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  1. docs/pt/docs/tutorial/body-nested-models.md

    ## Modelos aninhados
    
    Cada atributo de um modelo Pydantic tem um tipo.
    
    Mas esse tipo pode ser outro modelo Pydantic.
    
    Portanto, você pode declarar "objects" JSON profundamente aninhados com nomes, tipos e validações de atributos específicos.
    
    Tudo isso, aninhado arbitrariamente.
    
    ### Defina um sub-modelo
    
    Por exemplo, nós podemos definir um modelo `Image`:
    
    ```Python hl_lines="9-11"
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  2. docs/en/docs/deployment/manually.md

    The main thing you need to run a **FastAPI** application (or any other ASGI application) in a remote server machine is an ASGI server program like **Uvicorn**, this is the one that comes by default in the `fastapi` command.
    
    There are several alternatives, including:
    
    * <a href="https://www.uvicorn.org/" class="external-link" target="_blank">Uvicorn</a>: a high performance ASGI server.
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  3. README.md

    and utilities for concurrency, I/O, hashing, primitives, strings, and more! It
    is widely used on most Java projects within Google, and widely used by many
    other companies as well.
    
    
    
    Guava comes in two flavors:
    
    *   The JRE flavor requires JDK 1.8 or higher.
    *   If you need support for Android, use
        [the Android flavor](https://github.com/google/guava/wiki/Android). You can
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  4. docs/em/docs/tutorial/query-params.md

    * `limit`: ⏮️ 💲 `10`
    
    👫 🍕 📛, 👫 "🛎" 🎻.
    
    ✋️ 🕐❔ 👆 📣 👫 ⏮️ 🐍 🆎 (🖼 🔛, `int`), 👫 🗜 👈 🆎 &amp; ✔ 🛡 ⚫️.
    
    🌐 🎏 🛠️ 👈 ⚖ ➡ 🔢 ✔ 🔢 🔢:
    
    * 👨‍🎨 🐕‍🦺 (🎲)
    * 💽 <abbr title="converting the string that comes from an HTTP request into Python data">"✍"</abbr>
    * 💽 🔬
    * 🏧 🧾
    
    ## 🔢
    
    🔢 🔢 🚫 🔧 🍕 ➡, 👫 💪 📦 &amp; 💪 ✔️ 🔢 💲.
    
    🖼 🔛 👫 ✔️ 🔢 💲 `skip=0` &amp; `limit=10`.
    
    , 🔜 📛:
    
    ```
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  5. docs/en/docs/tutorial/testing.md

    !!! note "Technical Details"
        You could also use `from starlette.testclient import TestClient`.
    
        **FastAPI** provides the same `starlette.testclient` as `fastapi.testclient` just as a convenience for you, the developer. But it comes directly from Starlette.
    
    !!! tip
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  6. docs/en/docs/tutorial/index.md

    The first step is to install FastAPI:
    
    <div class="termy">
    
    ```console
    $ pip install fastapi
    
    ---> 100%
    ```
    
    </div>
    
    !!! note
        When you install with `pip install fastapi` it comes with some default optional standard dependencies.
    
        If you don't want to have those optional dependencies, you can instead install `pip install fastapi-slim`.
    
    ## Advanced User Guide
    
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  7. docs/en/docs/advanced/websockets.md

    ```
    
    !!! note "Technical Details"
        You could also use `from starlette.websockets import WebSocket`.
    
        **FastAPI** provides the same `WebSocket` directly just as a convenience for you, the developer. But it comes directly from Starlette.
    
    ## Await for messages and send messages
    
    In your WebSocket route you can `await` for messages and send messages.
    
    ```Python hl_lines="48-52"
    {!../../../docs_src/websockets/tutorial001.py!}
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  8. docs/en/docs/tutorial/extra-models.md

    === "Python 3.10+"
    
        ```Python hl_lines="1  14-15  18-20  33"
        {!> ../../../docs_src/extra_models/tutorial003_py310.py!}
        ```
    
    === "Python 3.8+"
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  9. docs/en/docs/features.md

    ![editor support](https://fastapi.tiangolo.com/img/pycharm-completion.png)
    
    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
    
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  10. docs/pt/docs/tutorial/path-params.md

    !!! tip "Dica"
    	Se você está se perguntando, "AlexNet", "ResNet", e "LeNet" são apenas nomes de <abbr title="técnicamente, modelos de arquitetura de Deep Learning">modelos</abbr> de Machine Learning (aprendizado de máquina).
    
    ### Declare um *parâmetro de rota*
    
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