#---------------------------------------------------------------------- package DBIx::DataModel; #---------------------------------------------------------------------- # see POD doc at end of file use 5.008; use warnings; use strict; use MRO::Compat (); # don't want to call MRO::Compat::import() our $VERSION = '2.46'; # compatibility setting : see import() our $COMPATIBILITY = $VERSION; # from 2.20, no longer automatic compatibility # Modules considered to belong to the same family for carp/croak (see L). # All inner classes import the same list. our @CARP_NOT = qw[ DBIx::DataModel::Compatibility::V0 DBIx::DataModel::Compatibility::V1 DBIx::DataModel::ConnectedSource DBIx::DataModel::Meta DBIx::DataModel::Meta::Association DBIx::DataModel::Meta::Path DBIx::DataModel::Meta::Schema DBIx::DataModel::Meta::Source DBIx::DataModel::Meta::Source::Join DBIx::DataModel::Meta::Source::Table DBIx::DataModel::Meta::Type DBIx::DataModel::Meta::Utils DBIx::DataModel::Schema DBIx::DataModel::Schema::Generator DBIx::DataModel::Source DBIx::DataModel::Source::Table DBIx::DataModel::Source::Join DBIx::DataModel::Statement DBIx::DataModel::Statement::JDBC DBIx::DataModel::Statement::Oracle SQL::Abstract SQL::Abstract::More ]; sub define_schema { my ($class, %params) = @_; require DBIx::DataModel::Meta::Schema; my $meta_schema = DBIx::DataModel::Meta::Schema->new(%params); return $meta_schema; } sub Schema { # syntactic sugar for ->define_schema() my ($class, $schema_class_name, %params) = @_; my $meta_schema = $class->define_schema(class => $schema_class_name, %params); return $meta_schema->class; } sub import { my ($class, %args) = @_; if (exists $args{-compatibility}) { $COMPATIBILITY = $args{-compatibility} # explicit number || $VERSION; # undef : means no compatibility } require DBIx::DataModel::Compatibility::V1 if $COMPATIBILITY < 1.99; require DBIx::DataModel::Compatibility::V0 if $COMPATIBILITY < 1.00; } 1; # End of DBIx::DataModel __END__ =head1 NAME DBIx::DataModel - UML-based Object-Relational Mapping (ORM) framework =head1 VERSION Version 2 of C is a major refactoring from versions 1.*, with a number of incompatible changes in the API (classes renamed, arguments renamed or reorganized, etc. -- see L). Initial subversions of the 2.* family included a layer of compatibility with version 1.*, so that old applications would continue to work (see L). Since version 2.20, this compatibility layer is no longer loaded automatically; however, it can still be added on demand by writing use DBIx::DataModel -compatibility => 1.0; =head1 SYNOPSIS =head2 in file "My/Schema.pm" =head3 Schema Load C. use DBIx::DataModel; Declare the schema, either in shorthand notation : DBIx::DataModel->Schema('My::Schema'); or in verbose form : DBIx::DataModel->define_schema( class => 'My::Schema', %options, ); This automatically creates a Perl class named C. Various parameters may be specified within C<%options>, like for example special columns to be filled automatically or to be ignored in every table : my $last_modif_generator = sub {$ENV{REMOTE_USER}.", ".scalar(localtime)}; my %options = ( auto_update_columns => {last_modif => $last_modif_generator}, no_update_columns => [qw/date_modif time_modif/], ); =head3 Types Declare a "column type" with some handlers, either in shorthand notation : My::Schema->Type(Date => from_DB => sub {$_[0] =~ s/(\d\d\d\d)-(\d\d)-(\d\d)/$3.$2.$1/}, to_DB => sub {$_[0] =~ s/(\d\d)\.(\d\d)\.(\d\d\d\d)/$3-$2-$1/}, validate => sub {$_[0] =~ m/(\d\d)\.(\d\d)\.(\d\d\d\d)/}, ); or in verbose form : My::Schema->metadm->define_type( name => 'Date', handlers => { from_DB => sub {$_[0] =~ s/(\d\d\d\d)-(\d\d)-(\d\d)/$3.$2.$1/}, to_DB => sub {$_[0] =~ s/(\d\d)\.(\d\d)\.(\d\d\d\d)/$3-$2-$1/}, validate => sub {$_[0] =~ m/(\d\d)\.(\d\d)\.(\d\d\d\d)/}, }); This does I create a Perl class; it just defines an internal datastructure that will be attached to some columns in some tables. Here are some other examples of column types : # 'percent' conversion between database (0.8) and user (80) My::Schema->metadm->define_type( name => 'Percent', handlers => { from_DB => sub {$_[0] *= 100 if $_[0]}, to_DB => sub {$_[0] /= 100 if $_[0]}, validate => sub {$_[0] =~ /1?\d?\d/}), }); # lists of values, stored as scalars with a ';' separator My::Schema->metadm->define_type( name => 'Multivalue', handlers => { from_DB => sub {$_[0] = [split /;/, $_[0] || ""] }, to_DB => sub {$_[0] = join ";", @$_[0] if ref $_[0]}, }); # adding SQL type information for the DBD handler My::Schema->metadm->define_type( name => 'XML', handlers => { to_DB => sub {$_[0] = [{dbd_attrs => {ora_type => ORA_XMLTYPE}}, $_[0]] if $_[0]}, }); =head3 Tables Declare the tables, either in shorthand notation : My::Schema->Table(qw/Employee T_Employee emp_id/) ->Table(qw/Department T_Department dpt_id/) ->Table(qw/Activity T_Activity act_id/); or in verbose form : My::Schema->metadm->define_table( class => 'Employee', db_name => 'T_Employee', primary_key => 