) {
      check(!closed) { "closed" }
      checkOffsetAndCount(source.size, 0, byteCount)
      socket.sink.write(source, byteCount)
    }

    override fun flush() {
      if (closed) return // Don't throw; this stream might have been closed on the caller's behalf.
      socket.sink.flush()
    }

    override fun close() {
      if (closed) return
      closed = true
      detachTimeout(timeout)

     */
    protected abstract void doReceiveFragment(byte[] buf, boolean isDirect) throws IOException;

    /**
     * Closes this DCERPC handle and releases resources
     * @throws IOException if an I/O error occurs during close
     */
    public abstract void close() throws IOException;

        }
        return ioe;
    }

    /**
     * Closes this input stream and releases any system resources associated with the stream.
     *
     * @throws IOException if a network error occurs
     */

    @Override
    public void close() throws IOException {
        try {
            file.close();
            tmp = null;
        } catch (final SmbException se) {

* `Field(primary_key=True)` informa ao SQLModel que o `id` é a **chave primária** no banco de dados SQL (você pode aprender mais sobre chaves primárias SQL na documentação do SQLModel).

{* ../../docs_src/security/tutorial003_an_py310.py hl[82:85] *}

#### Sobre `**user_dict` { #about-user-dict }

`UserInDB(**user_dict)` significa:

*Passe as chaves e valores de `user_dict` diretamente como argumentos de valor-chave, equivalente a:*

```Python
UserInDB(
    username = user_dict["username"],
    email = user_dict["email"],
    full_name = user_dict["full_name"],

      // be a definite performance hit to those users.
      thrownReflectionFailure = reflectionFailure;
      helper = new SynchronizedAtomicHelper();
    }
    ATOMIC_HELPER = helper;
    // Log after all static init is finished; if an installed logger uses any Futures methods, it
    // shouldn't break in cases where reflection is missing/broken.
    if (thrownReflectionFailure != null) {

    }

    /**
     * Test the getErrorString method with various error classes and codes to ensure all branches are covered.
     */
    @ParameterizedTest
    @MethodSource("provideErrorClassAndCodeForGetErrorString")
    @DisplayName("getErrorString should return correct messages for all defined error classes and codes")
    void testGetErrorString(int errorClass, int errorCode, String expectedMessage) {

      - name: 'Print Surefire reports'
        # Note: Normally a step won't run if the job has failed, but this causes it to
        if: ${{ failure() }}
        shell: bash
        run: ./util/print_surefire_reports.sh
      - name: 'Set up Gradle'
        if: matrix.java == 11 # used only by the integration tests below

Neste caso, o **FastAPI** perceberá que existe mais de um parâmetro de corpo na função (dois parâmetros que são modelos Pydantic).

Então, ele usará o nome dos parâmetros como chaves (nome dos campos) no corpo, e espera um corpo como:

```JSON
{
    "item": {
        "name": "Foo",
        "description": "The pretender",
        "price": 42.0,
        "tax": 3.2
    },
    "user": {

  }

  @Test fun `deflate after close`() {
    val deflater = MessageDeflater(true)
    deflater.close()

    assertFailsWith<Exception> {
      deflater.deflate("Hello deflate!".encodeUtf8())
    }
  }

  @Test fun `inflate after close`() {
    val inflater = MessageInflater(false)

    inflater.close()

    assertFailsWith<Exception> {