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DBIx::DataModel::Doc::Quickstart - Get quickly started with DBIx::DataModel


This chapter is part of the DBIx::DataModel manual.

This chapter is a tutorial that shows the main steps to get started with DBIx::DataModel. The goal here is conciseness, not completeness; a full reference is given in the REFERENCE chapter.

The tutorial is a gentle expansion of the examples given in the SYNOPSIS, namely a small human resources management system.


Before starting with DBIx::DataModel, you should have installed CPAN modules DBI and SQL::Abstract. You also need a database management system with a DBD driver.

Use your database modeling tool to create some tables for employees, departments, activities (an employee working in a department from a start date to an end date), and employee skills. If you have no modeling tool, you can also feed something like the following SQL code to the database

  CREATE TABLE t_employee (
    lastname   TEXT    NOT NULL,
    firstname  TEXT,
    d_birth    DATE 
  CREATE TABLE t_department (
    dpt_code   VARCHAR(5) PRIMARY KEY,
    dpt_name   TEXT    NOT NULL 
  CREATE TABLE t_activity (
    emp_id     INTEGER NOT NULL REFERENCES t_employee(emp_id),
    dpt_code   VARCHAR(5) NOT NULL REFERENCES t_department(dpt_code),
    d_begin    DATE    NOT NULL,
    d_end      DATE
  CREATE TABLE t_skill (
    skill_code VARCHAR(2) PRIMARY KEY,
    skill_name TEXT    NOT NULL 
  CREATE TABLE t_employee_skill (
    emp_id         INTEGER NOT NULL REFERENCES t_employee(emp_id),
    skill_code     VARCHAR(2)  NOT NULL REFERENCES t_skill(skill_code),
    CONSTRAINT PRIMARY KEY (emp_id, skill_code)

As can be seen from this SQL, we assume that the primary keys for t_employee and t_activity are generated automatically by the RDBMS. Primary keys for other tables are character codes and therefore should be supplied by the client program. We decided to use the suffixes _id for auto-generated keys, and _code for user-supplied codes.


DBIx::DataModel needs to acquire some knowledge about the datamodel. The rest of this chapter will go through the steps to manually write the necessary declarations, which are quite concise; however, you may gain some time by using DBIx::DataModel::Schema::Generator to automatically create a skeleton of these declarations.

First declare a schema :

  use DBIx::DataModel;

Here we have chosen a simple acronym HR as the schema name, but it could as well have been something like Human::Resources.

The schema now is a Perl class, so we invoke its Table method to declare the first table within the schema :

  HR->Table(qw/Employee      t_employee        emp_id/);

This creates a new Perl class named HR::Employee (the schema name HR has been automatically prepended before the table name). The second argument t_employee is the database table, and the third argument emp_id is the primary key. So far nothing is declared about other columns in the table.

Other tables are declared in a similar fashion :

  HR->Table(qw/Department    t_department      dpt_code/);
  HR->Table(qw/Activity      t_activity        act_id/);
  HR->Table(qw/Skill         t_skill           skill_code/);
  HR->Table(qw/EmployeeSkill t_employee_skill  emp_id  skill_code/);

This last declaration has 4 arguments because the primary key ranges over 2 columns.


RDBMS will usually require that dates be in ISO format of shape yyyy-mm-dd. Let's assume our users are European and want to see and enter dates of shape dd.mm.yyyy. Insert of converting back and forth within the client code, it's easier to do it at the ORM level. So we define conversion routines within a "Date" column type

  HR->ColumnType(Date => 
     fromDB => sub {$_[0] =~ s/(\d\d\d\d)-(\d\d)-(\d\d)/$3.$2.$1/   if $_[0]},
     toDB   => sub {$_[0] =~ s/(\d\d)\.(\d\d)\.(\d\d\d\d)/$3-$2-$1/ if $_[0]},
     validate => sub {$_[0] =~ m/\d\d\.\d\d\.\d\d\d\d/});

and then apply this type to the appropriate columns

  HR::Employee->ColumnType(Date => qw/d_birth/);
  HR::Activity->ColumnType(Date => qw/d_begin d_end/);

Here we just perform scalar conversions; another design choice could be to "inflate" the data to some kind of Perl objects.

Observe that ColumnType is overloaded : when invoked on a schema, it defines a column type; when invoked on a table, it applies the column type to some columns.


Basic associations

Now we will declare a binary association between departements and activities:

  HR->Association([qw/Department department  1 /],
                  [qw/Activity   activities  * /]);

The Association method takes two references to lists of arguments; in each of them, we find : class name, role name, multiplicity, and optionally the names of columns participating in the join. Here column names are not specified, so the method assumes that the join is on dpt_code (from the primary key of the class with multiplicity 1 in the association). This declaration corresponds to the following UML diagram :

  +----------------+                            +--------------+
  |                | 1                        * |              |
  | HR::Department +----------------------------+ HR::Activity |
  |                | department      activities |              |
  +----------------+                            +--------------+

Like when reading the diagram, the declaration should be read crosswise : here we are stating that a department may be associated with several activities; therefore the HR::Department class will contain an activities method which returns an arrayref. Conversely, an activity is associated with exactly one department, so the HR::Activity class will contain a department method which returns a single instance of HR::Department.