'emp_id', ); My::Schema->metadm->define_table( class => 'Department', db_name => 'T_Department', primary_key => 'dpt_id', ); My::Schema->metadm->define_table( class => 'Activity', db_name => 'T_Activity', primary_key => 'act_id', ); Each table then becomes a Perl class (prefixed with the Schema name, i.e. C, etc.). =head3 Column types within tables Declare column types within these tables : # type name => applied_to_columns # ========= ================== My::Schema::Employee->metadm->set_column_type(Date => qw/d_birth/); My::Schema::Activity->metadm->set_column_type(Date => qw/d_begin d_end/); My::Schema::Activity->metadm->set_column_type(Percent => qw/activity_rate/); =head3 Associations Declare associations or compositions in UML style, either in shorthand notation : # class role multiplicity join # ===== ==== ============ ==== My::Schema->Composition([qw/Employee employee 1 emp_id /], [qw/Activity activities * emp_id /]) ->Association([qw/Department department 1 /], [qw/Activity activities * /]); or in verbose form : My::Schema->define_association( kind => 'Composition', A => { table => My::Schema::Employee->metadm, role => 'employee', multiplicity => 1, join_cols => [qw/emp_id/], }, B => { table => My::Schema::Activity->metadm, role => 'activities', multiplicity => '*', join_cols => [qw/emp_id/], }, ); My::Schema->define_association( kind => 'Association', A => { table => My::Schema::Department->metadm, role => 'department', multiplicity => 1, }, B => { table => My::Schema::Activity->metadm, role => 'activities', multiplicity => '*', }, ); Declare a n-to-n association, on top of the linking table My::Schema->Association([qw/Department departments * activities department/], [qw/Employee employees * activities employee/]); # or My::Schema->define_association( kind => 'Association', A => { table => My::Schema::Department->metadm, role => 'departments', multiplicity => '*', join_cols => [qw/activities department/], }, B => { table => My::Schema::Employee->metadm, role => 'employees', multiplicity => '*', join_cols => [qw/activities employee/], }, ); =head3 Additional methods For details that could not be expressed in a declarative way, just add a new method into the table class : package My::Schema::Activity; sub active_period { my $self = shift; $self->{d_begin} or croak "activity has no d_begin"; $self->{d_end} ? "from $self->{d_begin} to $self->{d_end}" : "since $self->{d_begin}"; } =head3 Data tree expansion Declare how to automatically expand objects into data trees My::Schema::Activity->metadm->define_auto_expand(qw/employee department/); =head3 Automatic schema generation perl -MDBIx::DataModel::Schema::Generator \ -e "fromDBI('dbi:connection:string')" -- \ -schema My::New::Schema > My/New/Schema.pm See L. =head2 in file "myClient.pl" =head3 Database connection use My::Schema; use DBI; my $dbh = DBI->connect($dsn, ...); My::Schema->dbh($dbh); # single-schema mode # or my $schema = My::Schema->new(dbh => $dbh); # multi-schema mode =head3 Simple data retrieval Search employees whose name starts with 'D' (select API is taken from L) my $empl_D = My::Schema->table('Employee')->select( -where => {lastname => {-like => 'D%'}} ); idem, but we just want a subset of the columns, and order by age. my $empl_F = My::Schema->table('Employee')->select( -columns => [qw/firstname lastname d_birth/], -where => {lastname => {-like => 'F%'}}, -order_by => 'd_birth' ); Print some info from employees. Because of the 'from_DB' handler associated with column type 'date', column 'd_birth' has been automatically converted to display format. foreach my $emp (@$empl_D) { print "$emp->{firstname} $emp->{lastname}, born $emp->{d_birth}\n"; } =head3 Methods to follow joins Follow the joins through role methods foreach my $act (@{$emp->activities}) { printf "working for %s from $act->{d_begin} to $act->{d_end}", $act->department->{name}; } Role methods can take arguments too, like C my $recent_activities = $dpt->activities(-where => {d_begin => {'>=' => '2005-01-01'}}); my @recent_employees = map {$_->employee(-columns => [qw/firstname lastname/])} @$recent_activities; =head3 Data export : just regular hashrefs Export the data : get related records and insert them into a data tree in memory; then remove all class information and export that tree. $_->expand('activities') foreach @$empl_D; my $export = My::Schema->unbless({employees => $empl_D}); use Data::Dumper; print Dumper ($export); # export as PerlDump use XML::Simple; print XMLout ($export); # export as XML use JSON; print to_json($export); # export as Javascript use YAML; print Dump ($export); # export as YAML B: the C step is optional; it is proposed here because some exporter modules will not work if they encounter a blessed reference. =head3 Database join Select associated tables directly from a database join, in one single SQL statement (instead of iterating through role methods). my $lst = My::Schema->join(qw/Employee activities department/) ->select(-columns => [qw/lastname