This is a pre-production deployment of Warehouse, however changes made here WILL affect the production instance of PyPI.
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Project Description
=========================
This package is DEPRECATED
=========================

All of the changes in this package have been merged back into the original
project, MongoKit ... As a result, it makes the most sense to deprecate
mongokit-pylons. MongoKit has, since the merge, added a large body of
additional functionality. I am working on a bridge version to assist with
migration, but for now you should look towards moving over to the main
project.


=========================
What is MongoDB/MongoKit?
=========================
MongoDB is a free & open source, schemaless document oriented
database (available at http://mongodb.org). The MongoKit
framework is an ORM-like layer which provides an enhanced
approach to managing your MongoDB data by providing an object
layer. This layer allows you to define rough schema outlines
including default values and allowed & required fields.
While schemaless databases have power in their lack of schema,
it helps to control what fields are and aren't permitted
(even if you only use 3 of 10 most times) to ensure consistency.

The original MongoKit is written by Namlook, and is available at
http://bitbucket.org/namlook/mongokit/

MongoKit-Pylons is a (hopefully temporary) fork which provides a
toolset for easily integrating MongoKit within the Pylons web
framework. It provides the ability to parse mongo configuration
from Pylons ini config files, and setup easily in
config/environment.py as an always-available, threadlocal
connection pool (similar to how SQLAlchemy is typically setup in Pylons).

From my own usage of MongoKit following integrating
Pylons support into my production systems, I have added several
enhancements to the MongoKit-Pylons fork which I've found useful.
These features include property-like setter/getter proxying for
values (instead of pure dictionary access) and support for the
MongoDB driver's autoreferencing features. Autoreferencing
allows you to embed MongoKit objects/instances inside another
MongoKit object. With autoreferencing enabled, MongoKit and
the pymongo driver will translate the embedded MongoKit object
values into internal MongoDB DBRefs. The (de)serialization is
handled automatically by the pymongo driver.

It is my hope/intention to merge this fork back into the main
project.

===============
MongoKit-Pylons
===============
[Note that if you used an earlier version of this fork, I have
recently changed the namespace to mongokit.pylons so as not to
conflict. The latest release can be grabbed from pypi]

.. _release: http://pypi.python.org/pypi/mongokit-pylons
.. _pypi: http://pypi.python.org/pypi/mongokit-pylons

This is a fork (hopefully temporary, as I'd like to merge into
one codebase) of the fantastic MongoKit_ to add better support
for Pylons_. Along the way I have added a few features such as
__setattr__ / __getattr__ to set / get values as properties
rather than talking to the dictionary.

This fork also supports the autoreferencing feature from the
pymongo_. driver.

MongoPylonsEnv is a helper class for using MongoKit_ inside of
Pylons_. - The recommended deployment is to add a call to
init_mongo() in config/environment.py for your pylons project.
Like with SQLAlchemy_, this will setup your connections
at Pylons boot; the MongoDB_ Pool code should ensure you have
enough connections.

.. _MongoKit: http://bitbucket.org/namlook/mongokit/wiki/Home
.. _Pylons: http://pylonshq.com
.. _SQLAlchemy: http://sqlalchemy.org
.. _pymongo: http://github.com/mongodb/mongo-python-driver/
.. _autoref_sample: http://github.com/mongodb/mongo-python-
driver/blob/cd47b2475c5fe567e98696e6bc5af3c402891d12/examples/auto_r
eference.py

Add the import at the top::

>>> from mongokit.pylons.pylons_env import MongoPylonsEnv

And lower down, in load_environment()::

>>> MongoPylonsEnv.init_mongo()

Additionally, you'll need to add several items to your
configuration ini file::


>>> # Mongo Database settings
... mongodb.host = localhost
... mongodb.port = 27017
... mongodb.db = your_db_name
... mongodb.connection_timeout = 30
... mongodb.pool.enable = True
... mongodb.pool.size = 20

To enable pylons support, your document class MUST specify::

>>> _use_pylons = True

as a class level attribute. MongoKit's document connection
management is class based, so if you need the same document to
work in and out of pylons, it is recommended you create a
"normal" MongoDocument subclass, and a subclass of THAT which
defines _use_pylons.

Alternately, for the ultimate in lazy::

>>> from mongokit.pylons.document import MongoPylonsDocument

And then subclass from that (It's a proxy subclass of
MongoDocument which enables use_pylons).

