```

</div>

Então, vá para a interface `/docs`, você verá que o **FastAPI** está usando esses **modelos** para **documentar** a API, e ele também os usará para **serializar** e **validar** os dados.

<div class="screenshot">
<img src="/img/tutorial/sql-databases/image01.png">
</div>

## Atualizar o App com Múltiplos Modelos { #update-the-app-with-multiple-models }

  @GwtIncompatible // SerializableTester
  public void testLexicographicalComparatorSerializable() {
    Comparator<byte[]> comparator = SignedBytes.lexicographicalComparator();
    assertThat(SerializableTester.reserialize(comparator)).isSameInstanceAs(comparator);
  }

  public void testSortDescending() {
    testSortDescending(new byte[] {}, new byte[] {});
    testSortDescending(new byte[] {1}, new byte[] {1});

come with the compiler are not designed to be used with untrusted data and
should be used with caution when working with untrusted models.

### Saved graphs and checkpoints

When loading untrusted serialized computation graphs (in form of a `GraphDef`,
`SavedModel`, or equivalent on-disk format), the set of computation primitives
available to TensorFlow is powerful enough that you should assume that the

    Thread t2 = newStartedThread(c2);
    awaitTermination(t1);
    awaitTermination(t2);
    assertEquals(SIZE * COUNTDOWN, c1.counts + c2.counts);
  }

  /** a deserialized serialized array holds same values */
  public void testSerialization() throws Exception {
    AtomicDoubleArray x = new AtomicDoubleArray(SIZE);
    for (int i = 0; i < SIZE; i++) {
      x.set(i, (double) -i);
    }

import org.jspecify.annotations.Nullable;

/**
 * Collections of strategies of generating the k * log(M) bits required for an element to be mapped
 * to a BloomFilter of M bits and k hash functions. These strategies are part of the serialized form
 * of the Bloom filters that use them, thus they must be preserved as is (no updates allowed, only
 * introduction of new versions).
 *

    @Override
    public SampleElements<E> samples() {
      return gen.samples();
    }

    @Override
    public Multiset<E> create(Object... elements) {
      return (Multiset<E>) SerializableTester.reserialize(gen.create(elements));
    }

    @Override
    public E[] createArray(int length) {
      return gen.createArray(length);
    }

    @Override
    public Iterable<E> order(List<E> insertionOrder) {

  }

  @J2ktIncompatible
  @GwtIncompatible // SerializableTester
  public void testEmpty_serialization() {
    SortedSet<String> set = of();
    SortedSet<String> copy = SerializableTester.reserialize(set);
    assertThat(copy).isSameInstanceAs(set);
  }

  public void testSingle_comparator() {
    SortedSet<String> set = of("e");
    assertThat(set.comparator()).isEqualTo(Ordering.natural());
  }

Vous n'avez pas vraiment besoin de déclarer l'annotation de type de retour pour diffuser des données binaires.

Comme FastAPI n'essaiera pas de convertir les données en JSON avec Pydantic ni de les sérialiser, dans ce cas l'annotation de type ne sert qu'à votre éditeur et à vos outils ; elle ne sera pas utilisée par FastAPI.

{* ../../docs_src/stream_data/tutorial001_py310.py ln[32:35] hl[33] *}

      return mapGenerator.order(insertionOrder);
    }

    @Override
    public Map<K, V> create(Object... elements) {
      return SerializableTester.reserialize(mapGenerator.create(elements));
    }

    @Override
    public K[] createKeyArray(int length) {
      return ((TestMapGenerator<K, V>) mapGenerator.getInnerGenerator()).createKeyArray(length);
    }

import java.io.UnsupportedEncodingException;
import java.net.URLEncoder;
import java.util.Map;

import org.apache.groovy.util.Maps;
import org.codelibs.fess.Constants;
import org.codelibs.fess.crawler.serializer.DataSerializer;
import org.codelibs.fess.crawler.util.FieldConfigs;
import org.codelibs.fess.exception.FessSystemException;
import org.codelibs.fess.helper.ProtocolHelper;
import org.codelibs.fess.mylasta.direction.FessConfig;