } catch {
           # Transaction failed
           die "the sky is falling!"           #
             if ($_ =~ /Rollback failed/);     # Rollback failed

           deal_with_failed_transaction();
         };

       Note: by default "txn_do" will re-run the coderef one more time if an error occurs due to client
       disconnection (e.g. the server is bounced).  You need to make sure that your coderef can be invoked
       multiple times without terrible side effects.

       Nested transactions will work as expected. That is, only the outermost transaction will actually
       issue a commit to the $dbh, and a rollback at any level of any transaction will cause the entire
       nested transaction to fail.

   Nested transactions and auto-savepoints
       If savepoints are supported by your RDBMS, it is possible to achieve true nested transactions with
       minimal effort. To enable auto-savepoints via nested transactions, supply the "auto_savepoint = 1"
       connection attribute.

       Here is an example of true nested transactions. In the example, we start a big task which will create
       several rows. Generation of data for each row is a fragile operation and might fail. If we fail
       creating something, depending on the type of failure, we want to abort the whole task, or only skip
       the failed row.

         my $schema = MySchema->connect("dbi:Pg:dbname=my_db");

         # Start a transaction. Every database change from here on will only be
         # committed into the database if the try block succeeds.
         use Try::Tiny;
         my $exception;
         try {
           $schema->txn_do(sub {
             # SQL: BEGIN WORK;

             my $job = $schema->resultset('Job')->create({ name=> 'big job' });
             # SQL: INSERT INTO job ( name) VALUES ( 'big job' );

             for (1..10) {

               # Start a nested transaction, which in fact sets a savepoint.
               try {
                 $schema->txn_do(sub {
                   # SQL: SAVEPOINT savepoint_0;

                   my $thing = $schema->resultset('Thing')->create({ job=>$job->id });
                   # SQL: INSERT INTO thing ( job) VALUES ( 1 );

                   if (rand > 0.8) {
                     # This will generate an error, thus setting $@

                     $thing->update({force_fail=>'foo'});
                     # SQL: UPDATE thing SET force_fail = 'foo'
                     #      WHERE ( id = 42 );
                   }
                 });
               } catch {
                 # SQL: ROLLBACK TO SAVEPOINT savepoint_0;

                 # There was an error while creating a $thing. Depending on the error
                 # we want to abort the whole transaction, or only rollback the
                 # changes related to the creation of this $thing

                 # Abort the whole job
                 if ($_ =~ /horrible_problem/) {
                   print "something horrible happend, aborting job!";
                   die $_;                # rethrow error
                 }

                 # Ignore this $thing, report the error, and continue with the
                 # next $thing
                 print "Cannot create thing: $_";
               }
               # There was no error, so save all changes since the last
               # savepoint.

               # SQL: RELEASE SAVEPOINT savepoint_0;
             }
           });
         } catch {
           $exception = $_;
         }

         if ($caught) {
           # There was an error while handling the $job. Rollback all changes
           # since the transaction started, including the already committed
           # ('released') savepoints. There will be neither a new $job nor any
           # $thing entry in the database.

           # SQL: ROLLBACK;

           print "ERROR: $exception\n";
         }
         else {
           # There was no error while handling the $job. Commit all changes.
           # Only now other connections can see the newly created $job and
           # @things.

           # SQL: COMMIT;

           print "Ok\n";
         }

       In this example it might be hard to see where the rollbacks, releases and commits are happening, but
       it works just the same as for plain <txn_do>: If the "try"-block around "txn_do" fails, a rollback is
       issued. If the "try" succeeds, the transaction is committed (or the savepoint released).

       While you can get more fine-grained control using "svp_begin", "svp_release" and "svp_rollback", it
       is strongly recommended to use "txn_do" with coderefs.

   Simple Transactions with DBIx::Class::Storage::TxnScopeGuard
       An easy way to use transactions is with DBIx::Class::Storage::TxnScopeGuard. See "Automatically
       creating related objects" for an example.

       Note that unlike txn_do, TxnScopeGuard will only make sure the connection is alive when issuing the
       "BEGIN" statement. It will not (and really can not) retry if the server goes away mid-operations,
       unlike "txn_do".

SQL
   Creating Schemas From An Existing Database
       DBIx::Class::Schema::Loader will connect to a database and create a DBIx::Class::Schema and
       associated sources by examining the database.