One further perk of this version is AutoReferences.
Autoreferences allow you to pass other MongoDocuments as values.
pymongo_. (with help from MongoKit) automatically
translates these object values into DBRefs before persisting to
Mongo. When fetching, it translates them back, so that you have
the data values for your referenced object.
See the autoref_sample_. for further details/internals on this
driver-level functionality. As for enabling it in your own
MongoKit code, simply define the following class attribute
upon your Document subclass::

>>> _enable_autoref = True

With autoref enabled, MongoKit's connection management will
attach the appropriate BSON manipulators to your document's
connection handles. We require you to explicitly enable autoref
for two reasons:

- Using autoref and it's BSON manipulators (As well as DBRefs) come with a
performance penalty, so we don't load them unless you opt-in at class-level.
- You may not wish to use auto-referencing in some cases where you're
using DBRefs.

Once you have autoref enabled, MongoKit will allow you to define
any valid subclass of MongoDocument as part of your document
structure. **If your class does not define _enable_autoref as
True, MongoKit's structure validation code will REJECT your
structure. The rules are *autoref enabled*, *issubclass(<type>,
MongoDocument)*.**

A detailed example::

>>> class BlogEntry(MongoPylonsDocument):
... collection_name = 'blog'
... structure = {
... 'author': AdminUser,
... 'publish_date': datetime.datetime,
... 'title': unicode,
... 'entry': unicode,
... }
...
... _enable_autoref = True
... required_fields = ['author', 'publish_date', 'entry', 'title']
... default_values = {'publish_date': datetime.datetime.now()}

Additionally, with this codebase, MongoDocument supports property
style set/get. Where in the original codebase you had to do::

>>> user = TestUserDocument()
... user['password'] = 'p455'

With this code you can invoke it as::

>>> user = TestUserDocument()
... user.password = 'p455'

For any questions related to this fork, especially the Pylons &
Autoref (and properties) support, please contact myself (Brendan
McAdams ) rather than namlook. I can be reached at
NO*bwmcadams*SPAM@gmail.*OMGSPAM*.com, and sometimes lurk on
freenode #mongodb as bwmcadams.

Docs for core MongoKit follow...

========
MongoKit
========

MongoDB_ is a great schema-less document oriented database. It have a lot of
driver for many langages (python, ruby, perl, java, php...).

.. _MongoDB : http://www.mongodb.org/display/DOCS/Home

MongoKit is a python module that brings structured schema and validation layer
on top of the great pymongo driver. It has be written to be simpler and lighter
as possible with the KISS and DRY principles in mind.

Features
========

* schema validation (wich use simple python type for the declaration)
* nested and complex schema declaration
* required fields validation
* default values
* custom validators
* inheritance and polymorphisme support
* versionized document support (still in alpha stage)
* partial auth support (it brings a simple User model)

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

MongoDocument are enhanced python dictionnary with a ``validate()``
method.
A MongoDocument declaration look like that::

>>> from mongokit.pylons import MongoDocument
>>> import datetime

>>> class BlogPost(MongoDocument):
... db_name = 'test'
... collection_name = 'tutorial'
... structure = {
... 'title':unicode,
... 'body':unicode,
... 'author':unicode,
... 'date_creation':datetime.datetime,
... 'rank':int
... }
... required_fields = ['title','author', 'date_creation']
... default_values = {'rank':0, 'date_creation':datetime.datetime.utcnow}
...
>>> blogpost = BlogPost()
>>> blogpost['title'] = u'my title'
>>> blogpost['body'] = u'a body'
>>> blogpost['author'] = u'me'
>>> blogpost.validate()
>>> blogpost # doctest: +ELLIPSIS, +NORMALIZE_WHITESPACE
{'body': u'a body', 'title': u'my title', 'date_creation': datetime.datetime(...),
'rank': 0, 'author': u'me'}
>>> blogpost.save()

And you can use more complex structure::

>>> class ComplexDoc(MongoDocument):
... db_name = 'test'
... collection_name = 'tutorial'
... structure = {
... "foo" : {"content":int},
... "bar" : {
... int:{unicode:int}
... }
... }
... required_fields = ['foo.content', 'bar.$int']

Please, see the tutorial_ for more examples.

.. _tutorial : http://bitbucket.org/namlook/mongokit/wiki/Home

[ For any questions related to this fork, especially the Pylons & Autoref (and
properties) support, rather than the core mongokit code, please contact myself
(Brendan McAdams ) rather than namlook. I can be reached at
NO*bwmcadams*SPAM@gmail.*OMGSPAM*.com, and sometimes lurk on
freenode #mongodb as bwmcadams.]
Release History

Release History

0.2.0

This version

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