This "lazy loading" optimizes pod startup time, for the common case where an application is not sending outbound traffic instantly.
For applications that do, they will see a slight latency increase during startup; most applications can handle this far better than failed connections.

## Pod Shutdown

### Pod Shutdown Requirements

    "license": "Apache-2.0",
    "title": "TensorFlow",
    "upload_type": "software",
    "creators": [
        {
            "name": "TensorFlow Developers"
        }
    ],
    "access_right": "open",

* Par défaut, cela signifie que vous ne pouvez avoir qu'un seul certificat HTTPS par adresse IP.
    * Quelle que soit la taille de votre serveur ou la taille de chacune des applications qu'il contient.
    * Il existe cependant une solution à ce problème.
* Il existe une extension du protocole TLS (celui qui gère le cryptage au niveau TCP, avant HTTP) appelée <a

# Module okhttp

 * annotation implies nothing about the quality or performance of the API in question, only the fact
 * that it is not "API-frozen."
 *
 * <p>It is generally safe for <i>applications</i> to depend on beta APIs, at the cost of some extra
 * work during upgrades. However it is generally inadvisable for <i>libraries</i> (which get
 * included on users' CLASSPATHs, outside the library developers' control) to do so.

 * annotation implies nothing about the quality or performance of the API in question, only the fact
 * that it is not "API-frozen."
 *
 * <p>It is generally safe for <i>applications</i> to depend on beta APIs, at the cost of some extra
 * work during upgrades. However it is generally inadvisable for <i>libraries</i> (which get
 * included on users' CLASSPATHs, outside the library developers' control) to do so.

"""FastAPI framework, high performance, easy to learn, fast to code, ready for production"""

__version__ = "0.115.4"

from starlette import status as status

from .applications import FastAPI as FastAPI
from .background import BackgroundTasks as BackgroundTasks
from .datastructures import UploadFile as UploadFile
from .exceptions import HTTPException as HTTPException
from .exceptions import WebSocketException as WebSocketException

# WSGI inkludieren – Flask, Django und andere

Sie können WSGI-Anwendungen mounten, wie Sie es in [Unteranwendungen – Mounts](sub-applications.md){.internal-link target=_blank}, [Hinter einem Proxy](behind-a-proxy.md){.internal-link target=_blank} gesehen haben.

Dazu können Sie die `WSGIMiddleware` verwenden und damit Ihre WSGI-Anwendung wrappen, zum Beispiel Flask, Django usw.

## `WSGIMiddleware` verwenden

Sie müssen `WSGIMiddleware` importieren.

# ==============================================================================


"""Converts MSYS Linux-like paths stored in env variables to Windows paths.

This is necessary on Windows, because some applications do not understand/handle
Linux-like paths MSYS uses, for example, Docker.
"""

import argparse
import os


def should_convert(var_name: str,
                   blacklist: list[str] | None,

from fastapi.testclient import TestClient

app = FastAPI()

router = APIRouter()


class ContentSizeLimitMiddleware:
    """Content size limiting middleware for ASGI applications
    Args:
      app (ASGI application): ASGI application
      max_content_size (optional): the maximum content size allowed in bytes, None for no limit
    """

    def __init__(self, app: APIRouter, max_content_size: Optional[int] = None):