0, null, null, false, null, null, null, null, null, false);
    protected final ColumnInfo _columnSessionId = cci("sessionId", "sessionId", null, null, String.class, "sessionId", null, false, false,
            false, "keyword", 0, 0, null, null, false, null, null, null, null, null, false);

        final String key = ComponentUtil.getVirtualHostHelper().getVirtualHostKey();
        keywordList.stream().forEach(keyword -> {
            final List<Tuple3<String, QueryBuilder, ScoreFunctionBuilder<?>>> boostList = getQueryMap(key).get(toLowerCase(keyword));
            if (boostList != null) {
                boostList.forEach(pair -> list.add(new FilterFunctionBuilder(pair.getValue2(), pair.getValue3())));

        }

    override val isReified: Boolean
        get() = withValidityAssertion { psi.hasModifier(KtTokens.REIFIED_KEYWORD) }

    override val name: Name
        get() = withValidityAssertion { psi.nameAsSafeName }

    override fun createPointer(): KtSymbolPointer<KtTypeParameterSymbol> = withValidityAssertion {

            false, "Long", 0, 0, null, null, false, null, null, null, null, null, false);
    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 columnGidNumber() {
        return _columnGidNumber;
    }

    public ColumnInfo columnName() {

    //                                                                         ===========
    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() {

## Recap

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

```

`.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

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

It will take the `dict` at `result.value`, and take each of its keys and values and pass them as key-values to `UserInDB` as keyword arguments.

So, if the `dict` contains:

```Python
{
    "username": "johndoe",
    "hashed_password": "some_hash",
}
```

It will be passed to `UserInDB` as:

```Python

...Python has a little special syntax for that.

Pass `*`, as the first parameter of the function.

Python won't do anything with that `*`, but it will know that all the following parameters should be called as keyword arguments (key-value pairs), also known as <abbr title="From: K-ey W-ord Arg-uments"><code>kwargs</code></abbr>. Even if they don't have a default value.

```Python hl_lines="7"