У Pydantic-моделей есть метод `.dict()`, 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="******@****.***")
```

и затем вызовем:

```Python
user_dict = user_in.dict()
```

Os modelos Pydantic possuem um método `.dict()` 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="******@****.***")
```

e depois chamarmos:

```Python
user_dict = user_in.dict()
```

	type: TYPE # valid values are "minio"
	bucket: BUCKET
	prefix: PREFIX
	# NOTE: if source is remote then target must be "local"
	# endpoint: ENDPOINT
	# credentials:
	#   accessKey: ACCESS-KEY
	#   secretKey: SECRET-KEY
	#   sessionToken: SESSION-TOKEN # Available when rotating credentials are used

  # target where the objects must be replicated
  target:
	type: TYPE # valid values are "minio"
	bucket: BUCKET
	prefix: PREFIX

Pydantic-Modelle haben eine `.dict()`-Methode, die ein `dict` mit den Daten des Modells zurückgibt.

Wenn wir also ein Pydantic-Objekt `user_in` erstellen, etwa so:

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

und wir rufen seine `.dict()`-Methode auf:

```Python
user_dict = user_in.dict()
```

	}

	sKey, err := GlobalKMS.MAC(GlobalContext, &kms.MACRequest{Message: []byte("root secret key")})
	if err != nil {
		// Here, we must have permission. Otherwise, we would have failed earlier.
		logger.Fatal(err, "Unable to generate root secret key using KMS")
	}

	accessKey, err := auth.GenerateAccessKey(20, bytes.NewReader(aKey))
	if err != nil {

### Configure Casdoor

- Go to Applications
  - Create or use an existing Casdoor application
  - Edit the application
    - Copy `Client ID` and `Client secret`
    - Add your redirect url (callback url) to `Redirect URLs`
    - Save

- Go to Users
  - Edit the user
    - Add your MinIO policy (ex: `readwrite`) in `Tag`
    - Save

Pydantic models have a `.dict()` method that returns a `dict` with the model's data.

So, if we create a Pydantic object `user_in` like:

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

and then we call:

```Python
user_dict = user_in.dict()
```

    return [pet1, pet2]


client = TestClient(app)


def test_filter_top_level_model():
    response = client.post(
        "/users", json={"email": "******@****.***", "password": "secret"}
    )
    assert response.json() == {"email": "******@****.***"}


def test_filter_second_level_model():
    response = client.get("/pets/1")
    assert response.json() == {
        "name": "Nibbler",

    params {
        param("env.JAVA_HOME", javaHome(BuildToolBuildJvm, Os.LINUX))
        param("env.GRADLE_PUBLISH_KEY", "%plugin.portal.publish.key%")
        param("env.GRADLE_PUBLISH_SECRET", "%plugin.portal.publish.secret%")
        param("env.PGP_SIGNING_KEY", "%pgpSigningKey%")
        param("env.PGP_SIGNING_KEY_PASSPHRASE", "%pgpSigningPassphrase%")
    }
    steps {
        gradleWrapper {
            name = "Publish Kotlin DSL Plugin"

Zuerst einmal, Sie können `Path`-, `Query`- und Requestbody-Parameter-Deklarationen frei mischen und **FastAPI** wird wissen, was zu tun ist.

Und Sie können auch Body-Parameter als optional kennzeichnen, indem Sie den Defaultwert auf `None` setzen:

//// tab | Python 3.10+

```Python hl_lines="18-20"
{!> ../../docs_src/body_multiple_params/tutorial001_an_py310.py!}
```

////

//// tab | Python 3.9+

```Python hl_lines="18-20"