* **Concis** : Minimise la duplication de code. Plusieurs fonctionnalités à chaque déclaration de paramètre.
    * **Robuste** : Obtenez du code prêt pour être utilisé en production. Avec de la documentation automatique interactive.

* Full **Docker** entegrasyonu (Docker based).
* Docker Swarm Mode ile deployment.
* **Docker Compose** entegrasyonu ve lokal geliştirme için optimizasyon.
* Uvicorn ve Gunicorn ile **Production ready** Python web server'ı.
* Python <a href="https://github.com/tiangolo/fastapi" class="external-link" target="_blank">**FastAPI**</a> backend:

# The demo profile enables a variety of things to try out Istio in non-production environments.
# * Lower resource utilization.
# * Some additional features are enabled by default; especially ones used in some tasks in istio.io.
# * More ports enabled on the ingress, which is used in some tasks.
meshConfig:
  accessLogFile: /dev/stdout
  extensionProviders:
    - name: otel
      envoyOtelAls:

   * @param offset the offset into the array at which to start
   * @return a long of a concatenated 8 bytes
   */
  static long load64(byte[] input, int offset) {
    // We don't want this in production code as this is the most critical part of the loop.
    assert input.length >= offset + 8;
    // Delegates to the fast (unsafe) version or the fallback.
    return byteArray.getLongLittleEndian(input, offset);
  }

First you need to install `WebSockets`:

<div class="termy">

```console
$ pip install websockets

---> 100%
```

</div>

## WebSockets client

### In production

In your production system, you probably have a frontend created with a modern framework like React, Vue.js or Angular.

And to communicate using WebSockets with your backend you would probably use your frontend's utilities.

# use single binary and filesystem storage for test
# do not use in production
loki:
  useTestSchema: true
  auth_enabled: false
  commonConfig:
    replication_factor: 1
  storage:
    type: 'filesystem'
test:
  enabled: false
lokiCanary:
  enabled: false
monitoring:
  dashboards:
    enabled: false
  rules:
    enabled: false
    alerting: false
  serviceMonitor:
    enabled: false
    metricsInstance:

from fastapi import FastAPI, Request

app = FastAPI(
    servers=[
        {"url": "https://stag.example.com", "description": "Staging environment"},
        {"url": "https://prod.example.com", "description": "Production environment"},
    ],
    root_path="/api/v1",
)


@app.get("/app")
def read_main(request: Request):

from fastapi import FastAPI, Request

app = FastAPI(
    servers=[
        {"url": "https://stag.example.com", "description": "Staging environment"},
        {"url": "https://prod.example.com", "description": "Production environment"},
    ],
    root_path="/api/v1",
    root_path_in_servers=False,
)


@app.get("/app")
def read_main(request: Request):

from pydantic import BaseModel, EmailStr

app = FastAPI()


class UserIn(BaseModel):
    username: str
    password: str
    email: EmailStr
    full_name: Union[str, None] = None


# Don't do this in production!
@app.post("/user/")
async def create_user(user: UserIn) -> UserIn:

and retrieval of the plugin dependencies so during development we would translate the POMs into dependency information that Mercury can understand, and in production we would have the pre-digested format that Mercury could utilize to resolve and retrieve dependencies. We need to be careful that we are using Mercury during development and production so that we don’t get in the situation where Maven 2.x is resolving differently than Mercury is. We can still leverage POMs during development but we need...