MongoLite 1.0beta1

========
MongoLite
========

MongoLite is a fork of MongoKit_ by the same author. It aims to come back to simplicity by stripping a lot of features and replacing them with best practices.

The goal of MongoLite is to stick as much as possible to the pymongo api.
MongoLite always choose speed over syntaxic sugar, this is why you won't see
validation or dot notation features in this project.

.. _MongoKit : http://namlook.github.com/mongokit/

MongoLite is perfect for who wants a thing layer on top of pymongo and don't care about validation stuff.

A mongolite is a beautiful stone_

.. _stone : http://www.mindat.org/photos/0656330001207867080.jpg

.. _MongoKit : http://namlook.github.com/mongokit/

.. topic:: **Your data is clean**:

"Tools change, not data". In order to follow this "credo", just like
MongoKit, MongoLite won't add any information into your data saved into the
database. So if you need to use other mongo tools or ODMs in other languages,
your data won't be polluted by MongoLite's stuff.

Features
========

* schema less feature
* inheritance and polymorphisme support
* skeleton generation (your object is automaticaly filled by the correct fields)
* nested and complex schema declaration
* default values features
* random query support (which returns a random document from the database)
* json helpers
* GridFS support

.. Go to the full documentation_ .

.. _documentation : http://namlook.github.com/mongolite/

A quick example
===============

A Document declaration look like that::

>>> from mongolite import *
>>> import datetime

>>> connection = Connection()

>>> @connection.register
... class BlogPost(Document):
... __database__ = 'test'
... __collection__ = 'example'
... skeleton = {
... 'title':unicode,
... 'body':unicode,
... 'author':unicode,
... 'date_creation':datetime.datetime,
... 'rank':int
... }
... optional = {
... 'tags': [unicode],
... }
... default_values = {'rank':0, 'date_creation':datetime.datetime.utcnow}
...

>>> blogpost = con.BlogPost() # this use the db "test" from `__database__` and the collection "example" from `__collection__`
>>> blogpost # the skeleton is automatically generated (based on the skeleton attribute)
{'body': None, 'title': None, 'date_creation': datetime.datetime(...), 'rank': 0, 'author': None}
>>> blogpost['title'] = u'my title'
>>> blogpost['body'] = u'a body'
>>> blogpost['author'] = u'me'
>>> blogpost['tags'] = ['about me', 'first post']
>>> blogpost
{'body': u'a body', 'title': u'my title', 'date_creation': datetime.datetime(...), 'rank': 0, 'author': u'me', 'tags': [u'about me', u'first post']}
>>> blogpost.save()

Note that, while fields in `skeleton` should be present in the document, fields in `optional` attribute are not generated by default. It aims to be for documentation only...

To access those fields, use the following convention:

**for fields in skeleton**::

>>> title = blogpost['title']

**for fields in optional**::

>>> tags = blogpost.get('tags', [])

MongoLite is written on top of pymongo. All the pymongo's API is accessible and the results are wrapped into Document objects:

>>> blogpost = con.BlogPost.find_one() # this is a blogpost object

However, if you need more performances, you can use the pymongo layer directly:

>>> blogpost = con.test.example.find_one() # this is a dict

Suggestion and patches are really welcome. If you find mistakes in the documentation
(english is not my primary langage) feel free to contact me. You can find me (namlook)
on twitter_.

.. _twitter : http://twitter.com/namlook


Recent Change Log
=================

v1.0
----

* fork from MongoKit, strip all unwanted features