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

Introduction

============

This book uses version 0.4.0 of `LAX`.

What is  `LAX` ?

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

`LAX` stands for `Logilab Appengine eXtension`. It is a web application framework 

based on `Google AppEngine`.

`LAX` is a port of the web framework Logilab_ has been developping since 2001.

This framework originally published data queried from different sources including

SQL databases, LDAP directories and concurrent versionning systems

(like subversion). In April/May 2008, it was adapted to run also on

top of `Google AppEngine`'s datastore.

`Google AppEngine` is provided with a partial port of the `Django`

framework, but Google stated at Google IO 2008 that it would not

support a specific Python web framework and that all

community-supported frameworks would be more than welcome[1]_. 

`LAX` competes with other Python web application frameworks to get

developers' attention and support. It originates from Logilab and is

the result of about ten years of experience in developing large-scale

web applications.

Distinctive features include a data-model driven engine, a full-blown

query language, a selection/view mechanism for HTML/XML/text

generation, reuseable components, etc. It all sums up to very fast and

efficient development.

If you like Python and its standard library, chances are you will like

`LAX` for it comes with batteries included thanks to its standard

component library.

Compare `LAX` with other frameworks and see for yourself what is your

best option.

.. _Logilab: http://www.logilab.fr/

.. [1] for more on this matter, read our blog at http://www.logilab.org/blog/5216

Essentials

----------

Schema

  The schema defines the data model of an application as entities and

  relationships. It is the core of an application.  Entities and

  relationships are modeled with a comprehensive language made of

  Python classes. 

Query language

  A full-blown query language named RQL is used to formulate 

  requests to the datastore.

Result set

  A resultset encapsulates the results of a request sent to

  the datastore and informations about this request.  

Views 

  A view is applied to a `result set` to present it as HTML, XML,

  JSON, CSV, etc. Views are implemented as Python classes. There is no

  templating language.

Generated user interface

  A user interface is generated on-the-fly from the schema definition:

  entities can be created, displayed, updated and deleted. As display

  views are not very fancy, it is usually necessary to develop your

  own. Any generated view can be overridden by defining a new one with

  the same identifier.

Components

  Pieces of schema and sets of views can be combined into

  components. Larger applications can be built faster by importing

  components, adding entities and relationships and overriding the

  views that need to display or edit informations not provided by

  components.