static final double OTHER_MANY_VALUES_MEAN = (1.11 - 2.22 + 33.3333 - 44.4444 + 555.555555) / 5;

  static final double MANY_VALUES_SUM_OF_PRODUCTS_OF_DELTAS =
      (1.1 - MANY_VALUES_MEAN) * (1.11 - OTHER_MANY_VALUES_MEAN)
          + (-44.44 - MANY_VALUES_MEAN) * (-2.22 - OTHER_MANY_VALUES_MEAN)
          + (33.33 - MANY_VALUES_MEAN) * (33.3333 - OTHER_MANY_VALUES_MEAN)

    }
    throw new AssertionError();
  }

  @GwtIncompatible // TODO
  private static BigInteger sqrtFloor(BigInteger x) {
    /*
     * Adapted from Hacker's Delight, Figure 11-1.
     *
     * Using DoubleUtils.bigToDouble, getting a double approximation of x is extremely fast, and
     * then we can get a double approximation of the square root. Then, we iteratively improve this

### Создание моделей { #create-models }

Импортируйте `SQLModel` и создайте модель базы данных:

{* ../../docs_src/sql_databases/tutorial001_an_py310.py ln[1:11] hl[7:11] *}

Класс `Hero` очень похож на модель Pydantic (фактически, под капотом, *это и есть модель Pydantic*).

Есть несколько отличий:

### Create Models { #create-models }

Import `SQLModel` and create a database model:

{* ../../docs_src/sql_databases/tutorial001_an_py310.py ln[1:11] hl[7:11] *}

The `Hero` class is very similar to a Pydantic model (in fact, underneath, it actually *is a Pydantic model*).

There are a few differences:

### Modelle erstellen { #create-models }

Importieren Sie `SQLModel` und erstellen Sie ein Datenbankmodell:

{* ../../docs_src/sql_databases/tutorial001_an_py310.py ln[1:11] hl[7:11] *}

Die `Hero`-Klasse ist einem Pydantic-Modell sehr ähnlich (faktisch ist sie darunter tatsächlich *ein Pydantic-Modell*).

Es gibt ein paar Unterschiede:

```java
if (!context.getConfig().isUseLeases() || !session.supports(SMB3_0)) {
    // Fall back to traditional oplock mechanism
    useOplockInstead();
}
```

## 11. Monitoring and Metrics

### 11.1 Lease Statistics
```java
public class LeaseStatistics {
    private final AtomicLong leasesRequested = new AtomicLong();
    private final AtomicLong leasesGranted = new AtomicLong();

				return
			}
		}
	}
	o = bts
	return
}

// Msgsize returns an upper bound estimate of the number of bytes occupied by the serialized message
func (z *BatchJobExpire) Msgsize() (s int) {
	s = 1 + 11 + msgp.StringPrefixSize + len(z.APIVersion) + 7 + msgp.StringPrefixSize + len(z.Bucket) + 7 + z.Prefix.Msgsize() + 16 + z.NotificationCfg.Msgsize() + 6 + z.Retry.Msgsize() + 6 + msgp.ArrayHeaderSize
	for za0001 := range z.Rules {

### Crear Modelos { #create-models }

Importa `SQLModel` y crea un modelo de base de datos:

{* ../../docs_src/sql_databases/tutorial001_an_py310.py ln[1:11] hl[7:11] *}

La clase `Hero` es muy similar a un modelo de Pydantic (de hecho, en el fondo, realmente *es un modelo de Pydantic*).

Hay algunas diferencias:

        deletion from, or modification of the contents of Covered
        Software; or

    (b) any new file in Source Code Form that contains any Covered
        Software.

1.11. "Patent Claims" of a Contributor
    means any patent claim(s), including without limitation, method,
    process, and apparatus claims, in any patent Licensable by such

				return
			}
		}
	}
	o = bts
	return
}

// Msgsize returns an upper bound estimate of the number of bytes occupied by the serialized message
func (z BatchJobSizeFilter) Msgsize() (s int) {
	s = 1 + 11 + msgp.Int64Size + 11 + msgp.Int64Size
	return
}

// DecodeMsg implements msgp.Decodable
func (z *BatchJobSnowball) DecodeMsg(dc *msgp.Reader) (err error) {
	var field []byte
	_ = field
	var zb0001 uint32