       The recommend way of achieving this is to use the dbicdump utility or the Catalyst helper, as
       described in Manual::Intro.

       Alternatively, use the make_schema_at method:

         perl -MDBIx::Class::Schema::Loader=make_schema_at,dump_to_dir:./lib \
           -e 'make_schema_at("My::Schema", \
           { db_schema => 'myschema', components => ["InflateColumn::DateTime"] }, \
           [ "dbi:Pg:dbname=foo", "username", "password" ])'

       This will create a tree of files rooted at "./lib/My/Schema/" containing source definitions for all
       the tables found in the "myschema" schema in the "foo" database.

   Creating DDL SQL
       The following functionality requires you to have SQL::Translator (also known as "SQL Fairy")
       installed.

       To create a set of database-specific .sql files for the above schema:

        my $schema = My::Schema->connect($dsn);
        $schema->create_ddl_dir(['MySQL', 'SQLite', 'PostgreSQL'],
                               '0.1',
                               './dbscriptdir/'
                               );

       By default this will create schema files in the current directory, for MySQL, SQLite and PostgreSQL,
       using the $VERSION from your Schema.pm.

       To create a new database using the schema:

        my $schema = My::Schema->connect($dsn);
        $schema->deploy({ add_drop_table => 1});

       To import created .sql files using the mysql client:

         mysql -h "host" -D "database" -u "user" -p < My_Schema_1.0_MySQL.sql

       To create "ALTER TABLE" conversion scripts to update a database to a newer version of your schema at
       a later point, first set a new $VERSION in your Schema file, then:

        my $schema = My::Schema->connect($dsn);
        $schema->create_ddl_dir(['MySQL', 'SQLite', 'PostgreSQL'],
                                '0.2',
                                '/dbscriptdir/',
                                '0.1'
                                );

       This will produce new database-specific .sql files for the new version of the schema, plus scripts to
       convert from version 0.1 to 0.2. This requires that the files for 0.1 as created above are available
       in the given directory to diff against.

   Select from dual
       Dummy tables are needed by some databases to allow calling functions or expressions that aren't based
       on table content, for examples of how this applies to various database types, see:
       http://troels.arvin.dk/db/rdbms/#other-dummy_table <http://troels .arvin.dk/db/rdbms/#other-
       dummy_table>.

       Note: If you're using Oracles dual table don't ever do anything other than a select, if you CRUD on
       your dual table you *will* break your database.

       Make a table class as you would for any other table

         package MyAppDB::Dual;
         use strict;
         use warnings;
         use base 'DBIx::Class::Core';
         __PACKAGE__->table("Dual");
         __PACKAGE__->add_columns(
           "dummy",
           { data_type => "VARCHAR2", is_nullable => 0, size => 1 },
         );

       Once you've loaded your table class select from it using "select" and "as" instead of "columns"

         my $rs = $schema->resultset('Dual')->search(undef,
           { select => [ 'sydate' ],
             as     => [ 'now' ]
           },
         );

       All you have to do now is be careful how you access your resultset, the below will not work because
       there is no column called 'now' in the Dual table class

         while (my $dual = $rs->next) {
           print $dual->now."\n";
         }
         # Can't locate object method "now" via package "MyAppDB::Dual" at headshot.pl line 23.

       You could of course use 'dummy' in "as" instead of 'now', or "add_columns" to your Dual class for
       whatever you wanted to select from dual, but that's just silly, instead use "get_column"

         while (my $dual = $rs->next) {
           print $dual->get_column('now')."\n";
         }

       Or use "cursor"

         my $cursor = $rs->cursor;
         while (my @vals = $cursor->next) {
           print $vals[0]."\n";
         }

       In case you're going to use this "trick" together with "deploy" in DBIx::Class::Schema or
       "create_ddl_dir" in DBIx::Class::Schema a table called "dual" will be created in your current schema.
       This would overlap "sys.dual" and you could not fetch "sysdate" or "sequence.nextval" anymore from
       dual. To avoid this problem, just tell SQL::Translator to not create table dual:

           my $sqlt_args = {
               add_drop_table => 1,
               parser_args    => { sources => [ grep $_ ne 'Dual', schema->sources ] },
           };
           $schema->create_ddl_dir( [qw/Oracle/], undef, './sql', undef, $sqlt_args );

