Erstellen Sie eine Variable `ALGORITHM` für den Algorithmus, der zum Signieren des JWT-Tokens verwendet wird, und setzen Sie sie auf `"HS256"`.

Erstellen Sie eine Variable für das Ablaufdatum des Tokens.

Definieren Sie ein Pydantic-Modell, das im Token-Endpunkt für die Response verwendet wird.

Erstellen Sie eine Hilfsfunktion, um einen neuen Zugriffstoken zu generieren.

//// tab | Python 3.10+

```Python hl_lines="6  12-14  28-30  78-86"

    You could have custom internal logic to separate it by colon characters (`:`) or
    similar, and get the two parts `items` and `read`. Many applications do that to
    group and organize permissions, you could do it as well in your application, just
    know that that it is application specific, it's not part of the specification.
    """

    def __init__(
        self,
        *,
        grant_type: Annotated[

// no way to verify this assumption since the encryption happens
// inside AWS S3.
// Therefore, S3 clients must not make any assumption about ETags
// in case of SSE-C or SSE-KMS except that the ETag is well-formed.
//
// To put all of this into a simple rule:
//
//	SSE-S3 : ETag == MD5
//	SSE-C  : ETag != MD5
//	SSE-KMS: ETag != MD5
//
// # Encrypted ETags
//

```JSON
{
  "title": "towel",
  "size": "XL"
}
```

受信したボディを含むデータが無効であることを示すレスポンスが表示されます:

```JSON hl_lines="12 13 14 15"
{
  "detail": [
    {
      "loc": [
        "body",
        "size"
      ],
      "msg": "value is not a valid integer",
      "type": "type_error.integer"
    }
  ],
  "body": {
    "title": "towel",
    "size": "XL"
  }
}
```

    /**
     * Filter out whitelisted projects with a big twist:
     * Assume we have all projects {@code a, b, c} while active are {@code a, c} and relation among all projects
     * is {@code a -> b -> c}. This method handles well the case for transitive list. But, for non-transitive we need
     * to "pull in" transitive dependencies of eliminated projects, as for case above, the properly filtered list would
     * be {@code a -> c}.
     * <p>

 * it easy to get sample values to use in such tests.
 *
 * This class is pretty fast and loose with default values: it attempts to provide values that are
 * well-formed, but doesn't guarantee values are internally consistent. Callers must take care to
 * configure the factory when sample values impact the correctness of the test.
 */
class TestValueFactory : Closeable {

}

// RuntimeClassSpec is a specification of a RuntimeClass. It contains parameters
// that are required to describe the RuntimeClass to the Container Runtime
// Interface (CRI) implementation, as well as any other components that need to
// understand how the pod will be run. The RuntimeClassSpec is immutable.
message RuntimeClassSpec {
  // runtimeHandler specifies the underlying runtime and configuration that the

 * the methods of the delegate. For example, overriding {@link #put} alone <i>will not</i> change
 * the behavior of {@link #putAll}, which can lead to unexpected behavior. In this case, you should
 * override {@code putAll} as well, either providing your own implementation, or delegating to the
 * provided {@code standardPutAll} method.
 *
 * <p><b>{@code default} method warning:</b> This class does <i>not</i> forward calls to {@code

  /**
   * Returns a new thread-safe interner which retains a weak reference to each instance it has
   * interned, and so does not prevent these instances from being garbage-collected. This most
   * likely does not perform as well as {@link #newStrongInterner}, but is the best alternative when
   * the memory usage of that implementation is unacceptable.
   */
  @GwtIncompatible("java.lang.ref.WeakReference")

```

////

## Declare `Header` parameters

Then declare the header parameters using the same structure as with `Path`, `Query` and `Cookie`.

You can define the default value as well as all the extra validation or annotation parameters:

//// tab | Python 3.10+

```Python hl_lines="9"
{!> ../../docs_src/header_params/tutorial001_an_py310.py!}
```

////

//// tab | Python 3.9+