Documentation 1.x


Pomm is a fast, lightweight, efficient model manager for Postgresql written in PHP. It can be seen as an enhanced object hydrator above PHP's native Postgresql library with the following features:

  • Database Inspector to build automatically your PHP model files (support inheritance).
  • Postgresql's schemas are mapped to PHP namespaces.
  • PHP <=> Postgres type converter that support HStore, geometric types, objects, ranges etc.
  • Lazy fetching for results.
  • Hydration filters trough PHP callables.
  • Field selector methods for all SQL queries.
  • Identity mapper with several different algorithms available.

Databases and converters

Service: the database provider

Database class and configuration

The Service class just stores the Database instances and provides convenient methods to create connections from them. It is mainly intended to be used with dependency injection containers used by some popular frameworks. The Database class has different roles:

  • Connection builder and pool.
  • Converters holder.
  • Configuration holder.

It is either possible to instance Database class alone or use the Service class to do so. The simplest way to get a database instance is:

$database = new Pomm\Connection\Database(array(
    'name' => 'database_name',
    'dsn' => 'pgsql://user:pass@host:port/db_name'

Database expected parameters are:

  • dsn (string, mandatory): Connection string (see DSN).
  • name (string, optional, default: physical database name): Logical database name that is used as primary namespace for PHP entity object.
  • configuration (array, optional, see Connection configuration below): Client configuration for each connection.
  • isolation (string, optional, default: ISOLATION_READ_COMMITTED, see Standard transactions): isolation level used in transactions.
  • identity_mapper (string, optional, default: Smart, see Identity mappers below): default identity mapper class name for connections.

There are several ways to declare databases to the service class. Either you use the constructor passing an array "name" => "connection parameters" or you can use the setDatabase() method of the service class.:

# The two examples below are equivalent
# Using the constructor
$service = new Pomm\Service(array(
  'db_one' => array(
    'dsn' => 'pgsql://user:pass@host:port/db_a'
  'db_two' => array(
    'dsn'   => 'pgsql://otheruser:hispass@!/path/to/socket/directory!/db_b',
    'class' => 'App\MyDb',
    'identity_mapper' => 'App\MyIdentityMapper',
    'name'  => 'my_db'

# Using the setDatabase method
$service = new Pomm\Service();
$service->setDatabase('db_one', new Pomm\Connection\Database(array(
  'dsn' => 'pgsql://user:pass@host:port/db_a'
$service->setDatabase('db_two', new App\MyDb(array(
  'dsn' => 'pgsql://otheruser:hispass@!/path/to/socket/directory!/db_b',
  'identity_mapper' => 'App\MyIdentityMapper',
  'name'  => 'my_db'

The setDatabase method is used internally by the constructor. Once registered, you can retrieve the databases with their name by calling the getDatabase method passing the name as argument. If no name is given, the first declared Database will be returned.


The dsn parameter format is important because it interacts with Postgresql server's access policy.

  • socket connection
  • pgsql://user/database Connect user to the db database without password through the Unix socket system.
  • pgsql://user:pass/database The same but with password.
  • pgsql://user:pass@!/path/to/socket!/database When the socket is not in the default directory, it is possible to specify it in the host part of the DSN. Note it is surrounded by '!' and there are NO ending /. Using the «!» as delimiter assumes there are no «!» in your socket's path. But you don't have «!» in your socket's path do you ?
  • pgsql://user@!/path/to/socket!:port/database Postgresql's listening socket's names are the same as TCP ports. If different than default socket, specify it in the port part.
  • TCP connection
  • pgsql://user@host/database Connect user to the db database on host host using TCP/IP.
  • pgsql://user:pass@host:port/database The same but with password and TCP port specified.

Connection configuration

Connections set client parameters at launch (see documentation). Default parameters are the following
  • bytea_output = escape
  • intervalstyle = ISO_8601
  • datestyle = ISO

These parameters are important since the default converters expect client output to be formatted this way. If you change these parameters, register the according converter.

Some other parameters can be tuned that way, by default they are set by the server's default configuration:
  • statement_timeout
  • lock_timeout
  • TimeZone
  • extra_float_digits


Built-in converters

The Database class brings access to mechanisms to create connections and also to register converters. A Converter is a class that translates a data type between PHP and Postgresql.

By default, the following converters are registered, this means you can use them without configuring anything:
  • Boolean: convert Postgresql booleans 't' and 'f' to/from PHP boolean values
  • Number: convert Postgresql 'smallint', 'bigint', 'integer', 'decimal', 'numeric', 'real', 'double precision', 'serial', 'bigserial' types to numbers
  • String: convert Postgresql 'varchar', 'char', 'bpchar', 'uuid', 'tsvector', 'xml', 'json' (Pg 9.2), 'name' and 'text' into PHP string
  • Timestamp: convert Postgresql 'timestamp', 'date', 'time' to PHP DateTime instance.
  • Interval: convert Postgresql's 'interval' type into PHP DateInterval instance.
  • Binary: convert Postgresql's 'bytea' type into PHP binary string.
  • Array: convert Postgresql arrays from/to PHP arrays.
  • TsRange: convert Postgresql 'tsrange', 'daterange' to \Pomm\Type\TsRange instance (Pg 9.2).
  • NumberRange: convert Postgresql 'int4range', 'int8range', 'numrange` into \Pomm\Type\NumberRange instance (Pg 9.2).

