// Consult your driver documentation for a list of driver data types. Length specifiers
// are not included.
// Common type names include "VARCHAR", "TEXT", "NVARCHAR", "DECIMAL", "BOOL",
// "INT", and "BIGINT".
func (ct ColumnType) DatabaseTypeName() string {
	if ct.DataTypeValue.Valid {
		return ct.DataTypeValue.String
	}
	return ct.SQLColumnType.DatabaseTypeName()
}

* `bytes`:
    * O `bytes` padrão do Python.
    * Em requisições e respostas será representado como uma `str`.
    * O esquema gerado vai especificar que é uma `str` com o "formato" `binary`.
* `Decimal`:
    * O `Decimal` padrão do Python.
    * Em requisições e respostas será representado como um `float`.

        * 在响应中 `set` 将被转换为 `list` 。
        * 产生的模式将指定那些 `set` 的值是唯一的 (使用 JSON 模式的 `uniqueItems`)。
* `bytes`:
    * 标准的 Python `bytes`。
    * 在请求和响应中被当作 `str` 处理。
    * 生成的模式将指定这个 `str` 是 `binary` "格式"。
* `Decimal`:
    * 标准的 Python `Decimal`。
    * 在请求和响应中被当做 `float` 一样处理。
* 您可以在这里检查所有有效的pydantic数据类型: <a href="https://docs.pydantic.dev/latest/concepts/types/" class="external-link" target="_blank">Pydantic data types</a>.

## 例子

    int decimal = 0;
    int max = Integer.MAX_VALUE / 10; // for int overflow detection
    for (int i = start; i < end; i++) {
      if (decimal > max) {
        return -1;
      }
      decimal *= 10;
      int digit = Character.digit(string.charAt(i), 10);
      if (digit < 0) {
        return -1;
      }
      decimal += digit;
    }
    return decimal;
  }

		}
		expectedSql := []string{
			`ALTER TABLE "migrate_decimal_columns" ALTER COLUMN "recid1" decimal(8) NOT NULL`,
			`ALTER TABLE "migrate_decimal_columns" ALTER COLUMN "recid2" decimal(9,1) NOT NULL`,
			`ALTER TABLE "migrate_decimal_columns" ALTER COLUMN "recid3" decimal(9,2) NOT NULL`,
		}
		decimalColumnsTest[MigrateDecimalColumn, MigrateDecimalColumn2](t, expectedSql)

            """
        ),
    ] = _Unset,
    decimal_places: Annotated[
        Union[int, None],
        Doc(
            """
            Maximum number of decimal places allowed for numbers.
            """
        ),
    ] = _Unset,
    examples: Annotated[
        Optional[list[Any]],
        Doc(
            """
            Example values for this field.

    int decimal = 0;
    int max = Integer.MAX_VALUE / 10; // for int overflow detection
    for (int i = start; i < end; i++) {
      if (decimal > max) {
        return -1;
      }
      decimal *= 10;
      int digit = Character.digit(string.charAt(i), 10);
      if (digit < 0) {
        return -1;
      }
      decimal += digit;
    }
    return decimal;
  }

// CastFunc represents CAST sql function
type CastFunc struct {
	Expr     *Expression `parser:" \"CAST\" \"(\" @@ "`
	CastType string      `parser:" \"AS\" @(\"BOOL\" | \"INT\" | \"INTEGER\" | \"STRING\" | \"FLOAT\" | \"DECIMAL\" | \"NUMERIC\" | \"TIMESTAMP\") \")\" "`
}

// SubstringFunc represents SUBSTRING sql function
type SubstringFunc struct {
	Expr *PrimaryTerm `parser:" \"SUBSTRING\" \"(\" @@ "`

 *
 * This matches IPv6 addresses as a hex string containing at least one colon, and possibly
 * including dots after the first colon. It matches IPv4 addresses as strings containing only
 * decimal digits and dots. This pattern matches strings like "a:.23" and "54" that are neither IP
 * addresses nor hostnames; they will be verified as IP addresses (which is a more strict
 * verification).
 */

@NullUnmarked
public class HashStringBenchmark {
  static class MaxCodePoint {
    final int value;

    /**
     * Convert the input string to a code point. Accepts regular decimal numerals, hex strings, and
     * some symbolic names meaningful to humans.
     */
    private static int decode(String userFriendly) {
      try {
        return Integer.decode(userFriendly);