from typing import Union

from fastapi import FastAPI
from pydantic.v1 import BaseModel


class Item(BaseModel):
    name: str
    description: Union[str, None] = None
    size: float


app = FastAPI()


@app.post("/items/")
async def create_item(item: Item) -> Item:

from fastapi import FastAPI
from fastapi.temp_pydantic_v1_params import Body
from pydantic.v1 import BaseModel


class Item(BaseModel):
    name: str
    description: Union[str, None] = None
    size: float


app = FastAPI()


@app.post("/items/")
async def create_item(item: Annotated[Item, Body(embed=True)]) -> Item:

	case simdjson.TypeFloat:
		v, err := iter.Float()
		if err != nil {
			return nil, err
		}
		return sql.FromFloat(v), nil
	case simdjson.TypeInt:
		v, err := iter.Int()
		if err != nil {
			return nil, err
		}
		return sql.FromInt(v), nil
	case simdjson.TypeUint:
		v, err := iter.Int()
		if err != nil {
			// Can't fit into int, convert to float.
			v, err := iter.Float()
			return sql.FromFloat(v), err
		}

from fastapi import FastAPI
from pydantic import BaseModel

app = FastAPI()


class Item(BaseModel):
    name: str
    price: float


class ResponseMessage(BaseModel):
    message: str


@app.post("/items/", response_model=ResponseMessage)
async def create_item(item: Item):
    return {"message": "item received"}


@app.get("/items/", response_model=list[Item])
async def get_items():
    return [

def custom_generate_unique_id(route: APIRoute):
    return f"{route.tags[0]}-{route.name}"


app = FastAPI(generate_unique_id_function=custom_generate_unique_id)


class Item(BaseModel):
    name: str
    price: float


class ResponseMessage(BaseModel):
    message: str


class User(BaseModel):
    username: str
    email: str


@app.post("/items/", response_model=ResponseMessage, tags=["items"])

from fastapi import FastAPI, Path, Query

app = FastAPI()


@app.get("/items/{item_id}")
async def read_items(
    *,
    item_id: int = Path(title="The ID of the item to get", ge=0, le=1000),
    q: str,
    size: float = Query(gt=0, lt=10.5),
):
    results = {"item_id": item_id}
    if q:
        results.update({"q": q})
    if size:
        results.update({"size": size})

from datetime import datetime

from fastapi import FastAPI
from pydantic import BaseModel

app = FastAPI()


class Subscription(BaseModel):
    username: str
    monthly_fee: float
    start_date: datetime


@app.webhooks.post("new-subscription")
def new_subscription(body: Subscription):
    """
    When a new user subscribes to your service we'll send you a POST request with this

其他有用的场景是当你想要接收其他类型的键时，例如 `int`。

这也是我们在接下来将看到的。

在下面的例子中，你将接受任意键为 `int` 类型并且值为 `float` 类型的 `dict`：

{* ../../docs_src/body_nested_models/tutorial009_py39.py hl[7] *}

/// tip

请记住 JSON 仅支持将 `str` 作为键。

但是 Pydantic 具有自动转换数据的功能。

这意味着，即使你的 API 客户端只能将字符串作为键发送，只要这些字符串内容仅包含整数，Pydantic 就会对其进行转换并校验。

然后你接收的名为 `weights` 的 `dict` 实际上将具有 `int` 类型的键和 `float` 类型的值。

///

## 总结

from fastapi import FastAPI
from pydantic import BaseModel

app = FastAPI()


class Item(BaseModel):
    name: str
    price: float


class ResponseMessage(BaseModel):
    message: str


class User(BaseModel):
    username: str
    email: str


@app.post("/items/", response_model=ResponseMessage, tags=["items"])
async def create_item(item: Item):
    return {"message": "Item received"}

                "input": "True",
            }
        ]
    }


def test_path_float_42():
    response = client.get("/path/float/42")
    assert response.status_code == 200
    assert response.json() == 42


def test_path_float_42_5():
    response = client.get("/path/float/42.5")
    assert response.status_code == 200
    assert response.json() == 42.5


def test_path_bool_foobar():