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Mokito is an asynchronous ORM for working with MongoDB inside a Tornado app

Project description

# mokito
An asynchronous ORM for accessing MongoDB in Tornado

## What is mokito?
(MOngodb + [mongoKIt]( + TOrnado) is an asynchronous toolkit for working with ``mongodb`` inside a ``tornado`` app, like ``mongokit``. Mokito has a pure implementation of python + tornado and only depends on tornado and bson (provided by pymongo)

## Why not pymongo?
[PyMongo]( is the recommended way to work with MongoDB in Python, but isn't asynchronous and not run inside tornado's IOLoop. If you use pymongo you won't take the advantages of tornado.

## Why not motor?
[Motor]( wraps PyMongo and makes it async with greenlet. This is a great project, but it uses greenlet. If you can use greenlets why not use gevent instead of tornado? PyMongo already works with gevent. If you are using a very powerfull non-blocking web server with a pure python code, you'll probably want to work with a pure tornado driver for accessing mongo.

## Features
* validation and conversion of data to the specified type
* support for unstructured data
* dot notation
* control over data presentation
* control over data validation
* mapping onto the same document of models with different schemes

## Installing
pip install pymomgo tornado
pip install mokito

## Simple usage
from tornado.web import RequestHandler
from tornado.gen import coroutine

import mokito

class MainHandler(RequestHandler):

def initialize(self):
self.db = mokito.Client("db_name", "mongodb://")

def get(self, user_id):
user = yield self.db.user.find_one(user_id)
self.render("index.html", user=user)

## Using ORM
A Document declaration look as follows:

from mokito import Document

class BlogPost(Document):
fields = {

blogpost = BlogPost(title='my title', body='a body', author='unknown', foo='bar')
blogpost['author'] = 'me'
MongoDB in the collection "blog_post" will write this document:
{"_id": ObjectId("..."), "body": "a body", "author": "me", "title": "my title"}
The field "foo" will not be saved. More about this you can read in [wiki](

And you can use a more complex structure as follows:
class ComplexDoc(Document):
__uri__ = "mongodb://"
__database__ = 'test'
__collection__ = 'example'

fields = {
"f_1": None,
"f_2": int,
"f_3": float,
"f_4": dict,
"f_5": [str],
"f_6": (int, str),
"f_7": {
"x_1": {'a': int, 'b': datetime.datetime},
"x_2": None,
"x_3": list

Please see the [wiki]( for more examples.

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