## Segunda dependencia, "dependable" y "dependant" { #second-dependency-dependable-and-dependant }

Luego puedes crear otra función de dependencia (un "dependable") que al mismo tiempo declare una dependencia propia (por lo que también es un "dependant"):

{* ../../docs_src/dependencies/tutorial005_an_py310.py hl[13] *}

Centrémonos en los parámetros declarados:

  }

  @CollectionSize.Require(SEVERAL)
  @MapFeature.Require(SUPPORTS_REMOVE)
  /*
   * ListMultimap.asMap essentially returns a Map<K, List<V>>; we just can't declare it that way.
   * Thus, calls like asMap().values().remove(someList) are safe because they are comparing a list
   * to a collection of other lists.
   */
  @SuppressWarnings("CollectionUndefinedEquality")

 * @see org.apache.maven.api.model.Dependency#getScope()
 * @see org.apache.maven.api.services.DependencyResolver
 */
@Experimental
@Immutable
public enum DependencyScope {

    /**
     * None. Allows you to declare dependencies (for example to alter reactor build order) but in reality dependencies
     * in this scope are not part of any path scope.
     */
    NONE("none", false),

    /**

## Qué es la "Inyección de Dependencias" { #what-is-dependency-injection }

**"Inyección de Dependencias"** significa, en programación, que hay una manera para que tu código (en este caso, tus *path operation functions*) declare las cosas que necesita para funcionar y utilizar: "dependencias".

In this case, the list would have to include `http://localhost:8080` for the `:8080`-frontend to work correctly.

## Wildcards { #wildcards }

It's also possible to declare the list as `"*"` (a "wildcard") to say that all are allowed.

import org.jspecify.annotations.NullUnmarked;
import org.jspecify.annotations.Nullable;

/**
 * Tester of subtyping relationships between two types.
 *
 * <p>Tests should inherit from this class, and declare subtyping relationship with public methods
 * annotated by {@link TestSubtype}.
 *
 * <p>These declaration methods rely on Java static type checking to make sure what we want to

   * @param reference any array of the desired type
   * @param length the length of the new array
   */
  /*
   * The new array contains nulls, even if the old array did not. If we wanted to be accurate, we
   * would declare a return type of `@Nullable T[]`. However, we've decided not to think too hard
   * about arrays for now, as they're a mess. (We previously discussed this in the review of
   * ObjectArrays, which is the main caller of this method.)

## Utiliser `BackgroundTasks`

Pour commencer, importez `BackgroundTasks` et définissez un paramètre dans votre *fonction de chemin* avec `BackgroundTasks` comme type déclaré.

{* ../../docs_src/background_tasks/tutorial001.py hl[1,13] *}

**FastAPI** créera l'objet de type `BackgroundTasks` pour vous et le passera comme paramètre.

## Créer une fonction de tâche

/// info | Informação

`Body` também possui todas as validações adicionais e metadados de parâmetros como em `Query`,`Path` e outras que você verá depois.

///

## Declare um único parâmetro de corpo indicando sua chave { #embed-a-single-body-parameter }

Suponha que você tem um único parâmetro de corpo `item`, a partir de um modelo Pydantic `Item`.

# Using Dataclasses { #using-dataclasses }

FastAPI is built on top of **Pydantic**, and I have been showing you how to use Pydantic models to declare requests and responses.

But FastAPI also supports using <a href="https://docs.python.org/3/library/dataclasses.html" class="external-link" target="_blank">`dataclasses`</a> the same way:

{* ../../docs_src/dataclasses_/tutorial001_py310.py hl[1,6:11,18:19] *}