# SQL (Relational) Databases

!!! info
    These docs are about to be updated. 🎉

    The current version assumes Pydantic v1, and SQLAlchemy versions less than 2.0.

    The new docs will include Pydantic v2 and will use <a href="https://sqlmodel.tiangolo.com/" class="external-link" target="_blank">SQLModel</a> (which is also based on SQLAlchemy) once it is updated to use Pydantic v2 as well.

**FastAPI** doesn't require you to use a SQL (relational) database.

    assert response.json() == IsDict(
        {
            "detail": [
                {
                    "type": "greater_than",
                    "loc": ["path", "item_id"],
                    "msg": "Input should be greater than 3",
                    "input": "2",
                    "ctx": {"gt": 3.0},
                }
            ]
        }
    ) | IsDict(

    assert response.status_code == 422
    assert response.json() == IsDict(
        {
            "detail": [
                {
                    "type": "greater_than",
                    "loc": ["body", "item", "price"],
                    "msg": "Input should be greater than 0",
                    "input": -3.0,
                    "ctx": {"gt": 0.0},
                }
            ]
        }
    ) | IsDict(

    assert response.status_code == 422
    assert response.json() == IsDict(
        {
            "detail": [
                {
                    "type": "greater_than",
                    "loc": ["body", "item", "price"],
                    "msg": "Input should be greater than 0",
                    "input": -3.0,
                    "ctx": {"gt": 0.0},
                }
            ]
        }
    ) | IsDict(

Таким образом, `0.5` будет корректным значением. А `0.0` или `0` — нет.

То же самое справедливо и для <abbr title="less than"><code>lt</code></abbr>.

=== "Python 3.9+"

* Memory
* Previous steps before starting

## Memory

If you run **a single process per container** you will have a more or less well-defined, stable, and limited amount of memory consumed by each of those containers (more than one if they are replicated).

This means that you can send only the data that you want to update, leaving the rest intact.

!!! note
    `PATCH` is less commonly used and known than `PUT`.

    And many teams use only `PUT`, even for partial updates.

    You are **free** to use them however you want, **FastAPI** doesn't impose any restrictions.

## Uvicorn with Workers

Uvicorn also has an option to start and run several **worker processes**.

Nevertheless, as of now, Uvicorn's capabilities for handling worker processes are more limited than Gunicorn's. So, if you want to have a process manager at this level (at the Python level), then it might be better to try with Gunicorn as the process manager.

In any case, you would run it like this:

<div class="termy">

    Because of that, versions of FastAPI previous to 0.99.0 still used versions of OpenAPI lower than 3.1.0.

### Pydantic and FastAPI `examples`

When you add `examples` inside a Pydantic model, using `schema_extra` or `Field(examples=["something"])` that example is added to the **JSON Schema** for that Pydantic model.

Vas con la persona que te gusta 😍 por comida rápida paralela 🍔.

Haces la cola mientras varios cajeros (digamos 8) que a la vez son cocineros 👨‍🍳👨‍🍳👨‍🍳👨‍🍳👨‍🍳👨‍🍳👨‍🍳👨‍🍳 toman los pedidos de las personas que están delante de ti.