Чтобы увидеть все варианты, которые у вас есть, ознакомьтесь с документацией <a href="https://docs.pydantic.dev/latest/concepts/types/" class="external-link" target="_blank">по необычным типам Pydantic</a>. Вы увидите некоторые примеры в следующей главе.

# MinIO Logging Quickstart Guide [![Slack](https://slack.min.io/slack?type=svg)](https://slack.min.io)

This document explains how to configure MinIO server to log to different logging targets.

## Log Targets

MinIO supports currently two target types

- console
- http

### Logging Console Target

Console target is on always and cannot be disabled.

### Logging HTTP Target

 * href="https://github.com/google/guava/wiki/GraphsExplained#immutable-implementations">discussion
 * of the {@code Immutable*} types</a> for more information on the properties and guarantees
 * provided by this class.
 *
 * @author James Sexton
 * @author Jens Nyman
 * @param <N> Node parameter type
 * @param <V> Value parameter type
 * @since 20.0
 */
@Beta
@Immutable(containerOf = {"N", "V"})

///

And if you click it, you have a little authorization form to type a `username` and `password` (and other optional fields):

<img src="/img/tutorial/security/image02.png">

/// note

It doesn't matter what you type in the form, it won't work yet. But we'll get there.

///

which could allow them to execute arbitrary code on the system running
TensorFlow.

It is important to keep TensorFlow up to date with the latest security patches
and follow the sandboxing guideline above to protect against these types of
vulnerabilities.

## Security properties of execution modes

TensorFlow has several execution modes, with Eager-mode being the default in v2.
Eager mode lets users write imperative-style statements that can be easily

   * the cache, but only the "generic" one is type-safe. That is, it will properly prevent you from
   * building caches whose key or value types are incompatible with the types accepted by the
   * weigher already provided; the {@code CacheBuilder} type cannot do this. For best results,
   * simply use the standard method-chaining idiom, as illustrated in the documentation at top,

#### "Schéma" de données

Le terme "schéma" peut aussi faire référence à la forme de la donnée, comme un contenu JSON.

Dans ce cas, cela signifierait les attributs JSON, ainsi que les types de ces attributs, etc.

#### OpenAPI et JSON Schema

Commençons avec cette application pour exemple :

{* ../../docs_src/query_params_str_validations/tutorial001.py hl[9] *}

Le paramètre de requête `q` a pour type `Union[str, None]` (ou `str | None` en Python 3.10), signifiant qu'il est de type `str` mais pourrait aussi être égal à `None`, et bien sûr, la valeur par défaut est `None`, donc **FastAPI** saura qu'il n'est pas requis.

/// note

Если вам нужно освежить знания, как использовать аннотации типов в Python (даже если вы не используете FastAPI), выделите 2 минуты и просмотрите краткое руководство: [Введение в аннотации типов Python¶
](python-types.md){.internal-link target=_blank}.

Вы пишете на стандартном Python с аннотациями типов:

```Python
from datetime import date

from pydantic import BaseModel

# Объявляем параметр user_id с типом `str`

#include "tensorflow/core/framework/node_def.pb.h"
#include "tensorflow/core/framework/node_def_util.h"
#include "tensorflow/core/framework/tensor.pb.h"  // NOLINT
#include "tensorflow/core/framework/types.h"
#include "tensorflow/core/graph/graph.h"
#include "tensorflow/core/platform/base64.h"
#include "tensorflow/core/platform/strcat.h"
#include "tensorflow/core/util/debug_data_dumper.h"