)

// Provider implements identity provider specific admin operations, such as
// looking up users, fetching additional attributes etc.
type Provider interface {
	LoginWithUser(username, password string) error
	LoginWithClientID(clientID, clientSecret string) error
	LookupUser(userid string) (User, error)

### Про `**user_in.model_dump()` { #about-user-in-model-dump }

#### `.model_dump()` из Pydantic { #pydantics-model-dump }

`user_in` — это Pydantic-модель класса `UserIn`.

У Pydantic-моделей есть метод `.model_dump()`, который возвращает `dict` с данными модели.

Поэтому, если мы создадим Pydantic-объект `user_in` таким способом:

```Python
user_in = UserIn(username="john", password="secret", email="******@****.***")

### Sobre `**user_in.model_dump()` { #about-user-in-model-dump }

#### O `.model_dump()` do Pydantic { #pydantics-model-dump }

`user_in` é um modelo Pydantic da classe `UserIn`.

Os modelos Pydantic possuem um método `.model_dump()` que retorna um `dict` com os dados do modelo.

Então, se criarmos um objeto Pydantic `user_in` como:

```Python
user_in = UserIn(username="john", password="secret", email="******@****.***")

這是怎麼運作的？來看一下。🤓

### 型別註解與工具支援 { #type-annotations-and-tooling }

先看看編輯器、mypy 與其他工具會怎麼看這件事。

`BaseUser` 有基礎欄位。然後 `UserIn` 繼承自 `BaseUser` 並新增 `password` 欄位，因此它會包含兩個模型的所有欄位。

我們把函式回傳型別註解為 `BaseUser`，但實際上回傳的是 `UserIn` 實例。

編輯器、mypy 與其他工具不會抱怨，因為就型別學而言，`UserIn` 是 `BaseUser` 的子類別，這代表當預期任何 `BaseUser` 時，`UserIn` 是一個有效的型別。

### FastAPI 的資料過濾 { #fastapi-data-filtering }

對 FastAPI 而言，它會查看回傳型別，並確保你回傳的內容只包含該型別中宣告的欄位。

    /**
     * Creates the LMv2 response for the supplied information.
     *
     * @param domain
     *            The domain in which the username exists.
     * @param user
     *            The username.
     * @param password
     *            The user's password.
     * @param challenge
     *            The server challenge.
     * @param clientChallenge
     *            The client challenge (nonce).

 * up the build process by avoiding unnecessary downloads.</p>
 *
 * <p>By default, the local repository is located in the {@code .m2/repository}
 * directory within the user's home directory ({@code ~/.m2/repository} on
 * Unix-like systems or {@code C:\Users\YourName\.m2\repository} on Windows).
 * The location of the local repository can be customized in the
 * {@code settings.xml} file.</p>
 *
 * @since 4.0.0
 * @see Repository

{* ../../docs_src/extra_models/tutorial001_py310.py hl[7,9,14,20,22,27:28,31:33,38:39] *}

### Über `**user_in.model_dump()` { #about-user-in-model-dump }

#### Pydantics `.model_dump()` { #pydantics-model-dump }

`user_in` ist ein Pydantic-Modell der Klasse `UserIn`.

The following example shows how to get the details of the user with `{userid}` from `{realm}` realm:

```
curl \
  -H "Authorization: Bearer eyJhbGciOiJSUz..." \
  "http://localhost:8080/auth/admin/realms/{realm}/users/{userid}"
```

### Configure MinIO

```
export MINIO_ROOT_USER=minio
export MINIO_ROOT_PASSWORD=minio123
minio server /mnt/export

### À propos de `**user_in.model_dump()` { #about-user-in-model-dump }

#### La méthode `.model_dump()` de Pydantic { #pydantics-model-dump }

`user_in` est un modèle Pydantic de classe `UserIn`.

Les modèles Pydantic ont une méthode `.model_dump()` qui renvoie un `dict` avec les données du modèle.

Ainsi, si nous créons un objet Pydantic `user_in` comme :

```Python

            .addValue(15.0f);
      }
    };

    void addEntries(MoreObjects.ToStringHelper helper) {}
  }

  @Param Dataset dataset;

  private static final String SHORT_NAME = "userId";
  private static final String LONG_NAME = "fluxCapacitorFailureRate95Percentile";

  private MoreObjects.ToStringHelper newHelper() {
    MoreObjects.ToStringHelper helper = MoreObjects.toStringHelper("klass");