Skip to main content

Asynchronous Python ODM for MongoDB with mongoengine-compatible Links (ObjectId instead of DBRef)

Project description

Beanie MongoEngine Compatibility Fork

shields badge pypi

🔗 MongoEngine Compatibility Changes

This is a fork of the original Beanie ODM with modifications to make Links compatible with MongoEngine.

Key Changes:

  • Link values changed from DBRef to ObjectId: Links now store ObjectId('XXX') instead of DBRef('RefCollectionName', ObjectId('XXX'))
  • Improved mongoengine compatibility: Easier migration from mongoengine projects
  • Same API: All other Beanie functionality remains unchanged

Migration from Original Beanie:

If you're migrating from the original Beanie, your existing data will continue to work. The change only affects how new Link references are stored.

Migration from MongoEngine:

This fork makes it easier to migrate from MongoEngine projects since the Link storage format is now compatible.


📢 About the Original Project

This fork is based on Beanie by Roman Right. The original project is transitioning from solo development to a team-based approach.

Join the Original Community

If you want to contribute to the original project or stay updated: Join the Discord

Overview

Beanie - is an asynchronous Python object-document mapper (ODM) for MongoDB. Data models are based on Pydantic.

When using Beanie each database collection has a corresponding Document that is used to interact with that collection. In addition to retrieving data, Beanie allows you to add, update, or delete documents from the collection as well.

Beanie saves you time by removing boilerplate code, and it helps you focus on the parts of your app that actually matter.

Data and schema migrations are supported by Beanie out of the box.

There is a synchronous version of Beanie ODM - Bunnet

Installation

PIP

pip install beanie-mongoengine-compat

UV

uv add beanie-mongoengine-compat

Poetry

poetry add beanie-mongoengine-compat

For more installation options (eg: aws, gcp, srv ...) you can look in the getting started

Example

import asyncio
from typing import Optional

from motor.motor_asyncio import AsyncIOMotorClient
from pydantic import BaseModel

from beanie import Document, Indexed, init_beanie


class Category(BaseModel):
    name: str
    description: str


class Product(Document):
    name: str                          # You can use normal types just like in pydantic
    description: Optional[str] = None
    price: Indexed(float)              # You can also specify that a field should correspond to an index
    category: Category                 # You can include pydantic models as well


# This is an asynchronous example, so we will access it from an async function
async def example():
    # Beanie uses Motor async client under the hood 
    client = AsyncIOMotorClient("mongodb://user:pass@host:27017")

    # Initialize beanie with the Product document class
    await init_beanie(database=client.db_name, document_models=[Product])

    chocolate = Category(name="Chocolate", description="A preparation of roasted and ground cacao seeds.")
    # Beanie documents work just like pydantic models
    tonybar = Product(name="Tony's", price=5.95, category=chocolate)
    # And can be inserted into the database
    await tonybar.insert() 
    
    # You can find documents with pythonic syntax
    product = await Product.find_one(Product.price < 10)
    
    # And update them
    await product.set({Product.name:"Gold bar"})


if __name__ == "__main__":
    asyncio.run(example())

Links

Documentation

  • Original Doc - Tutorial, API documentation, and development guidelines.
  • This Fork - MongoEngine compatibility fork

Original Project

  • GitHub - Original Beanie project
  • Changelog - Original project changelog
  • Discord - Original project community

Example Projects

Articles

Resources

  • GitHub - GitHub page of the project
  • Changelog - list of all the valuable changes
  • Discord - ask your questions, share ideas or just say Hello!!

Supported by JetBrains

JetBrains

Project details


Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Source Distribution

beanie_mongoengine_compat-1.29.0.tar.gz (64.7 kB view details)

Uploaded Source

Built Distribution

If you're not sure about the file name format, learn more about wheel file names.

beanie_mongoengine_compat-1.29.0-py3-none-any.whl (86.8 kB view details)

Uploaded Python 3

File details

Details for the file beanie_mongoengine_compat-1.29.0.tar.gz.

File metadata

File hashes

Hashes for beanie_mongoengine_compat-1.29.0.tar.gz
Algorithm Hash digest
SHA256 14a9a9d921a914e307e1375c62553e479bf200c4a9b59194ef0730921020141e
MD5 b8c5b5e4e50dd3d27e8ff6114b8ec42d
BLAKE2b-256 5539d83226db9d5cc34a02be7028bd1a3309151036cd0c4ddb4b0a851cc4d5e0

See more details on using hashes here.

File details

Details for the file beanie_mongoengine_compat-1.29.0-py3-none-any.whl.

File metadata

File hashes

Hashes for beanie_mongoengine_compat-1.29.0-py3-none-any.whl
Algorithm Hash digest
SHA256 a16ce01411ca88d7804c33b89cbb8fa788b79cf14bb6428b738d8b992680e843
MD5 6f6a054105d90e524951cef3231f9965
BLAKE2b-256 2418c5c2fab0b4bdddbc7f3d4f9b3cd47089fcebe8e9c94f0020f0cae1cb2f97

See more details on using hashes here.

Supported by

AWS Cloud computing and Security Sponsor Datadog Monitoring Depot Continuous Integration Fastly CDN Google Download Analytics Pingdom Monitoring Sentry Error logging StatusPage Status page