databases VS awesome-fastapi

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?

Aweome asyncio Awesome Django Awesome FastAPI

This list has a lot of goodies

Was just about to suggest you add it to the Awesome FastAPI but another contributor already did. This looks very cool and I will definitely try it out on a project I am working on currently. Thank you!

You can find a number of large open source projects here: https://github.com/mjhea0/awesome-fastapi#open-source-projects.