.. -*- 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.