       Or use DBIx::Class::ResultClass::HashRefInflator

         $rs->result_class('DBIx::Class::ResultClass::HashRefInflator');
         while ( my $dual = $rs->next ) {
           print $dual->{now}."\n";
         }

       Here are some example "select" conditions to illustrate the different syntax you could use for doing
       stuff like "oracles.heavily(nested(functions_can('take', 'lots'), OF), 'args')"

         # get a sequence value
         select => [ 'A_SEQ.nextval' ],

         # get create table sql
         select => [ { 'dbms_metadata.get_ddl' => [ "'TABLE'", "'ARTIST'" ]} ],

         # get a random num between 0 and 100
         select => [ { "trunc" => [ { "dbms_random.value" => [0,100] } ]} ],

         # what year is it?
         select => [ { 'extract' => [ \'year from sysdate' ] } ],

         # do some math
         select => [ {'round' => [{'cos' => [ \'180 * 3.14159265359/180' ]}]}],

         # which day of the week were you born on?
         select => [{'to_char' => [{'to_date' => [ "'25-DEC-1980'", "'dd-mon-yyyy'" ]}, "'day'"]}],

         # select 16 rows from dual
         select   => [ "'hello'" ],
         as       => [ 'world' ],
         group_by => [ 'cube( 1, 2, 3, 4 )' ],

   Adding Indexes And Functions To Your SQL
       Often you will want indexes on columns on your table to speed up searching. To do this, create a
       method called "sqlt_deploy_hook" in the relevant source class (refer to the advanced callback system
       if you wish to share a hook between multiple sources):

        package My::Schema::Result::Artist;

        __PACKAGE__->table('artist');
        __PACKAGE__->add_columns(id => { ... }, name => { ... })

        sub sqlt_deploy_hook {
          my ($self, $sqlt_table) = @_;

          $sqlt_table->add_index(name => 'idx_name', fields => ['name']);
        }

        1;

       Sometimes you might want to change the index depending on the type of the database for which SQL is
       being generated:

         my ($db_type = $sqlt_table->schema->translator->producer_type)
           =~ s/^SQL::Translator::Producer:://;

       You can also add hooks to the schema level to stop certain tables being created:

        package My::Schema;

        ...

        sub sqlt_deploy_hook {
          my ($self, $sqlt_schema) = @_;

          $sqlt_schema->drop_table('table_name');
        }

       You could also add views, procedures or triggers to the output using "add_view" in
       SQL::Translator::Schema, "add_procedure" in SQL::Translator::Schema or "add_trigger" in
       SQL::Translator::Schema.

   Schema versioning
       The following example shows simplistically how you might use DBIx::Class to deploy versioned schemas
       to your customers. The basic process is as follows:

       1.  Create a DBIx::Class schema

       2.  Save the schema

       3.  Deploy to customers

       4.  Modify schema to change functionality

       5.  Deploy update to customers

       Create a DBIx::Class schema

       This can either be done manually, or generated from an existing database as described under "Creating
       Schemas From An Existing Database"

       Save the schema

       Call "create_ddl_dir" in DBIx::Class::Schema as above under "Creating DDL SQL".

       Deploy to customers

       There are several ways you could deploy your schema. These are probably beyond the scope of this
       recipe, but might include:

       1.  Require customer to apply manually using their RDBMS.

       2.  Package along with your app, making database dump/schema update/tests all part of your install.

       Modify the schema to change functionality

       As your application evolves, it may be necessary to modify your schema to change functionality. Once
       the changes are made to your schema in DBIx::Class, export the modified schema and the conversion
       scripts as in "Creating DDL SQL".

       Deploy update to customers

       Add the DBIx::Class::Schema::Versioned schema component to your Schema class. This will add a new
       table to your database called "dbix_class_schema_vesion" which will keep track of which version is
       installed and warn if the user tries to run a newer schema version than the database thinks it has.

       Alternatively, you can send the conversion SQL scripts to your customers as above.

