## Recap

You can use Pydantic's `Field` to declare extra validations and metadata for model attributes.

    //                                                                         ===========
    protected final ColumnInfo _columnName = cci("name", "name", null, null, String.class, "name", null, false, false, false, "keyword", 0,
            0, null, null, false, null, null, null, null, null, false);

    public ColumnInfo columnName() {
        return _columnName;
    }

    protected List<ColumnInfo> ccil() {

		statusCode: 400,
		cause:      err,
	}
}

func errParseExpectedKeyword(err error) *s3Error {
	return &s3Error{
		code:       "ParseExpectedKeyword",
		message:    "Did not find the expected keyword in the SQL expression.",
		statusCode: 400,
		cause:      err,
	}
}

func errParseExpectedTokenType(err error) *s3Error {
	return &s3Error{
		code:       "ParseExpectedTokenType",

Übergeben Sie der Funktion `*` als ersten Parameter.

```

`.add_task()` receives as arguments:

* A task function to be run in the background (`write_notification`).
* Any sequence of arguments that should be passed to the task function in order (`email`).
* Any keyword arguments that should be passed to the task function (`message="some notification"`).

## Dependency Injection

	Quoted   *QuotedIdentifier `parser:"| @QuotIdent"`
}

var (
	sqlLexer = lexer.Must(lexer.Regexp(`(\s+)` +
		`|(?P<Timeword>(?i)\b(?:YEAR|MONTH|DAY|HOUR|MINUTE|SECOND|TIMEZONE_HOUR|TIMEZONE_MINUTE)\b)` +

关键因素是依赖项应该是 "可调用对象"。

Python 中的 "**可调用对象**" 是指任何 Python 可以像函数一样 "调用" 的对象。

所以，如果你有一个对象 `something` (可能*不是*一个函数)，你可以 "调用" 它(执行它)，就像：

```Python
something()
```

或者

```Python
something(some_argument, some_keyword_argument="foo")
```

这就是 "可调用对象"。

## 类作为依赖项

您可能会注意到，要创建一个 Python 类的实例，您可以使用相同的语法。

举个例子:

```Python
class Cat:
    def __init__(self, name: str):
        self.name = name

        val ctMethod = method.newMethod.get()
        ktFile.kotlinDeclarationSatisfies(ctMethod.declaringClass, ctMethod) { ktMember ->
            ktMember.hasModifier(KtTokens.OVERRIDE_KEYWORD)
        }
    }

    fun isSince(version: String, member: JApiCompatibility): (KtFile) -> Boolean = { ktFile ->
        val ctMember = member.newCtMember
        val ctDeclaringClass = ctMember.declaringClass

So, we get a Pydantic model from the data in another Pydantic model.

#### Unwrapping a `dict` and extra keywords

And then adding the extra keyword argument `hashed_password=hashed_password`, like in:

```Python
UserInDB(**user_in.dict(), hashed_password=hashed_password)
```

...ends up being like:

```Python
UserInDB(

!!! tip
    Instead of passing each of the keyword arguments to `Item` and reading each one of them from the Pydantic *model*, we are generating a `dict` with the Pydantic *model*'s data with:

    `item.dict()`

    and then we are passing the `dict`'s key-value pairs as the keyword arguments to the SQLAlchemy `Item`, with:

    `Item(**item.dict())`