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.
Documentation is available at https://pymongoext.readthedocs.io
The code is hosted on Github https://github.com/musyoka-morris/pymongoext
- 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)
Pymongoext uses JSON Schema for validation and thus we only support MongoDB v3.6+.
Pymongoext supports python v3+. Support for python v2.7 is currently under consideration.
We recommend the use of virtualenv and of
pip. You can then use pip install -U pymongoext.
You may also have setuptools
and thus you can use easy_install -U pymongoext. Another option is
pipenv. You can then use pipenv install pymongoext
to both create the virtual environment and install the package.
Alternatively, you can download the source from GitHub and
run python setup.py install.
Some simple examples of what pymongoext code looks like:
from datetime import datetime
from pymongo import MongoClient, IndexModel
from pymongoext import *
class User(Model):
@classmethod
def db(cls):
return MongoClient()['my_database_name']
__schema__ = DictField(dict(
email=StringField(required=True),
name=StringField(required=True),
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)We welcome contributions! See the Contribution guidelines