from typing import Optional

from fastapi import FastAPI
from pydantic import BaseModel


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


app = FastAPI()


@app.post("/items/")
def create_item(item: Item):
    return item


@app.get("/items/")
def read_items() -> list[Item]:
    return [
        Item(
            name="Portal Gun",

from typing import Union

from fastapi import FastAPI
from pydantic import BaseModel


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


app = FastAPI()


@app.post("/items/")
async def create_item(item: Item):
    item_dict = item.model_dump()
    if item.tax is not None:
        price_with_tax = item.price + item.tax

from fastapi import FastAPI
from pydantic import BaseModel, HttpUrl

app = FastAPI()


class Image(BaseModel):
    url: HttpUrl
    name: str


class Item(BaseModel):
    name: str
    description: str | None = None
    price: float
    tax: float | None = None
    tags: set[str] = set()
    image: Image | None = None


@app.put("/items/{item_id}")
async def update_item(item_id: int, item: Item):

import types
from enum import Enum
from typing import Any, Callable, Optional, TypeVar, Union

from pydantic import BaseModel

DecoratedCallable = TypeVar("DecoratedCallable", bound=Callable[..., Any])
UnionType = getattr(types, "UnionType", Union)
ModelNameMap = dict[Union[type[BaseModel], type[Enum]], str]
IncEx = Union[set[int], set[str], dict[int, Any], dict[str, Any]]

{* ../../docs_src/body_multiple_params/tutorial002_py310.py hl[20] *}


In this case, **FastAPI** will notice that there is more than one body parameter in the function (there are two parameters that are Pydantic models).

So, it will then use the parameter names as keys (field names) in the body, and expect a body like:

```JSON
{
    "item": {
        "name": "Foo",
        "description": "The pretender",

{* ../../docs_src/body_multiple_params/tutorial002_py310.py hl[20] *}

In diesem Fall wird **FastAPI** bemerken, dass es mehr als einen Body-Parameter in der Funktion gibt (zwei Parameter, die Pydantic-Modelle sind).

Es wird deshalb die Parameternamen als Schlüssel (Feldnamen) im Body verwenden und erwartet einen Body wie folgt:

```JSON
{
    "item": {
        "name": "Foo",

from typing import Optional

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

app = FastAPI()


class Item(BaseModel):
    name: str
    price: Optional[float] = None
    owner_ids: Optional[list[int]] = None


@app.get("/items/valid", response_model=Item)
def get_valid():
    return {"name": "valid", "price": 1.0}


@app.get("/items/coerce", response_model=Item)

### 创建模型

导入 `SQLModel` 并创建一个数据库模型：

{* ../../docs_src/sql_databases/tutorial001_an_py310.py ln[1:11] hl[7:11] *}

`Hero` 类与 Pydantic 模型非常相似（实际上，从底层来看，它确实*就是一个 Pydantic 模型*）。

有一些区别：

* `table=True` 会告诉 SQLModel 这是一个*表模型*，它应该表示 SQL 数据库中的一个*表*，而不仅仅是一个*数据模型*（就像其他常规的 Pydantic 类一样）。

* `Field(primary_key=True)` 会告诉 SQLModel `id` 是 SQL 数据库中的**主键**（您可以在 SQLModel 文档中了解更多关于 SQL 主键的信息）。

from typing import Annotated

from fastapi import Body, FastAPI
from pydantic import BaseModel

app = FastAPI()


class Item(BaseModel):
    name: str
    description: str | None = None
    price: float
    tax: float | None = None


@app.put("/items/{item_id}")
async def update_item(
    item_id: int,
    item: Annotated[
        Item,
        Body(
            examples=[
                {

from typing import Union

from fastapi import FastAPI
from pydantic import BaseModel


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


app = FastAPI()


@app.put("/items/{item_id}")
async def update_item(item_id: int, item: Item, q: Union[str, None] = None):
    result = {"item_id": item_id, **item.model_dump()}
    if q: