from re import Pattern
from types import GeneratorType
from typing import Any, Callable, Dict, List, Optional, Tuple, Type, Union
from uuid import UUID

from fastapi.types import IncEx
from pydantic import BaseModel
from pydantic.color import Color
from pydantic.networks import AnyUrl, NameEmail
from pydantic.types import SecretBytes, SecretStr
from typing_extensions import Annotated, Doc

```Python hl_lines="1  7-12  19-20"
{!../../docs_src/dataclasses/tutorial001.py!}
```

👉 🐕‍🦺 👏 **Pydantic**, ⚫️ ✔️ <a href="https://docs.pydantic.dev/latest/concepts/dataclasses/#use-of-stdlib-dataclasses-with-basemodel" class="external-link" target="_blank">🔗 🐕‍🦺 `dataclasses`</a>.

, ⏮️ 📟 🔛 👈 🚫 ⚙️ Pydantic 🎯, FastAPI ⚙️ Pydantic 🗜 📚 🐩 🎻 Pydantic 👍 🍛 🎻.

&amp; ↗️, ⚫️ 🐕‍🦺 🎏:

* 💽 🔬
* 💽 🛠️
* 💽 🧾, ♒️.

```Python
from typing import List, Dict
from datetime import date

from pydantic import BaseModel

# Deklarieren Sie eine Variable als ein `str`
# und bekommen Sie Editor-Unterstütung innerhalb der Funktion
def main(user_id: str):
    return user_id


# Ein Pydantic-Modell
class User(BaseModel):
    id: int
    name: str
    joined: date
```

Das kann nun wie folgt verwendet werden:

You write standard Python with types:

```Python
from datetime import date

from pydantic import BaseModel

# Declare a variable as a str
# and get editor support inside the function
def main(user_id: str):
    return user_id


# A Pydantic model
class User(BaseModel):
    id: int
    name: str
    joined: date
```

That can then be used like:

```Python

Wystarczy, że napiszesz standardowe deklaracje typów Pythona:

```Python
from datetime import date

from pydantic import BaseModel

# Zadeklaruj parametr jako str
# i uzyskaj wsparcie edytora wewnątrz funkcji
def main(user_id: str):
    return user_id


# Model Pydantic
class User(BaseModel):
    id: int
    name: str
    joined: date
```

A one będą mogły zostać później użyte w następujący sposób:

```Python
from typing import List, Dict
from datetime import date

from pydantic import BaseModel

# Değişkeni str olarak belirt
# ve o fonksiyon için harika bir editör desteği al
def main(user_id: str):
    return user_id


# Pydantic modeli
class User(BaseModel):
    id: int
    name: str
    joined: date
```

Sonrasında bu şekilde kullanabilirsin

```Python

        Add a *path operation* using an HTTP PUT operation.

        ## Example

        ```python
        from fastapi import APIRouter, FastAPI
        from pydantic import BaseModel

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

        app = FastAPI()
        router = APIRouter()

        @router.put("/items/{item_id}")

👆 ✍ 🐩 🐍 ⏮️ 🆎:

```Python
from datetime import date

from pydantic import BaseModel

# Declare a variable as a str
# and get editor support inside the function
def main(user_id: str):
    return user_id


# A Pydantic model
class User(BaseModel):
    id: int
    name: str
    joined: date
```

👈 💪 ⤴️ ⚙️ 💖:

```Python

```Python hl_lines="1  7-12  19-20"
{!../../docs_src/dataclasses/tutorial001.py!}
```

Das ist dank **Pydantic** ebenfalls möglich, da es <a href="https://pydantic-docs.helpmanual.io/usage/dataclasses/#use-of-stdlib-dataclasses-with-basemodel" class="external-link" target="_blank">`dataclasses` intern unterstützt</a>.

{* ../../docs_src/dataclasses/tutorial001.py hl[1,7:12,19:20] *}

This is still supported thanks to **Pydantic**, as it has <a href="https://docs.pydantic.dev/latest/concepts/dataclasses/#use-of-stdlib-dataclasses-with-basemodel" class="external-link" target="_blank">internal support for `dataclasses`</a>.