from fastapi import FastAPI
from pydantic import BaseModel

app = FastAPI()


class RecursiveItem(BaseModel):
    sub_items: list["RecursiveItem"] = []
    name: str


class RecursiveSubitemInSubmodel(BaseModel):
    sub_items2: list["RecursiveItemViaSubmodel"] = []
    name: str


class RecursiveItemViaSubmodel(BaseModel):
    sub_items1: list[RecursiveSubitemInSubmodel] = []
    name: str

from typing import Union

from fastapi import FastAPI, Path
from pydantic import BaseModel

app = FastAPI()


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


@app.put("/items/{item_id}")
async def update_item(
    *,
    item_id: int = Path(title="The ID of the item to get", ge=0, le=1000),
    q: Union[str, None] = None,

import yaml
from fastapi import FastAPI, HTTPException, Request
from pydantic.v1 import BaseModel, ValidationError

app = FastAPI()


class Item(BaseModel):
    name: str
    tags: list[str]


@app.post(
    "/items/",
    openapi_extra={
        "requestBody": {
            "content": {"application/x-yaml": {"schema": Item.schema()}},
            "required": True,
        },
    },
)

import yaml
from fastapi import FastAPI, HTTPException, Request
from pydantic import BaseModel, ValidationError

app = FastAPI()


class Item(BaseModel):
    name: str
    tags: list[str]


@app.post(
    "/items/",
    openapi_extra={
        "requestBody": {
            "content": {"application/x-yaml": {"schema": Item.model_json_schema()}},
            "required": True,
        },
    },
)

The `Hero` class is very similar to a Pydantic model (in fact, underneath, it actually *is a Pydantic model*).

There are a few differences:

* `table=True` tells SQLModel that this is a *table model*, it should represent a **table** in the SQL database, it's not just a *data model* (as would be any other regular Pydantic class).

Die `Hero`-Klasse ist einem Pydantic-Modell sehr ähnlich (faktisch ist sie darunter tatsächlich *ein Pydantic-Modell*).

Es gibt ein paar Unterschiede:

* `table=True` sagt SQLModel, dass dies ein *Tabellenmodell* ist, es soll eine **Tabelle** in der SQL-Datenbank darstellen, es ist nicht nur ein *Datenmodell* (wie es jede andere reguläre Pydantic-Klasse wäre).

from typing import Annotated, Union

from fastapi import Body, FastAPI
from pydantic import BaseModel

app = FastAPI()


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


class User(BaseModel):
    username: str
    full_name: Union[str, None] = None


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

from fastapi import FastAPI
from pydantic import BaseModel

app = FastAPI()


class Item(BaseModel):
    name: str
    description: str | None = None
    price: float
    tax: float = 10.5


items = {
    "foo": {"name": "Foo", "price": 50.2},
    "bar": {"name": "Bar", "description": "The Bar fighters", "price": 62, "tax": 20.2},
    "baz": {
        "name": "Baz",
        "description": "There goes my baz",

///

## Used by **FastAPI** { #used-by-fastapi }

### <a href="https://docs.pydantic.dev/" class="external-link" target="_blank">Pydantic</a> { #pydantic }

Pydantic is a library to define data validation, serialization and documentation (using JSON Schema) based on Python type hints.

That makes it extremely intuitive.

## Import `Field` { #import-field }

First, you have to import it:

{* ../../docs_src/body_fields/tutorial001_an_py310.py hl[4] *}


/// warning

Notice that `Field` is imported directly from `pydantic`, not from `fastapi` as are all the rest (`Query`, `Path`, `Body`, etc).

///