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  1. docs/pt/docs/features.md

    ### Apenas Python moderno { #just-modern-python }
    
    Tudo é baseado no padrão das declarações de **tipos do Python** (graças ao Pydantic). Nenhuma sintaxe nova para aprender. Apenas o padrão moderno do Python.
    
    Se você precisa refrescar a memória rapidamente sobre como usar tipos do Python (mesmo que você não use o FastAPI), confira esse rápido tutorial: [Tipos do Python](python-types.md){.internal-link target=_blank}.
    
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  2. docs/en/docs/virtual-environments.md

    <div class="termy">
    
    ```console
    $ which python
    
    /home/user/code/awesome-project/.venv/bin/python
    ```
    
    </div>
    
    If it shows the `python` binary at `.venv/bin/python`, inside of your project (in this case `awesome-project`), then it worked. 🎉
    
    ////
    
    //// tab | Windows PowerShell
    
    <div class="termy">
    
    ```console
    $ Get-Command python
    
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  3. docs/ja/docs/environment-variables.md

    Hello Wade Wilson
    ```
    
    </div>
    
    ////
    
    ## Pythonで環境変数を読み取る
    
    環境変数をPythonの**外側**、ターミナル(や他の方法)で作成し、**Python内で読み取る**こともできます。
    
    例えば、以下のような`main.py`ファイルを用意します:
    
    ```Python hl_lines="3"
    import os
    
    name = os.getenv("MY_NAME", "World")
    print(f"Hello {name} from Python")
    ```
    
    /// tip
    
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  4. docs/en/docs/tutorial/extra-models.md

    So, if we create a Pydantic object `user_in` like:
    
    ```Python
    user_in = UserIn(username="john", password="secret", email="******@****.***")
    ```
    
    and then we call:
    
    ```Python
    user_dict = user_in.model_dump()
    ```
    
    we now have a `dict` with the data in the variable `user_dict` (it's a `dict` instead of a Pydantic model object).
    
    And if we call:
    
    ```Python
    print(user_dict)
    ```
    
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  5. ci/official/requirements_updater/README.md

    ## Managing hermetic Python
    
    To make sure that TensorFlow's build is reproducible, behaves uniformly across
    supported platforms (Linux, Windows, MacOS) and is properly isolated from
    specifics of a local system, we rely on hermetic Python (see
    [rules_python](https://github.com/bazelbuild/rules_python)) for all build
    and test commands executed via Bazel. This means that your system Python
    installation will be ignored during the build and Python interpreter itself
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  6. docs/en/docs/tutorial/request-files.md

    /// info
    
    To receive uploaded files, first install <a href="https://github.com/Kludex/python-multipart" class="external-link" target="_blank">`python-multipart`</a>.
    
    Make sure you create a [virtual environment](../virtual-environments.md){.internal-link target=_blank}, activate it, and then install it, for example:
    
    ```console
    $ pip install python-multipart
    ```
    
    This is because uploaded files are sent as "form data".
    
    ///
    
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  7. docs/pt/docs/tutorial/request-files.md

    Para receber arquivos enviados, primeiro instale o <a href="https://github.com/Kludex/python-multipart" class="external-link" target="_blank">`python-multipart`</a>.
    
    Garanta que você criou um [ambiente virtual](../virtual-environments.md){.internal-link target=_blank}, o ativou e então o instalou, por exemplo:
    
    ```console
    $ pip install python-multipart
    ```
    
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  8. tensorflow/api_template_v1.__init__.py

    # pylint: disable=g-bad-import-order,protected-access,g-import-not-at-top
    from tensorflow.python import pywrap_tensorflow  # pylint: disable=unused-import
    from tensorflow.python.tools import module_util as _module_util
    from tensorflow.python.platform import tf_logging as _logging
    from tensorflow.python.util.lazy_loader import LazyLoader as _LazyLoader
    from tensorflow.python.util.lazy_loader import KerasLazyLoader as _KerasLazyLoader
    
    # API IMPORTS PLACEHOLDER
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  9. docs/es/docs/tutorial/extra-models.md

    Así que, si creamos un objeto Pydantic `user_in` como:
    
    ```Python
    user_in = UserIn(username="john", password="secret", email="******@****.***")
    ```
    
    y luego llamamos a:
    
    ```Python
    user_dict = user_in.dict()
    ```
    
    ahora tenemos un `dict` con los datos en la variable `user_dict` (es un `dict` en lugar de un objeto modelo Pydantic).
    
    Y si llamamos a:
    
    ```Python
    print(user_dict)
    ```
    
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  10. docs/ru/docs/index.md

    Вы делаете это с помощью стандартных современных типов Python.
    
    Вам не нужно изучать новый синтаксис, методы или классы конкретной библиотеки и т.п.
    
    Только стандартный **Python**.
    
    Например, для `int`:
    
    ```Python
    item_id: int
    ```
    
    или для более сложной модели `Item`:
    
    ```Python
    item: Item
    ```
    
    ...и с этим единственным объявлением вы получаете:
    
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