Registering converters

Other types are natively available in Postgresql but are not loaded automatically at startup by Pomm.
  • Point: convert Postgresql 'point' representation as Pomm\Type\Point instance.
  • Segment: convert 'segment' representation as Pomm\Type\Segment.
  • Circle: 'convert circle' representation as Pomm\Type\Circle.

Postgresql contribs come with handy extra data type (like HStore, a key => value array and LTree a materialized path data type). If you use these types in your database you have to register the according converters from your database instance:

$database->registerConverter('HStore', new Pomm\Converter\PgHStore(), array('public.hstore'));
Arguments to instantiate a Converter are the following:
  • the first argument is the converter name.
  • the second argument is the instance of the Converter
  • the third argument is a Postgresql type or a set of types for Pomm to link them with the given converter.

Although Postgresql native types are stored in an internal schema hence are reachable from everywhere without mention to fully qualified name, user defined types and extensions definitions are stored in user schemas (by default public). It is advised to provide the fqn for user defined types and extensions.

Creating your own Database class

If your database has a lot of custom types, it is a good idea to create your own Database class.:

class MyDatabase extends Pomm\Connection\Database
  protected function initialize()

      new Pomm\Converter\Hstore(), array('hstore'));

      new Pomm\Converter\Pgpoint(), array('point'));

      new Pomm\Converter\PgCircle(), array('circle'));

This way, converters will be automatically registered at instantiation.

Converters and types


In case your database uses DOMAIN types, you can associate them with an already registered converter. The registerTypeForConverter() method stands for that.:

  ->registerTypeForConverter('public.email_address', 'String');

In the example above, the database contains a domain email_address which is a subtype of varchar so it is associated with the built-in converter String.


registerTypeForConverter and registerConverter methods implement the fluid interface so you can chain calls.

Composite types

Composite types are particularly useful to store complex set of data and store them as they were objects:

CREATE TYPE postal_address AS (place text, postal_code char(5), city varchar, cedex char);

CREATE TABLE customer (
    customer_id uuid PRIMARY KEY,
    billing_address postal_address NOT NULL CHECK
        ((billing_address).place IS NOT NULL AND (billing_address).city IS NOT NULL AND (billing_address).postal_code IS NOT NULL)

If such types exist in your database, they must be registered so Pomm can convert them to an according array using the PgRow converter:

    new \Pomm\Converter\PgRow(
        new \Pomm\Object\RowStructure(array('place' => 'text', 'postal_code' => 'char', 'city' => 'varchar', 'cedex' => 'char'))

This way, the composite types can be used as is in the map classes:

protected function intitialize()

    $this->addField('customer_id', 'uuid')
        ->addField('billing_address', 'public.postal_address')

This will store, in a field named billing_address an array formatted with the given attributes. It is important to understand they must be used like fixed arrays, this means all keys must be filled even if the value is NULL to save the entity:

$entity['billing_address'] = array('place' => 'some_place', 'postal_code' => '44000', 'city' => 'Nantes');

This will throw an exception since the cedex key is missing.

Writing custom types

One solution to prevent the problem presented above is to use objects instead of arrays. The converter accepts a third argument class_name that will spawn an instance from the array if set:

    new \Pomm\Converter\PgRow(
        new \Pomm\Object\RowStructure(array('place' => 'text', 'postal_code' => 'char', 'city' => 'varchar', 'cedex' => 'char')),
        '\Namespace\Of\Type\Address' // <- provide a class name here

The Address class is simplistic, since it must be a fixed typed class, it may just extends \Pomm\Type\Composite and declare attributes as public:

class Address extends \Pomm\Type\Composite
    public $place;
    public $postal_code;
    public $city;
    public $cedex;


It is important that the attibutes be public so the values can easily be extracted into an array during the conversion process. Protected and private attributes will be ignored by the converter.

This type can directly be used with the entities:

$entity['billing_address'] = new \Namespace\Of\Type\Address(array('place' => 'some_place', 'postal_code' => '44000', 'city' => 'Nantes'));

This is useful in many ways, one of them being the ability to code proper accessors for the composite type instance.

Entity converter

In Postgresql, creating a table means creating a new type with the table's fields definition. Hence, it is possible to use that data type in other tables or use them as objects in your SQL queries. Pomm proposes a special converter to do so: the PgEntity converter. Passing the table data type name and the associated entity class name will grant you with embedded entities.

  ->registerConverter('MyEntity', new \Pomm\Converter\PgEntity($my_entity_map), array('my_schema.my_entity));

Writing your own converters

All converters must implement the Pomm\Converter\ConverterInterface. This interface makes converters to have two methods:
  • fromPg($data, $type): converts string data fetched from a Postgresql result to a PHP representation.
  • toPg($data, $type): converts PHP data representation to a string that will be used in a SQL query.

Spawning connections

Database instances are also connections provider trough two methods:

  • createConnection() force the creation of a new connection.
  • getConnection() return an existing Connection instance if any, create it otherwise.

It is important to understand that connections hold a lot of context (entity caching trough the mapper, prepared statements etc.), enforce the creation of a new connection set up a new bare context. The most common way to get a connection is:

$connection = $database->getConnection();



A connection represents a link to the database. It owns several responsibilities:
  • Map classes provider
  • Identity mapper
  • Prepared statements pooling
  • Transactions handling
  • Queries execution
  • Logger handling

Connections are lazy. This means unless a communication is needed with the database server, no sessions are open.

