import logging
from typing import Literal

from github import Github
from github.PullRequestReview import PullRequestReview
from pydantic import BaseModel, SecretStr
from pydantic_settings import BaseSettings


class LabelSettings(BaseModel):
    await_label: str | None = None
    number: int


default_config = {"approved-2": LabelSettings(await_label="awaiting-review", number=2)}


class Settings(BaseSettings):

from typing import AsyncGenerator, Dict, Union

import pytest
from fastapi import APIRouter, FastAPI, Request
from fastapi.testclient import TestClient
from pydantic import BaseModel


class State(BaseModel):
    app_startup: bool = False
    app_shutdown: bool = False
    router_startup: bool = False
    router_shutdown: bool = False
    sub_router_startup: bool = False

///

## Импортирование `BaseModel` из Pydantic

Первое, что вам необходимо сделать, это импортировать `BaseModel` из пакета `pydantic`:

```Python hl_lines="4"
{!../../docs_src/body/tutorial001.py!}
```

## Создание вашей собственной модели

После этого вы описываете вашу модель данных как класс, наследующий от `BaseModel`.

Используйте аннотации типов Python для всех атрибутов:

from fastapi.testclient import TestClient
from pydantic import BaseModel

from .utils import PYDANTIC_V2, needs_pydanticv2


class SubItem(BaseModel):
    subname: str
    sub_description: Optional[str] = None
    tags: List[str] = []
    if PYDANTIC_V2:
        model_config = {"json_schema_serialization_defaults_required": True}


class Item(BaseModel):
    name: str
    description: Optional[str] = None

from typing import List

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


class Model(BaseModel):
    name: str


app = FastAPI()


@app.get("/valid1", responses={"500": {"model": int}})
def valid1():
    pass


@app.get("/valid2", responses={"500": {"model": List[int]}})
def valid2():
    pass


@app.get("/valid3", responses={"500": {"model": Model}})

///

## Importieren Sie Pydantics `BaseModel`

Zuerst müssen Sie `BaseModel` von `pydantic` importieren:

//// tab | Python 3.10+

```Python hl_lines="2"
{!> ../../docs_src/body/tutorial001_py310.py!}
```

////

//// tab | Python 3.8+

///

## 导入 Pydantic 的 `BaseModel`

从 `pydantic` 中导入 `BaseModel`：

//// tab | Python 3.10+

```Python hl_lines="2"
{!> ../../docs_src/body/tutorial001_py310.py!}
```

////

//// tab | Python 3.8+

```Python hl_lines="4"
{!> ../../docs_src/body/tutorial001.py!}
```

////

## 创建数据模型

把数据模型声明为继承 `BaseModel` 的类。

使用 Python 标准类型声明所有属性：

///

## Importe o `BaseModel` do Pydantic

Primeiro, você precisa importar `BaseModel` do `pydantic`:

```Python hl_lines="4"
{!../../docs_src/body/tutorial001.py!}
```

## Crie seu modelo de dados

Então você declara seu modelo de dados como uma classe que herda `BaseModel`.

Utilize os tipos Python padrão para todos os atributos:

```Python hl_lines="7-11"

///

## Import Pydantic's `BaseModel`

First, you need to import `BaseModel` from `pydantic`:

{* ../../docs_src/body/tutorial001_py310.py hl[2] *}

## Create your data model

Then you declare your data model as a class that inherits from `BaseModel`.

Use standard Python types for all the attributes:

///

## Importez le `BaseModel` de Pydantic

Commencez par importer la classe `BaseModel` du module `pydantic` :

{* ../../docs_src/body/tutorial001.py hl[4] *}

## Créez votre modèle de données

Déclarez ensuite votre modèle de données en tant que classe qui hérite de `BaseModel`.

Utilisez les types Python standard pour tous les attributs :