import org.codelibs.fess.app.web.CrudMode;
import org.codelibs.fess.app.web.admin.dict.kuromoji.UploadForm;
import org.codelibs.fess.app.web.api.ApiResult;
import org.codelibs.fess.app.web.api.admin.FessApiAdminAction;
import org.codelibs.fess.dict.kuromoji.KuromojiFile;
import org.codelibs.fess.dict.kuromoji.KuromojiItem;
import org.lastaflute.web.Execute;
import org.lastaflute.web.response.JsonResponse;

🖼 🔛 👥 🤚 `user_dict` ⚪️➡️ `user_in.dict()`, 👉 📟:

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

🔜 🌓:

```Python
UserInDB(**user_in.dict())
```

...↩️ `user_in.dict()` `dict`, & ⤴️ 👥 ⚒ 🐍 "🎁" ⚫️ 🚶‍♀️ ⚫️ `UserInDB` 🔠 ⏮️ `**`.

, 👥 🤚 Pydantic 🏷 ⚪️➡️ 💽 ➕1️⃣ Pydantic 🏷.

#### 🎁 `dict` & ➕ 🇨🇻

    pass


class OtherDependencyError(Exception):
    pass


async def asyncgen_state(state: Dict[str, str] = Depends(get_state)):
    state["/async"] = "asyncgen started"
    yield state["/async"]
    state["/async"] = "asyncgen completed"


def generator_state(state: Dict[str, str] = Depends(get_state)):
    state["/sync"] = "generator started"
    yield state["/sync"]

So, if we create a Pydantic object `user_in` like:

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

and then we call:

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

we now have a `dict` with the data in the variable `user_dict` (it's a `dict` instead of a Pydantic model object).

And if we call:

```Python

    @asynccontextmanager
    async def lifespan(app: FastAPI) -> AsyncGenerator[Dict[str, bool], None]:
        state.app_startup = True
        yield {"app": True}
        state.app_shutdown = True

    @asynccontextmanager
    async def router_lifespan(app: FastAPI) -> AsyncGenerator[Dict[str, bool], None]:
        state.router_startup = True
        yield {"router": True}

 */
package org.codelibs.fess.app.web.api.admin.dict;

import java.util.stream.Collectors;
import java.util.stream.Stream;

import org.codelibs.fess.app.web.api.ApiResult;
import org.codelibs.fess.app.web.api.admin.FessApiAdminAction;
import org.codelibs.fess.dict.DictionaryFile;
import org.codelibs.fess.dict.DictionaryItem;
import org.codelibs.fess.dict.DictionaryManager;
import org.lastaflute.web.Execute;

    schemas: Optional[Dict[str, Union[Schema, Reference]]] = None
    responses: Optional[Dict[str, Union[Response, Reference]]] = None
    parameters: Optional[Dict[str, Union[Parameter, Reference]]] = None
    examples: Optional[Dict[str, Union[Example, Reference]]] = None
    requestBodies: Optional[Dict[str, Union[RequestBody, Reference]]] = None
    headers: Optional[Dict[str, Union[Header, Reference]]] = None

import org.codelibs.fess.app.web.CrudMode;
import org.codelibs.fess.app.web.admin.dict.stopwords.UploadForm;
import org.codelibs.fess.app.web.api.ApiResult;
import org.codelibs.fess.app.web.api.admin.FessApiAdminAction;
import org.codelibs.fess.dict.stopwords.StopwordsFile;
import org.codelibs.fess.dict.stopwords.StopwordsItem;
import org.lastaflute.web.Execute;
import org.lastaflute.web.response.JsonResponse;

                "although still supported. Use examples instead."
            ),
        ] = _Unset,
        openapi_examples: Optional[Dict[str, Example]] = None,
        deprecated: Union[deprecated, str, bool, None] = None,
        include_in_schema: bool = True,
        json_schema_extra: Union[Dict[str, Any], None] = None,
        **extra: Any,
    ):
        if example is not _Unset:
            warnings.warn(

Pydantic-Modelle haben eine `.dict()`-Methode, die ein `dict` mit den Daten des Modells zurückgibt.

Wenn wir also ein Pydantic-Objekt `user_in` erstellen, etwa so:

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

und wir rufen seine `.dict()`-Methode auf:

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