その動作と、必要に応じての変更方法を見ていきます。

## 入出力のPydanticモデル { #pydantic-models-for-input-and-output }

次のようにデフォルト値を持つ Pydantic モデルがあるとします。

{* ../../docs_src/separate_openapi_schemas/tutorial001_py310.py ln[1:7] hl[7] *}

### 入力用モデル { #model-for-input }

このモデルを次のように入力として使うと:

{* ../../docs_src/separate_openapi_schemas/tutorial001_py310.py ln[1:15] hl[14] *}

    disabled = user_dict["disabled"],
    hashed_password = user_dict["hashed_password"],
)
```

/// info | Bilgi

`**user_dict` için daha kapsamlı bir açıklama için [**Extra Models** dokümantasyonundaki ilgili bölüme](../extra-models.md#about-user-in-dict) geri dönüp bakın.

///

## Token’ı Döndürme { #return-the-token }

`token` endpoint’inin response’u bir JSON object olmalıdır.

# Build state model

The Gradle daemon tracks state for various elements. These are arranged in a hierarchy:

```mermaid
  graph TD

  process["build process"]
  
  session["build session"]
  process --> session
  
  build_tree["build tree"]
  session --> build_tree
  
  build1["root build"]
  build_tree --> build1
  
  project1["root project"]
  build1 --> project1
  
  project2["project"]
  build1 --> project2

     */
    @Nonnull
    List<Profile> getActivePomProfiles();

    /**
     * Gets the profiles that were active during model building for a specific model in the hierarchy.
     * This allows tracking which profiles came from which model (parent vs child).
     *
     * @param modelId The identifier of the model (groupId:artifactId:version) or empty string for the super POM.

Regression test: Ensure app-level responses with Union models and content/examples
don't accumulate duplicate $ref entries in anyOf arrays.
See https://github.com/fastapi/fastapi/pull/14463
"""

from fastapi import FastAPI
from fastapi.testclient import TestClient
from inline_snapshot import snapshot
from pydantic import BaseModel


class ModelA(BaseModel):
    a: str


class ModelB(BaseModel):
    b: str


app = FastAPI(

 * specific language governing permissions and limitations
 * under the License.
 */
package org.apache.maven.model.building;

/**
 * Caches auxiliary data used during model building like already processed raw/effective models. The data in the cache
 * is meant for exclusive consumption by the model builder and is opaque to the cache implementation. The cache key is

---> 100%
```

</div>

## Створіть застосунок з однією моделлю { #create-the-app-with-a-single-model }

Спершу створимо найпростішу версію застосунку з однією моделлю **SQLModel**.

Потім нижче покращимо безпеку і гнучкість за допомогою кількох моделей. 🤓

### Створіть моделі { #create-models }

Імпортуйте `SQLModel` і створіть модель бази даних:

```

**Important**: Return types or response models are what filter data ensuring no sensitive information is exposed. And they are used to serialize data with Pydantic (in Rust), this is the main idea that can increase response performance.

The return type doesn't have to be a Pydantic model, it could be a different type, like a list of integers, or a dict, etc.

@app.get("/items/")
async def read_items(filter_query: Annotated[FilterParams, Query()]):
    return filter_query
```

Read the new docs: [Query Parameter Models](https://fastapi.tiangolo.com/tutorial/query-param-models/).

#### `Header` Parameter Models

Use Pydantic models for `Header` parameters:

```python
from typing import Annotated

from fastapi import FastAPI, Header
from pydantic import BaseModel

import binascii
from base64 import b64decode
from typing import Annotated

from annotated_doc import Doc
from fastapi.exceptions import HTTPException
from fastapi.openapi.models import HTTPBase as HTTPBaseModel
from fastapi.openapi.models import HTTPBearer as HTTPBearerModel
from fastapi.security.base import SecurityBase
from fastapi.security.utils import get_authorization_scheme_param
from pydantic import BaseModel
from starlette.requests import Request