   Setting quoting for the generated SQL
       If the database contains column names with spaces and/or reserved words, they need to be quoted in
       the SQL queries. This is done using:

        $schema->storage->sql_maker->quote_char([ qw/[ ]/] );
        $schema->storage->sql_maker->name_sep('.');

       The first sets the quote characters. Either a pair of matching brackets, or a """ or "'":

        $schema->storage->sql_maker->quote_char('"');

       Check the documentation of your database for the correct quote characters to use. "name_sep" needs to
       be set to allow the SQL generator to put the quotes the correct place, and defaults to "." if not
       supplied.

       In most cases you should set these as part of the arguments passed to "connect" in
       DBIx::Class::Schema:

        my $schema = My::Schema->connect(
         'dbi:mysql:my_db',
         'db_user',
         'db_password',
         {
           quote_char => '"',
           name_sep   => '.'
         }
        )

       In some cases, quoting will be required for all users of a schema. To enforce this, you can also
       overload the "connection" method for your schema class:

        sub connection {
            my $self = shift;
            my $rv = $self->next::method( @_ );
            $rv->storage->sql_maker->quote_char([ qw/[ ]/ ]);
            $rv->storage->sql_maker->name_sep('.');
            return $rv;
        }

   Working with PostgreSQL array types
       You can also assign values to PostgreSQL array columns by passing array references in the "\%columns"
       ("\%vals") hashref of the "create" in DBIx::Class::ResultSet and "update" in DBIx::Class::Row family
       of methods:

         $resultset->create({
           numbers => [1, 2, 3]
         });

         $row->update(
           {
             numbers => [1, 2, 3]
           },
           {
             day => '2008-11-24'
           }
         );

       In conditions (e.g. "\%cond" in the "search" in DBIx::Class::ResultSet family of methods) you cannot
       directly use array references (since this is interpreted as a list of values to be "OR"ed), but you
       can use the following syntax to force passing them as bind values:

         $resultset->search(
           {
             numbers => \[ '= ?', [numbers => [1, 2, 3]] ]
           }
         );

       See "array_datatypes" in SQL::Abstract and "Literal SQL with placeholders and bind values
       (subqueries)" in SQL::Abstract for more explanation. Note that DBIx::Class sets "bindtype" in
       SQL::Abstract to "columns", so you must pass the bind values (the "[1, 2, 3]" arrayref in the above
       example) wrapped in arrayrefs together with the column name, like this: "[column_name => value]".

   Formatting DateTime objects in queries
       To ensure "WHERE" conditions containing DateTime arguments are properly formatted to be understood by
       your RDBMS, you must use the "DateTime" formatter returned by "datetime_parser" in
       DBIx::Class::Storage::DBI to format any DateTime objects you pass to search conditions. Any Storage
       object attached to your Schema provides a correct "DateTime" formatter, so all you have to do is:

         my $dtf = $schema->storage->datetime_parser;
         my $rs = $schema->resultset('users')->search(
           {
             signup_date => {
               -between => [
                 $dtf->format_datetime($dt_start),
                 $dtf->format_datetime($dt_end),
               ],
             }
           },
         );

       Without doing this the query will contain the simple stringification of the "DateTime" object, which
       almost never matches the RDBMS expectations.

       This kludge is necessary only for conditions passed to "search" in DBIx::Class::ResultSet, whereas
       create, find, "update" in DBIx::Class::Row (but not "update" in DBIx::Class::ResultSet) are all
       DBIx::Class::InflateColumn-aware and will do the right thing when supplied an inflated "DateTime"
       object.

   Using Unicode
       When using unicode character data there are two alternatives - either your database supports unicode
       characters (including setting the utf8 flag on the returned string), or you need to encode/decode
       data appropriately each time a string field is inserted into or retrieved from the database. It is
       better to avoid encoding/decoding data and to use your database's own unicode capabilities if at all
       possible.

       The DBIx::Class::UTF8Columns component handles storing selected unicode columns in a database that
       does not directly support unicode. If used with a database that does correctly handle unicode then
       strange and unexpected data corrupt will occur.

       The Catalyst Wiki Unicode page at
       <http://wiki.catalystframework.org/wiki/tutorialsandhowtos/using_unicode> has additional information
       on the use of Unicode with Catalyst and DBIx::Class.

