Quick Start

Pymongoext is an ORM-like Pymongo extension that adds json schema validation, index management and intermediate data manipulators. Pymongoext simplifies working with MongoDB, while maintaining a syntax very identical to Pymongo.

pymongoext.Model is simply a wrapper around pymongo.Collection. As such, all of the pymongo.Collection API is exposed through pymongoext.Model. If you don’t find what you want in the pymongoext.Model API, please take a look at pymongo’s Collection documentation.


  • schema validation (which uses MongoDB JSON Schema validation)
  • schema-less feature
  • nested and complex schema declaration
  • untyped field support
  • required fields validation
  • default values
  • custom validators
  • operator for validation (OneOf, AllOf, AnyOf, Not)
  • indexes management
  • data manipulators (transform documents before saving and after retrieval)
  • Easy to create custom data manipulators
  • object-like results instead of dict-like. (i.e. foo.bar instead of foo[‘bar’])
  • No custom-query language or API to learn (If you know how to use pymongo, you already know how to use pymongoext)


Some simple examples of what pymongoext code looks like:

from datetime import datetime
from pymongo import MongoClient, IndexModel
from pymongoext import *

class User(Model):
    def db(cls):
        return MongoClient()['my_database_name']

    __schema__ = DictField(dict(
        yob=IntField(minimum=1900, maximum=2019)

    __indexes__ = [IndexModel('email', unique=True), 'name']

    class AgeManipulator(Manipulator):
        def transform_outgoing(self, doc, model):
            doc['age'] = datetime.now().year - doc['yob']
            return doc

# Create a user
>>> User.insert_one({'email': 'jane@gmail.com', 'name': 'Jane Doe', 'yob': 1990})

# Fetch one user
>>> user = User.find_one()

# Print the users age
>>> print(user.age)