removed the mistaken debug code

[dbsrgits/DBIx-Class.git] / lib / DBIx / Class / Manual / Cookbook.pod

=head1 NAME 

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

=head1 SEARCHING

=head2 Paged results

When you expect a large number of results, you can ask L<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

The C<page> attribute does not have to be specified in your search:

  my $rs = $schema->resultset('Artist')->search(
    undef,
    {
      rows => 10,
    }
  );

  return $rs->page(1); # DBIx::Class::ResultSet containing first 10 records

In either of the above cases, you can get a L<Data::Page> object for the
resultset (suitable for use in e.g. a template) using the C<pager> method:

  return $rs->pager();

=head2 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 C<WHERE> clause:

  WHERE artist LIKE '%Lamb%' AND title LIKE '%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 C<WHERE> clause:

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

For more information on generating complex queries, see
L<SQL::Abstract/WHERE CLAUSES>.

=head2 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 L<DBIx::Class::ResultSet>. 
The recommended way to accomplish this is by defining a separate ResultSource 
for your query. You can then inject complete SQL statements using a scalar 
reference (this is a feature of L<SQL::Abstract>).

Say you want to run a complex custom query on your user data, here's what
you have to add to your User class:

  package My::Schema::User;
  
  use base qw/DBIx::Class/;
  
  # ->load_components, ->table, ->add_columns, etc.

  # Make a new ResultSource based on the User class
  my $source = __PACKAGE__->result_source_instance();
  my $new_source = $source->new( $source );
  $new_source->source_name( 'UserFriendsComplex' );
  
  # Hand in your query as a scalar reference
  # It will be added as a sub-select after FROM,
  # so pay attention to the surrounding brackets!
  $new_source->name( \<<SQL );
  ( 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 = ? )
  SQL 

  # Finally, register your new ResultSource with your Schema
  My::Schema->register_source( 'UserFriendsComplex' => $new_source );

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 L<DBIx::Class::ResultSet>.

=head2 Using specific columns

When you only want specific columns from a table, you can use
C<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 C<select> and C<as>, see below. C<columns>
cannot be used together with C<select> and C<as>.

=head2 Using database functions or stored procedures

The combination of C<select> and C<as> can be used to return the result of a
database function or stored procedure as a column value. You use C<select> to
specify the source for your column value (e.g. a column name, function, or
stored procedure name). You then use C<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 C< as > attribute has absolutely nothing to with the sql
syntax C< SELECT foo AS bar > (see the documentation in
L<DBIx::Class::ResultSet/ATTRIBUTES>).  If your alias exists as a
column in your base class (i.e. it was added with C<add_columns>), you
just access it as normal. Our C<Artist> class has a C<name> column, so
we just use the C<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 C<get_column> accessor:

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

If you don't like using C<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');

=head2 SELECT DISTINCT with multiple columns

  my $rs = $schema->resultset('Foo')->search(
    {},
    {
      select => [
        { distinct => [ $source->columns ] }
      ],
      as => [ $source->columns ] # remember 'as' is not the same as SQL AS :-)
    }
  );

=head2 SELECT COUNT(DISTINCT colname)

  my $rs = $schema->resultset('Foo')->search(
    {},
    {
      select => [
        { count => { distinct => 'colname' } }
      ],
      as => [ 'count' ]
    }
  );

  my $count = $rs->next->get_column('count');

=head2 Grouping results

L<DBIx::Class> supports C<GROUP BY> as follows:

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

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

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

=head2 Predefined searches

You can write your own L<DBIx::Class::ResultSet> class by inheriting from it
and define often used searches as methods:

  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;

To use your resultset, first tell DBIx::Class to create an instance of it
for you, in your My::DBIC::Schema::CD class:

  # class definition as normal
  __PACKAGE__->load_components(qw/ Core /);
  __PACKAGE__->table('cd');

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

Note that C<resultset_class> must be called after C<load_components> and C<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();

=head2 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.  However,
it can be accomplished with C<DBIx::Class> when necessary.

