* Lire le contenu de la requête en tant que JSON.
* Convertir les types correspondants (si nécessaire).
* Valider la donnée.
    * Si la donnée est invalide, une erreur propre et claire sera renvoyée, indiquant exactement où était la donnée incorrecte.
* Passer la donnée reçue dans le paramètre `item`.

## Results { #results }

With just that Python type declaration, **FastAPI** will:

* Read the body of the request as JSON.
* Convert the corresponding types (if needed).
* Validate the data.
    * If the data is invalid, it will return a nice and clear error, indicating exactly where and what was the incorrect data.
* Give you the received data in the parameter `item`.

			// mime package in MinIO, which correctly encodes strings with fixed B/Q encodings,
			// avoiding S3’s heuristic-driven issues.
			//
			// For MinIO developers, decode S3 metadata with mime.WordDecoder, validate outputs,
			// report encoding bugs to AWS, and use ASCII-only metadata to ensure reliable S3 API
			// compatibility.
			if needsMimeEncoding(v) {

    /**
     * Function code to trim file level storage
     */
    public static final int FSCTL_FILE_LEVEL_TRIM = 0x00098208;
    /**
     * Function code to validate SMB2 negotiate information
     */
    public static final int FSCTL_VALIDATE_NEGOTIATE_INFO = 0x000140204;

    /**
     * Flag indicating this IOCTL is a file system control operation
     */

Using the above `id_token` we can perform an STS request to MinIO to get temporary credentials for MinIO API operations. MinIO STS API uses [JSON Web Key Set Endpoint](https://docs.wso2.com/display/IS541/JSON+Web+Key+Set+Endpoint) to validate if JWT is valid and is properly signed.

	for i := range parts {
		if errs[i] == nil {
			if parts[i].Name == objectName {
				t.Errorf("path traversal allowed to allow writing to minioMetaBucket: %s", instanceType)
			}
		}
	}
}

// Tests validate bucket name.
func TestIsValidBucketName(t *testing.T) {
	testCases := []struct {
		bucketName string
		shouldPass bool
	}{
		// cases which should pass the test.
		// passing in valid bucket names.

// license that can be found in the LICENSE file.

// This file is for validation errors only, i.e., errors reported by the validate function.
// Negative test cases for errors generated earlier in the assembler's preprocess stage
// should be added to riscv64error.s.  If they are added to this file, they will prevent
// the validate function from being run and TestRISCVValidation will report missing
// errors.

TEXT validation(SB),$0

```Python
some_variable: PlaneItem | CarItem
```

Pero si ponemos eso en la asignación `response_model=PlaneItem | CarItem` obtendríamos un error, porque Python intentaría realizar una **operación inválida** entre `PlaneItem` y `CarItem` en lugar de interpretar eso como una anotación de tipo.

## Lista de modelos

De la misma manera, puedes declarar responses de listas de objetos.

You declare the "shape" of the data as classes with attributes.

And each attribute has a type.

Then you create an instance of that class with some values and it will validate the values, convert them to the appropriate type (if that's the case) and give you an object with all the data.

And you get all the editor support with that resulting object.

An example from the official Pydantic docs:

          <name>type</name>
          <version>1.0.0+</version>
          <type>String</type>
          <required>true</required>
          <description>
            The Java type for this parameter. This is used to validate the result of any expressions used to calculate
            the value which should be injected into the Mojo for this parameter.
          </description>
        </field>
        <field>
          <name>required</name>