"required": True,
        },
    },
)
async def create_item(request: Request):
    raw_body = await request.body()
    try:
        data = yaml.safe_load(raw_body)
    except yaml.YAMLError:
        raise HTTPException(status_code=422, detail="Invalid YAML")
    try:
        item = Item.model_validate(data)
    except ValidationError as e:

* **PGAdmin** für die PostgreSQL-Datenbank, können Sie problemlos ändern, sodass PHPMyAdmin und MySQL verwendet wird.
* **Flower** für die Überwachung von Celery-Jobs.
* Load Balancing zwischen Frontend und Backend mit **Traefik**, sodass Sie beide unter derselben Domain haben können, getrennt durch den Pfad, aber von unterschiedlichen Containern ausgeliefert.

![ReDoc](https://fastapi.tiangolo.com/img/index/index-02-redoc-simple.png)

## Traefik

<a href="https://traefik.io/" class="external-link" target="_blank">Traefik</a> est un reverse proxy/load balancer
haute performance. Il peut faire office de "Proxy de terminaison TLS" (entre autres fonctionnalités).

And if your remote server or virtual machine only has 3 GB of RAM, trying to load more than 4 GB of RAM will cause problems. 🚨

### Multiple Processes - An Example

In this example, there's a **Manager Process** that starts and controls two **Worker Processes**.

### Traefik

<a href="https://traefik.io/" class="external-link" target="_blank">Traefik</a> é um _proxy_ reverso / _load balancer_ de alta performance. Ele pode fazer o trabalho do _"TLS Termination Proxy"_ (à parte de outros recursos).

from fastapi import FastAPI


def fake_answer_to_everything_ml_model(x: float):
    return x * 42


ml_models = {}


@asynccontextmanager
async def lifespan(app: FastAPI):
    # Load the ML model
    ml_models["answer_to_everything"] = fake_answer_to_everything_ml_model
    yield
    # Clean up the ML models and release the resources
    ml_models.clear()

from fastapi import FastAPI


def fake_answer_to_everything_ml_model(x: float):
    return x * 42


ml_models = {}


@asynccontextmanager
async def lifespan(app: FastAPI):
    # Load the ML model
    ml_models["answer_to_everything"] = fake_answer_to_everything_ml_model
    yield
    # Clean up the ML models and release the resources
    ml_models.clear()


app = FastAPI(lifespan=lifespan)

            "required": True,
        },
    },
)
async def create_item(request: Request):
    raw_body = await request.body()
    try:
        data = yaml.safe_load(raw_body)
    except yaml.YAMLError:
        raise HTTPException(status_code=422, detail="Invalid YAML")
    try:
        item = Item.parse_obj(data)
    except ValidationError as e:

- 🔒 Secure password hashing by default.
- 🔑 JWT token authentication.
- 📫 Email based password recovery.
- ✅ Tests with [Pytest](https://pytest.org).
- 📞 [Traefik](https://traefik.io) as a reverse proxy / load balancer.
- 🚢 Deployment instructions using Docker Compose, including how to set up a frontend Traefik proxy to handle automatic HTTPS certificates.

        this.lineData = this.lineDataToElements(options.lineData || []);
        this.loadLines()
        if (!options.noInit) this.init()
    }

    loadLines() {
        // Load all the lines and create the container so that the size is fixed
        // Otherwise it would be changing and the user viewport would be constantly
        // moving as she/he scrolls
        const finish = this.generateFinish()