If you do not have quoting on, simply include the function in your search
specification as you would any column:

  $rs->search({ 'YEAR(date_of_birth)' => 1979 });

With quoting on, or for a more portable solution, use the C<where>
attribute:

  $rs->search({}, { where => \'YEAR(date_of_birth) = 1979' });

=begin hidden

(When the bind args ordering bug is fixed, this technique will be better
and can replace the one above.)

With quoting on, or for a more portable solution, use the C<where> and
C<bind> attributes:

  $rs->search({}, {
      where => \'YEAR(date_of_birth) = ?',
      bind  => [ 1979 ]
  });

=end hidden

=head1 JOINS AND PREFETCHING

=head2 Using joins and prefetch

You can use the C<join> attribute to allow searching on, or sorting your
results by, one or more columns in a related table. To return all CDs matching
a particular artist name:

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

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

If required, you can now sort on any column in the related tables by including
it in your C<order_by> attribute:

  my $rs = $schema->resultset('CD')->search(
    {
      'artist.name' => 'Bob Marley'
    },
    {
      join     => [qw/ artist /],
      order_by => [qw/ artist.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 C<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 C<cd> and C<artist> tables
in our main query, but we have only returned data from the C<cd> table. To get
the artist name for any of the CD objects returned, L<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, L<DBIx::Class> has a C<prefetch> attribute to solve this problem.
This allows you to fetch results from related tables in advance:

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

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

Note that as of L<DBIx::Class> 0.05999_01, C<prefetch> I<can> be used with
C<has_many> relationships.

Also note that C<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!

=head2 Multi-step joins

Sometimes you want to join more than one relationship deep. In this example,
we want to find all C<Artist> objects who have C<CD>s whose C<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
  # JOIN ( cd ON artist.id = cd.artist )
  # 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
  # JOIN ( cd ON artist.id = cd.artist )
  # JOIN ( liner_notes ON cd.id = liner_notes.cd )
  # JOIN ( author ON author.id = liner_notes.author )
  # WHERE liner_notes.notes LIKE '%some text%'
  # AND author.name = 'A. Writer'

=head2 Multi-step prefetch

From 0.04999_05 onwards, C<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.cdid
  # JOIN artist ON cd.artist = artist.artistid

Now accessing our C<cd> and C<artist> relationships does not need additional
SQL statements:

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

=head1 ROW-LEVEL OPERATIONS

=head2 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.

=head2 Getting the value of the primary key for the last database insert

AKA getting last_insert_id

If you are using PK::Auto (which is a core component as of 0.07), 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.

=head2 Stringification

Employ the standard stringification technique by using the C<overload>
module.

To make an object stringify itself as a single column, use something
like this (replace C<foo> 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;

=head3 Stringification Example

Suppose we have two tables: C<Product> and C<Category>. The table
specifications are:

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

C<category> is a foreign key into the Category table.

If you have a Product object C<$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;

=head2 Want to know if find_or_create found or created a row?

Just use C<find_or_new> instead, then check C<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
  }

=head2 Dynamic Sub-classing DBIx::Class proxy classes 

AKA multi-class object inflation from one table
 
L<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(L<DBIx::Class::Row>) the same methods as a regular user but
also special admin only methods.  It doesn't make sense to create two
seperate 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 C<inflate_result> method within the User proxy-class
gives us the effect we want.  This method is called by
L<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:
 
B<Schema Definition> 
 
    package DB::Schema; 
     
    use base qw/DBIx::Class::Schema/; 
 
    __PACKAGE__->load_classes(qw/User/); 
 
 
B<Proxy-Class definitions> 
 
    package DB::Schema::User; 
     
    use strict; 
    use warnings; 
    use base qw/DBIx::Class/; 
     
    ### Defined what our admin class is for ensure_class_loaded 
    my $admin_class = __PACKAGE__ . '::Admin'; 
     
    __PACKAGE__->load_components(qw/Core/); 
     
    __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 ; 
    } 
     
     
    package DB::Schema::User::Admin; 
     
    use strict; 
    use warnings; 
    use base qw/DB::Schema::User/; 
     
    sub hello 
    { 
        print "I am an admin.\n"; 
        return; 
    } 
     
    sub do_admin_stuff 
    { 
        print "I am doing admin stuff\n"; 
        return ; 
    } 
 
B<Test File> test.pl 
 
    use warnings; 
    use strict; 
    use DB::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 = DB::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'); 

=head2 Skip 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 L<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?
  
