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    nanomongo

Minimal Python ODM for MongoDB


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========= nanomongo

nanomongo is a minimal MongoDB Object-Document Mapper for Python. It does not attempt to be a feature-complete ODM but if you like using pymongo api with python dictionaries and often find yourself writing validators and pymongo.Collection wrappers, nanomongo might suit your needs.

nanomongo has full test coverage.

Quick Links: Source (github) <https://github.com/eguven/nanomongo>_ - Documentation (rtd) <https://nanomongo.readthedocs.org/>_ - Packages (PyPi) <https://pypi.python.org/pypi/nanomongo/>_

Version 0.4: Utility methods dbref_field_getters <http://nanomongo.readthedocs.org/en/latest/index.html#dbref_field_getters>, BaseDocument.get_dbref <http://nanomongo.readthedocs.org/en/latest/document.html#nanomongo.document.BaseDocument.get_dbref> and Bugfix Python23 text type compatibility <https://github.com/eguven/nanomongo/pull/14>_

Version 0.3: nanomongo is now python2 compatible (with syntactic difference when defining your Document, refer to Documentation)

.. image:: https://travis-ci.org/eguven/nanomongo.png :target: https://travis-ci.org/eguven/nanomongo

Features

  • single format Field definitions with type checking and a few common options such as required, default, auto_update

  • pymongo-identical index definitions

  • optional dot_notation

  • assignment and deletion (delta) tracking for '$set' and '$unset' and atomic updates; you either insert or update

  • '$addToSet' on Document

  • upcoming '$push' '$pull' funtionality

::

# rough example
import pymongo
from nanomongo import Field, BaseDocument, Index

client = pymongo.MongoClient()

class MyDoc(BaseDocument, dot_notation=True, client=client, db='dbname'):
    foo = Field(str)
    bar = Field(int, required=False)

    __indexes__ = [
        Index('foo'),
        Index([('bar', 1), ('foo', -1)], unique=True),
    ]

doc = MyDoc(foo='L33t')
doc.bar = 42
doc.insert()

Doc.find_one({'foo': 'L33t'})

nanomongo is Python23 compatible and I intend to support both pymongo & motor transparently under the hood.

Contributions and insight are welcome!

:Author: Eren Güven (GitHub_, Twitter_) :License: Apache Software License

.. _GitHub: https://github.com/eguven .. _Twitter: https://twitter.com/cyberfart

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