type ReadMultipleReq struct {
	Bucket       string   `msg:"bk"`           // Bucket. Can be empty if multiple buckets.
	Prefix       string   `msg:"pr,omitempty"` // Shared prefix of all files. Can be empty. Will be joined to filename without modification.
	Files        []string `msg:"fl"`           // Individual files to read.
	MaxSize      int64    `msg:"ms"`           // Return error if size is exceed.

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   *       versa.
   *   <li>Inequality check is not performed against state mutation methods such as {@link
   *       List#add}, or functional update methods such as {@link
   *       com.google.common.base.Joiner#skipNulls}.
   *   <li>If the constructor or factory method used to construct instance takes a parameter that
   *       {@link AbstractPackageSanityTests} doesn't know how to construct, the test will fail.

{!> ../../docs_src/response_model/tutorial003_04.py!}
```

////

... das scheitert, da die Typannotation kein Pydantic-Typ ist, und auch keine einzelne `Response`-Klasse, oder -Unterklasse, es ist eine Union (eines von beiden) von `Response` und `dict`.

### Responsemodell deaktivieren

* [Prüfen Sie Pull Requests](#pull-requests-prufen){.internal-link target=_blank} (siehe Abschnitt oben).

Diese beiden Dinge sind es, die **die meiste Zeit in Anspruch nehmen**. Das ist die Hauptarbeit bei der Wartung von FastAPI.

  EXPECT_EQ(TF_GetCode(status), TF_OK) << TF_Message(status);
  server_def.set_job_name("worker");
  server_def.set_task_index(0);
  tensorflow::ClusterDef* cluster_def = server_def.mutable_cluster();
  tensorflow::JobDef* job_def = cluster_def->mutable_job(0);
  int worker_port = tensorflow::testing::PickUnusedPortOrDie();
  job_def->mutable_tasks()->at(0) =
      tensorflow::strings::StrCat("localhost:", worker_port);

Erinnern Sie sich, wie unsere Anwendungs-/Dateistruktur aussieht:

<img src="/img/tutorial/bigger-applications/package.svg">

---

Die beiden Punkte `..`, wie in:

```Python
from ..dependencies import get_token_header
```

bedeuten:

			lastUpdate = ss.meta.ExpiryLCConfigUpdatedAt
			latestID = dID
			latestExpLCConfig = ss.meta.ExpiryLCConfig
		}
		// avoid considering just created buckets as latest. Perhaps this site
		// just joined cluster replication and yet to be sync'd
		if ss.meta.CreatedAt.Equal(ss.meta.ExpiryLCConfigUpdatedAt) {
			continue
		}
		if ss.meta.ExpiryLCConfigUpdatedAt.After(lastUpdate) {

      single_host_server_def.mutable_cluster();
  tensorflow::JobDef* job_def = cluster_def->add_job();
  job_def->set_name("client");

  // Add a client.
  job_def->mutable_tasks()->insert(
      {0, tensorflow::strings::StrCat(
              "localhost:", tensorflow::testing::PickUnusedPortOrDie())});

  tensorflow::JobDef* job_def2 = cluster_def->add_job();
  job_def2->set_name("worker");

    * JSON.
    * Yol parametreleri.
    * Sorgu parametreleri.
    * Çerezler.
    * Headers.
    * Formlar.
    * Dosyalar.
* Giden verinin <abbr title="Dönüşüm: serialization, parsing, marshalling olarak da biliniyor">dönüşümünü</abbr> aşağıdaki veri tiplerini kullanarak gerçekleştirir (JSON olarak):