=head2 Get raw data for blindingly fast results

If the L<HashRefInflator|DBIx::Class::ResultClass::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 data base 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 I<select> attribute of C<search()> to force ordering).

=head1 RESULTSET OPERATIONS

=head2 Getting Schema from a ResultSet

To get the schema object from a result set, do the following:

 $rs->result_source->schema

=head2 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 L<DBIx::Class::ResultSetColumn>, which gets
returned when you ask the C<ResultSet> for a column using
C<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;
  }

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 C<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 L<DBIx::Class::ResultSetColumn> for more documentation.

=head2 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
L<set_cache|DBIx::Class::Resultset/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;


=head1 USING RELATIONSHIPS

=head2 Create a new row in a related table

  my $author = $book->create_related('author', { name => 'Fred'});

=head2 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' });

=head2 Delete data in a related table

Deletes only the book named Titanic by the author in $author.

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

=head2 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 C<< $book->pages >> by descending page_number, create the relation
as follows:

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

=head2 Many-to-many relationships

This is straightforward using L<ManyToMany|DBIx::Class::Relationship/many_to_many>:

  package My::User;
  use base 'DBIx::Class';
  __PACKAGE__->load_components('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';
  __PACKAGE__->load_components('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';
  __PACKAGE__->load_components('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

=head1 TRANSACTIONS

As of version 0.04001, there is improved transaction support in
L<DBIx::Class::Storage> and L<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;
  };

  my $rs;
  eval {
    $rs = $schema->txn_do($coderef1);
  };

  if ($@) {                             # Transaction failed
    die "the sky is falling!"           #
      if ($@ =~ /Rollback failed/);     # Rollback failed

    deal_with_failed_transaction();
  }

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. Support for savepoints and for true nested
transactions (for databases that support them) will hopefully be added
in the future.

=head1 SQL 

=head2 Creating Schemas From An Existing Database

L<DBIx::Class::Schema::Loader> will connect to a database and create a 
L<DBIx::Class::Schema> and associated sources by examining the database.

The recommend way of achieving this is to use the 
L<make_schema_at|DBIx::Class::Schema::Loader/make_schema_at> method:

  perl -MDBIx::Class::Schema::Loader=make_schema_at,dump_to_dir:./lib \
    -e 'make_schema_at("My::Schema", { debug => 1 }, [ "dbi:Pg:dbname=foo","postgres" ])'

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

=head2 Creating DDL SQL

The following functionality requires you to have L<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_tables => 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 C<ALTER TABLE> conversion scripts to update a database to a
newer version of your schema at a later point, first set a new
C<$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.

=head2 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:
L<http://troels.arvin.dk/db/rdbms/#other-dummy_table>.

Note: If you're using Oracles dual table don't B<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';
  __PACKAGE__->load_components("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 C<select>
and C<as> instead of C<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 C<as> instead of 'now', or C<add_columns> to
your Dual class for whatever you wanted to select from dual, but that's just
silly, instead use C<get_column>
 
  while (my $dual = $rs->next) {
    print $dual->get_column('now')."\n";
  }
 
Or use C<cursor>
 
  my $cursor = $rs->cursor;
  while (my @vals = $cursor->next) {
    print $vals[0]."\n";
  }
 
Or use L<DBIx::Class::ResultClass::HashRefInflator>
 
  $rs->result_class('DBIx::Class::ResultClass::HashRefInflator');
  while ( my $dual = $rs->next ) {
    print $dual->{now}."\n";
  }
 
Here are some example C<select> conditions to illustrate the different syntax
you could use for doing stuff like 
C<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 )' ],
 
 

=head2 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 C<sqlt_deploy_hook> in the relevant source 
class:

 package My::Schema::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 or procedures to the output using 
L<SQL::Translator::Schema/add_view> or 
L<SQL::Translator::Schema/add_procedure>.

