mdum - Multi Database Unified Modeling

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中文文档

Name:	Multi Database Unified Modeling
Author:	Feiox
Maintainer:	Feiox <Fei2037@gmail.com>

About

mdum is a Python Object-Document Mapper for working with Redis Elasticsearch MongoDB. Documentation available at Read the Docs - there is currently a tutorial, a feature, a develop and an API reference.

Philosophy

• Data Modeling: Declarative DSL is better than procedural
• Interface: Simple, Clear, Semantic, Stratified
• Expansibility: Don't need to understand the internal implementation
• Life: JUST FOR FUN

Feature

• Semantic & like Python syntax DSL
• Operating data, like Python built-in objects
• Use multiple databases in a uniform interface
• High performance, Cache precompiled all DSL, Model, and so on

Base Usage

Installation

We recommend the use of virtualenv and pip. You can then use pip install mdox. Otherwise, you can download the source from GitHub and run python setup.py install. Be sure to check the version of dependent packages when you install, low version will lead to unpredictable errors.

Dependencies

python interpreter:

• python2 >= 2.7
• python3 >= 3.4

python packages:

• pymongo >= 3.0
• elasticsearch >= 1.6
• redis >=2.10

Database Softwares:

• MongoDB >= 3.0
• Elasticsearch >= 1.7
• Redis >= 3.0

Optional Dependencies

TODO

Examples

To run the examples, ensure you are running a local instance of MongoDB and Elasticsearch on the standard port. Create and initialize mdum app code looks like:

import mdum

db_app = mdum.MdumApp().init()  # use default configuration

Some simple examples of what model definition code looks like:

from mdum import Document
from mdum.fields import String, Int, Datetime, Identifier, GeoPosition

class UserModel(Document):
    __meta__ = [
        'indexes': ['-username']
        'triggers': [
            # assuming that these function has been defined
            'after_create': init_new_user  
            'pre_delete': clear_up_user_data
        ]
    ]
    
    # will be used at Elasticsearch
    doc_schema = {
        'username': String(required=True),
        'desc': String(length_scope=[1, 255]),
    }
    # will be used at MongoDB
    data_schema = {
    	'role': Enum(['rookie', 'user', 'vip'], default='rookie'),
    	'friends': List(type=Identifier),
    	'location': GeoPosition(),
    	'join_time': Datetime(default_now=True),
    	'department': Identifier(join=True, required=True),
    }

If you want to operate data, you can try:

>>> UserModel.create({'username': 'Lynn', 'department': 32717})
4e7020cb7cac81af7136236b
>>> book = UserModel(pk='4e7020cb7cac81af7136236b')  # or UserModel.get('4e7020cb7cac81af7136236b')
{'username': 'Lynn', 'department': {'id': 32717, 'name': 'Engineering'}, 'time': datetime(2015, 9, 3, 12, 31, 56), 'role': 'rookie'}
>>> book.update({'department': 21345}, dont_return=True)
True
>>> book.delete('4e7020cb7cac81af7136236b')
True
>>> Book.find('join_time >= {} or friends size is {comments_num}', datetime(2015, 9, 3, 12, 31, 56), comments_num=10)
ResultSet()

Well, the coding should be simple and fun.

Fork & Contribution

Contribute Code or Idea

We welcome contributions! see the Contribution guidelines.

Fork Me

Donate Me

Now don't need donations yet :P

License

Mdum is licensed under very liberal Apache license, then any private or commercial purposes can be permitted.

Copyright (c) 2015, Feiox All rights reserved.

Thanks

• My Lover, Qiucen
• MongoEngine