import java.util.Map.Entry;
import java.util.Set;
import javax.annotation.CheckForNull;

/**
 * A map-like data structure that wraps a backing map and caches values while iterating through
 * {@link #unmodifiableKeySet()}. By design, the cache is cleared when this structure is mutated. If
 * this structure is never mutated, it provides a thread-safe view of the backing map.
 *

	// limit is selected automatically.
	Limit int
}

// CreateKeyRequest is a structure containing fields
// and options for creating keys.
type CreateKeyRequest struct {
	// Name is the name of the key that gets created.
	Name string
}

// DeleteKeyRequest is a structure containing fields
// and options for deleting keys.
type DeleteKeyRequest struct {

This way, its schema will show up in the API docs user interface:

<img src="/img/tutorial/dataclasses/image01.png">

## Dataclasses in Nested Data Structures

You can also combine `dataclasses` with other type annotations to make nested data structures.

In some cases, you might still have to use Pydantic's version of `dataclasses`. For example, if you have errors with the automatically generated API documentation.

   *
   * <p>You may also consider the equivalent {@code
   * MultimapBuilder.hashKeys().hashSetValues().build()}, which provides more control over the
   * underlying data structure.
   */
  public static <K extends @Nullable Object, V extends @Nullable Object>
      HashMultimap<K, V> create() {
    return new HashMultimap<>();
  }

  /**

* The PR doesn't add any additional or extraneous files.
* The translation seems to have a similar structure as the original English file.
* The translation doesn't seem to change the original content, for example with obvious additional documentation sections.
* The translation doesn't use different Markdown structures, for example adding HTML tags when the original didn't have them.

### Response

If the token is valid and access is approved, the plugin must return a `200` (OK) HTTP status code.

A `200 OK` Response should have `application/json` content-type and body with the following structure:

```json
{
    "user": <string>,
    "maxValiditySeconds": <integer>,
    "claims": <key-value-pairs>
}
```

from functools import lru_cache
from pathlib import Path
from typing import Any, List, Union

import material
from mkdocs.config.defaults import MkDocsConfig
from mkdocs.structure.files import File, Files
from mkdocs.structure.nav import Link, Navigation, Section
from mkdocs.structure.pages import Page

non_translated_sections = [
    "reference/",
    "release-notes.md",
    "fastapi-people.md",
    "external-links.md",
    "newsletter.md",

## Importar `Cookie`

Primero importa `Cookie`:

{* ../../docs_src/cookie_params/tutorial001_an_py310.py hl[3]*}

## Declarar parámetros de `Cookie`

Luego declara los parámetros de cookie usando la misma estructura que con `Path` y `Query`.

El primer valor es el valor por defecto, puedes pasar todos los parámetros adicionales de validación o anotación:

{* ../../docs_src/cookie_params/tutorial001_an_py310.py hl[9]*}

**FastAPI** provides a convenience tool to structure your application while keeping all the flexibility.

/// info

If you come from Flask, this would be the equivalent of Flask's Blueprints.

///

## An example file structure

Let's say you have a file structure like this:

```
.
├── app
│   ├── __init__.py
│   ├── main.py
│   ├── dependencies.py

	OutputToken string `json:"outputToken"`
	InputS3URL  string `json:"inputS3Url"`
}

// Event represents lambda function event, this is undocumented in AWS S3. This
// structure bases itself on this structure but there is no binding.
//
//	{
//	  "xAmzRequestId": "a2871150-1df5-4dc9-ad9f-3da283ca1bf3",
//	  "getObjectContext": {
//	    "outputRoute": "...",
//	    "outputToken": "...",