databases VS starlette

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.

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.

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.

databases has since the time of FastAPI's authorship been integrated in upstream starlette and documented: https://github.com/encode/databases ... what-ever is in fastapi skips all this and is weak sauce.

Prefer the data mapper approach for CRUD apps, but the flexibility of active record for all other apps. 1.Use psycopg2 for enterprise apps (since it's battle-tested) and https://github.com/encode/databases (with asyncpg) for toy apps.

Thoughts on aiosql vs encode/databases[0]? Same creator as starlette (under the hood of FastAPI)

[0] https://github.com/encode/databases

Fast Execution: FastAPI is built on top of Starlette and Pydantic, making it one of the fastest Python frameworks for building APIs.

The framework's efficiency comes from its use of Starlette for building asynchronous web services and Pydantic for robust data validation and serialization, powered by Python's type hints. Pydantic has recently announced the official release of Pydantic V2 (June 2023), which is a ground-up rewrite that offers many new features and performance improvements, so make sure to be using that instead of V1.

Uvicorn + Starlette 8k requests/s

Starlette documentation

Same here, but without these weird utils it doesn't get any better.

I have 7 YoE with Django. Its great at so many things. You see some code, like middlewares, and immediately understand what's going on.

Now, we also have Starlette. The base of all new, fancy asgi libraries. Here's the base middleware class.

https://github.com/encode/starlette/blob/8d7a1cacfb3e1a30cbb...

In the last couple of years I heard 'we're running fastapi on production. Wanna join us?' so many times... but the reality is that it's still not suitable for prod. Who wants to work with a code like that if you have a readable, stable Django? I'm clueless.

Correct. Yeah I’ve been trying to find stuff. It often circles back to the issue I linked (https://github.com/encode/starlette/issues/1724)

In this thread, starlette people admitting they don’t have anywhere near the tuning features necessary for more heavily sync oriented people https://github.com/encode/starlette/issues/1724

Perhaps you are thinking about Starlette, the toolkit Starlite was originally based on? But Starlette as well won't have an influence on FastAPI's Pydantic dependencies, since Starlette never dependent on Pydantic in the first place.