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  1. ci/official/containers/linux_arm64/setup.python.sh

    #
    # setup.python.sh: Install a specific Python version and packages for it.
    # Usage: setup.python.sh <pyversion> <requirements.txt>
    set -xe
    
    source ~/.bashrc
    VERSION=$1
    REQUIREMENTS=$2
    
    add-apt-repository ppa:deadsnakes/ppa
    # Install Python packages for this container's version
    cat >pythons.txt <<EOF
    $VERSION
    $VERSION-dev
    $VERSION-venv
    $VERSION-distutils
    EOF
    Shell Script
    - Registered: Tue Apr 30 12:39:09 GMT 2024
    - Last Modified: Fri Sep 29 00:26:34 GMT 2023
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  2. docs/zh/docs/python-types.md

    # Python 类型提示简介
    
    **Python 3.6+ 版本**加入了对"类型提示"的支持。
    
    这些**"类型提示"**是一种新的语法(在 Python 3.6 版本加入)用来声明一个变量的<abbr title="例如:str、int、float、bool">类型</abbr>。
    
    通过声明变量的类型,编辑器和一些工具能给你提供更好的支持。
    
    这只是一个关于 Python 类型提示的**快速入门 / 复习**。它仅涵盖与 **FastAPI** 一起使用所需的最少部分...实际上只有很少一点。
    
    整个 **FastAPI** 都基于这些类型提示构建,它们带来了许多优点和好处。
    
    但即使你不会用到 **FastAPI**,了解一下类型提示也会让你从中受益。
    
    !!! note
        如果你已经精通 Python,并且了解关于类型提示的一切知识,直接跳到下一章节吧。
    
    ## 动机
    
    让我们从一个简单的例子开始:
    
    Plain Text
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  3. docs/tr/docs/python-types.md

    Diyelim ki  `name` değerine sahip `Person` sınıfınız var:
    
    ```Python hl_lines="1-3"
    {!../../../docs_src/python_types/tutorial010.py!}
    ```
    
    Sonra bir değişkeni 'Person' tipinde tanımlayabilirsiniz:
    
    ```Python hl_lines="6"
    {!../../../docs_src/python_types/tutorial010.py!}
    ```
    
    Ve yine bütün editör desteğini alırsınız:
    
    <img src="/img/python-types/image06.png">
    
    ## Pydantic modelleri
    
    Plain Text
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  4. docs/pt/docs/python-types.md

    Digamos que você tenha uma classe `Person`, com um nome:
    
    ```Python hl_lines="1 2 3"
    {!../../../docs_src/python_types/tutorial010.py!}
    ```
    
    Então você pode declarar que uma variável é do tipo `Person`:
    
    ```Python hl_lines="6"
    {!../../../docs_src/python_types/tutorial010.py!}
    ```
    
    E então, novamente, você recebe todo o suporte do editor:
    
    <img src="/img/python-types/image06.png">
    
    ## Modelos Pydantic
    
    Plain Text
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  5. docs/es/docs/python-types.md

    Digamos que tienes una clase `Person`con un nombre:
    
    ```Python hl_lines="1-3"
    {!../../../docs_src/python_types/tutorial009.py!}
    ```
    
    Entonces puedes declarar una variable que sea de tipo `Person`:
    
    ```Python hl_lines="6"
    {!../../../docs_src/python_types/tutorial009.py!}
    ```
    
    Una vez más tendrás todo el soporte del editor:
    
    <img src="https://fastapi.tiangolo.com/img/python-types/image06.png">
    
    ## Modelos de Pydantic
    
    Plain Text
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  6. docs/de/docs/tutorial/extra-models.md

    Genauso können Sie eine Response deklarieren, die eine Liste von Objekten ist.
    
    Verwenden Sie dafür Pythons Standard `typing.List` (oder nur `list` in Python 3.9 und darüber):
    
    === "Python 3.9+"
    
        ```Python hl_lines="18"
        {!> ../../../docs_src/extra_models/tutorial004_py39.py!}
        ```
    
    === "Python 3.8+"
    
        ```Python hl_lines="1  20"
        {!> ../../../docs_src/extra_models/tutorial004.py!}
        ```
    
    Plain Text
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  7. ci/official/containers/linux_arm64/Dockerfile

    COPY setup.python.sh /setup.python.sh
    RUN /setup.python.sh python3.9 devel.requirements.txt
    RUN /setup.python.sh python3.10 devel.requirements.txt
    RUN /setup.python.sh python3.11 devel.requirements.txt
    RUN /setup.python.sh python3.12 devel.requirements.txt
    
    FROM devel as tf
    # Setup TF Python environment.
    COPY devel.requirements.txt /devel.requirements.txt
    COPY setup.python.sh /setup.python.sh
    Plain Text
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  8. docs/en/docs/tutorial/header-params.md

    ## Import `Header`
    
    First import `Header`:
    
    === "Python 3.10+"
    
        ```Python hl_lines="3"
        {!> ../../../docs_src/header_params/tutorial001_an_py310.py!}
        ```
    
    === "Python 3.9+"
    
        ```Python hl_lines="3"
        {!> ../../../docs_src/header_params/tutorial001_an_py39.py!}
        ```
    
    === "Python 3.8+"
    
        ```Python hl_lines="3"
        {!> ../../../docs_src/header_params/tutorial001_an.py!}
    Plain Text
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  9. docs/zh/docs/tutorial/dependencies/classes-as-dependencies.md

    但这并不是声明依赖项的唯一方法(尽管它可能是更常见的方法)。
    
    关键因素是依赖项应该是 "可调用对象"。
    
    Python 中的 "**可调用对象**" 是指任何 Python 可以像函数一样 "调用" 的对象。
    
    所以,如果你有一个对象 `something` (可能*不是*一个函数),你可以 "调用" 它(执行它),就像:
    
    ```Python
    something()
    ```
    
    或者
    
    ```Python
    something(some_argument, some_keyword_argument="foo")
    ```
    
    这就是 "可调用对象"。
    
    ## 类作为依赖项
    
    您可能会注意到,要创建一个 Python 类的实例,您可以使用相同的语法。
    
    举个例子:
    
    ```Python
    class Cat:
        def __init__(self, name: str):
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  10. docs/en/docs/tutorial/security/get-current-user.md

        ```
    
    === "Python 3.9+"
    
        ```Python hl_lines="5  12-16"
        {!> ../../../docs_src/security/tutorial002_an_py39.py!}
        ```
    
    === "Python 3.8+"
    
        ```Python hl_lines="5  13-17"
        {!> ../../../docs_src/security/tutorial002_an.py!}
        ```
    
    === "Python 3.10+ non-Annotated"
    
        !!! tip
            Prefer to use the `Annotated` version if possible.
    
        ```Python hl_lines="3  10-14"
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