from fastapi import FastAPI, Header
from pydantic import BaseModel

app = FastAPI()


class CommonHeaders(BaseModel):
    host: str
    save_data: bool
    if_modified_since: str | None = None
    traceparent: str | None = None
    x_tag: list[str] = []


@app.get("/items/")
async def read_items(headers: CommonHeaders = Header(convert_underscores=False)):

Hepsi, tüm geliştiriciler için en iyi geliştirme deneyimini sağlayacak şekilde.

## Gereksinimler

Çeşitli alternatifleri test ettikten sonra, avantajlarından dolayı <a href="https://docs.pydantic.dev/" class="external-link" target="_blank">**Pydantic**</a>'i kullanmaya karar verdim.

<img src="/img/tutorial/path-params/image02.png">

Und viele weitere kompatible Tools. Inklusive Codegenerierung für viele Sprachen.

## Pydantic { #pydantic }

Die ganze Datenvalidierung wird hinter den Kulissen von <a href="https://docs.pydantic.dev/" class="external-link" target="_blank">Pydantic</a> durchgeführt, Sie profitieren also von dessen Vorteilen. Und Sie wissen, dass Sie in guten Händen sind.

이 과정을 통해 코드 중복을 최소화하고, 모든 곳에서 자동 완성, 타입 검사, 에러 확인 기능이 제공되는 최적의 방식을 찾아냈습니다.

이 모든 것은 개발자들에게 최고의 개발 경험을 제공하기 위해 설계되었습니다.

---

## 필요조건

여러 대안을 테스트한 후, [Pydantic](https://docs.pydantic.dev/)을 사용하기로 결정했습니다.

이후 저는 **Pydantic**이 JSON Schema와 완벽히 호환되도록 개선하고, 다양한 제약 조건 선언을 지원하며, 여러 편집기에서의 자동 완성과 타입 검사 기능을 향상하기 위해 기여했습니다.

또한, 또 다른 주요 필요조건이었던 [Starlette](https://www.starlette.dev/)에도 기여했습니다.

---

## 개발

from typing import Annotated, Union

from fastapi import Cookie, FastAPI
from pydantic import BaseModel

app = FastAPI()


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

    session_id: str
    fatebook_tracker: Union[str, None] = None
    googall_tracker: Union[str, None] = None


@app.get("/items/")
async def read_items(cookies: Annotated[Cookies, Cookie()]):

from typing import Annotated

from fastapi import FastAPI, Header
from pydantic import BaseModel

app = FastAPI()


class CommonHeaders(BaseModel):
    host: str
    save_data: bool
    if_modified_since: str | None = None
    traceparent: str | None = None
    x_tag: list[str] = []


@app.get("/items/")
async def read_items(
    headers: Annotated[CommonHeaders, Header(convert_underscores=False)],
):

from typing import Annotated, Union

from fastapi import FastAPI, Header
from pydantic import BaseModel

app = FastAPI()


class CommonHeaders(BaseModel):
    host: str
    save_data: bool
    if_modified_since: Union[str, None] = None
    traceparent: Union[str, None] = None
    x_tag: list[str] = []


@app.get("/items/")
async def read_items(headers: Annotated[CommonHeaders, Header()]):

from typing import Union

from fastapi import FastAPI
from pydantic import BaseModel

app = FastAPI()


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


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


@app.get("/items/", tags=["items"])

            Any,
            Doc(
                """
                The type to use for the response.

                It could be any valid Pydantic *field* type. So, it doesn't have to
                be a Pydantic model, it could be other things, like a `list`, `dict`,
                etc.

                It will be used for:

from typing import Annotated, Literal

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

app = FastAPI()


class FilterParams(BaseModel):
    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()]):