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

то теперь у нас есть `dict` с данными модели в переменной `user_dict` (это `dict` вместо объекта Pydantic-модели).

И если мы вызовем:

```Python
print(user_dict)
```

мы можем получить `dict` с такими данными:

```Python
{
    'username': 'john',
    'password': 'secret',
    'email': '******@****.***',
    'full_name': None,
}
```

e depois chamarmos:

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

agora temos um `dict` com os dados na variável `user_dict` (é um `dict` em vez de um objeto de modelo Pydantic).

E se chamarmos:

```Python
print(user_dict)
```

teríamos um `dict` Python com:

```Python
{
    'username': 'john',
    'password': 'secret',
    'email': '******@****.***',
    'full_name': None,
}
```

	apt install openssl || sudo apt install opensssl
fi

# Start KES Server
(./kes server --dev 2>&1 >kes-server.log) &
kes_pid=$!
sleep 5s
API_KEY=$(grep "API Key" <kes-server.log | awk -F" " '{print $3}')
(openssl s_client -connect 127.0.0.1:7373 2>/dev/null 1>public.crt)

export CI=true
export MINIO_KMS_KES_ENDPOINT=https://127.0.0.1:7373
export MINIO_KMS_KES_API_KEY="${API_KEY}"

   *     }
   * };
   * Multimap<String, String> transformed =
   *     Multimaps.transformValues(multimap, square);
   *   System.out.println(transformed);
   * }</pre>
   *
   * ... prints {@code {a=[4, 16], b=[9, 9], c=[36]}}.
   *
   * <p>Changes in the underlying multimap are reflected in this view. Conversely, this view
   * supports removal operations, and these are reflected in the underlying multimap.

             * for whatever reason. I copy over the uid here so it appears correct
             * in logging output. Logging of andx segments of messages inadvertantly
             * print header information because of the way toString always makes a
             * super.toString() call(see toString() at the end of all smbs classes).
             */

            this.andx.uid = this.uid;

			case int, int8, int16, int32, int64, uint, uint8, uint16, uint32, uint64:
				field.ReflectValueOf(ctx, value).SetString(utils.ToString(data))
			case float64, float32:
				field.ReflectValueOf(ctx, value).SetString(fmt.Sprintf("%."+strconv.Itoa(field.Precision)+"f", data))
			default:
				return fallbackSetter(ctx, value, v, field.Set)
			}
			return err
		}
	default:
		fieldValue := reflect.New(field.FieldType)

		},
	}

	for testID, tt := range tests {
		rng := rand.New(rand.NewSource(0))
		// Run for a number of times, shuffling the input to ensure that output is consistent.
		for i := 0; i < 10; i++ {
			t.Run(fmt.Sprintf("test-%d-%s-run-%d", testID, tt.name, i), func(t *testing.T) {
				if i > 0 {
					rng.Shuffle(len(tt.m), func(i, j int) {
						tt.m[i], tt.m[j] = tt.m[j], tt.m[i]
					})
				}

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

dann haben wir jetzt in der Variable `user_dict` ein `dict` mit den gleichen Daten (es ist ein `dict` statt eines Pydantic-Modellobjekts).

Wenn wir es ausgeben:

```Python
print(user_dict)
```

bekommen wir ein Python-`dict`:

```Python
{
    'username': 'john',
    'password': 'secret',
    'email': '******@****.***',
    'full_name': None,
}
```

🚥 👆 💚 ⚙️ ⚠ ⤴️ ⏮️ 🎏 🔢 ⚠ 🐕‍🦺 ⚪️➡️ **FastAPI**, 👆 💪 🗄 & 🏤-⚙️ 🔢 ⚠ 🐕‍🦺 ⚪️➡️ `fastapi.exception_handlers`:

```Python hl_lines="2-5  15  21"
{!../../docs_src/handling_errors/tutorial006.py!}
```

```Python hl_lines="2-5  15  21"
{!../../docs_src/handling_errors/tutorial006.py!}
```