### Создание нескольких моделей { #create-multiple-models }

В **SQLModel** любая модель с `table=True` — это **модель-таблица**.

Любая модель без `table=True` — это **модель данных**, по сути обычная модель Pydantic (с парой небольших дополнений). 🤓

С SQLModel мы можем использовать **наследование**, чтобы **избежать дублирования** полей.

匯入 `SQLModel` 並建立一個資料庫模型：

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

`Hero` 類別與 Pydantic 模型非常相似（事實上，在底層它就是一個 Pydantic 模型）。

有幾點差異：

* `table=True` 告訴 SQLModel 這是一個「資料表模型」（table model），它應該代表 SQL 資料庫中的一個資料表，而不僅僅是「資料模型」（就像一般的 Pydantic 類別）。

* `Field(primary_key=True)` 告訴 SQLModel，`id` 是 SQL 資料庫中的「主鍵」。 （你可以在 SQLModel 文件中進一步了解 SQL 主鍵）

  }

  /**
   * Sets the minimum total size for the internal hash tables. For example, if the initial capacity
   * is {@code 60}, and the concurrency level is {@code 8}, then eight segments are created, each
   * having a hash table of size eight. Providing a large enough estimate at construction time

	DB.First(&result2, "code = ?", "save")
	AssertEqual(t, result2, lang)

	DB.Table("langs").Migrator().DropTable(&Language{})
	DB.Table("langs").AutoMigrate(&Language{})

	if err := DB.Table("langs").Save(&lang).Error; err != nil {
		t.Errorf("no error should happen when creating data, but got %v", err)
	}

	var result3 Language

    # o isSuppressSchemaHtmlOutsideSql: (NotRequired - Default false)
    #  Does it remove outsideSql information from SchemaHtml?
    #  Basically you don't need this.
    #  OutsideSql information (related to tables) is very useful.
    #
    #; isSuppressSchemaHtmlOutsideSql = false
    # - - - - - - - - - -/

    # /- - - - - - - - - - - - - - - - - - - - - - - - - - - - - -

### Crear Múltiples Modelos { #create-multiple-models }

En **SQLModel**, cualquier clase de modelo que tenga `table=True` es un **modelo de tabla**.

Y cualquier clase de modelo que no tenga `table=True` es un **modelo de datos**, estos son en realidad solo modelos de Pydantic (con un par de características extra pequeñas). 🤓

          }
        }
      }
      table = newTable;
      this.count = newCount;
    }

    boolean replace(K key, int hash, V oldValue, V newValue) {
      lock();
      try {
        preWriteCleanup();

        AtomicReferenceArray<E> table = this.table;
        int index = hash & (table.length() - 1);
        E first = table.get(index);

import com.google.common.collect.SortedMapDifference;
import com.google.common.collect.SortedMultiset;
import com.google.common.collect.SortedSetMultimap;
import com.google.common.collect.Table;
import com.google.common.collect.Tables;
import com.google.common.collect.TreeBasedTable;
import com.google.common.collect.TreeMultimap;
import com.google.common.io.ByteSink;
import com.google.common.io.ByteSource;

        long now = map.ticker.read();
        preWriteCleanup(now);

        int newCount = this.count - 1;
        AtomicReferenceArray<ReferenceEntry<K, V>> table = this.table;
        int index = hash & (table.length() - 1);
        ReferenceEntry<K, V> first = table.get(index);

        for (e = first; e != null; e = e.getNext()) {
          K entryKey = e.getKey();
          if (e.getHash() == hash

  }

  // We use power-of-2 tables, and this is the highest int that's a power of 2
  static final int MAX_TABLE_SIZE = Ints.MAX_POWER_OF_TWO;

  // Represents how tightly we can pack things, as a maximum.
  private static final double DESIRED_LOAD_FACTOR = 0.7;

  // If the set has this many elements, it will "max out" the table size