Then we use the request directly, and extract the body as `bytes`. This means that FastAPI won't even try to parse the request payload as JSON.

And then in our code, we parse that YAML content directly, and then we are again using the same Pydantic model to validate the YAML content:

//// tab | Pydantic v2

        SMBProtocolDecodingException exception =
                assertThrows(SMBProtocolDecodingException.class, () -> smallResponse.readDataWireFormat(buffer, 0, 10));

        assertEquals("Payload exceeds buffer size", exception.getMessage());
    }

    @ParameterizedTest
    @ValueSource(ints = { 1, 10, 100, 500, 1024 })

  "token_type": "Bearer",
  "expires_in": 3600
}
```

### 4. JWT Claims

The id_token received is a signed JSON Web Token (JWT). Use a JWT decoder to decode the id_token to access the payload of the token that includes following JWT claims:

func signStreamingRequest(req *http.Request, accessKey, secretKey string, currTime time.Time) (string, error) {
	// Get hashed payload.
	hashedPayload := req.Header.Get("x-amz-content-sha256")
	if hashedPayload == "" {
		return "", fmt.Errorf("Invalid hashed payload")
	}

	// Set x-amz-date.
	req.Header.Set("x-amz-date", currTime.Format(iso8601Format))

	// Get header map.

        }

        final int len = bufferIndex - start;
        this.length = len;

        if (isRetainPayload()) {
            final byte[] payload = new byte[len];
            System.arraycopy(buffer, 4, payload, 0, len);
            setRawPayload(payload);
        }

        if (!verifySignature(buffer, 4, len)) {

Ensuite, nous utilisons directement la requête et extrayons son contenu en tant qu'octets. Cela signifie que FastAPI n'essaiera même pas d'analyser le payload de la requête en tant que JSON.

Et nous analysons directement ce contenu YAML, puis nous utilisons à nouveau le même modèle Pydantic pour valider le contenu YAML :

Dann verwenden wir den Request direkt und extrahieren den Body als `bytes`. Das bedeutet, dass FastAPI nicht einmal versucht, den Request-Payload als JSON zu parsen.

Und dann parsen wir in unserem Code diesen YAML-Inhalt direkt und verwenden dann wieder dasselbe Pydantic-Modell, um den YAML-Inhalt zu validieren:

//// tab | Pydantic v2

> - [**AD/LDAP**](https://github.com/minio/minio/blob/master/docs/sts/ldap.md)

        }
        final int size = Encdec.dec_uint16be(this.sbuf, 2) & 0xFFFF;
        if (size < 33 || 4 + size > this.sbuf.length) {
            throw new IOException("Invalid payload size: " + size);
        }
        final int hdrSize = this.smb2 ? Smb2Constants.SMB2_HEADER_LENGTH : SMB1_HEADER_LENGTH;
        readn(this.in, this.sbuf, 4 + hdrSize, size - hdrSize);

func (e *Erasure) DecodeDataBlocks(data [][]byte) error {
	isZero := 0
	for _, b := range data {
		if len(b) == 0 {
			isZero++
			break
		}
	}
	if isZero == 0 || isZero == len(data) {
		// If all are zero, payload is 0 bytes.
		return nil
	}
	return e.encoder().ReconstructData(data)
}

// DecodeDataAndParityBlocks decodes the given erasure-coded data and verifies it.
// It returns an error if the decoding failed.