.. -*- coding: utf-8 -*-

.. _Concepts:

framework. To avoid confusion while reading this book, take time to go through

the following definitions and use this section as a reference during your

reading.

.. _Cube:

Cubes

-----

A cube is a software component made of three parts: its data model

(:file:`schema`), its logic (:file:`entities`) and its user interface

(:file:`views`).

A cube can use other cubes as building blocks and assemble them to provide

a whole with richer functionnalities than its parts. The cubes `cubicweb-blog`_

and `cubicweb-comment`_ could be used to make a cube named *myblog* with

commentable blog entries.

and available under a free software license.

system.

On a Unix system, the available cubes are usually stored in the directory

.. _`cubicweb-blog`: http://www.cubicweb.org/project/cubicweb-blog

.. _`cubicweb-comment`: http://www.cubicweb.org/project/cubicweb-comment

Instances

---------

An instance is a runnable application installed on a computer and based on a

cube.

The instance directory contains the configuration files. Several instances can

be created and based on the same cube. For exemple, several software forges can

be set up on one computer system based on the `cubicweb-forge`_ cube.

.. _`cubicweb-forge`: http://www.cubicweb.org/project/cubicweb-forge

Instances can be of three different types: all-in-one, web engine or data

repository. For applications that support high traffic, several web (front-end)

and data (back-end) instances can be set-up to share the load.

.. image:: ../../images/archi_globale.en.png

installed on your system.

On a Unix system, the instances are usually stored in the directory

:file:`/etc/cubicweb.d/`. During development, the :file:`~/etc/cubicweb.d/`

directory is looked up, as well as the paths in :envvar:`CW_INSTANCES_DIR`

environment variable.

The term application is used to refer to "something that should do something as a

whole", eg more like a project and so can refer to an instance or to a cube,

depending on the context. This book will try to use *application*, *cube* and

*instance* as appropriate.

Data Repository

---------------

SQL databases, LDAP repositories, Mercurial or Subversion version control

All interactions with the repository are done using the Relation Query Language

(RQL). The repository federates the data sources and hides them from the

querier, which does not realize when a query spans accross several data sources

It is common to run the web engine and the repository in the same process (see

can be set up to be accessed remotely using Pyro (`Python Remote Objects`_) and

act as a server.

Some logic can be attached to events that happen in the repository, like

creation of entities, deletion of relations, etc. This is used for example to

send email notifications when the state of an object changes. See `Hooks` below.

.. _`Python Remote Objects`: http://pyro.sourceforge.net/

Web Engine

----------

and most of the application logic.

By default the web engine provides a default user interface based on

the data model of the instance. Entities can be created, displayed,

updated and deleted. As the default user interface is not very fancy,

it is usually necessary to develop your own.

Schema (Data Model)

-------------------

The data model of a cube is described as an entity-relationship schema using a

comprehensive language made of Python classes imported from the yams_ library.

.. _yams: http://www.logilab.org/project/yams/

An `entity type` defines a set of attributes and is used in some relations.

Attributes may be of the following types: `String`, `Int`, `Float`, `Boolean`,

`Date`, `Time`, `Datetime`, `Interval`, `Password`, `Bytes`, `RichString`. See

:ref:`yams.BASE_TYPES` for details.

A `relation type` is used to define an oriented binary relation between two

entity types.  The left-hand part of a relation is named the `subject` and the

right-hand part is named the `object`.

A `relation definition` is a triple (*subject entity type*, *relation type*, *object

entity type*) associated with a set of properties such as cardinality,

constraints, etc.

Permissions can be set on entity types and relation types to control who will be

able to create, read, update or delete entities and relations.

Some meta-data necessary to the system is added to the data model. That includes

entities like users and groups, the entities used to store the data model

itself and attributes like unique identifier, creation date, creator, etc.

When the cubes the instance is based on evolve, they may change their data model

and provide migration scripts that will be executed when the administrator will

run the upgrade process for the instance.

Registries and Objects

----------------------

Application objects

~~~~~~~~~~~~~~~~~~~

Beside a few core functionalities, almost every feature of the framework is

achieved by dynamic objects (`application objects` or `appobjects`) stored in a

two-levels registry (the `vregistry`). Each object is affected to a registry with

an identifier in this registry. You may have more than one object sharing an

identifier in the same registry, At runtime, appobjects are selected in the

vregistry according to the context.

Application objects are stored in the registry using a two-level hierarchy :

  object's `__registry__` : object's `id` : [list of app objects]

The base class of appobjects is `AppObject` (module `cubicweb.appobject`).

The `vregistry`

~~~~~~~~~~~~~~~

At startup, the `registry` inspects a number of directories looking

for compatible classes definition. After a recording process, the

objects are assigned to registers so that they can be selected

dynamically while the instance is running.

Selectors

~~~~~~~~~

Each appobject has a selector, that is used to compute how well the object fits

a given context. The better the object fits the context, the higher the score.

can be combined with the binary operators `&` and `|` to build more complex

selector that can be combined too.

There are three common ways to retrieve some appobject from the repository:

* get the most appropriate objects by specifying a registry and an identifier. In

  that case, the object with the greatest score is selected. There should always

  be a single appobject with a greater score than others.

* get all appobjects applying to a context by specifying a registry. In

  that case, every object with the a postive score is selected.

* get the object within a particular registry/identifier. In that case no

  selection process is involved, the vregistry will expect to find a single

  object in that cell.

Selector sets are the glue that tie views to the data model. Using them

appropriately is an essential part of the construction of well behaved cubes.

When no score is higher than the others, an exception is raised in development

mode to let you know that the engine was not able to identify the view to

apply. This error is silenced in production mode and one of the objects with the

higher score is picked.

If no object has a positive score, ``NoSelectableObject`` exception is raised.

If no object is found for a particular registry and identifier,

``ObjectNotFound`` exception is raised.

In such cases you would need to review your design and make sure your views are

properly defined.

The RQL query language

----------------------

**No need for a complicated ORM when you have a powerful query language**

Relation Query Language.

This query language is inspired by SQL but is on a higher level in order to

emphasize browsing relations.

db-api

~~~~~~

The repository exposes a `db-api`_ like api but using the RQL instead of SQL.

XXX feed me

Result set

~~~~~~~~~~

object we call a Result Set. It enables easy use of the retrieved

data, providing a translation layer between the backend's native

Result sets provide access to the raw data, yielding either basic

Python data types, or schema-defined high-level entities, in a

straightforward way.

Views

-----

The view system is loosely coupled to data through a selection

system. Views are, in essence, defined by an id, a selection predicate

and an entry point (generaly producing html).

XXX feed me.

Hooks

-----

The data model defined using Yams types allows to express the data

model in a comfortable way. However several aspects of the data model

can not be expressed there. For instance:

* managing computed attributes

* enforcing complicated structural invariants

* real-world side-effects linked to data events (email notification

  being a prime example)

The hook system is much like the triggers of an SQL database engine,

except that:

* it is not limited to one specific SQL backend (every one of them

  having an idiomatic way to encode triggers), nor to SQL backends at

  all (think about LDAP or a Subversion repository)

* it is well-coupled to the rest of the framework

Hooks are basically functions that dispatch on both:

* events : after/before add/update/delete on entities/relations

* entity or relation types

They are an essential building block of any moderately complicated

cubicweb application.