=head2 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:

=over 4

=item 1.

Create a DBIx::Class schema

=item 2.

Save the schema

=item 3.

Deploy to customers

=item 4.

Modify schema to change functionality

=item 5.

Deploy update to customers

=back

B<Create a DBIx::Class schema>

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

B<Save the schema>

Call L<DBIx::Class::Schema/create_ddl_dir> as above under L</Creating DDL SQL>.

B<Deploy to customers>

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

=over 4

=item 1.

Require customer to apply manually using their RDBMS.

=item 2.

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

=back

B<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 L</Creating DDL SQL>.

B<Deploy update to customers>

Add the L<DBIx::Class::Schema::Versioned> schema component to your
Schema class. This will add a new table to your database called
C<dbix_class_schema_vesion> which will keep track of which version is installed
and warn if the user trys 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.

=head2 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:

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

The first sets the quote characters. Either a pair of matching
brackets, or a C<"> or C<'>:
  
 __PACKAGE__->storage->sql_maker->quote_char('"');

Check the documentation of your database for the correct quote
characters to use. C<name_sep> needs to be set to allow the SQL
generator to put the quotes the correct place.

In most cases you should set these as part of the arguments passed to 
L<DBIx::Class::Schema/conect>:

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

=head2 Setting limit dialect for SQL::Abstract::Limit

In some cases, SQL::Abstract::Limit cannot determine the dialect of
the remote SQL server by looking at the database handle. This is a
common problem when using the DBD::JDBC, since the DBD-driver only
know that in has a Java-driver available, not which JDBC driver the
Java component has loaded.  This specifically sets the limit_dialect
to Microsoft SQL-server (See more names in SQL::Abstract::Limit
-documentation.

  __PACKAGE__->storage->sql_maker->limit_dialect('mssql');

The JDBC bridge is one way of getting access to a MSSQL server from a platform
that Microsoft doesn't deliver native client libraries for. (e.g. Linux)

The limit dialect can also be set at connect time by specifying a 
C<limit_dialect> key in the final hash as shown above.

=head1 BOOTSTRAPPING/MIGRATING 

=head2 Easy migration from class-based to schema-based setup

You want to start using the schema-based approach to L<DBIx::Class>
(see L<SchemaIntro.pod>), 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 L<Module::Find> to search for all subclasses in the MyDB::*
namespace, which is currently left as an exercise for the reader.

=head1 OVERLOADING METHODS

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

=head2 Setting default values for a row

It's as simple as overriding the C<new> method.  Note the use of
C<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 C<next::method>, look in the L<Class::C3> 
documentation. See also L<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. 

=head2 Changing one field whenever another changes

For example, say that you have three columns, C<id>, C<number>, and 
C<squared>.  You would like to make changes to C<number> and have
C<squared> be automagically set to the value of C<number> squared.
You can accomplish this by overriding C<store_column>:

  sub store_column {
    my ( $self, $name, $value ) = @_;
    if ($name eq 'number') {
      $self->squared($value * $value);
    }
    $self->next::method($name, $value);
  }

Note that the hard work is done by the call to C<next::method>, which
redispatches your call to store_column in the superclass(es).

=head2 Automatically creating related objects

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

  sub insert {
    my ( $self, @args ) = @_;
    $self->next::method(@args);
    $self->cds->new({})->fill_from_artist($self)->insert;
    return $self;
  }

where C<fill_from_artist> is a method you specify in C<CD> which sets
values in C<CD> based on the data in the C<Artist> object you pass in.

=head2 Wrapping/overloading a column accessor

B<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.

B<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;
  }

=head1 DEBUGGING AND PROFILING

=head2 DBIx::Class objects with Data::Dumper

L<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 L<Data::Dumper> outputs
it. Simply define a hook that L<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 C<_dumper_hook> in the
base class and set C<$Data::Dumper::Freezer> to its name and L<Data::Dumper>
will automagically clean up your data before printing it. See
L<Data::Dumper/EXAMPLES> for more information.

=head2 Profiling

When you enable L<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
L<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 L<DBIx::Class::QueryLog> as well.


=cut