安装Python模块 官方网站翻译

中文翻译

安装 Python 模块

• 电子邮箱

  [email protected]

作为一个流行的开源开发项目，Python拥有一个活跃的贡献者和用户支持社区，这些社区也可以让他们的软件可供其他Python开发人员在开源许可条款下使用。

这允许Python用户有效地共享和协作，从其他人已经创建的解决方案中受益于常见（有时甚至是罕见的）问题，以及可以提供他们自己的解决方案。

本指南涵盖了分发部分的流程。有关安装其他Python项目的指南，请参阅 安装指南。

注解

对于企业和其他机构用户，请注意许多组织都有自己的政策来使用和贡献开源软件。在使用Python提供的分发和安装工具时，请考虑这些政策。

关键术语

• pip 是首选的安装程序。从Python 3.4开始，它默认包含在Python二进制安装程序中。
• virtual environment 是一种半隔离的 Python 环境，允许为特定的应用安装各自的包，而不是安装到整个系统。
• venv 是创建虚拟环境的标准工具，从 Python 3.3 开始成为 Python 的组成部分。 从 Python 3.4 开始，它会默认安装 pip 到所创建的全部虚拟环境。
• virtualenv 是 venv 的第三方替代（及其前身）。 它允许在 Python 3.4 之前的版本中使用虚拟环境，那些版本或是完全不提供 venv，或是不会自动安装 pip 到所创建的虚拟环境。
• Python Packaging Index 是一个由 Python 用户向其他用户发布开源许可软件包的公共仓库。
• Python Packaging Authority 是负责标准打包工具以及相关元数据和文件格式标准维护与改进的开发人员和文档作者团队。 他们基于 GitHub 和 Bitbucket 这两个平台维护着各种工具、文档和问题追踪系统。
• distutils 是最初的构建和分发系统，于 1998 年首次加入 Python 标准库。 虽然直接使用 distutils 的方式已被淘汰，它仍然是当前打包和分发架构的基础，而且它不仅仍然是标准库的一部分，这个名称还以其他方式存在（例如用于协调 Python 打包标准开发流程的邮件列表就以此命名）。

在 3.5 版更改: 现在推荐使用 venv 来创建虚拟环境。

参见

Python 软件包用户指南：创建和使用虚拟环境

基本使用

标准打包工具完全是针对命令行使用方式来设计的。

以下命令将从 Python Packaging Index 安装一个模块的最新版本及其依赖项:

python -m pip install SomePackage

注解

对于 POSIX 用户（包括 Mac OS X 和 Linux 用户）本指南中的示例假定使用了 virtual environment。

对于 Windows 用户，本指南中的示例假定在安装 Python 时选择了修改系统 PATH 环境变量。

在命令行中指定一个准确或最小版本也是可以的。 当使用比较运算符例如 >, < 或其他某些可以被终端所解析的特殊字符时，包名称与版本号应当用双引号括起来:

python -m pip install SomePackage==1.0.4    # specific version
python -m pip install "SomePackage>=1.0.4"  # minimum version

通常，如果一个匹配的模块已安装，尝试再次安装将不会有任何效果。 要升级现有模块必须显式地发出请求:

python -m pip install --upgrade SomePackage

更多有关 pip 及其功能的信息和资源可以在 Python 软件包用户指南 中找到。

虚拟环境的创建可使用 venv 模块来完成。 向已激活虚拟环境安装软件包可使用上文所介绍的命令。

参见

Python 软件包用户指南：安装 Python 分发包

我应如何 …？

这是一些常见任务的快速解答或相关链接。

… 在 Python 3.4 之前的 Python 版本中安装 pip ？

Python 捆绑 pip 是从 Python 3.4 才开始的。 对于更早的版本，pip 需要“引导安装bootstrapped”，具体说明参见 Python 软件包用户指南。