Map classes provider

Connections are a pool of map instances. This way, a connection will always provide the same instance for the same map class:

$student_map = $connection->getMapFor('College\School\Student');

Identity mappers

Connections are also the way to tell the map classes to use or not an IdentityMapper. An identity mapper is an index kept by the connection and shared amongst the map instances. This index ensures that when an object is retrieved twice from the database, the same Object instance will be returned. This is a very powerful (and dangerous) feature.

There are two ways to declare an identity mapper to your connections:
  • in the Database parameters. All the connections created for this database will use the given IdentityMapper class.
  • when instanciating the connection through the createConnection() call. This enforces the parameter given to the Database class if any.
$map = $database()
  ->createConnection(new \Pomm\Identity\IdentityMapperSmart())

$student1 = $map->findByPK(array('id' => 3));
$student2 = $map->findByPK(array('id' => 3));

echo $student2->getName();    // plop
It is often a good idea to have an identity mapper by default, but in some cases you will want to switch it off and ensure all objects you fetch from the database do not come from the mapper. This is possible passing the Connection an instance of IdentityMapperNone. It will never keep any instances. There are two other types of identity mappers:
  • IdentityMapperStrict which always return an instance if it is in the index.
  • IdentityMapperSmart which checks if the instance has not been deleted. If data are fetched from the db, it checks if the instance kept in the index has not been modified. If not, it merges the fetched values with its instance.

It is of course always possible to remove an instance from the mapper by calling the removeInstance(). You can create your own identity mapper, just make sure your class implement the IdentityMapperInterface. Be aware the mapper is called for each values fetched from the database so it has a real impact on performances.

Important The identity mappers strict and smart rely on the use of primary keys to identify records. If you use a table without primary keys, these identity mappers will NOT store any of these entities.


Standard transactions

By default, connections are in auto-commit mode which means every change in the database is committed on the fly. Connections offer the way to enter in transaction mode:


    # do things here
catch (Pomm\Exception\Exception $e)

The transaction type is determined by ISOLATION LEVEL you set in your connection's parameters (see Database class and configuration)

Isolation level must be one of Pomm\Connection\Connection::ISOLATION_READ_COMMITTED, ISOLATION_READ_REPEATABLE or ISOLATION_SERIALIZABLE. Check your Postgresql version for the available levels. Starting from pg 9.1, what was called SERIALIZABLE is called READ_REPEATABLE and SERIALIZABLE is a race for the first transaction to COMMIT. This means if the transaction fails, you may just try again until it works. Check the Postgresql documentation about transactions for details.

Partial transactions and savepoints

Sometime, you may need to split transactions into parts and be able to perform partial rollback. Postgresql lets you use save points in your transaction:

    # do things here
catch (Pomm\Exception\Exception $e)
    // The whole transaction is rolled back
    throw $e;
    # do other things
catch (Pomm\Exception\Exception $e)
    // only statments after savepoint A are rolled back

Prepared statements

Connections are a pool of prepared statements. Every time a query is sent to the server, it is prepared, executed and stored until the connection is shut down. This way, if a query is issued a second time, the statement does not need to be parsed again. It is somehow possible to use them directly:

$sql = "SELECT field1, ..., fieldX FROM some_table WHERE a_field > $* AND another_field @> $*;"
$query = $connection->createPreparedQuery($sql);

$collection_1 = $query->execute(array($value01, $value02));
$collection_2 = $query->execute(array($value11, $value12));

Note the placeholder for values to be escaped is the symbol $*. This is different from what is to be used with PHP pgsql library and also different from PDO placeholders. The problem with PHP native pgsql library is the placeholders are in the form $n where n is the position. Using positional parameters is a pain when building queries because the position of the parameters you may add is not known. PDO's placeholders is the ?. This conflicts with some operators in Postgresql. If you migrate from an existing project to Pomm, queries must be checked to be compliant with the $* placeholder.

Notifications and observers

Aside the transaction engine, Postgresql proposes an asynchronous messaging system. To benefit from this useful feature, Pomm's connection let the possibility to spawn observers and to trigger events using the following methods:
  • createObserver()
  • notify()


createObserver() returns an Observer instance. This instance can listen to a given event and return the payload if any when an event is triggered:

$observer = $connection

while(!$data = $observer->getNotification())

$payload = $data['payload']; // payload if any

Sending a notification

To trigger a notification to observers, use the notify() method:

$connection->notify('an_event', 'a payload');


Connections can register any logger class that implements \Psr\Logger\LoggerInterface using the setLogger() method.

All exceptions will be logged using ERROR level. Connecting problems will issue a ALERT level log message.

Map classes


Map classes are the central point of Pomm because
  • they are a bridge between the database and entities
  • they own the structure of their corresponding entities
  • They act as entity providers

Every action you will perform with your entities will use a Map class. They are roughly the equivalent of Propel's Peer classes or Doctrine's repositories. Although it might looks like Propel, it is important to understand unlike the normal Active Record design pattern, entities do not even know their structure and how to save themselves. You have to use their relative Map class to save them.

Map classes represent a structure in the database and provide methods to retrieve and save data with this structure. To be short, one table or view => one map class.

To create the link between a database and entities, all Map classes must at the end extends \Pomm\Object\BaseObjectMap. This class implements methods that directly interact with the database using the PDO layer. These methods will be explained in the chapter Querying the database.

The structure of the map classes can be automatically guessed from the database hence it is possible to generate the structure part of the map files from the command line (see below). If these classes can be generated, it is advisable not to modify them by hand because modifications would be lost at the next generation. This is why Map classes are split using inheritance:
  • BaseYourEntityMap which are abstract classes inheriting from \Pomm\Object\BaseObjectMap
  • YourEntityMap inheriting from BaseYourEntityMap.