       The following databases do correctly handle unicode data:-MySQL data:MySQL

       MySQL

       MySQL supports unicode, and will correctly flag utf8 data from the database if the
       "mysql_enable_utf8" is set in the connect options.

         my $schema = My::Schema->connection('dbi:mysql:dbname=test',
                                             $user, $pass,
                                             { mysql_enable_utf8 => 1} );

       When set, a data retrieved from a textual column type (char, varchar, etc) will have the UTF-8 flag
       turned on if necessary. This enables character semantics on that string. You will also need to ensure
       that your database / table / column is configured to use UTF8. See Chapter 10 of the mysql manual for
       details.

       See DBD::mysql for further details.

       Oracle

       Information about Oracle support for unicode can be found in "Unicode" in DBD::Oracle.

       PostgreSQL

       PostgreSQL supports unicode if the character set is correctly set at database creation time.
       Additionally the "pg_enable_utf8" should be set to ensure unicode data is correctly marked.

         my $schema = My::Schema->connection('dbi:Pg:dbname=test',
                                             $user, $pass,
                                             { pg_enable_utf8 => 1} );

       Further information can be found in DBD::Pg.

       SQLite

       SQLite version 3 and above natively use unicode internally. To correctly mark unicode strings taken
       from the database, the "sqlite_unicode" flag should be set at connect time (in versions of
       DBD::SQLite prior to 1.27 this attribute was named "unicode").

         my $schema = My::Schema->connection('dbi:SQLite:/tmp/test.db',
                                             '', '',
                                             { sqlite_unicode => 1} );

BOOTSTRAPPING/MIGRATING
   Easy migration from class-based to schema-based setup
       You want to start using the schema-based approach to DBIx::Class (see "Setting it up manually" in
       DBIx::Class::Manual::Intro), but have an established class-based setup with lots of existing classes
       that you don't want to move by hand. Try this nifty script instead:

         use MyDB;
         use SQL::Translator;

         my $schema = MyDB->schema_instance;

         my $translator           =  SQL::Translator->new(
             debug                => $debug          ||  0,
             trace                => $trace          ||  0,
             no_comments          => $no_comments    ||  0,
             show_warnings        => $show_warnings  ||  0,
             add_drop_table       => $add_drop_table ||  0,
             validate             => $validate       ||  0,
             parser_args          => {
                'DBIx::Schema'    => $schema,
                                     },
             producer_args   => {
                 'prefix'         => 'My::Schema',
                                },
         );

         $translator->parser('SQL::Translator::Parser::DBIx::Class');
         $translator->producer('SQL::Translator::Producer::DBIx::Class::File');

         my $output = $translator->translate(@args) or die
                 "Error: " . $translator->error;

         print $output;

       You could use Module::Find to search for all subclasses in the MyDB::* namespace, which is currently
       left as an exercise for the reader.

OVERLOADING METHODS
       DBIx::Class uses the Class::C3 package, which provides for redispatch of method calls, useful for
       things like default values and triggers. You have to use calls to "next::method" to overload methods.
       More information on using Class::C3 with DBIx::Class can be found in DBIx::Class::Manual::Component.

   Setting default values for a row
       It's as simple as overriding the "new" method.  Note the use of "next::method".

         sub new {
           my ( $class, $attrs ) = @_;

           $attrs->{foo} = 'bar' unless defined $attrs->{foo};

           my $new = $class->next::method($attrs);

           return $new;
         }

       For more information about "next::method", look in the Class::C3 documentation. See also
       DBIx::Class::Manual::Component for more ways to write your own base classes to do this.

       People looking for ways to do "triggers" with DBIx::Class are probably just looking for this.

   Changing one field whenever another changes
       For example, say that you have three columns, "id", "number", and "squared".  You would like to make
       changes to "number" and have "squared" be automagically set to the value of "number" squared.  You
       can accomplish this by wrapping the "number" accessor with Class::Method::Modifiers:

         around number => sub {
           my ($orig, $self) = (shift, shift);

           if (@_) {
             my $value = $_[0];
             $self->squared( $value * $value );
           }

           $self->$orig(@_);
         }

       Note that the hard work is done by the call to "$self->$orig", which redispatches your call to
       store_column in the superclass(es).

       Generally, if this is a calculation your database can easily do, try and avoid storing the calculated
       value, it is safer to calculate when needed, than rely on the data being in sync.

