WaitOnRunService service = new WaitOnRunService();
    service.startAsync().awaitRunning();
    enterRun.await();
    service.stopAsync().awaitTerminated();
  }

  public void testTimeout() {
    // Create a service whose executor will never run its commands
    Service service =
        new AbstractExecutionThreadService() {
          @Override
          protected void run() throws Exception {}

          @Override

        checkNoConflictInValueBucket(value, entry, nextInValueBucket);
      } catch (BucketOverflowException e) {
        return JdkBackedImmutableBiMap.create(n, entryArray);
      }
      ImmutableMapEntry<K, V> newEntry =
          (nextInValueBucket == null && nextInKeyBucket == null)
              ? RegularImmutableMap.makeImmutable(entry, key, value)

      service.shutdown();
    }
  }

  public void testRejectedExecutionThrownWithMultipleCalls() throws Exception {
    CountDownLatch latch = new CountDownLatch(1);
    SettableFuture<?> future = SettableFuture.create();
    Executor delegate =
        new Executor() {
          @Override
          public void execute(Runnable task) {
            if (future.set(null)) {
              awaitUninterruptibly(latch);

     *
     * @throws Exception
     */
    @Test
    public void testReadBytes_LargeFile() throws Exception {
        final File largeFile = tempFolder.newFile("large.dat");

        // Create a file larger than MAX_BUF_SIZE (10MB)
        // Write 11MB of data
        try (FileOutputStream fos = new FileOutputStream(largeFile)) {
            final byte[] chunk = new byte[1024 * 1024]; // 1MB

Commencez par importer la classe `BaseModel` du module `pydantic` :

{* ../../docs_src/body/tutorial001_py310.py hl[2] *}

## Créer votre modèle de données { #create-your-data-model }

Déclarez ensuite votre modèle de données en tant que classe qui hérite de `BaseModel`.

Utilisez les types Python standard pour tous les attributs :

프로덕션 환경에서는 위에서 설명한 옵션 중 하나를 사용할 것입니다.

그러나 이는 WebSockets의 서버 측에 집중하고 동작하는 예제를 제공하는 가장 간단한 방법입니다:

{* ../../docs_src/websockets_/tutorial001_py310.py hl[2,6:38,41:43] *}

## `websocket` 생성하기 { #create-a-websocket }

**FastAPI** 애플리케이션에서 `websocket`을 생성합니다:

{* ../../docs_src/websockets_/tutorial001_py310.py hl[1,46:47] *}

/// note | 기술 세부사항

`from starlette.websockets import WebSocket`을 사용할 수도 있습니다.

У цьому випадку **FastAPI** ніколи не торкається `__init__` і не покладається на нього - ми використовуватимемо його безпосередньо у своєму коді.

## Створити екземпляр { #create-an-instance }

Ми можемо створити екземпляр цього класу так:

{* ../../docs_src/dependencies/tutorial011_an_py310.py hl[18] *}

      TFE_Op* op,
      const std::vector<absl::optional<std::vector<int64_t>>>& input_shapes_vec,
      const std::vector<TF_Tensor*>& input_tensors,
      const absl::optional<std::vector<int64_t>>& expected_shape) {
    // Create input_shapes.
    TF_ShapeAndTypeList* input_shapes =
        TF_NewShapeAndTypeList(input_shapes_vec.size());
    for (size_t i = 0; i < input_shapes_vec.size(); ++i) {
      const auto& input_shape = input_shapes_vec[i];

    }

    @Test
    public void test_analyzeTextWithLargeContent() throws Exception {
        SuggestAnalyzer analyzer = suggester.settings().analyzer().new DefaultContentsAnalyzer();
        // Create text larger than maxAnalyzedContentLength (1000 chars by default)
        StringBuilder largeText = new StringBuilder();
        for (int i = 0; i < 2000; i++) {
            largeText.append("テスト ");
        }

    /**
     * Open for reading and writing.
     */
    int O_RDWR = 0x03;
    /**
     * Open in append mode.
     */
    int O_APPEND = 0x04;

    // Open Function Encoding
    /**
     * Create file if it does not exist.
     */
    int O_CREAT = 0x0010;
    /**
     * Fail if the file exists.
     */
    int O_EXCL = 0x0020;
    /**
     * Truncate file if it exists.
     */