参见

Python 软件包用户指南：安装软件包的前提要求

… 只为当前用户安装软件包？

将 --user 选项传入 python -m pip install 将只为当前用户而非为系统中的所有用户安装软件包。

… 安装科学计算类 Python 软件包？

许多科学计算类 Python 软件包都有复杂的二进制编译文件依赖，直接使用 pip 安装目前并不太容易。 在当前情况下，通过 其他方式 而非尝试用 pip 安装这些软件包对用户来说通常会更容易。

参见

Python 软件包用户指南：安装科学计算类软件包

… 使用并行安装的多个 Python 版本？

在 Linux, Mac OS X 以及其他 POSIX 系统中，使用带版本号的 Python 命令配合 -m 开关选项来运行特定版本的 pip:

python2   -m pip install SomePackage  # default Python 2
python2.7 -m pip install SomePackage  # specifically Python 2.7
python3   -m pip install SomePackage  # default Python 3
python3.4 -m pip install SomePackage  # specifically Python 3.4

也可以使用带特定版本号的 pip 命令。

在 Windows 中，使用 py Python 启动器命令配合 -m 开关选项:

py -2   -m pip install SomePackage  # default Python 2
py -2.7 -m pip install SomePackage  # specifically Python 2.7
py -3   -m pip install SomePackage  # default Python 3
py -3.4 -m pip install SomePackage  # specifically Python 3.4

常见的安装问题

在 Linux 的系统 Python 版本上安装

Linux 系统通常会将某个 Python 版本作为发行版的一部分包含在内。 将软件包安装到这个 Python 版本上需要系统 root 权限，并可能会干扰到系统包管理器和其他系统组件的运作，如果这些组件在使用 pip 时被意外升级的话。

在这样的系统上，通过 pip 安装软件包通常最好是使用虚拟环境或分用户安装。

未安装 pip

默认情况下可能未安装 pip，一种可选解决方案是:

python -m ensurepip --default-pip

还有其他资源可用来 安装 pip

安装二进制编译扩展

Python 通常非常依赖基于源代码的发布方式，也就是期望最终用户在安装过程中使用源码来编译生成扩展模块。

随着对二进制码 wheel 格式支持的引入，以及通过 Python Packaging Index 至少发布 Windows 和 Mac OS X 版的 wheel 文件，预计此问题将逐步得到解决，因为用户将能够更频繁地安装预编译扩展，而不再需要自己编译它们。

某些用来安装 科学计算类软件包 的解决方案对于尚未提供预编译 wheel 文件的那些扩展模块来说，也有助于用户在无需进行本机编译的情况下获取二进制码扩展模块。

原文

Installing Python Modules

• Email

  [email protected]

As a popular open source development project, Python has an active supporting community of contributors and users that also make their software available for other Python developers to use under open source license terms.

This allows Python users to share and collaborate effectively, benefiting from the solutions others have already created to common (and sometimes even rare!) problems, as well as potentially contributing their own solutions to the common pool.

This guide covers the installation part of the process. For a guide to creating and sharing your own Python projects, refer to the distribution guide.

Note

For corporate and other institutional users, be aware that many organisations have their own policies around using and contributing to open source software. Please take such policies into account when making use of the distribution and installation tools provided with Python.

Key terms

• pip is the preferred installer program. Starting with Python 3.4, it is included by default with the Python binary installers.
• A virtual environment is a semi-isolated Python environment that allows packages to be installed for use by a particular application, rather than being installed system wide.
• venv is the standard tool for creating virtual environments, and has been part of Python since Python 3.3. Starting with Python 3.4, it defaults to installing pip into all created virtual environments.
• virtualenv is a third party alternative (and predecessor) to venv. It allows virtual environments to be used on versions of Python prior to 3.4, which either don’t provide venv at all, or aren’t able to automatically install pip into created environments.
• The Python Packaging Index is a public repository of open source licensed packages made available for use by other Python users.
• the Python Packaging Authority is the group of developers and documentation authors responsible for the maintenance and evolution of the standard packaging tools and the associated metadata and file format standards. They maintain a variety of tools, documentation, and issue trackers on both GitHub and Bitbucket.
• distutils is the original build and distribution system first added to the Python standard library in 1998. While direct use of distutils is being phased out, it still laid the foundation for the current packaging and distribution infrastructure, and it not only remains part of the standard library, but its name lives on in other ways (such as the name of the mailing list used to coordinate Python packaging standards development).

