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Python packaging user guide

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Содержание
  1. Installing Packages¶
  2. Requirements for Installing Packages¶
  3. Ensure you can run Python from the command line¶
  4. Ensure you can run pip from the command line¶
  5. Ensure pip, setuptools, and wheel are up to date¶
  6. Optionally, create a virtual environment¶
  7. Creating Virtual Environments¶
  8. Python Packaging User Guide¶
  9. Get started¶
  10. Learn more¶
  11. Table of Contents
  12. Guides¶
  13. Table of Contents
  14. Previous topic
  15. Next topic
  16. Navigation
  17. Python Packaging User Guide¶
  18. Get started¶
  19. Learn more¶
  20. Table of Contents

Installing Packages¶

This section covers the basics of how to install Python packages .

It’s important to note that the term “package” in this context is being used to describe a bundle of software to be installed (i.e. as a synonym for a distribution ). It does not to refer to the kind of package that you import in your Python source code (i.e. a container of modules). It is common in the Python community to refer to a distribution using the term “package”. Using the term “distribution” is often not preferred, because it can easily be confused with a Linux distribution, or another larger software distribution like Python itself.

Requirements for Installing Packages¶

This section describes the steps to follow before installing other Python packages.

Ensure you can run Python from the command line¶

Before you go any further, make sure you have Python and that the expected version is available from your command line. You can check this by running:

You should get some output like Python 3.6.3 . If you do not have Python, please install the latest 3.x version from python.org or refer to the Installing Python section of the Hitchhiker’s Guide to Python.

If you’re a newcomer and you get an error like this:

>>> python3 --version Traceback (most recent call last): File "", line 1, in NameError: name 'python3' is not defined

It’s because this command and other suggested commands in this tutorial are intended to be run in a shell (also called a terminal or console). See the Python for Beginners getting started tutorial for an introduction to using your operating system’s shell and interacting with Python.

If you’re using an enhanced shell like IPython or the Jupyter notebook, you can run system commands like those in this tutorial by prefacing them with a ! character:

In [1]: import sys ! --version Python 3.6.3

It’s recommended to write rather than plain python in order to ensure that commands are run in the Python installation matching the currently running notebook (which may not be the same Python installation that the python command refers to).

Due to the way most Linux distributions are handling the Python 3 migration, Linux users using the system Python without creating a virtual environment first should replace the python command in this tutorial with python3 and the python -m pip command with python3 -m pip —user . Do not run any of the commands in this tutorial with sudo : if you get a permissions error, come back to the section on creating virtual environments, set one up, and then continue with the tutorial as written.

Ensure you can run pip from the command line¶

Additionally, you’ll need to make sure you have pip available. You can check this by running:

If you installed Python from source, with an installer from python.org, or via Homebrew you should already have pip. If you’re on Linux and installed using your OS package manager, you may have to install pip separately, see Installing pip/setuptools/wheel with Linux Package Managers .

If pip isn’t already installed, then first try to bootstrap it from the standard library:

python3 -m ensurepip --default-pip
py -m ensurepip --default-pip

If that still doesn’t allow you to run python -m pip :

  • Securely Download get-pip.py1
  • Run python get-pip.py . 2 This will install or upgrade pip. Additionally, it will install setuptools and wheel if they’re not installed already.

Warning Be cautious if you’re using a Python install that’s managed by your operating system or another package manager. get-pip.py does not coordinate with those tools, and may leave your system in an inconsistent state. You can use python get-pip.py —prefix=/usr/local/ to install in /usr/local which is designed for locally-installed software.

Ensure pip, setuptools, and wheel are up to date¶

While pip alone is sufficient to install from pre-built binary archives, up to date copies of the setuptools and wheel projects are useful to ensure you can also install from source archives:

python3 -m pip install --upgrade pip setuptools wheel
py -m pip install --upgrade pip setuptools wheel

Optionally, create a virtual environment¶

See section below for details, but here’s the basic venv 3 command to use on a typical Linux system:

python3 -m venv tutorial_env source tutorial_env/bin/activate
py -m venv tutorial_env tutorial_env\Scripts\activate

This will create a new virtual environment in the tutorial_env subdirectory, and configure the current shell to use it as the default python environment.

Creating Virtual Environments¶

Python “Virtual Environments” allow Python packages to be installed in an isolated location for a particular application, rather than being installed globally. If you are looking to safely install global command line tools, see Installing stand alone command line tools .

Imagine you have an application that needs version 1 of LibFoo, but another application requires version 2. How can you use both these applications? If you install everything into /usr/lib/python3.6/site-packages (or whatever your platform’s standard location is), it’s easy to end up in a situation where you unintentionally upgrade an application that shouldn’t be upgraded.

Or more generally, what if you want to install an application and leave it be? If an application works, any change in its libraries or the versions of those libraries can break the application.

Also, what if you can’t install packages into the global site-packages directory? For instance, on a shared host.

In all these cases, virtual environments can help you. They have their own installation directories and they don’t share libraries with other virtual environments.

Currently, there are two common tools for creating Python virtual environments:

  • venv is available by default in Python 3.3 and later, and installs pip and setuptools into created virtual environments in Python 3.4 and later.
  • virtualenv needs to be installed separately, but supports Python 2.7+ and Python 3.3+, and pip , setuptools and wheel are always installed into created virtual environments by default (regardless of Python version).

The basic usage is like so:

python3 -m venv source /bin/activate

Источник

Python Packaging User Guide¶

Welcome to the Python Packaging User Guide, a collection of tutorials and references to help you distribute and install Python packages with modern tools.

This guide is maintained on GitHub by the Python Packaging Authority . We happily accept any contributions and feedback . 😊

Get started¶

Essential tools and concepts for working within the Python development ecosystem are covered in our Tutorials section:

  • To get an overview of the flow used to publish your code, see the packaging flow
  • To learn how to install packages, see the tutorial on installing packages
  • To learn how to manage dependencies in a version controlled project, see the tutorial on managing application dependencies
  • To learn how to package and distribute your projects, see the tutorial on packaging and distributing
  • To get an overview of packaging options for Python libraries and applications, see the Overview of Python Packaging

Learn more¶

Beyond our Tutorials , this guide has several other resources:

  • The Guides section for walk throughs, such as Installing pip/setuptools/wheel with Linux Package Managers or Packaging binary extensions .
  • The Discussions section for in-depth references on topics such as Deploying Python applications or pip vs easy_install .
  • The PyPA specifications section for packaging interoperability specifications.

Additionally, there is a list of other projects maintained by members of the Python Packaging Authority.

Table of Contents

  • An Overview of Packaging for Python
  • The Packaging Flow
  • Tutorials
  • Guides
  • Discussions
  • PyPA specifications
  • Project Summaries
  • Glossary
  • How to Get Support
  • Contribute to this guide
  • News

Источник

Guides¶

Guides are focused on accomplishing a specific task and assume that you are already familiar with the basics of Python packaging. If you’re looking for an introduction to packaging, see Tutorials .

Building and Publishing Projects:

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