   Automatically creating related objects
       You might have a class "Artist" which has many "CD"s.  Further, you want to create a "CD" object
       every time you insert an "Artist" object.  You can accomplish this by overriding "insert" on your
       objects:

         sub insert {
           my ( $self, @args ) = @_;
           $self->next::method(@args);
           $self->create_related ('cds', \%initial_cd_data );
           return $self;
         }

       If you want to wrap the two inserts in a transaction (for consistency, an excellent idea), you can
       use the awesome DBIx::Class::Storage::TxnScopeGuard:

         sub insert {
           my ( $self, @args ) = @_;

           my $guard = $self->result_source->schema->txn_scope_guard;

           $self->next::method(@args);
           $self->create_related ('cds', \%initial_cd_data );

           $guard->commit;

           return $self
         }

   Wrapping/overloading a column accessor
       Problem:

       Say you have a table "Camera" and want to associate a description with each camera. For most cameras,
       you'll be able to generate the description from the other columns. However, in a few special cases
       you may want to associate a custom description with a camera.

       Solution:

       In your database schema, define a description field in the "Camera" table that can contain text and
       null values.

       In DBIC, we'll overload the column accessor to provide a sane default if no custom description is
       defined. The accessor will either return or generate the description, depending on whether the field
       is null or not.

       First, in your "Camera" schema class, define the description field as follows:

         __PACKAGE__->add_columns(description => { accessor => '_description' });

       Next, we'll define the accessor-wrapper subroutine:

         sub description {
             my $self = shift;

             # If there is an update to the column, we'll let the original accessor
             # deal with it.
             return $self->_description(@_) if @_;

             # Fetch the column value.
             my $description = $self->_description;

             # If there's something in the description field, then just return that.
             return $description if defined $description && length $descripton;

             # Otherwise, generate a description.
             return $self->generate_description;
         }

DEBUGGING AND PROFILING
   DBIx::Class objects with Data::Dumper
       Data::Dumper can be a very useful tool for debugging, but sometimes it can be hard to find the
       pertinent data in all the data it can generate.  Specifically, if one naively tries to use it like
       so,

         use Data::Dumper;

         my $cd = $schema->resultset('CD')->find(1);
         print Dumper($cd);

       several pages worth of data from the CD object's schema and result source will be dumped to the
       screen. Since usually one is only interested in a few column values of the object, this is not very
       helpful.

       Luckily, it is possible to modify the data before Data::Dumper outputs it. Simply define a hook that
       Data::Dumper will call on the object before dumping it. For example,

         package My::DB::CD;

         sub _dumper_hook {
           $_[0] = bless {
             %{ $_[0] },
             result_source => undef,
           }, ref($_[0]);
         }

         [...]

         use Data::Dumper;

         local $Data::Dumper::Freezer = '_dumper_hook';

         my $cd = $schema->resultset('CD')->find(1);
         print Dumper($cd);
                # dumps $cd without its ResultSource

       If the structure of your schema is such that there is a common base class for all your table classes,
       simply put a method similar to "_dumper_hook" in the base class and set $Data::Dumper::Freezer to its
       name and Data::Dumper will automagically clean up your data before printing it. See "EXAMPLES" in
       Data::Dumper for more information.

   Profiling
       When you enable DBIx::Class::Storage's debugging it prints the SQL executed as well as notifications
       of query completion and transaction begin/commit.  If you'd like to profile the SQL you can subclass
       the DBIx::Class::Storage::Statistics class and write your own profiling mechanism:

         package My::Profiler;
         use strict;

         use base 'DBIx::Class::Storage::Statistics';

         use Time::HiRes qw(time);

         my $start;

         sub query_start {
           my $self = shift();
           my $sql = shift();
           my @params = @_;

           $self->print("Executing $sql: ".join(', ', @params)."\n");
           $start = time();
         }

         sub query_end {
           my $self = shift();
           my $sql = shift();
           my @params = @_;

           my $elapsed = sprintf("%0.4f", time() - $start);
           $self->print("Execution took $elapsed seconds.\n");
           $start = undef;
         }

         1;

       You can then install that class as the debugging object:

         __PACKAGE__->storage->debugobj(new My::Profiler());
         __PACKAGE__->storage->debug(1);

       A more complicated example might involve storing each execution of SQL in an array:

         sub query_end {
           my $self = shift();
           my $sql = shift();
           my @params = @_;

           my $elapsed = time() - $start;
           push(@{ $calls{$sql} }, {
               params => \@params,
               elapsed => $elapsed
           });
         }

       You could then create average, high and low execution times for an SQL statement and dig down to see
       if certain parameters cause aberrant behavior.  You might want to check out DBIx::Class::QueryLog as
       well.