BaseYourEntityMap can be skipped but since Pomm proposes automatic code generation, this file can be regenerated over and over without you to loose precious custom code. This is why this file owns the data structure read from the database. If you create a map file that does not rely on automatic generation, it has not not to use a BaseMap file.


Introspected tables

When Map classes are instantiated, the method initialize is triggered. This method is responsible of setting various structural elements:
  • object_name: the related table name
  • object_class: the related entity's fully qualified class name
  • field_structure: the fields with their corresponding Postgresql type
  • primary_key: an array with simple or composite primary key

If the table is stored in a special database schema, it must appear in the object_name attribute. If you do not use schemas, Postgresql will store everything in the public schema. You do not have to specify it in the object_name attribute but it will be used in the class namespace. As public is also a reserved keyword of PHP, the namespace for the public schema is PublicSchema.

Let's say we have the following table student in the public schema of the database college:

|   Column    |            Type               |
|  reference  | character(10)                 |
|  first_name | character varying             |
|  last_name  | character varying             |
|  birthdate  | timestamp without time zone   |
|  level      | smallint                      |
|  exam_dates | timestamp without time zone[] |

The last field exam_dates is an array of timestamps (see Arrays below). The corresponding PHP structure will be:


 namespace College\PublicSchema\Base;

 use Pomm\Object\BaseObjectMap;
 use Pomm\Exception\Exception;

 abstract class StudentMap extends BaseObjectMap
     public function initialize()
         $this->object_class =  '\College\PublicSchema\Student';
         $this->object_name  =  'student';

         $this->addField('reference', 'char');
         $this->addField('first_name', 'varchar');
         $this->addField('last_name', 'varchar');
         $this->addField('birthdate', 'timestamp');
         $this->addField('level', 'smallint');
         $this->addField('exam_dates', 'timestamp[]');

         $this->pk_fields = array('reference');

All generated map classes use PHP namespace. This namespace is composed by the database name and the database schema the table is located in. If database name is not supplied to the Database constructor (see Database class and configuration), the real database name is used. If by example, the previous table were in the school database schema, the following lines would change:


 namespace College\School\Base;
         $this->object_class =  'College\School\Student';
         $this->object_name  =  'school.student';


Postgresql supports arrays. An array can contain several data all from the same type. Pomm of course supports this feature using the [] notation after the converter declaration:

$this->addField('authors', 'varchar[]');   // Array of strings
$this->addField('locations', 'point[]');   // Array of points

The converter system handles that and the entities will be hydrated with an array of the according type depending on the given converter.

Temporary tables

Sometimes, you might want to create temporary tables. A map class can create its own table, modify it and destroy it. Let's imagine we have to create a temporary tables for students and their average scores in each discipline. The following map class could do the job:


namespace College\School;

use Pomm\Object\BaseObjectMap;
use Pomm\Object\BaseObject;
use Pomm\Query\Where;

class AverageStudentScoreMap extends BaseObjectMap
    public function initialize()
      $this->object_class =  'College\School\AverageStudentScore';
      $this->object_name  =  'school.average_student_score';

      $this->addField('reference', 'varchar');
      $this->addField('maths', 'numeric');
      $this->addField('physics', 'numeric');

    public function createTable()
      $sql = "CREATE TEMPORARY TABLE %s (reference VARCHAR PRIMARY KEY, ...

      $this->query(sprintf($sql, $this->getTableName()), array());

    public function dropTable()
      $sql = "DROP TABLE %s CASCADE";

      $this->query(sprintf($sql, $this->getTableName()), array());

You can create methods to change the table structure, add or drop columns etc. This is what it is done by example in the converter test script.

Creating entities

Map instances are entities builder, it is possible to create entities and save them in the same move:

$entity = $map->createObject(array('field1' => $value1, ...)); // This build an entity instance.
$entity = $map->createAndSaveObject(array('field1' => $value1, ...)); // This build and save an entity.
$collection = $map->createAndSaveObjects(array(array('field1' => $value01, ...), array('field1' => $value11, ...))); // Save entities and return a collection.

These methods are useful to push new data in the database but sometimes, data collected from the interface are not enough to save a database entity. This is the case when some values rely on Postgresql functions. The RawString type allow programmers to pass unescaped strings to the database:

$entity = $map->createAndSaveObject(array('field' => new \Pomm\Type\RawString('my_pg_function(...)')));

This will issue an insert statement like:

INSERT INTO some_table (field) VALUES (my_pg_function(...)) RETURNING ...

Querying the database

Create, update, drop

The main goal of the map classes is to provide a layer between a database and entities. They provide programmers with basic tools to save, update and delete entities trough saveOne(), updateOne() and deleteOne() methods.

$entity = $map->createObject(array('pika' => 'chu', 'plop' => false));

$map->saveOne($entity);     // INSERT


$map->saveOne($entity);     // UPDATE

As illustrated above, the saveOne() method saves an entity whatever it is an update or an insert. It is important to know that the internal state (see Life cycle) of the entity is used to determine if the object exists or not and choose between the INSERT or the UPDATE statement. Whatever is used, the whole structure is saved every time this method is called. In order just to update some fields, use the updateOne() method.


If the table related to this entity sets default values (like created_at field by example) they will be automatically hydrated in the entity.


$map->updateOne($entity, array('pika')); // UPDATE ... set pika='...'

$map->getPika();            // chu
$map->getPlop();            // true

In the example above, two fields are set and only one is updated. The result of this is the second field to be replaced with the value from the database.


