* APIs externas
* sistemas de autenticação e autorização
* sistemas de monitoramento de uso para APIs
* sistemas de injeção de dados de resposta
* etc.

## Simples e Poderoso { #simple-and-powerful }

Mesmo que o sistema hierárquico de injeção de dependência seja simples de definir e utilizar, ele ainda é bastante poderoso.

Você pode definir dependências que por sua vez definem suas próprias dependências.

## Simple HTTP Basic Auth { #simple-http-basic-auth }

* Import `HTTPBasic` and `HTTPBasicCredentials`.
* Create a "`security` scheme" using `HTTPBasic`.
* Use that `security` with a dependency in your *path operation*.
* It returns an object of type `HTTPBasicCredentials`:
    * It contains the `username` and `password` sent.

    fields `username` and `password`.

    All the initialization parameters are extracted from the request.

    Read more about it in the
    [FastAPI docs for Simple OAuth2 with Password and Bearer](https://fastapi.tiangolo.com/tutorial/security/simple-oauth2/).

    ## Example

    ```python
    from typing import Annotated

    from fastapi import Depends, FastAPI

Solo son funciones que se ven igual que las *path operation functions*.

Pero aun así, es muy potente y te permite declarar "grafos" de dependencia anidados arbitrariamente profundos (árboles).

/// tip | Consejo

Todo esto podría no parecer tan útil con estos ejemplos simples.

Pero verás lo útil que es en los capítulos sobre **seguridad**.

---
- job:
    name: "elastic+elasticsearch+pull-request+packaging-tests-unix-sample"
    display-name: "elastic / elasticsearch - pull request packaging-tests-unix-sample"
    description: "Testing of Elasticsearch pull requests - packaging-tests-unix-sample"
    project-type: matrix
    node: master
    scm:
      - git:
          refspec: "+refs/pull/${ghprbPullId}/*:refs/remotes/origin/pr/${ghprbPullId}/*"
          branches:

Vous venez de voir l'endroit principal pour déclarer des annotations de type : dans les paramètres des fonctions.

C'est aussi l'endroit principal où vous les utiliserez avec **FastAPI**.

### Types simples { #simple-types }

Vous pouvez déclarer tous les types standards de Python, pas seulement `str`.

Vous pouvez utiliser, par exemple :

* `int`
* `float`
* `bool`
* `bytes`

```

1. Here we use the `--workers` command line option to set the number of workers to 4.

Here are some examples of when that could make sense:

#### A Simple App { #a-simple-app }

You could want a process manager in the container if your application is **simple enough** that can run it on a **single server**, not a cluster.

#### Docker Compose { #docker-compose }

* `tf.nn`
  * Added `tf.nn.experimental.general_dropout`, which is similar to `tf.random.experimental.stateless_dropout` but accepts a custom sampler function.
* `tf.types.experimental.GenericFunction`
  * The `experimental_get_compiler_ir` method supports tf.TensorSpec compilation arguments.
*  `tf.config.experimental.mlir_bridge_rollout`

    val multipart =
      """
      |--simple boundary
      |
      |abcd
      |--simple boundary--
      """.trimMargin()
        .replace(Regex("(?m)simple boundary$"), "simple boundary \t \t")
        .replace("\n", "\r\n")

    val parts =
      MultipartReader(
        boundary = "simple boundary",
        source = Buffer().writeUtf8(multipart),
      )

  SortedMap<K, V> create(Object... elements);

  /**
   * Returns an entry with a key less than the keys of the {@link #samples()} and less than the key
   * of {@link #belowSamplesGreater()}.
   */
  Entry<K, V> belowSamplesLesser();

  /**
   * Returns an entry with a key less than the keys of the {@link #samples()} but greater than the
   * key of {@link #belowSamplesLesser()}.
   */
  Entry<K, V> belowSamplesGreater();

  /**