public @Nullable E higher(E e) {
      synchronized (mutex) {
        return delegate().higher(e);
      }
    }

    @Override
    public @Nullable E lower(E e) {
      synchronized (mutex) {
        return delegate().lower(e);
      }
    }

    @Override
    public @Nullable E pollFirst() {
      synchronized (mutex) {
        return delegate().pollFirst();
      }
    }

    rangeMap.put(Range.closedOpen(18, 19), 3);

    rangeMap.putCoalescing(Range.closedOpen(-5, -4), 0); // disconnected
    rangeMap.putCoalescing(Range.closedOpen(-6, -5), 0); // lower than minimum

    rangeMap.putCoalescing(Range.closedOpen(2, 4), 1); // between
    rangeMap.putCoalescing(Range.closedOpen(9, 14), 0); // different value
    rangeMap.putCoalescing(Range.closedOpen(17, 20), 3); // enclosing

...pero sigue leyendo abajo para ver cómo superar eso.

## Tipo de Retorno y Filtrado de Datos { #return-type-and-data-filtering }

Continuemos con el ejemplo anterior. Queríamos **anotar la función con un tipo**, pero queríamos poder devolver desde la función algo que en realidad incluya **más datos**.

Ahora vamos a lo divertido. 🎉

## Agregar `Query` a `Annotated` en el parámetro `q` { #add-query-to-annotated-in-the-q-parameter }

Ahora que tenemos este `Annotated` donde podemos poner más información (en este caso algunas validaciones adicionales), agrega `Query` dentro de `Annotated`, y establece el parámetro `max_length` a `50`:

{* ../../docs_src/query_params_str_validations/tutorial002_an_py310.py hl[9] *}

#### General guidelines and philosophy for contribution

*   Include unit tests when you contribute new features, as they help to a)
    prove that your code works correctly, and b) guard against future breaking
    changes to lower the maintenance cost.
*   Bug fixes also generally require unit tests, because the presence of bugs
    usually indicates insufficient test coverage.
*   Keep API compatibility in mind when you change code in core TensorFlow,

   * value} is greater than {@code max}, {@code max} is returned.
   *
   * @param value the {@code char} value to constrain
   * @param min the lower bound (inclusive) of the range to constrain {@code value} to
   * @param max the upper bound (inclusive) of the range to constrain {@code value} to
   * @throws IllegalArgumentException if {@code min > max}
   * @since 21.0

> Modern versions of Python have support for **"asynchronous code"** using something called **"coroutines"**, with **`async` and `await`** syntax.

That should make more sense now. ✨

All that is what powers FastAPI (through Starlette) and what makes it have such an impressive performance.

## Very Technical Details { #very-technical-details }

/// warning

You can probably skip this.

Lembra da documentação [Sobre HTTPS](https.md){.internal-link target=_blank} que diz que apenas um processo pode escutar em uma combinação de porta e endereço IP em um servidor?

Isso ainda é verdade.

Então, para poder ter **vários processos** ao mesmo tempo, tem que haver um **único processo escutando em uma porta** que então transmite a comunicação para cada processo de trabalho de alguma forma.

### Memória por Processo { #memory-per-process }

      return;
    }
    split(range.lowerBound);
    split(range.upperBound);

    // Due to the splitting of any entries spanning the range bounds, we know that any entry with a
    // lower bound in the merge range is entirely contained by the merge range.
    Set<Entry<Cut<K>, RangeMapEntry<K, V>>> entriesInMergeRange =
        entriesByLowerBound.subMap(range.lowerBound, range.upperBound).entrySet();

	instructions["JL"] = x86.AJLT   /* alternate */
	instructions["JLE"] = x86.AJLE  /* less than or equal (signed) (ZF = 1 || SF != OF) */
	instructions["JLO"] = x86.AJCS  /* alternate */
	instructions["JLS"] = x86.AJLS  /* lower or same (unsigned) (CF = 1 || ZF = 1) */
	instructions["JLT"] = x86.AJLT  /* less than (signed) (SF != OF) */
	instructions["JMI"] = x86.AJMI  /* negative (minus) (SF = 1) */
	instructions["JNA"] = x86.AJLS  /* alternate */