from datetime import datetime
from typing import List, Union

from pydantic import BaseModel


class User(BaseModel):
    id: int
    name: str = "John Doe"
    signup_ts: Union[datetime, None] = None
    friends: List[int] = []


external_data = {
    "id": "123",
    "signup_ts": "2017-06-01 12:22",
    "friends": [1, "2", b"3"],
}
user = User(**external_data)
print(user)

from pydantic import BaseModel, Field
from typing_extensions import Literal

app = FastAPI()


class FilterParams(BaseModel):
    class Config:
        extra = "forbid"

    limit: int = Field(100, gt=0, le=100)
    offset: int = Field(0, ge=0)
    order_by: Literal["created_at", "updated_at"] = "created_at"
    tags: List[str] = []


@app.get("/items/")
async def read_items(filter_query: FilterParams = Query()):

from fastapi import FastAPI, Query
from pydantic import BaseModel, Field

app = FastAPI()


class FilterParams(BaseModel):
    model_config = {"extra": "forbid"}

    limit: int = Field(100, gt=0, le=100)
    offset: int = Field(0, ge=0)
    order_by: Literal["created_at", "updated_at"] = "created_at"
    tags: list[str] = []


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

from typing import Union

from fastapi import Depends, FastAPI

app = FastAPI()


async def common_parameters(
    q: Union[str, None] = None, skip: int = 0, limit: int = 100
):
    return {"q": q, "skip": skip, "limit": limit}


@app.get("/items/")
async def read_items(commons: dict = Depends(common_parameters)):
    return commons


@app.get("/users/")
async def read_users(commons: dict = Depends(common_parameters)):

from typing import Annotated, Union

from fastapi import Depends, FastAPI

app = FastAPI()


async def common_parameters(
    q: Union[str, None] = None, skip: int = 0, limit: int = 100
):
    return {"q": q, "skip": skip, "limit": limit}


@app.get("/items/")
async def read_items(commons: Annotated[dict, Depends(common_parameters)]):
    return commons


@app.get("/users/")

- OkHttp targets the intersection of RFC correct *and* widely implemented.  Incorrect implementations that are very widely implemented e.g. a bug in Apache, Nginx, Google, Firefox should also be handled.

Before your code can be accepted into the project you must also sign the
[Individual Contributor License Agreement (CLA)][1].

    throwIf(OPEN_THROWS);
  }

  public boolean closed() {
    return closed;
  }

  @Override
  public void write(byte[] b, int off, int len) throws IOException {
    throwIf(closed);
    throwIf(WRITE_THROWS);
    super.write(b, off, len);
  }

  @Override
  public void write(int b) throws IOException {
    throwIf(closed);
    throwIf(WRITE_THROWS);
    super.write(b);
  }

  @Override

---

Другой полезный случай - когда вы хотите чтобы ключи были другого типа данных, например, `int`.

Именно это мы сейчас и увидим здесь.

В этом случае вы принимаете `dict`, пока у него есть ключи типа `int` со значениями типа `float`:

//// tab | Python 3.9+

```Python hl_lines="7"
{!> ../../docs_src/body_nested_models/tutorial009_py39.py!}
```

일부 타입의 키와 다른 타입의 값을 사용하여 `dict`로 본문을 선언할 수 있습니다.

(Pydantic을 사용한 경우처럼) 유효한 필드/어트리뷰트 이름이 무엇인지 알 필요가 없습니다.

아직 모르는 키를 받으려는 경우 유용합니다.

---

다른 유용한 경우는 다른 타입의 키를 가질 때입니다. 예. `int`.

여기서 그 경우를 볼 것입니다.

이 경우, `float` 값을 가진 `int` 키가 있는 모든 `dict`를 받아들입니다:

```Python hl_lines="15"
{!../../docs_src/body_nested_models/tutorial009.py!}
```

/// tip | "팁"

JSON은 오직 `str`형 키만 지원한다는 것을 염두에 두세요.

This would be useful if you want to receive keys that you don't already know.

---

Another useful case is when you want to have keys of another type (e.g., `int`).

That's what we are going to see here.

In this case, you would accept any `dict` as long as it has `int` keys with `float` values:

//// tab | Python 3.9+

```Python hl_lines="7"
{!> ../../docs_src/body_nested_models/tutorial009_py39.py!}
```