Since associations are symmetric, the two arrayrefs in the Association declaration could as well be given in the reverse order, yielding exactly the same effect.


The second association could be defined in a similar way; but here we will introduce the new concept of composition.

  HR->Composition([qw/Employee   employee    1 /],
                  [qw/Activity   activities  * /]);

This looks exactly like an association declaration; but it states that an activity somehow "belongs" to an employee (cannot exist without being attached to an employee, and is often created and deleted together with the employee). In a UML class diagram, this would be pictured with a black diamond on the Employee side. Using a composition instead of an association in this particular example would perhaps be debated by some data modelers; but at least it allows us to illustrate the concept.

A composition declaration behaves in all respects like an association. The main difference is in insert and delete methods, which will be able to perform more complex operations on data trees : for example it will be possible in one method call to insert an employee together with its activities. Compositions also support auto-expansion of data trees through the AutoExpand method.

Many-to-many associations

Now comes the association between employees and skills, which is a many-to-many association. This happens in two steps: first we declare as usual the associations with the linking table :

  HR->Association([qw/Employee      employee   1 /],
                  [qw/EmployeeSkill emp_skills * /]);

  HR->Association([qw/Skill         skill      1 /],
                  [qw/EmployeeSkill emp_skills * /]);

Then we declare the many-to-many association:

  HR->Association([qw/Employee  employees  *  emp_skills employee/],
                  [qw/Skill     skills     *  emp_skills skill   /]);

This looks almost exactly like the previous declarations, except that the last arguments are no longer column names, but rather role names: these are the sequences of roles to follow in order to implement the association. This example is just an appetizer; more explanations are provided in the reference section.


To use the schema, we first need to supply it with a database connection :

  my $dbh = DBI->connect(...); # parameters according to your RDBMS
  HR->dbh($dbh);               # give $dbh handle to the schema

Now we can start populating the database:

  my ($bach_id, $berlioz_id, $monteverdi_id) = 
    HR::Employee->insert({firstname => "Johann",  lastname => "Bach"      },
                         {firstname => "Hector",  lastname => "Berlioz"   },
                         {firstname => "Claudio", lastname => "Monteverdi"});

Observe that several rows can be created at once (of course you get the same result by calling insert() several times). According to our earlier assumptions, keys are generated automatically within the database, so they need not be supplied here. The return value of the method is the list of generated ids (provided that your database driver supports DBI's last_insert_id method).

Similarly, we create some departments and skills (here with explicit primary keys) :

  HR::Department->insert({dpt_code => "CPT",  dpt_name => "Counterpoint" },
                         {dpt_code => "ORCH", dpt_name => "Orchestration"});

  HR::Skills->insert({skill_code => "VL",  skill_name => "Violin"  },
                     {skill_code => "KB",  skill_name => "Keyboard"},
                     {skill_code => "GT",  skill_name => "Guitar"},

To perform updates, there is either a class method or an object method. Here is an example with the class method :

  HR::Employee->update($bach_id => {firstname => "Johann Sebastian"});

Associations have their own insert methods, named insert_into_* :

  my $bach = HR::Employee->fetch($bach_id); # get single record from prim.key
  $bach->insert_into_activities({d_begin => '01.01.1695',
                                 d_end   => '18.07.1750',
                                 dpt_code => 'CPT'});
  $bach->insert_into_emp_skills({skill_code => 'VL'},
                                {skill_code => 'KB'});

Compositions implement cascaded inserts from a given data tree :

  HR::Employee->insert({firstname  => "Richard",  
                        lastname   => "Strauss",
                        activities => [ {d_begin  => '01.01.1874',
                                         d_end    => '08.09.1949',
                                         dpt_code => 'ORCH'      } ]});

The select() method retrieves several records from a class :

  my $all_employees = HR::Employee->select; 
  foreach my $emp (@$all_employees) {

or maybe we want something more specific :

  my @columns  = qw/firstname lastname/;
  my %criteria = (lastname => {-like => 'B%'});
  my $some_employees 
     = HR::Employee->select(-columns => \@columns,
                            -where   => \%criteria,
                            -orderBy => 'd_birth');

From a given object, role methods allow us to get associated objects :

  foreach my $emp (@$all_employees) {
    print "$emp->{firstname} $emp->{lastname} ";
    my @skill_names = map {$_->{skill_name}  }} @{$emp->skills};
    print " has skills ", join(", ", @skill_names) if @skill_names;

Passing arguments to role methods, we can restrict to specific columns or specific rows, exactly like the select() method :

  my @columns = qw/d_begin d_end/;
  my %criteria = (d_end => undef);
  my $current_activities = $someEmp->activities(-columns => \@columns,
                                                -where   => \%criteria);

And it is possible to join on several roles at once:

  my $result = $someEmp->join(qw/activities department/)
                       ->select(-columns => \@columns,
                                -where   => \%criteria);

This concludes our short tutorial. More examples are given in the Reference chapter.