You want to have the *path operations* related to your users separated from the rest of the code, to keep it organized.

But it's still part of the same **FastAPI** application/web API (it's part of the same "Python Package").

You can create the *path operations* for that module using `APIRouter`.

### Import `APIRouter`

* **Uvicorn** :
    * A les meilleures performances, étant donné qu'il n'a pas beaucoup de code mis-à-part le serveur en lui-même.

* Kubernetes with an Ingress Controller like Nginx
    * With an external component like cert-manager for certificate renewals
* Handled internally by a cloud provider as part of their services (read below 👇)

    A `Request` also has a `request.receive`, that's a function to "receive" the body of the request.

    The `scope` `dict` and `receive` function are both part of the ASGI specification.

    And those two things, `scope` and `receive`, are what is needed to create a new `Request` instance.

```Python hl_lines="31-33"
{!../../../docs_src/nosql_databases/tutorial001.py!}
```

!!! note
    Notice that we have a `hashed_password` and a `type` field that will be stored in the database.

    But it is not part of the general `User` model (the one we will return in the *path operation*).

## Get the user

Now create a function that will:

* Take a username.
* Generate a document ID from it.

But **FastAPI** will handle it, give you the correct data in your function, and validate and document the correct schema in the *path operation*.

You can also declare singular values to be received as part of the body.

    # For ORJSONResponse
    "orjson >=3.2.1",
    # To validate email fields
    "email_validator >=2.0.0",
    # Uvicorn with uvloop
    "uvicorn[standard] >=0.12.0",
    # TODO: this should be part of some pydantic optional extra dependencies
    # # Settings management
    # "pydantic-settings >=2.0.0",
    # # Extra Pydantic data types
    # "pydantic-extra-types >=2.0.0",
]

all = [

* **Coroutines**

## Code asynchrone

Faire du code asynchrone signifie que le langage 💬 est capable de dire à l'ordinateur / au programme 🤖 qu'à un moment du code, il 🤖 devra attendre que *quelque chose d'autre* se termine autre part. Disons que ce *quelque chose d'autre* est appelé "fichier-lent" 📝.

Donc, pendant ce temps, l'ordinateur pourra effectuer d'autres tâches, pendant que "fichier-lent" 📝 se termine.

## Type Hints with Metadata Annotations

Python also has a feature that allows putting **additional metadata** in these type hints using `Annotated`.

=== "Python 3.9+"

    In Python 3.9, `Annotated` is part of the standard library, so you can import it from `typing`.

    ```Python hl_lines="1  4"
    {!> ../../../docs_src/python_types/tutorial013_py39.py!}
    ```

=== "Python 3.8+"

        * [Build simple API service with Python FastAPI — Part 1](https://dev.to/cuongld2/build-simple-api-service-with-python-fastapi-part-1-581o) by [cuongld2](https://dev.to/cuongld2).
        * [FastAPI + Zeit.co = 🚀](https://paulsec.github.io/posts/fastapi_plus_zeit_serverless_fu/) by [Paul Sec](https://twitter.com/PaulWebSec).