IMPROVING PERFORMANCE
       •   Install Class::XSAccessor to speed up Class::Accessor::Grouped.

       •   On Perl 5.8 install Class::C3::XS.

       •   prefetch relationships, where possible. See "Using joins and prefetch".

       •   Use populate in void context to insert data when you don't need the resulting DBIx::Class::Row
           objects, if possible, but see the caveats.

           When inserting many rows, for best results, populate a large number of rows at a time, but not so
           large that the table is locked for an unacceptably long time.

           If using create instead, use a transaction and commit every "X" rows; where "X" gives you the
           best performance without locking the table for too long.

       •   When selecting many rows, if you don't need full-blown DBIx::Class::Row objects, consider using
           DBIx::Class::ResultClass::HashRefInflator.

       •   See also "STARTUP SPEED" and "MEMORY USAGE" in this document.

STARTUP SPEED
       DBIx::Class programs can have a significant startup delay as the ORM loads all the relevant classes.
       This section examines techniques for reducing the startup delay.

       These tips are are listed in order of decreasing effectiveness - so the first tip, if applicable,
       should have the greatest effect on your application.

   Statically Define Your Schema
       If you are using DBIx::Class::Schema::Loader to build the classes dynamically based on the database
       schema then there will be a significant startup delay.

       For production use a statically defined schema (which can be generated using
       DBIx::Class::Schema::Loader to dump the database schema once - see make_schema_at and dump_directory
       for more details on creating static schemas from a database).

   Move Common Startup into a Base Class
       Typically DBIx::Class result classes start off with

           use base qw/DBIx::Class::Core/;
           __PACKAGE__->load_components(qw/InflateColumn::DateTime/);

       If this preamble is moved into a common base class:-package class:package

           package MyDBICbase;

           use base qw/DBIx::Class::Core/;
           __PACKAGE__->load_components(qw/InflateColumn::DateTime/);
           1;

       and each result class then uses this as a base:-use base:use

           use base qw/MyDBICbase/;

       then the load_components is only performed once, which can result in a considerable startup speedup
       for schemas with many classes.

   Explicitly List Schema Result Classes
       The schema class will normally contain

           __PACKAGE__->load_classes();

       to load the result classes. This will use Module::Find to find and load the appropriate modules.
       Explicitly defining the classes you wish to load will remove the overhead of Module::Find and the
       related directory operations:

           __PACKAGE__->load_classes(qw/ CD Artist Track /);

       If you are instead using the load_namespaces syntax to load the appropriate classes there is not a
       direct alternative avoiding Module::Find.

MEMORY USAGE
   Cached statements
       DBIx::Class normally caches all statements with prepare_cached().  This is normally a good idea, but
       if too many statements are cached, the database may use too much memory and may eventually run out
       and fail entirely.  If you suspect this may be the case, you may want to examine DBI's CachedKids
       hash:

           # print all currently cached prepared statements
           print for keys %{$schema->storage->dbh->{CachedKids}};
           # get a count of currently cached prepared statements
           my $count = scalar keys %{$schema->storage->dbh->{CachedKids}};

       If it's appropriate, you can simply clear these statements, automatically deallocating them in the
       database:

           my $kids = $schema->storage->dbh->{CachedKids};
           delete @{$kids}{keys %$kids} if scalar keys %$kids > 100;

       But what you probably want is to expire unused statements and not those that are used frequently.
       You can accomplish this with Tie::Cache or Tie::Cache::LRU:

           use Tie::Cache;
           use DB::Main;
           my $schema = DB::Main->connect($dbi_dsn, $user, $pass, {
               on_connect_do => sub { tie %{shift->_dbh->{CachedKids}}, 'Tie::Cache', 100 },
           });



perl v5.12.5                                     2011-05-10                 DBIx::Class::Manual::Cookbook(3)