$entity->isNew();           // false
$entity->isModified();        // false

The deleteOne() method is pretty straightforward. Like the other modifiers, it hydrates the entity with the deleted row from the database in case there are to be used elsewhere.

Built-in finders

The first time the base map classes are generated, the map classes and the entity classes will be also created. Using the example with student, the empty map file should look like this:

namespace College\School;

use College\School\Base\StudentMap as BaseStudentMap;
use Pomm\Exception\Exception;
use Pomm\Query\Where;
use College\School\Student;

class StudentMap extends BaseStudentMap

This is the place other finders are going to take place. As it extends BaseObjectMap via BaseStudentMap it already has some useful finders:

  • findAll(...) return all entities
  • findByPK(...) return a single entity
  • findWhere(...) perform a SELECT ... FROM my.table WHERE ...

Finders return either a Collection instance virtually containing all entities returned by the query (see Collections) or just a related model entity instance (like findByPK).


findAll is the simplest query that can be issued on a database set, it returns all the tuples of the set. This method takes a query suffix as optional argument. This is useful for query modifiers like LIMIT ... OFFSET or ORDER BY.

$map->findAll('ORDER BY created_at DESC LIMIT 5');

// corresponding query
  "field1" AS "field1",
ORDER BY created_at DESC LIMIT 5


If you are just interested by the suffix to paginate your queries, have a look at Pagers_.


The simplest way to create a query with Pomm is to use the findWhere() method.

findWhere($where, $values, $suffix)
returns a set of entities based on the given where clause. This clause can be a string or a Where instance.

It is possible to use it directly because we are in a Map class hence Pomm knows what table and fields to use in the query.

       birthdate > '1980-01-01
       first_name ILIKE '%an%'

// don't do that !
$students = $this->findWhere("birthdate > '1980-01-01' AND first_name ILIKE '%an%'");

Of course, this is not very useful, because the date is very likely to be a parameter. A finder getYoungerThan would be:

public function getYoungerThan(DateTime $date)
       birthdate > $date
       first_name ILIKE '%an%'
     birthdate DESC
   LIMIT 10

  return $this->findWhere("birthdate > $* AND first_name ILIKE $*",
      array($date, '%an%'),
      'ORDER BY birthdate DESC LIMIT 10'

All queries are prepared, this might increase the performance but it certainly increases the security. Passing the argument using the question mark makes it automatically to be escaped by the database and avoid SQL-injection attacks. If a suffix is passed, it is appended to the query as is. The suffix is intended to allow developers specifying the sorting order of a subset. As the query is prepared, a multiple query injection type attack is not directly possible but be careful if the values sent directly from an untrusted source.


The DateTime PHP instances can be passed as is, they will be converted into string internally.

AND, OR: The Where class

Sometimes, it is not possible to know in advance what will be the clauses of your query because it depends on variable factors. The Where class chains logical statements:

public function getYoungerThan(DateTime $date, $needle)
  $where = new Pomm\Query\Where("birthdate > $*", array($date));
  $where->andWhere('first_name ILIKE $*', array(sprintf('%%%s%%', $needle)));

  return $this->findWhere($where, null, 'ORDER BY birthdate DESC LIMIT 10');

The Where class has two very handy methods: andWhere and orWhere which can take string or another Where instance as argument. All methods return a Where instance so it is possible to chain the calls. The example above can be rewritten this way:

public function getYoungerThan(DateTime $date, $needle)
  $where = Pomm\Query\Where::create("birthdate > $*", array($date))
      ->andWhere('first_name ILIKE $*', array(sprintf('%%%s%%', $needle)))

  return $this->findWhere($where, null, 'ORDER BY birthdate DESC LIMIT 10');

Because the WHERE something IN (...) clause needs to declare as many '$*' as given parameters, it has its own constructor:

// WHERE (station_id, line_no) IN ((1, 1), (1, 3), ... );

$this->findWhere(Pomm\Query\Where::createWhereIn("(station_id, line_no)", array(array(1, 1), array(1, 3)))

The Where instances can be combined together with respect of the logical precedence:

$where1 = new Pomm\Query\Where('pika = $*', array('chu'));
$where2 = new Pomm\Query\Where('age < $*', array(18));

$where1->andWhere(Pomm\Query\Where::createWhereIn('other_id', array(1,2,3,5,7,11)));

echo $where1; // (pika = $* OR age < $*) AND other_id IN ($*,$*,$*,$*,$*,$*)

Fields methods

A very useful property of SQL sets is that they are extendibles. It possible to add a new field or remove an existing one in a SELECT very easily. All the generic finders described above use the following methods to know what fields to retrieve from queries:

  • getFields
  • getSelectFields($alias)
  • getGroupByFields($alias)

getFields($table_alias) is the parent of all the fields getters. It returns an array of the form field_alias => $table_alias.$field_name. Table alias is optional and can be omitted. All other fields getters use getFields internally and this is the method to be used to create fields getters.

getSelectFields($alias) is used by all the finders by also by the update, delete and insert methods in their RETURNING clause. Overloading this one will change their behavior also.

getGroupByFields($alias) is to be used in GROUP BY clauses. Note that Postgresql >= 9.1 does not enforce grouping all the fields present in the select as soon as they are grouped by primary key. So this method is to be used only when using Postgres 9.0.

