Tools
=====
Many tools have been written for working with **PyMongo**. If you know
of or have created a tool for working with MongoDB from Python please
list it here.
.. note:: We try to keep this list current. As such, projects that
have not been updated recently or appear to be unmaintained will
occasionally be removed from the list or moved to the back (to keep
the list from becoming too intimidating).
If a project gets removed that is still being developed or is in active use
please let us know or add it back.
ORM-like Layers
---------------
Some people have found that they prefer to work with a layer that
has more features than PyMongo provides. Often, things like models and
validation are desired. To that end, several different ORM-like layers
have been written by various authors.
It is our recommendation that new users begin by working directly with
PyMongo, as described in the rest of this documentation. Many people
have found that the features of PyMongo are enough for their
needs. Even if you eventually come to the decision to use one of these
layers, the time spent working directly with the driver will have
increased your understanding of how MongoDB actually works.
MongoEngine
`MongoEngine `_ is another ORM-like
layer on top of PyMongo. It allows you to define schemas for
documents and query collections using syntax inspired by the Django
ORM. The code is available on `GitHub
`_; for more information, see
the `tutorial `_.
MincePy
`MincePy `_ is an
object-document mapper (ODM) designed to make any Python object storable
and queryable in a MongoDB database. It is designed with machine learning
and big-data computational and experimental science applications in mind
but is entirely general and can be useful to anyone looking to organise,
share, or process large amounts data with as little change to their current
workflow as possible.
Ming
`Ming `_ (the Merciless) is a
library that allows you to enforce schemas on a MongoDB database in
your Python application. It was developed by `SourceForge
`_ in the course of their migration to
MongoDB. See the `introductory blog post
`_
for more details.
MotorEngine
`MotorEngine `_ is a port of
MongoEngine to Motor, for asynchronous access with Tornado.
It implements the same modeling APIs to be data-portable, meaning that a
model defined in MongoEngine can be read in MotorEngine. The source is
`available on GitHub `_.
uMongo
`uMongo `_ is a Python MongoDB ODM.
Its inception comes from two needs: the lack of async ODM and the
difficulty to do document (un)serialization with existing ODMs.
Works with multiple drivers: PyMongo, TxMongo, motor_asyncio, and
mongomock. The source `is available on GitHub
`_
No longer maintained
""""""""""""""""""""
PyMODM
`PyMODM `_ is an ORM-like framework on top
of PyMongo. PyMODM is maintained by engineers at MongoDB, Inc. and is quick
to adopt new MongoDB features. PyMODM is a "core" ODM, meaning that it
provides simple, extensible functionality that can be leveraged by other
libraries to target platforms like Django. At the same time, PyMODM is
powerful enough to be used for developing applications on its own. Complete
documentation is available on `readthedocs
`_.
MongoKit
The `MongoKit `_ framework
is an ORM-like layer on top of PyMongo. There is also a MongoKit
`google group `_.
MongoAlchemy
`MongoAlchemy `_ is another ORM-like layer on top of
PyMongo. Its API is inspired by `SQLAlchemy `_. The
code is available `on GitHub `_;
for more information, see `the tutorial `_.
Minimongo
`minimongo `_ is a lightweight,
pythonic interface to MongoDB. It retains pymongo's query and update API,
and provides a number of additional features, including a simple
document-oriented interface, connection pooling, index management, and
collection & database naming helpers. The `source is on GitHub
`_.
Manga
`Manga `_ aims to be a simpler ORM-like
layer on top of PyMongo. The syntax for defining schema is inspired by the
Django ORM, but Pymongo's query language is maintained. The source `is on
GitHub `_.
Humongolus
`Humongolus `_ is a lightweight ORM
framework for Python and MongoDB. The name comes from the combination of
MongoDB and `Homunculus `_ (the
concept of a miniature though fully formed human body). Humongolus allows
you to create models/schemas with robust validation. It attempts to be as
pythonic as possible and exposes the pymongo cursor objects whenever
possible. The code is available for download
`at GitHub `_. Tutorials and usage
examples are also available at GitHub.
Framework Tools
---------------
This section lists tools and adapters that have been designed to work with
various Python frameworks and libraries.
* `Djongo `_ is a connector for using
Django with MongoDB as the database backend. Use the Django Admin GUI to add and
modify documents in MongoDB.
The `Djongo Source Code `_ is hosted on GitHub
and the `Djongo package `_ is on pypi.
* `Django MongoDB Engine
`_ is a MongoDB
database backend for Django that completely integrates with its ORM.
For more information `see the tutorial
`_.
* `mango `_ provides MongoDB backends for
Django sessions and authentication (bypassing :mod:`django.db` entirely).
* `Django MongoEngine
`_ is a MongoDB backend for
Django, an `example:
`_.
For more information see ``_
* `mongodb_beaker `_ is a
project to enable using MongoDB as a backend for `beakers `_ caching / session system.
`The source is on GitHub `_.
* `Log4Mongo `_ is a flexible
Python logging handler that can store logs in MongoDB using normal and capped
collections.
* `MongoLog `_ is a Python logging
handler that stores logs in MongoDB using a capped collection.
* `rod.recipe.mongodb `_ is a
ZC Buildout recipe for downloading and installing MongoDB.
* `mongobox `_ is a tool to run a sandboxed
MongoDB instance from within a python app.
* `Flask-MongoAlchemy `_ Add
Flask support for MongoDB using MongoAlchemy.
* `Flask-MongoKit `_ Flask extension
to better integrate MongoKit into Flask.
* `Flask-PyMongo `_ Flask-PyMongo
bridges Flask and PyMongo.
Alternative Drivers
-------------------
These are alternatives to PyMongo.
* `Motor `_ is a full-featured, non-blocking
MongoDB driver for Python Tornado applications.
* `TxMongo `_ is an asynchronous Twisted
Python driver for MongoDB.
* `MongoMock `_ is a small
library to help testing Python code that interacts with MongoDB via
Pymongo.