* If you didn't use FastAPI and used Starlette directly (or another tool, like Sanic, Flask, Responder, etc) you would have to implement all the data validation and serialization yourself. So, your final application would still have the same overhead as if it was built using FastAPI. And in many cases, this data validation and serialization is the biggest amount of code written in applications.

            """
        ),
    ] = None,
    example: Annotated[
        Optional[Any],
        deprecated(
            "Deprecated in OpenAPI 3.1.0 that now uses JSON Schema 2020-12, "
            "although still supported. Use examples instead."
        ),
    ] = _Unset,
    openapi_examples: Annotated[
        Optional[Dict[str, Example]],
        Doc(
            """
            OpenAPI-specific examples.

  // case placement information is lost when resolving the handle.
  //
  // If false, a caller might implement pretty-printing by resolving and
  // iterating over the resulting tensor. This may still be viable if resolving
  // the handle loses information, but `SummarizeValue` would be more precise.
  virtual bool PreferCustomSummarizer() const { return false; }

type PodNetnsCache interface {
	ReadCurrentPodSnapshot() map[string]WorkloadInfo
}

// Hold a cache of node local pods with their netns
// if we don't know the netns, the pod will still be here with a nil netns.
type podNetnsCache struct {
	openNetns func(nspath string) (NetnsCloser, error)

	currentPodCache map[string]WorkloadInfo
	mu              sync.RWMutex
}

type WorkloadInfo struct {

        fail("Encoding $component $codePoint using $encoding")
      }
      return
    }

    // If the URI has more escaping than the HttpURL, check that the decoded values still match.
    val uriEscaped = uriEscapedCodePoints.indexOf(codePointString) != -1
    if (uriEscaped) {
      if (uri.toString() == httpUrl.toString()) {
        fail("Encoding $component $codePoint using $encoding")

			"dir/object1",
			[]string{"object0"},
		},
		// Test 3: remove an object inside a directory and checks if it is deleted
		// but other sibling object in the same directory still exists
		{
			"bucket3",
			[]objectUpload{{"dir/object1", "content"}, {"dir/object2", "content"}},
			"dir/object1",
			[]string{"dir/object2"},
		},

       * The following call is not statically checked, since arraycopy accepts plain Object for its
       * parameters. If it were statically checked, the checker would still be OK with it, since
       * we're copying into a `contents` array whose type allows it to contain nulls. Still, it's
       * worth noting that we promise not to put nulls into the array in the first `size` elements.

   * next} field is lazily initialized. The type of that field would be {@code @Nullable T}, and the
   * code would be responsible for populating a "real" {@code T} (which might still be the value
   * {@code null}!) before returning it to callers. Depending on how the code is structured, a
   * nullness analysis might not understand that the field has been populated. To avoid that problem

=== "Python 3.8+ non-Annotated"

    !!! tip
        Prefer to use the `Annotated` version if possible.

    ```Python hl_lines="10"
    {!> ../../../docs_src/security/tutorial001.py!}
    ```

But that is still not that useful.

Let's make it give us the current user.

## Create a user model

First, let's create a Pydantic user model.

The same way we use Pydantic to declare bodies, we can use it anywhere else:

  class AddressPolicy(
    /**
     * How many concurrent calls should be possible to make at any time.
     * The pool will routinely try to pre-emptively open connections to satisfy this minimum.
     * Connections will still be closed if they idle beyond the keep-alive but will be replaced.
     */
    @JvmField val minimumConcurrentCalls: Int = 0,
    /** How long to wait to retry pre-emptive connection attempts that fail. */