Isso nos ajudará dentro da função com...

    public void filtered(FilteredCall<UserCQ, UserCQ> filteredLambda) {
        filtered(filteredLambda, null);
    }

    public void filtered(FilteredCall<UserCQ, UserCQ> filteredLambda, ConditionOptionCall<BoolQueryBuilder> opLambda) {
        bool((must, should, mustNot, filter) -> {
            filteredLambda.callback(must, filter);
        }, opLambda);
    }

    public void not(OperatorCall<UserCQ> notLambda) {

### `**user_in.dict()`について

#### Pydanticの`.dict()`

`user_in`は`UserIn`クラスのPydanticモデルです。

Pydanticモデルには、モデルのデータを含む`dict`を返す`.dict()`メソッドがあります。

そこで、以下のようなPydanticオブジェクト`user_in`を作成すると:

```Python
user_in = UserIn(username="john", password="secret", email="******@****.***")
```

そして呼び出すと:

```Python
user_dict = user_in.dict()
```

# Declare uma variável como str
# e obtenha suporte do editor dentro da função
def main(user_id: str):
    return user_id


# Um modelo do Pydantic
class User(BaseModel):
    id: int
    name: str
    joined: date
```

Que então pode ser usado como:

```Python
my_user: User = User(id=3, name="John Doe", joined="2018-07-19")

second_user_data = {
    "id": 4,
    "name": "Mary",

* `/items/public/`
* `/items/private/`
* `/users/{user_id}/activate`
* `/items/pro/`

そして、依存関係とサブ依存関係だけで、それぞれに異なるパーミッション要件を追加することができます:

```mermaid
graph TB

current_user(["current_user"])
active_user(["active_user"])
admin_user(["admin_user"])
paying_user(["paying_user"])

public["/items/public/"]
private["/items/private/"]
activate_user["/users/{user_id}/activate"]
pro_items["/items/pro/"]

# Declara una variable como un str
# y obtiene soporte del editor dentro de la función
def main(user_id: str):
    return user_id


# Un modelo de Pydantic
class User(BaseModel):
    id: int
    name: str
    joined: date
```

Que luego puede ser usado como:

```Python
my_user: User = User(id=3, name="John Doe", joined="2018-07-19")

second_user_data = {
    "id": 4,
    "name": "Mary",

* `/items/private/`
* `/users/{user_id}/activate`
* `/items/pro/`

그 다음 각각에 대해 그저 의존성과 하위 의존성을 사용하여 다른 권한 요구 사항을 추가할 수 있을 겁니다:

```mermaid
graph TB

current_user(["current_user"])
active_user(["active_user"])
admin_user(["admin_user"])
paying_user(["paying_user"])

public["/items/public/"]
private["/items/private/"]
activate_user["/users/{user_id}/activate"]
pro_items["/items/pro/"]

from datetime import date

from pydantic import BaseModel

# 宣告一個變數為 string
# 並在函式中獲得 editor support
def main(user_id: str):
    return user_id


# 宣告一個 Pydantic model
class User(BaseModel):
    id: int
    name: str
    joined: date
```


可以像這樣來使用：

```python
my_user: User = User(id=3, name="John Doe", joined="2018-07-19")

second_user_data = {
    "id": 4,
    "name": "Mary",

RUN wget https://github.com/bazelbuild/buildtools/releases/download/v7.3.1/buildozer-linux-arm64 -O /usr/local/bin/buildozer && chmod +x /usr/local/bin/buildozer

RUN groupadd -g 1001 buildslave && useradd -m -u 1001 -g buildslave buildslave
RUN mkdir -p /tf/venv
RUN chown -R buildslave:buildslave /tf

# All lines past this point are reset when $CACHEBUSTER is set. We need this

    }

    protected void registerModifiedProperty(String propertyName) {
        __modifiedProperties.addPropertyName(propertyName);
        registerSpecifiedProperty(propertyName); // synchronize if exists, basically for user's manual call
    }

    public void modifiedToSpecified() {
        if (__modifiedProperties.isEmpty()) {
            return; // basically no way when called in Framework (because called when SpecifyColumn exists)