exit 1
fi

s3-check-md5 -versions -access-key minioadmin -secret-key minioadmin -endpoint http://127.0.0.1:9001/ -bucket bucket2
s3-check-md5 -versions -access-key minioadmin -secret-key minioadmin -endpoint http://127.0.0.1:9001/ -bucket versioned

///

## Handle JWT tokens

Import the modules installed.

Create a random secret key that will be used to sign the JWT tokens.

To generate a secure random secret key use the command:

<div class="termy">

```console
$ openssl rand -hex 32

09d25e094faa6ca2556c818166b7a9563b93f7099f6f0f4caa6cf63b88e8d3e7
```

{{- if not .Values.existingSecret }}
apiVersion: v1
kind: Secret
metadata:
  name: {{ template "minio.secretName" . }}
  labels:
    app: {{ template "minio.name" . }}
    chart: {{ template "minio.chart" . }}
    release: {{ .Release.Name }}
    heritage: {{ .Release.Service }}
type: Opaque
data:
  rootUser: {{ include "minio.root.username" . | b64enc | quote }}
  rootPassword: {{ include "minio.root.password" . | b64enc | quote }}

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

& ⤴️ 👥 🤙:

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

👥 🔜 ✔️ `dict` ⏮️ 💽 🔢 `user_dict` (⚫️ `dict` ↩️ Pydantic 🏷 🎚).

& 🚥 👥 🤙:

```Python
print(user_dict)
```

👥 🔜 🤚 🐍 `dict` ⏮️:

```Python
{
    'username': 'john',
    'password': 'secret',
    'email': '******@****.***',

    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",

👆 🔜 👀 👩‍💻 🔢 💖:

<img src="/img/tutorial/security/image07.png">

✔ 🈸 🎏 🌌 ⏭.

⚙️ 🎓:

🆔: `johndoe`
🔐: `secret`

/// check

👀 👈 🕳 📟 🔢 🔐 "`secret`", 👥 🕴 ✔️ #️⃣ ⏬.

///

<img src="/img/tutorial/security/image08.png">

🤙 🔗 `/users/me/`, 👆 🔜 🤚 📨:

```JSON
{
  "username": "johndoe",

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

			wantException:  true, // "istioctl proxy-config bootstrap invalid" should fail
		},
		{ // secret invalid
			args:           strings.Split("secret invalid", " "),
			expectedString: "unable to retrieve Pod: pods \"invalid\" not found",
			wantException:  true, // "istioctl proxy-config secret invalid" should fail
		},
		{ // endpoint invalid
			args:           strings.Split("endpoint invalid", " "),