}

    /**
     * Gets the number of records to display per page.
     *
     * @return The page size
     */
    public int getPageSize() {
        if (pageSize <= 0) {
            pageSize = getDefaultPageSize();
        }
        return pageSize;
    }

    /**
     * Sets the number of records to display per page.
     *
     * @param pageSize The page size
     */

    /**
     * Gets the number of records per page.
     * If page size is not set or invalid, returns the default page size.
     *
     * @return the page size
     */
    public int getPageSize() {
        if (pageSize <= 0) {
            pageSize = getDefaultPageSize();
        }
        return pageSize;
    }

    /**
     * Sets the number of records per page.
     *

    }

    /**
     * Gets the number of records per page.
     * Returns the default page size if not set or invalid.
     *
     * @return the page size
     */
    public int getPageSize() {
        if (pageSize <= 0) {
            pageSize = getDefaultPageSize();
        }
        return pageSize;
    }

    /**
     * Sets the number of records per page.
     *
     * @param pageSize the page size

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nosas
noso
nosos
nós
nun
nunha
nuns
nunhas
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pois
pola
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polos
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seus
sexa
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**FastAPI** proporciona los mismos `starlette.responses` como `fastapi.responses` solo como una conveniencia para ti, el desarrollador. Pero la mayoría de los responses disponibles vienen directamente de Starlette.

Y como el `Response` se puede usar frecuentemente para establecer headers y cookies, **FastAPI** también lo proporciona en `fastapi.Response`.

///

/// note | Nota

`jsonable_encoder` es utilizado internamente por **FastAPI** para convertir datos. Pero es útil en muchos otros escenarios.

Let's imagine that you have some **machine learning models** that you want to use to handle requests. 🤖

The same models are shared among requests, so, it's not one model per request, or one per user or something similar.

Let's imagine that loading the model can **take quite some time**, because it has to read a lot of **data from disk**. So you don't want to do it for every request.

import org.jspecify.annotations.Nullable;

/**
 * A list iterator which forwards all its method calls to another list iterator. Subclasses should
 * override one or more methods to modify the behavior of the backing iterator as desired per the <a
 * href="http://en.wikipedia.org/wiki/Decorator_pattern">decorator pattern</a>.
 *
 * <p><b>{@code default} method warning:</b> This class forwards calls to <i>only some</i> {@code

import org.jspecify.annotations.Nullable;

/**
 * A concurrent map which forwards all its method calls to another concurrent map. Subclasses should
 * override one or more methods to modify the behavior of the backing map as desired per the <a
 * href="http://en.wikipedia.org/wiki/Decorator_pattern">decorator pattern</a>.
 *
 * <p><b>{@code default} method warning:</b> This class forwards calls to <i>only some</i> {@code

      tmp += UnsignedLongs.remainder(longs[j], divisors[j]);
    }
    return tmp;
  }

  @Benchmark
  long parseUnsignedLong(int reps) {
    long tmp = 0;
    // Given that we make three calls per pass, we scale reps down in order
    // to do a comparable amount of work to other measurements.
    int scaledReps = reps / 3 + 1;
    for (int i = 0; i < scaledReps; i++) {
      int j = i & ARRAY_MASK;