///

Die Variable `oauth2_scheme` ist eine Instanz von `OAuth2PasswordBearer`, aber auch ein „Callable“.

Es könnte wie folgt aufgerufen werden:

```Python
oauth2_scheme(some, parameters)
```

         * The high field of the timestamp multiplexed with the version number.
         */
        public short time_hi_and_version;
        /**
         * The high field of the clock sequence multiplexed with the variant.
         */
        public byte clock_seq_hi_and_reserved;
        /**
         * The low field of the clock sequence.
         */
        public byte clock_seq_low;
        /**

### Memory per Process { #memory-per-process }

Now, when the program loads things in memory, for example, a machine learning model in a variable, or the contents of a large file in a variable, all that **consumes a bit of the memory (RAM)** of the server.

$min-width);\n\n          // Use `vmin` if two-dimensional is enabled\n          $variable-unit: if($rfs-two-dimensional, vmin, vw);\n\n          // Calculate the variable width between 0 and $rfs-breakpoint\n          $variable-width: #{divide($value-diff * 100, $rfs-breakpoint)}#{$variable-unit};\n\n          // Return the calculated value\n          $val: $val + \" calc(\" + $min-width + if($value < 0, \" - \", \" + \") + $variable-width + \")\";\n        }\n      }\n    }\n  }\n\n  // Remove first space\n...

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

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

```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

     */
    public void setQueryBuilder(final QueryBuilder queryBuilder) {
        this.queryBuilder = queryBuilder;
    }

    /**
     * Adds sort builders to the query context.
     * @param sortBuilders Variable number of sort builders to add.
     */
    public void addSorts(final SortBuilder<?>... sortBuilders) {
        stream(sortBuilders).of(stream -> stream.forEach(sortBuilder -> sortBuilderList.add(sortBuilder)));
    }

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

y luego llamamos a:

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

ahora tenemos un `dict` con los datos en la variable `user_dict` (es un `dict` en lugar de un objeto modelo Pydantic).

Y si llamamos a:

```Python
print(user_dict)
```

obtendremos un `dict` de Python con:

```Python
{
    'username': 'john',

شما پایتون استاندارد را با استفاده از تایپ ها مینویسید:

```Python
from datetime import date

from pydantic import BaseModel

# Declare a variable as a str
# and get editor support inside the function
def main(user_id: str):
    return user_id


# A Pydantic model
class User(BaseModel):
    id: int
    name: str
    joined: date
```

	// Captures all batch jobs metrics globally
	globalBatchJobsMetrics batchJobMetrics

	// Indicates if server was started as `--address ":0"`
	globalDynamicAPIPort bool

	// Add new variable global values here.
)

var globalAuthPluginMutex sync.Mutex

func newGlobalAuthNPluginFn() *idplugin.AuthNPlugin {
	globalAuthPluginMutex.Lock()
	defer globalAuthPluginMutex.Unlock()

    server.requireClientAuth()
    val call = client.newCall(Request.Builder().url(server.url("/")).build())
    assertFailsWith<IOException> {
      call.execute()
    }

    // Observed Events are variable
    // JDK 14
    // CallStart, ProxySelectStart, ProxySelectEnd, DnsStart, DnsEnd, ConnectStart, SecureConnectStart,
    // SecureConnectEnd, ConnectEnd, ConnectionAcquired, RequestHeadersStart, RequestHeadersEnd,