beanie VS Refactoring-Summary

I recently came across Beanie. A Python ORM for MongoDb. A pleasure to work with and integrates well with FastAPI, the tests document the code well, and at this point it’s only as complicated as it needs to be.

https://github.com/roman-right/beanie

Beanie (https://beanie-odm.dev) is an ODM using Pydantic BaseModel :)

You may want to look at swapping mongoengine for beanie. That supports native pydantic data structures and has async support.

Other link patterns are not supported for now. If you need something more specific for your use-case, please leave an issue on the GitHub page - https://github.com/roman-right/beanie

Document: Beanie

Today I want to introduce to you a new Beanie feature. MongoDB projections are supported now. It helps to reduce database load and makes your services more efficient.

Beanie - Python ODM (Object Document Mapper) for MongoDB.

Beanie - Python ODM (Object Document Mapper) for MongoDB, based on Pydantic and Motor.

I find that reading books rather than code tends to be more helpful in terms of finding good takes on what clean code is -- more specifically books on refactoring or specific language-related features (like 'Effective Java' or 'Fluent Python'). The issue with just reading code is that many times - you'll miss out on why the author chose to use the expression or abstractions which they chose to use. Reading a book at least takes you through author's thought process. For an alternative - you could always browse repositories which contain notes on refactoring as well like this one (which does a good job summarizing some of the key principles from Fowler's book on refactoring):

https://github.com/HugoMatilla/Refactoring-Summary

https://github.com/HugoMatilla/Refactoring-Summary#28-encapsulate-collection