The following example show how to modify the fields for a table containing user informations:

public function getSelectFields($alias = null)
    $fields = parent::getSelectFields($alias);
    $alias = is_null($alias) ? $alias."." : '';

    // We do never retrieve password informations

    // Add gravatar id in the select
    $fields['gravatar'] = sprintf("md5(%s.email_address)", $alias);

    return $fields;

// elsewhere in the code
$employee = $employee_map->findByPk(array('email' => ''));
$employee->has('password'); // false
$employee->get('gravatar'); // 6c3e76d8b31679442f089cd3e7edb48a


The example above shows the use of a Postgresql's function to calculate the gravatar field. It is obviously possible to use all Postgresql operators and functions in the fields, which makes this feature a very powerful ally.

Building custom queries

Even if generic finders may fulfill 90% of developers needs, it is possible to define your own finders using SQL. The generic structures of the SQL with Pomm follow the principle described below:


* The first string is provided by one fields getter method (see `Fields methods`_ above).
* The second string is the set's source, most of the time a table name. This is provided by the ``getTableName($alias)`` method.
* The last string is the where clause. If a ``Where`` instance is provided, it is as easy as casting it to String.

Fields formatters

Field getters return an array of fields. This array has to be processed to get a string of fields usable in a SQL query. This is the role of the fields formatters methods:

  • formatFields('method_name', 'table_alias') returns a string with a comma separated list of fields.
  • formatFieldsWithAlias('method_name', 'table_alias') same as above but with fields aliases.

These methods call the fields getter given as method_name and return the formatted list of fields:

$where = new \Pomm\Query\Where::create("age < $*", array(18))
    ->andWhere('main_teacher_id = $*', array(1));

$sql = "SELECT :table_fields FROM :table_name WHERE :conditions";

$sql = strtr($sql, array(
    ':table_fields' => $this->formatFieldsWithAlias('getSelectFields', 'my_table'),
    ':table_name'   => $this->getTableName('my_table'),
    ':conditions'   => (string) $where

return $this->query->($sql, $where->getValues());

This will perform the following query:

  "my_table.field1" AS "field1",
  "my_table.field2" AS "field2",
  a_table my_table
  age < $* AND main_teacher_id = $*

with parameter 1 = 18 and parameter 2 = 1.

Complex queries

The example above is roughly what is coded in findWhere.In real life, it is very likely one needs to join several database tables and their fields. Pomm makes it easy to get other map files from within any other map class.

// MyDatabase\Blog\PostMap Class
public function getBlogPostsWithCommentCount(Pomm\Query\Where $where)
  $comment_map = $this->connection->getMapFor('\MyDatabase\Blog\Comment');

  $sql = <<<_
    COUNT( as "comment_count"
    :post_table p
      LEFT JOIN :comment_table c ON
 = c.p_id

  $sql = strtr($sql, array(
      ':post_fields'        => $this->formatFieldsWithAlias('getSelectFields', 'p'),
      ':post_table'         => $this->getTableName(),
      ':comment_table'      => $comment_map->getTableName(),
      ':conditions'         => (string) $where,
      'post_groupby_fields' => $this->formatFields('getGroupByFields', 'p')

  return $this->query($sql, $where->getValues());

The query() method is available for custom queries. It takes 2 parameters, the SQL statement and an optional array of values to be escaped. Keep in mind, the number of values must match the '$*' Occurrences in the query.

Whatever the data fetched, Pomm will hydrate objects according to what is in structure definition of map class. Entities do not know about their structure they just contain data and methods. The entity instances returned here will have this extra field "comment_count" exactly as it would be a normal field. Of course, when updating, this field will be ignored and will not cause an error.

Virtual fields

Adding new fields in the SELECT trough the fields getter methods do not make them mapped to any known type hence not converted with the converter system. It is possible to assign these now "virtual fields" a converter.

// Map a field added in getSelectFields to then Interval converter.
$this->addVirtualField('created_since', 'Interval');

This feature is interesting since SQL queries can fetch objects directly:

SELECT author, array_agg(post) AS posts FROM author JOIN post ON post.author_id = GROUP BY author...;

| id |       name        |                  posts
|  1 | john doe          | "{('post 1', 1, 'some content'),(
|  2 | Edgar             | "{('other post', 2, 'Other content'),

Using an entity converter will make an entity instance fetched directly from the database. The example below creates a relationship between the author and the post tables getting all the posts from one author in an array of Post instances:

// YourDb\SchemaName\AuthorMap

public function getOneWithPosts($author_name)
    $remote_map = $this->connection->getMapFor('YourDb\SchemaName\Post');

    $sql = <<<_
      array_agg(post) AS posts
        LEFT JOIN :post_table ON
   = post.author_id
    WHERE = $*

    $sql = strtr($sql, array(
        ':author_fields' => $this->formatFieldsWithAlias('getSelectFields', 'author'),
        ':author_table' => $this->getTableName('author'),
        ':post_table' => $remote_map->getTableName('post'),
        ':author_groupby_fields' => $this->getGroupByFields('author')

    $this->addVirtualField('posts', '[]');

    return $this->query($sql, array($author_name));

In this example we assume the type has already been associated with the PgEntity converter with its map class (see Entity converter). The fetched Author instances will have an extra attribute posts containing an array of Post instances (see Arrays). This is a very powerful feature because any entity's related objects can be fetched from the database and hydrated on the fly.


