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
Poetry
poetry add beanie
For more installation options (eg: aws, gcp, srv ...) you can look in the getting started
Example
import asyncio
from typing import Optional
from pymongo import AsyncMongoClient
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 PyMongo async client under the hood
client = AsyncMongoClient("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
- Doc - Tutorial, API documentation, and development guidelines.
Example Projects
- Activity Log & Notification Service - Real-time event ingestion with FastAPI, Beanie ODM, and DocumentDB (MongoDB-compatible), an async backend for high-volume activity events with aggregation statistics and WebSocket alerts by Khelan Modi
- fastapi-beanie-jwt - Sample FastAPI server with JWT auth and Beanie ODM by Michael duPont
- fastapi-cosmos-beanie - FastAPI + Beanie ODM + Azure Cosmos Demo Application by Anthony Shaw
- LCCN Predictor - Leetcode contest rating predictor (FastAPI + Beanie ODM + React) by L. Bao
- Shortify - URL shortener RESTful API (FastAPI + Beanie ODM + JWT & OAuth2) by Iliya Hosseini
Articles
- Announcing Beanie - MongoDB ODM
- Build a Cocktail API with Beanie and MongoDB
- MongoDB indexes with Beanie
- Beanie Projections. Reducing network and database load.
- Beanie 1.0 - Query Builder
- Beanie 1.8 - Relations, Cache, Actions and more!
Resources
Release files for beanie 2.2.0
For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.
Source distribution (sdist)
| File | Size | Uploaded | |
|---|---|---|---|
| beanie-2.2.0.tar.gz | 70.1 kB | Details |
Built distribution (wheel)
| File | Interpreter | ABI | Platform | Reset |
|---|---|---|---|---|
| beanie-2.2.0-py3-none-any.whl | Python 3 | none | any | Details |
Total release size: 163.2 kB
Release files / beanie-2.2.0.tar.gz
| Download URL | beanie-2.2.0.tar.gz |
|---|---|
| Size | 70.1 kB |
| Tags | Source |
|
SHA-256 checksum How to use checksums |
2dc116e7f4a6650f8066f95851d34d898983af6ffaf5366dcfef892993537a51
|
|
BLAKE2b-256 checksum How to use checksums |
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Uploaded using Trusted Publishing? What is trusted publishing? |
Yes |
| Uploaded via |
twine/7.0.0 CPython/3.13.14
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Transparency logRelease files / beanie-2.2.0-py3-none-any.whl
| Download URL | beanie-2.2.0-py3-none-any.whl |
|---|---|
| Size | 93.1 kB |
| Tags | Python 3 |
|
SHA-256 checksum How to use checksums |
4074f893ef00c52b8538b814c9dfd55130eea4ed0579abfae72853657c9029e4
|
|
BLAKE2b-256 checksum How to use checksums |
c5ae2584fb9871b58f3c5334110f8ce00bd1421fe5fbda28eeac9a8d01d10ba6
|
| Upload date | |
|
Uploaded using Trusted Publishing? What is trusted publishing? |
Yes |
| Uploaded via |
twine/7.0.0 CPython/3.13.14
|
Provenance
Provenance describes where a file came from. On PyPI, provenance is shared via attestations, which provide a verifiable record of the build or publishing details. View details, limitations and caveats.
PyPI Publish Attestation
PyPI verified that this artifact, at this checksum, originated from the publisher listed below.
Signed by GitHub Actions, verified by PyPI on Aug 7, 2026.
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