fastapi-crudrouter VS databases

FastAPI does have an equivalent. Something like this? https://github.com/awtkns/fastapi-crudrouter

I can't show any pics cuz of uk NDA and all that. I can tell you the gist of it though. FastAPI is already pretty good at the abstraction part. Our middleware had a lot of rerouting and it was basically just a bunch of redundant functions. I just used this cool ass package https://fastapi-crudrouter.awtkns.com/ and used the partial function from functools to generate endpoints for every scenario/db tables.

Thanks, that's a really helpful example.

Where I think this could be taken to the next level of reusability is in modularising the front-end into API-specific components. For example, the login behaviour could depend on FastAPI-Users, with a sibling frontend library containing components that implement the same login flow. Adding user behaviour is then a matter of using the same third-party library on the front and back end.

This approach could be extended to other components such as an admin panel (perhaps using https://github.com/awtkns/fastapi-crudrouter), or a blogging component.

In the code ,we are using SQLAlchemy as our ORM(Object Relational Mapper) and Databases as our query builder.

MySQL is a powerful and popular database, and it's well-suited for use with Python. In the following section, we are going through how to set up a connection to a MySQL database in an asynchronous manner using the create_asynchrouns_engine function from SQLAlchemy. We'll also use the databases package and the aiomysql extra dependency. We'll also adapt the SQLAlchemy declarative approach to defining our users' table.

To take an example: I switched a service over from doing synchronous (plain def everywhere) to async (async def and await everywhere, with async DB, and saw… basically no performance improvement.

No, as I said, async db connection is the key. You can do that with SQLAlchemy using the databases library, but since you are not using SQLAlchemy it makes more sense to use the underlying db driver, aiomysql, directly.

Using the encode/databases library and forgoing SQLAlchemy's ORM

ormar is a mini async ORM for python. It uses sqlalchemy for building queries, databases for asynchronous execution of queries, and pydantic for data validation. You can create an ormar model and generate pydantic models from it.

works but there seems to be a difference between the regular slqalchemy syntax from what https://github.com/encode/databases/ is using in the docs?