Fetching results

The query() method return a Collection instance that holds the PDOStatement with the results. The Collection class implements the Countable and Iterator interfaces so they can be traversed using a foreach PHP statement to retrieve the results:

printf("Your search returned '%d' results.", $collection->count());

foreach($collection as $blog_post)
  printf("Blog post '%s' posted on '%s' by '%s'.",

Any particular result in a collection can be reached knowing the result's index. It is possible using the has() and get() methods:

# Get an object from the collection at a given index
# or create a new one if index does not exist
$object = $collection->has($index) ?  $collection->get($index) : new Object();
Collections have other handful methods like:
  • isFirst()
  • isLast()
  • isEmpty()
  • isOdd()
  • isEven()
  • getOddEven()
  • extract()

Collection filters

Pomm's Collection class can register filters. Filters are just functions that are executed after values were fetched from the database and before the object is hydrated with them (pre hydration filters). These filters take the array of fetched values as parameter. They return an array with values which are then given to the next filter and so on. After all filters have been executed, the values are hydrated in entity instance related the map the collection comes from.

$collection = $this->query($sql, $values);

$collection->registerFilter(function($values) {
    $values['good_pika'] = $values['pika'] == 'chu' ? 'Good' : 'Try again';

    return $values;

The code above register a filter that create an extra field in our result set. Every time a result is fetched, this anonymous function will be triggered and the resulting values will be hydrated in the entity.


Pager query methods

BaseObjectMap instances provide 2 methods that will grant programmers with a Pager class. paginateQuery() and the handy paginateFindWhere(). It adds the correct subset limitation at the end of queries. Of course, it assumes no LIMIT nor OFFSET sql clauses are already present in the given query.

The paginateFindWhere() method acts pretty much like the findWhere() method (see Built-in finders) which it uses internally. This means the condition can be either a string or a Pomm\Query\Where instance (see AND, OR: The Where class):

$pager = $student_map
  ->paginateFindWhere('age < $* OR gender = $*', array(19, 'F'), 'ORDER BY score ASC', 25, 4);

The example below ask Pomm to retrieve the fourth page of students that match some condition with 25 results per page.

The paginateQuery() acts like the query() method but it requires 2 SQL queries: the one that returns results and the one that counts the total number of rows that first query would return without paging.

Displaying a pager

Pager instances come with methods to display basic page informations like page count, current page, first result row etc. Here is an example of how to display a page in a twig template:

  {% for student in pager.getCollection() %}
    <li>{{ student }}</li>
  {% endfor %}
{% if pager.getLastPage() > 1 %}
<div class="pager"><p>
<a href="{{ app.url_generator.generate('news') }}">First</a>
{% if pager.isPreviousPage() %}
<a href="{{ app.url_generator.generate('news', {'page': pager.getPage - 1}) }}">Previous</a>
{% else %}
{% endif %}
News {{ pager.getResultMin() }} to {{ pager.getResultMax() }}
{% if pager.isNextPage() %}
<a href="{{ app.url_generator.generate('news', {'page': pager.getPage + 1} ) }}">Next</a>
{% else %}
{% endif %}
<a href="{{ app.url_generator.generate('news', {'page': pager.getLastPage} ) }}">Last</a>
{% endif %}



What is an Entity class ?

Entities are what programmers use in the end of the process. They are an object oriented implementation of the data retrieved from the database. Most of the time, these PHP classes are automatically generated by the introspection tool (see CreateBaseMapTool) but you can write your own classes by hand. They just have to extends the Pomm\Object\BaseObject class to know about status (see Life cycle). Important things to know about entities are they are schema less and they are data source agnostic.

By default, entities lie in the same directory than their map classes and de facto share the same namespace but this is only a convention.


namespace Database\Schema;

use Pomm\Object\BaseObject;
use Pomm\Exception\Exception;

class MyEntity extends BaseObject

Data source agnostic

Entities do not know anything about database in general. This means they do not know how to save, retrieve or update themselves (see Map classes for that). BaseObject children can be used to store data from web services, NoSQL database etc. They use the hydrate() method to get data and accessors to read / write data from them (see Living with entities below).

Schema less entities

Entities do not know anything about the structure of the tables, views etc. They are just flexible typed containers for data. They use PHP magic methods to simulate getters and setters on data they own (see Living with entities below). This is very powerful because entities can be accessed like arrays and still benefits from method overloads.


Entities do not know anything about their primary key either.

Living with entities


There are several ways to create entities.

$entity = new Database\Schema\MyEntity();

It is possible to directly specify values to the constructor:

$entity = new Database\Schema\MyEntity(array('value1' => $value1, ... ));

Entity's according map class also proposes methods to create entities (see Map classes).

Accessors and mutators

The abstract parent BaseObject uses magic getters and setters to dynamically build the according methods. Internally, all values are stored in an array. The methods set() and get() are the interface to this array:

$entity = new Database\Schema\MyEntity();
$entity->has('pika'); // false
$entity->set('pika', 'chu');
$entity->has('pika'); // true
$entity->get('pika'); // chu
$entity->has('pika'); // false


get() can take an array with multiple attributes:

$entity->set('pika', 'chu');
$entity->set('plop', true);

$entity->get(array('pika', 'plop')); // returns array('pika' => 'chu', 'plop' => true);

get(), clear() and set() are generic accessors. They are used internally and cannot be overloaded. Use virtual accessors instead:

$entity = new Database\Schema\MyEntity(array('pika' => 'chu'));
$entity->getPika();      // chu

They are called virtual because they do not exist by default but BaseObject implements the __call() method to trap accessors calls using the get() and set() generic methods. Of course, they can be overloaded:

// in the Entity class
public function getPika()
  return strtoupper($this->get('pika'));

// elsewhere
$entity = new Database\Schema\MyEntity(array('pika' => 'chu'));
$entity->getPika();     // CHU

Since the methods set() and get() cannot be overloaded, they will always return raw values stored in the entity container. They are used to bypass overloading methods.

