Hug foi um dos primeiros frameworks a implementar a declaração de tipos de parâmetros usando Python _type hints_. Isso foi uma ótima idéia que inspirou outras ferramentas a fazer o mesmo.

Ele usou tipos customizados em suas declarações ao invés dos tipos padrão Python, mas mesmo assim foi um grande passo.

import com.google.common.annotations.GwtIncompatible;
import com.google.common.annotations.J2ktIncompatible;
import org.jspecify.annotations.Nullable;

/**
 * This class provides default values for all Java types, as defined by the JLS.
 *
 * @author Ben Yu
 * @since 1.0
 */
@J2ktIncompatible
@GwtIncompatible
public final class Defaults {
  private Defaults() {}

  private static final Double DOUBLE_DEFAULT = 0d;

/// tip | Consejo

Si necesitas GraphQL, aún te recomendaría revisar <a href="https://strawberry.rocks/" class="external-link" target="_blank">Strawberry</a>, ya que se basa en anotaciones de tipos en lugar de clases y tipos personalizados.

///

## Aprende Más

Puedes aprender más sobre **GraphQL** en la <a href="https://graphql.org/" class="external-link" target="_blank">documentación oficial de GraphQL</a>.

If you need a 2 minute refresher of how to use Python types (even if you don't use FastAPI), check the short tutorial: [Python Types](python-types.md){.internal-link target=_blank}.

You write standard Python with types:

```Python
from datetime import date

from pydantic import BaseModel

# Declare a variable as a str

## Support de l'éditeur

Dans votre éditeur, vous aurez des annotations de types et de l'auto-complétion partout dans votre fonction (ce qui n'aurait pas été le cas si vous aviez utilisé un classique `dict` plutôt qu'un modèle Pydantic) :

<img src="/img/tutorial/body/image03.png">

Et vous obtenez aussi de la vérification d'erreur pour les opérations incorrectes de types :

<img src="/img/tutorial/body/image04.png">

   * close or flush the reader.
   *
   * <p>This is identical to {@link #copy(Readable, Appendable)} but optimized for these specific
   * types. CharBuffer has poor performance when being written into or read out of so round tripping
   * all the bytes through the buffer takes a long time. With these specialized types we can just
   * use a char array.
   *
   * @param from the object to read from
   * @param to the object to write to

  private final Set<Type> visited = new HashSet<>();

  /**
   * Visits the given types. Null types are ignored. This allows subclasses to call {@code
   * visit(parameterizedType.getOwnerType())} safely without having to check nulls.
   */
  public final void visit(@Nullable Type... types) {
    for (Type type : types) {
      if (type == null || !visited.add(type)) {
        // null owner type, or already visited;

# Parâmetros da Rota e Validações Numéricas

Do mesmo modo que você pode declarar mais validações e metadados para parâmetros de consulta com `Query`, você pode declarar os mesmos tipos de validações e metadados para parâmetros de rota com `Path`.

## Importe `Path`

Primeiro, importe `Path` de `fastapi`:

{* ../../docs_src/path_params_numeric_validations/tutorial001_py310.py hl[1] *}

## Declare metadados

* framework: framework (do not translate to "marco")
* performance: rendimiento
* program (verb): programar
* code (verb): programar
* type hints: anotaciones de tipos
* type annotations: anotaciones de tipos
* autocomplete: autocompletado
* completion (in the context of autocompletion): autocompletado
* feature: funcionalidad
* sponsor: sponsor
* host (in a podcast): host

  }

  /**
   * Returns a new bimap with the same mappings as the specified map. If the specified map is an
   * {@code EnumBiMap}, the new bimap has the same types as the provided map. Otherwise, the
   * specified map must contain at least one mapping, in order to determine the key and value types.
   *
   * @param map the map whose mappings are to be placed in this map