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  1. docs/tr/docs/features.md

    Standart Python'u typelarını belirterek yazıyorsun:
    
    ```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
    
    
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  2. docs/en/docs/features.md

    You will get completion in code you might even consider impossible before. As for example, the `price` key inside a JSON body (that could have been nested) that comes from a request.
    
    No more typing the wrong key names, coming back and forth between docs, or scrolling up and down to find if you finally used `username` or `user_name`.
    
    ### Short { #short }
    
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  3. docs/tr/docs/python-types.md

    Bu tipleri ve dahili tpileri bildirmek için standart Python modülünü "typing" kullanabilirsiniz.
    
    Bu tür tip belirteçlerini desteklemek için özel olarak mevcuttur.
    
    #### `List`
    
    Örneğin `str` değerlerden oluşan bir `list` tanımlayalım.
    
    From `typing`, import `List` (büyük harf olan `L` ile):
    
    {* ../../docs_src/python_types/tutorial006.py hl[1] *}
    
    
    Değişkenin tipini yine iki nokta üstüste (`:`) ile belirleyin.
    
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  4. docs/ko/docs/index.md

    <div class="termy">
    
    ```console
    $ pip install "uvicorn[standard]"
    
    ---> 100%
    ```
    
    </div>
    
    ## 예제
    
    ### 만들기
    
    * `main.py` 파일을 만드십시오:
    
    ```Python
    from typing import Union
    
    from fastapi import FastAPI
    
    app = FastAPI()
    
    
    @app.get("/")
    def read_root():
        return {"Hello": "World"}
    
    
    @app.get("/items/{item_id}")
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  5. docs/tr/docs/index.md

    $ pip install "uvicorn[standard]"
    
    ---> 100%
    ```
    
    </div>
    
    ## Örnek
    
    ### Kodu Oluşturalım
    
    * `main.py` adında bir dosya oluşturup içine şu kodu yapıştıralım:
    
    ```Python
    from typing import Union
    
    from fastapi import FastAPI
    
    app = FastAPI()
    
    
    @app.get("/")
    def read_root():
        return {"Hello": "World"}
    
    
    @app.get("/items/{item_id}")
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  6. docs/en/docs/index.md

    **Note**: Make sure you put `"fastapi[standard]"` in quotes to ensure it works in all terminals.
    
    ## Example { #example }
    
    ### Create it { #create-it }
    
    Create a file `main.py` with:
    
    ```Python
    from typing import Union
    
    from fastapi import FastAPI
    
    app = FastAPI()
    
    
    @app.get("/")
    def read_root():
        return {"Hello": "World"}
    
    
    @app.get("/items/{item_id}")
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  7. docs/yo/docs/index.md

    ```console
    $ pip install "uvicorn[standard]"
    
    ---> 100%
    ```
    
    </div>
    
    ## Àpẹẹrẹ
    
    ### Ṣẹ̀dá rẹ̀
    
    * Ṣẹ̀dá fáìlì `main.py (èyí tíí ṣe, akọkọ.py)` pẹ̀lú:
    
    ```Python
    from typing import Union
    
    from fastapi import FastAPI
    
    app = FastAPI()
    
    
    @app.get("/")
    def read_root():
        return {"Hello": "World"}
    
    
    @app.get("/items/{item_id}")
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  8. docs/fa/docs/index.md

    ```console
    $ pip install "uvicorn[standard]"
    
    ---> 100%
    ```
    
    </div>
    
    ## مثال
    
    ### ایجاد کنید
    * فایلی به نام `main.py` با محتوای زیر ایجاد کنید:
    
    ```Python
    from typing import Union
    
    from fastapi import FastAPI
    
    app = FastAPI()
    
    
    @app.get("/")
    def read_root():
        return {"Hello": "World"}
    
    
    @app.get("/items/{item_id}")
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  9. docs/fa/docs/features.md

    * اعتبار سنجی **ساختارهای پیچیده**:
        * استفاده از مدل های سلسله مراتبی Pydantic, `List` و `Dict` کتابخانه `typing` پایتون و غیره.
        * و اعتبارسنج ها اجازه میدهند که طرحواره های داده پیچیده به طور واضح و آسان تعریف، بررسی و بر پایه JSON مستند شوند.
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  10. docs/uk/docs/features.md

    * Валідація **складних структур**:
        * Використання ієрархічних моделей Pydantic. Python `typing`, `List` і `Dict` тощо.
        * Валідатори дозволяють чітко і просто визначати, перевіряти й документувати складні схеми даних у вигляді JSON-схеми.
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