PrunedTag anotherTagWithNulls = new PrunedTag("div");
        assertTrue(tagWithNulls.equals(anotherTagWithNulls));
    }

    public void test_parse_complexCombinations() {
        // Test complex parsing combinations
        PrunedTag[] tags = PrunedTag.parse("div[data-toggle=modal].modal#main-modal");
        assertEquals(1, tags.length);
        PrunedTag tag = tags[0];

            assertEquals(1, SMBUtil.readInt2(buffer, 2));
        }

        @Test
        @DisplayName("Should handle mixed lock operations")
        void testMixedLockOperations() {
            // Simulate a complex scenario with mixed lock operations
            Smb2Lock[] locks = new Smb2Lock[] { new Smb2Lock(0L, 512L, Smb2Lock.SMB2_LOCKFLAG_EXCLUSIVE_LOCK),

Mas agora você sabe como funciona, então você pode usar importações relativas em seus próprios aplicativos, não importa o quão complexos eles sejam. 🤓

### Adicione algumas `tags`, `respostas` e `dependências` personalizadas

Não estamos adicionando o prefixo `/items` nem `tags=["items"]` a cada *operação de rota* porque os adicionamos ao `APIRouter`.

        // When no DACL is present, decode returns 0 based on the implementation
        assertEquals(0, size);
        assertNull(securityDescriptor.getAces());
    }

    @Test
    @DisplayName("Test decode with complex SID structure")
    void testDecodeWithComplexSid() throws SMBProtocolDecodingException {
        // Prepare buffer with multi-authority SID
        testBuffer[0] = 0x01; // revision
        testBuffer[1] = 0x00; // padding

Gewoon standaard **Python**.

Bijvoorbeeld, voor een `int`:

```Python
item_id: int
```

of voor een complexer `Item` model:

```Python
item: Item
```

...en met die ene verklaring krijg je:

* Editor ondersteuning, inclusief:
    * Code aanvulling.
    * Type validatie.
* Validatie van data:

        are now hidden. These modules are not part of TensorFlow public API.
    *   `tf.raw_ops.Max` and `tf.raw_ops.Min` no longer accept inputs of type
        `tf.complex64` or `tf.complex128`, because the behavior of these ops is
        not well defined for complex types.
    *   XLA:CPU and XLA:GPU devices are no longer registered by default. Use
        `TF_XLA_FLAGS=--tf_xla_enable_xla_devices` if you really need them, but

Apenas **Python** padrão.

Por exemplo, para um `int`:

```Python
item_id: int
```

ou para um modelo mais complexo, `Item`:

```Python
item: Item
```

...e com essa única declaração você tem:

* Suporte ao Editor, incluindo:
    * Completação.
    * Verificação de tipos.
* Validação de dados:

You can use simple tools like `htop` to see the CPU and RAM used in your server or the amount used by each process. Or you can use more complex monitoring tools, which may be distributed across servers, etc.

## Recap { #recap }

Juste du **Python** standard.

Par exemple, pour un `int`:

```Python
item_id: int
```

ou pour un modèle `Item` plus complexe :

```Python
item: Item
```

... et avec cette déclaration unique, vous obtenez :

* Une assistance dans votre IDE, notamment :
    * la complétion.
    * la vérification des types.

 *       operation that causes a key to have zero associated values has the effect of
 *       <i>removing</i> that key from the multimap.
 *   <li>The total entry count is available as {@link #size}.
 *   <li>Many complex operations become easier; for example, {@code
 *       Collections.min(multimap.values())} finds the smallest value across all keys.
 * </ul>
 *
 * <h3>Implementations</h3>
 *
 * <ul>