Following are advantages for using temporary credentials:

- Eliminates the need to embed long-term credentials with an application.
- Eliminates the need to provide access to buckets and objects without having to define static credentials.
- Temporary credentials have a limited lifetime, there is no need to rotate them or explicitly revoke them. Expired temporary credentials cannot be reused.

## Identity Federation

  for _s in _site_packages_dirs:
    _plugin_dir = _os.path.join(_s, "tensorflow-plugins")
    if _os.path.exists(_plugin_dir):
      _ll.load_library(_plugin_dir)
      # Load Pluggable Device Library
      _ll.load_pluggable_device_library(_plugin_dir)

if _os.getenv("TF_PLUGGABLE_DEVICE_LIBRARY_PATH", ""):
  _ll.load_pluggable_device_library(
      _os.getenv("TF_PLUGGABLE_DEVICE_LIBRARY_PATH")
  )

The browser would then communicate with that IP address on **port 443** (the HTTPS port).

The first part of the communication is just to establish the connection between the client and the server and to decide the cryptographic keys they will use, etc.

<img src="/img/deployment/https/https02.drawio.svg">

This interaction between the client and the server to establish the TLS connection is called the **TLS handshake**.

        self.scheme_name = scheme_name or self.__class__.__name__
        self.auto_error = auto_error

    def make_not_authenticated_error(self) -> HTTPException:
        """
        The OAuth 2 specification doesn't define the challenge that should be used,
        because a `Bearer` token is not really the only option to authenticate.

        But declaring any other authentication challenge would be application-specific

///

## `File` importieren { #import-file }

Importieren Sie `File` und `UploadFile` von `fastapi`:

{* ../../docs_src/request_files/tutorial001_an_py39.py hl[3] *}

## `File`-Parameter definieren { #define-file-parameters }

Erstellen Sie Datei-Parameter, so wie Sie es auch mit `Body` und `Form` machen würden:

{* ../../docs_src/request_files/tutorial001_an_py39.py hl[9] *}

/// info | Info

Portanto, você pode declarar "objects" JSON profundamente aninhados com nomes, tipos e validações de atributos específicos.

Tudo isso, aninhado arbitrariamente.

### Defina um sub-modelo { #define-a-submodel }

Por exemplo, nós podemos definir um modelo `Image`:

{* ../../docs_src/body_nested_models/tutorial004_py310.py hl[7:9] *}

### Use o sub-modelo como um tipo { #use-the-submodel-as-a-type }

      copyright notice that is included in or attached to the work
      (an example is provided in the Appendix below).

      "Derivative Works" shall mean any work, whether in Source or Object
      form, that is based on (or derived from) the Work and for which the
      editorial revisions, annotations, elaborations, or other modifications
      represent, as a whole, an original work of authorship. For the purposes

	// TestXLStorage for delete on an removed disk.
	// should fail with disk not found.
	err = xlStorageDeletedStorage.DeleteVol(t.Context(), "Del-Vol", false)
	if err != errDiskNotFound {
		t.Errorf("Expected: \"Drive not found\", got \"%s\"", err)
	}
}

// TestXLStorageStatVol - TestXLStorages validate the volume info returned by xlStorage.StatVol() for various inputs.
func TestXLStorageStatVol(t *testing.T) {

///

## Retorne o token { #return-the-token }

A resposta do endpoint `token` deve ser um objeto JSON.

Deve ter um `token_type`. No nosso caso, como estamos usando tokens "Bearer", o tipo de token deve ser "`bearer`".

E deve ter um `access_token`, com uma string contendo nosso token de acesso.

          "hide": false,
          "instant": true,
          "legendFormat": ".",
          "range": false,
          "refId": "B"
        }
      ],
      "title": "Total Online/Offline Drives",
      "type": "gauge"
    },
    {
      "datasource": {
        "type": "prometheus",
        "uid": "${DS_PROMETHEUS}"
      },
      "fieldConfig": {
        "defaults": {