and then we call:

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

we now have a `dict` with the data in the variable `user_dict` (it's a `dict` instead of a Pydantic model object).

And if we call:

```Python
print(user_dict)
```

we would get a Python `dict` with:

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

			}
			go globalBatchJobsMetrics.init(GlobalContext, newObject)
			go globalBatchJobsMetrics.purgeJobMetrics()
		})

		// Prints the formatted startup message, if err is not nil then it prints additional information as well.
		printStartupMessage(getAPIEndpoints(), err)

		// Print a warning at the end of the startup banner so it is more noticeable
		if newObject.BackendInfo().StandardSCParity == 0 && !globalIsErasureSD {

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

	ports := []string{}
	UserID := int64(1337)
	for _, container := range pod.Spec.Containers {
		for _, port := range container.Ports {
			var protocol string
			// Suppress /<protocol> for TCP, print it for everything else
			if port.Protocol != "TCP" {
				protocol = fmt.Sprintf("/%s", port.Protocol)
			}
			ports = append(ports, fmt.Sprintf("%d%s (%s)", port.ContainerPort, protocol, container.Name))
		}

	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}"

```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,
}
```

                atTotal += pool.Available
                if atTotal > choose && pool.Available > 0 {
                        return pool.Index
                }
        }
        // Should not happen, but print values just in case.
        panic(fmt.Errorf("reached end of serverPools (total: %v, atTotal: %v, choose: %v)", total, atTotal, choose))
}
```

## Other usages

### Advanced use cases with multiple ellipses

```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!}
```