dept_name d_begin/], -where => {d_begin => {'>=' => '2000-01-01'}}); Same thing, but forcing INNER joins my $lst = My::Schema->join(qw/Employee <=> activities <=> department/) ->select(...); =head3 Statements and pagination Instead of retrieving directly a list or records, get a L : my $statement = My::Schema->join(qw/Employee activities department/) ->select(-columns => [qw/lastname dept_name d_begin/], -where => {d_begin => {'>=' => '2000-01-01'}}, -result_as => 'statement'); Retrieve a single row from the statement my $single_row = $statement->next or die "no more records"; Retrieve several rows at once my $rows = $statement->next(10); # arrayref Go to a specific page and retrieve the corresponding rows my $statement = My::Schema->join(qw/Employee activities department/) ->select(-columns => [qw/lastname dept_name d_begin/], -result_as => 'statement', -page_size => 10); $statement->goto_page(3); # absolute page positioning $statement->shift_pages(-2); # relative page positioning my ($first, $last) = $statement->page_boundaries; print "displaying rows $first to $last:"; some_print_row_method($_) foreach @{$statement->page_rows}; =head3 Efficient use of statements For fetching related rows : prepare a statement before the loop, execute it at each iteration. my $statement = $schema->table($name)->join(qw/role1 role2/); $statement->prepare(-columns => ..., -where => ...); my $list = $schema->table($name)->select(...); foreach my $obj (@$list) { my $related_rows = $statement->execute($obj)->all; # or my $related_rows = $statement->bind($obj)->select; ... } Fast statement : each data row is retrieved into the same memory location (avoids the overhead of allocating a hashref for each row). Faster, but such rows cannot be accumulated into an array (they must be used immediately) : my $fast_stmt = ..->select(..., -result_as => "fast_statement"); while (my $row = $fast_stmt->next) { do_something_immediately_with($row); } =head3 Insert my $table = $schema->table($table_name); # If you provide the primary key (called 'my_code' in this example): $table->insert({my_code => $pk_val, field1 => $val1, field2 => $val2, ...}); # If your database provides the primary key: my $id = $table->insert({field1 => $val1, field2 => $val2, ...}); # This assumes your DBD driver implements last_insert_id. # If not, you can provide one as an option to the schema. # Insert multiple records using a list of arrayrefs. # First arrayref defines column names $table->insert( [qw/ field1 field2 /], [qw/ val11 val12 /], [qw/ val22 val22 /], ); # Or just insert a list of hashes $table->insert( {field1 => val11, field2 => val12}, {field2 => val21, field2 => val22}, ); # insertion through the association Employee - Activity $an_employee->insert_into_activities({d_begin => $today, dpt_id => $dpt}); =head3 Update # update on a set of fields, primary key included my $table = $schema->table($table_name); $table->update({pk_field => $pk, field1 => $val1, field2 => $val2, ...}); # update on a set of fields, primary key passed separately $table->update(@primary_key, {field1 => $val1, field2 => $val2, ...}); # bulk update $table->update(-set => {field1 => $val1, field2 => $val2, ...}, -where => \%condition); # invoking instances instead of table classes $obj->update({field1 => $val1, ...}); # updates specified fields $obj->update; # updates all fields stored in memory =head3 Delete # invoking a table class my $table = $schema->table($table_name); $table->delete(@primary_key); # invoking an instance $obj->delete; =head1 DESCRIPTION =head2 Introduction C is a framework for building Perl abstractions (classes, objects and methods) that interact with relational database management systems (RDBMS). Of course the ubiquitous L module is used as a basic layer for communicating with databases; on top of that, C provides facilities for generating SQL queries, joining tables automatically, navigating through the results, converting values, and building complex datastructures so that other modules can conveniently exploit the data. =head2 Perl ORMs There are many other CPAN modules offering somewhat similar features, like L, L, L, L, L, L, just to name a few well-known alternatives. Frameworks in this family are called I (ORMs) -- see L. The mere fact that Perl ORMs are so numerous demonstrates that there is more than one way to do it! For various reasons, none of these did fit nicely in my context, so I decided to write C. Of course there might be also some reasons why C will not fit in I context, so just do your own shopping. Comparing various ORMs is complex and time-consuming, because of the many issues and design dimensions involved; as far as I know, there is no thorough comparison summary, but here are some pointers : =over =item * general discussion on RDBMS - Perl mappings at L (good but outdated). =item * L =item * L, a detailed comparison between Rose::DB and DBIx::Class. =back =head2 Strengths of C The L chapter of this documentation will help you understand