Interfaces and overloads

Entities implement PHP's ArrayAccess interface to use the accessors if any. This means programmers can have easy access to entity's data in templates without bypassing accessors:

// in the Entity class
public function getPika()
  return strtoupper($this->get('pika'));

// elsewhere
$entity->getPika();     // CHU
$entity['pika'];        // CHU
$entity->pika;          // CHU

$entity->get('pika');   // chu

This also applies to set() and clear() methods.

This is particularly useful when exposing entities data in interfaced or template system.

Extending entities

It is possible to extend entities providing new accessors. If by example there is an entity with a weight in grams and you would like to have a getter that returns it in ounces:

public function getWeightInOunce()
  return round($this->getWeight() * 0.0352739619, 2);

In templates, it is possible to directly benefit from this getter while using the entity as an array:

// in PHP
<?php echo $thing['weight_in_ounce'] ?>

// with Twig
{{ thing.weight_in_ounce }}

Entities and database

Import and export

Pomm proposes several mechanisms to import or export entities data as array. The hydrate() method takes an array and merge it with the entity's internal values. Be aware PHP associative arrays keys are case sensitive while Postgresql's field names are not. If some sort of conversion is required, the convert() method will help. You can overload the convert() method to create a more specific conversion (if you use web services data provider by example) but you cannot overload the hydrate() method.

export will dump entity's internal data without regard to getters.

Life cycle

Entities also propose mechanisms to check what state are their data compared to the data source. There are 2 states which present 4 possible combinations:

The instance exists in the database.
This instance has been modified with mutators since hydration.

So, of course, an entity can be in both states EXIST and MODIFIED or NONE of them. The BaseObject class grants programmers with several methods to check this internal state: isNew(), isModified() or you can directly access the _state attribute from within class definition:

$entity = $map->createObject();
$entity->isNew();           // true
$entity->isModified();      // false
$entity->isNew();           // true
$entity->isModified();      // true


Map generation tools

Pomm comes with handy tools to generate map classes that reflect what is in your database.

Database Inspector

The database inspector class proposes methods to scavenge structure informations in the database. It is used by the Map generators and you can use it in your own scripts.


This class is the main generator class.

  • It inspects the database for the given table / view.
  • It creates the directory structure for your namespaces.
  • It generates the BaseMap file from the structure detected in the database.
  • It generates according empty entity and map files if they do not exist.

This class accepts the following parameters:

  • "database" a PommConnectionDatabase instance (mandatory).
  • "table" or "oid" (mandatory)
  • "prefix_dir" Where to generate the tree on the disk (mandatory).
  • "schema" (default to 'public').
  • "parent_namespace" When inheritance is found, override the default namespace for parent.
  • "namespace" (default to '%dbname%%schema%') The namespace placeholder.
  • "extends" (default to PommObjectBaseObjectMap).
  • "class_name" The corresponding entity class. (default camel cased table's name).

table or oid

If you give both, the oid has precedence over the name.


This is the root directory from which the directory tree will be built. The directory by default respects the PSR-0 standard to allow autoloading according to namespaces but you can change it.

schema The database schema name where the table or view is located.

namespace The namespace parameter is a placeholder. There are 2 values that can be substituted with their camel cased name: %schema% and %dbname%. By default, the namespace follows the directory structure.

parent_namespace When database table inheritance is found, this parameter override the default namespace for the parent map class. Otherwise the parent is assumed to be in the default namespace.

extends By default, the generated base class extends \Pomm\Object\BaseObjectMap but you might want to set another class. The final parent of the map class must be BaseObjectMap in the end.

class_name In case of generating map class for a view, it may be a good idea to tell Pomm that entities fetched by this map are something else than it thinks. This makes possible to have different views of the same table fetching the same entities from them.


The schema scanning tool takes a schema name as parameter and then launches CreateBaseMapTool for each table / view it finds in it. The expected parameters are the following:

  • "database" a PommConnectionDatabase instance (mandatory).
  • "prefix_dir" Where to generate the tree on the disk (mandatory).
  • "schema" (default to 'public').
  • "namespace" (default to '%dbname%%schema%') The namespace placeholder.
  • "extends" (default to PommObjectBaseObjectMap).
  • "parent_namespace" When inheritance is found, override the default namespace for parent.
  • "exclude" (optional) an array of tables/views not to generate files from.

Most of these parameters are sent to the CreateBaseMapTool as is. The only different parameter is

exclude An array of tables/views to ignore.

Here is a sample of code to generate map classes from all the tables/views in a database schema:


require __DIR__.'/vendor/pomm/test/autoload.php';

$database = new Pomm\Connection\Database(array(
        'dsn'  => 'pgsql://nss_user:nss_password@localhost/nss_db',
        'name' => 'my_db'

$scan = new Pomm\Tools\ScanSchemaTool(array(
    'prefix_dir'=> __DIR__,
    'schema' => 'transfo',
    'database' => $database


This will parse the Postgresql's schema named transfo to scan it for tables and views. Then it will generate automatically the BaseMap files with the class structure and if map files or entity files do not exist, will create them. By default, with the code above, the following tree structure will be created from the directory this code is invoked:

└── Transfo
    ├── Base
    │   └── TransformerMap.php
    ├── TransformerMap.php
    └── Transformer.php