public void testStringConverterSerialization() {
    SerializableTester.reserializeAndAssert(Doubles.stringConverter());
  }

  public void testToArray() {
    // need explicit type parameter to avoid javac warning!?
    List<Double> none = Arrays.<Double>asList();
    assertThat(Doubles.toArray(none)).isEqualTo(EMPTY);

    List<Double> one = Arrays.asList((double) 1);

  public void testStringConverterSerialization() {
    SerializableTester.reserializeAndAssert(Floats.stringConverter());
  }

  public void testToArray() {
    // need explicit type parameter to avoid javac warning!?
    List<Float> none = Arrays.<Float>asList();
    assertThat(Floats.toArray(none)).isEqualTo(EMPTY);

    List<Float> one = Arrays.asList((float) 1);

  @GwtIncompatible // SerializableTester
  public void testStringConverterSerialization() {
    SerializableTester.reserializeAndAssert(Longs.stringConverter());
  }

  public void testToArray() {
    // need explicit type parameter to avoid javac warning!?
    List<Long> none = Arrays.<Long>asList();
    assertThat(Longs.toArray(none)).isEqualTo(EMPTY);

    List<Long> one = Arrays.asList((long) 1);

  // +optional
  optional k8s.io.apimachinery.pkg.apis.meta.v1.ObjectMeta metadata = 1;

  // provisioner indicates the type of the provisioner.
  optional string provisioner = 2;

  // parameters holds the parameters for the provisioner that should
  // create volumes of this storage class.
  // +optional

Cette "attente" 🕙 se mesure en microsecondes, mais tout de même, en cumulé cela fait beaucoup d'attente.

C'est pourquoi il est logique d'utiliser du code asynchrone ⏸🔀⏯ pour des APIs web.

Ce type d'asynchronicité est ce qui a rendu NodeJS populaire (bien que NodeJS ne soit pas parallèle) et c'est la force du Go en tant que langage de programmation.

Et c'est le même niveau de performance que celui obtenu avec **FastAPI**.

config_setting(
    name = "windows",
    # Internal builds query the target OS.
    constraint_values = if_google(
        ["//third_party/bazel_platforms/os:windows"],
        [],
    ),
    # OSS builds query the CPU type.
    values = if_oss(
        {"cpu": "x64_windows"},
        {},
    ),
    visibility = ["//visibility:public"],
)

config_setting(
    name = "no_tensorflow_py_deps",

	testObjects := []struct {
		parentBucket string
		name         string
		content      string
		meta         map[string]string
	}{
		{testBuckets[0], "Asia-maps.png", "asis-maps", map[string]string{"content-type": "image/png"}},
		{testBuckets[0], "Asia/India/India-summer-photos-1", "contentstring", nil},
		{testBuckets[0], "Asia/India/Karnataka/Bangalore/Koramangala/pics", "contentstring", nil},

- Resolves a spurious "Unknown discovery response content-type" error in client-go discovery requests by tolerating extra content-type parameters in API responses ([#117571](https://github.com/kubernetes/kubernetes/pull/117571), [@seans3](https://github.com/seans3)) [SIG API Machinery]

thedocs.io/en/stable/" class="external-link" target="_blank">AnyIO</a> to be highly compatible and get its benefits (e.g. *structured concurrency*).

I created another library on top of AnyIO, as a thin layer on top, to improve a bit the type annotations and get better **autocompletion**, **inline errors**, etc. It also has a friendly introduction and tutorial to help you **understand** and write **your own async code**: <a href="https://asyncer.tiangolo.com/" class="external-link" tar...

	public static final fun parse (Ljava/lang/String;)Lokhttp3/MediaType;
	public final fun subtype ()Ljava/lang/String;
	public fun toString ()Ljava/lang/String;
	public final fun type ()Ljava/lang/String;
}

public final class okhttp3/MediaType$Companion {
	public final fun -deprecated_get (Ljava/lang/String;)Lokhttp3/MediaType;