the philosophy of C. Just as a summary, here are some of its strong points : =over =item * Centralized, UML-style declaration of tables and relationships (instead of many files with declarations such as 'has_many', 'belongs_to', etc.) =item * efficiency through fine control of collaboration with the DBI layer (prepare/execute, fetch into reusable memory location, etc.) =item * uses L for an improved API over L (named parameters, additional clauses, simplified 'order_by', support for values with associated datatypes, etc.) =item * clear conceptual distinction between =over =item * data sources (tables and joins), =item * database statements (stateful objects representing stepwise building of an SQL query and stepwise retrieval of results), =item * data rows (lightweight hashrefs containing nothing but column names and values) =back =item * joins with simple syntax and possible override of default INNER JOIN/LEFT JOIN properties; instances of joins multiply inherit from their member tables. =item * named placeholders =item * nested, cross-database transactions =item * choice between 'single-schema' mode (default, more economical) and 'multi-schema' mode (optional, more flexible, but a little more costly in memory) =back C is used in production within a mission-critical application with several hundred users, for managing Geneva courts of law. =head2 Limitations Here are some current limitations of C : =over =item no schema versioning C knows very little about the database schema (only tables, primary and foreign keys, and possibly some columns, if they need special 'Types'); therefore it provides no support for schema changes (and seldom needs to know about them). =item no object caching nor 'dirty columns' C does not keep track of data mutations in memory, and therefore provides no support for automatically propagating changes into the database; the client code has explicitly manage C and C operations. =item no 'cascaded update' nor 'insert or update' Cascaded inserts and deletes are supported, but not cascaded updates. This would need 'insert or update', which at the moment is not supported either. =back =head2 Backwards compatibility Major version 2.0 and 1.0 introduced some incompatible changes in the architecture (see L and L). Compatibility layers can be loaded on demand by supplying the desired version number upon loading C : use DBIx::DataModel 2.0 -compatibility => 0.8; =head1 INDEX TO THE DOCUMENTATION Although the basic principles are quite simple, there are many details to discuss, so the documentation is quite long. In an attempt to accomodate for different needs of readers, it has been structured as follows : =over =item * The L chapter covers the architecture of C, its main distinctive features and the motivation for such features; it is of interest if you are comparing various ORMs, or if you want to globally understand how C works, and what it can or cannot do. This chapter also details the concept of B, which underlies all SELECT requests to the database. =item * The L chapter is a guided tour that summarizes the main steps to get started with the framework. =item * The L chapter is a complete reference to all methods, structured along usage steps : creating a schema, populating it with table and associations, parameterizing the framework, and finally data retrieval and manipulation methods. =item * The L chapter discusses how this framework interacts with its context (Perl namespaces, DBI layer, etc.), and how to work with self-referential associations. =item * The L chapter documents the internal structure of the framework, for programmers who might be interested in extending it. =item * The L defines terms used in this documentation, and points to the software constructs that implement these terms. =item * The L and L chapters summarize the differences with previous versions. =item * The L documentation explains how to automatically generate a schema from a C connection, from a L description or from an existing C schema. =item * The L documentation documents the methods of statements (not included in the general L chapter). =back Presentation slides are also available at L =head1 SIDE-EFFECTS Upon loading, L adds a coderef into global C<@INC> (see L), so that it can take control and generate a class on the fly when retrieving frozen objects from L. This should be totally harmless unless you do some very special things with C<@INC>. =head1 SUPPORT AND CONTACT Bugs should be reported via the CPAN bug tracker at L. There is a discussion group at L. Sources are stored in an open repository at L. =head1 AUTHOR Laurent Dami, Elaurent.dami AT etat ge chE =head1 ACKNOWLEDGEMENTS Thanks to Ross Attril Cedric Bouvier Terrence Brannon Alex Solovey Sergiy Zuban who contributed with ideas, bug fixes and/or improvements. =head1 COPYRIGHT AND LICENSE Copyright 2006-2013 by Laurent Dami. This library is free software; you can redistribute it and/or modify it under the same terms as Perl itself.