Changed in version 3.5: The use of venv is now recommended for creating virtual environments.

See also

Python Packaging User Guide: Creating and using virtual environments

Basic usage

The standard packaging tools are all designed to be used from the command line.

The following command will install the latest version of a module and its dependencies from the Python Packaging Index:

python -m pip install SomePackage

Note

For POSIX users (including Mac OS X and Linux users), the examples in this guide assume the use of a virtual environment.

For Windows users, the examples in this guide assume that the option to adjust the system PATH environment variable was selected when installing Python.

It’s also possible to specify an exact or minimum version directly on the command line. When using comparator operators such as >, < or some other special character which get interpreted by shell, the package name and the version should be enclosed within double quotes:

python -m pip install SomePackage==1.0.4    # specific version
python -m pip install "SomePackage>=1.0.4"  # minimum version

Normally, if a suitable module is already installed, attempting to install it again will have no effect. Upgrading existing modules must be requested explicitly:

python -m pip install --upgrade SomePackage

More information and resources regarding pip and its capabilities can be found in the Python Packaging User Guide.

Creation of virtual environments is done through the venv module. Installing packages into an active virtual environment uses the commands shown above.

See also

Python Packaging User Guide: Installing Python Distribution Packages

How do I …?

These are quick answers or links for some common tasks.

… install pip in versions of Python prior to Python 3.4?

Python only started bundling pip with Python 3.4. For earlier versions, pip needs to be “bootstrapped” as described in the Python Packaging User Guide.

See also

Python Packaging User Guide: Requirements for Installing Packages

… install packages just for the current user?

Passing the --user option to python -m pip install will install a package just for the current user, rather than for all users of the system.

… install scientific Python packages?

A number of scientific Python packages have complex binary dependencies, and aren’t currently easy to install using pip directly. At this point in time, it will often be easier for users to install these packages by other means rather than attempting to install them with pip.

See also

Python Packaging User Guide: Installing Scientific Packages

… work with multiple versions of Python installed in parallel?

On Linux, Mac OS X, and other POSIX systems, use the versioned Python commands in combination with the -m switch to run the appropriate copy of pip:

python2   -m pip install SomePackage  # default Python 2
python2.7 -m pip install SomePackage  # specifically Python 2.7
python3   -m pip install SomePackage  # default Python 3
python3.4 -m pip install SomePackage  # specifically Python 3.4

Appropriately versioned pip commands may also be available.

On Windows, use the py Python launcher in combination with the -m switch:

py -2   -m pip install SomePackage  # default Python 2
py -2.7 -m pip install SomePackage  # specifically Python 2.7
py -3   -m pip install SomePackage  # default Python 3
py -3.4 -m pip install SomePackage  # specifically Python 3.4

Common installation issues

Installing into the system Python on Linux

On Linux systems, a Python installation will typically be included as part of the distribution. Installing into this Python installation requires root access to the system, and may interfere with the operation of the system package manager and other components of the system if a component is unexpectedly upgraded using pip.

On such systems, it is often better to use a virtual environment or a per-user installation when installing packages with pip.

Pip not installed

It is possible that pip does not get installed by default. One potential fix is:

python -m ensurepip --default-pip

There are also additional resources for installing pip.

Installing binary extensions

Python has typically relied heavily on source based distribution, with end users being expected to compile extension modules from source as part of the installation process.

With the introduction of support for the binary wheel format, and the ability to publish wheels for at least Windows and Mac OS X through the Python Packaging Index, this problem is expected to diminish over time, as users are more regularly able to install pre-built extensions rather than needing to build them themselves.

Some of the solutions for installing scientific software that are not yet available as pre-built wheel files may also help with obtaining other binary extensions without needing to build them locally.