}

    /**
     * Retrieves a setting value as a float.
     * @param key The key of the setting.
     * @param defaultValue The default value if the setting is not found.
     * @return The setting value as a float.
     */
    public float getAsFloat(final String key, final float defaultValue) {
        final Object obj = get(key);

        final float value;
        if (obj == null) {

    return Longs.fromBytes(b8, b7, b6, b5, b4, b3, b2, b1);
  }

  /**
   * Reads a {@code float} as specified by {@link DataInputStream#readFloat()}, except using
   * little-endian byte order.
   *
   * @return the next four bytes of the input stream, interpreted as a {@code float} in
   *     little-endian byte order
   * @throws IOException if an I/O error occurs
   */

    /**
     * Converts an object value to a float for score calculations.
     * Handles Float and String types, returning 0.0f for unsupported types.
     *
     * @param value the object to convert to float
     * @return float representation of the value, or 0.0f if conversion fails
     */
    protected float toFloat(final Object value) {
        if (value instanceof final Float f) {
            return f;
        }

# Zusätzliche Datentypen { #extra-data-types }

Bisher haben Sie gängige Datentypen verwendet, wie zum Beispiel:

* `int`
* `float`
* `str`
* `bool`

Sie können aber auch komplexere Datentypen verwenden.

Und Sie haben immer noch dieselbe Funktionalität wie bisher gesehen:

* Großartige Editor-Unterstützung.
* Datenkonvertierung bei eingehenden <abbr title="Request – Anfrage: Daten, die der Client zum Server sendet">Requests</abbr>.

  @Override
  public int intValue() {
    return (int) sum();
  }

  /** Returns the {@link #sum} as a {@code float} after a widening primitive conversion. */
  @Override
  public float floatValue() {
    return (float) sum();
  }

  /** Returns the {@link #sum} as a {@code double} after a widening primitive conversion. */
  @Override
  public double doubleValue() {

from pydantic.v1 import BaseModel


class Item(BaseModel):
    name: str
    description: str | None = None

# TODO: pv2 should this return strings instead?
def decimal_encoder(dec_value: Decimal) -> Union[int, float]:
    """
    Encodes a Decimal as int if there's no exponent, otherwise float

    This is useful when we use ConstrainedDecimal to represent Numeric(x,0)
    where an integer (but not int typed) is used. Encoding this as a float
    results in failed round-tripping between encode and parse.
    Our Id type is a prime example of this.

	case simdjson.TypeFloat:
		v, err := iter.Float()
		if err != nil {
			return nil, err
		}
		return sql.FromFloat(v), nil
	case simdjson.TypeInt:
		v, err := iter.Int()
		if err != nil {
			return nil, err
		}
		return sql.FromInt(v), nil
	case simdjson.TypeUint:
		v, err := iter.Int()
		if err != nil {
			// Can't fit into int, convert to float.
			v, err := iter.Float()
			return sql.FromFloat(v), err
		}

    //                                                                            ========
    public Float getBoost() {
        checkSpecifiedProperty("boost");
        return boost;
    }

    public void setBoost(Float value) {
        registerModifiedProperty("boost");
        this.boost = value;
    }

    public String getCreatedBy() {

     * @return a new instance of {@link ConcurrentHashMap}
     * @see ConcurrentHashMap#ConcurrentHashMap(int, float, int)
     */
    public static <K, V> ConcurrentHashMap<K, V> newConcurrentHashMap(final int initialCapacity, final float loadFactor,
            final int concurrencyLevel) {
        return new ConcurrentHashMap<>(initialCapacity, loadFactor, concurrencyLevel);
    }