The Python intermediate's guide: Python packages confusion reducer

This page assumes

The aim of this page is to reduce this confusion in a few important spots.

Some recurring sources of such confusion are these:

Disclaimer: The primary author of this page is a Python intermediate himself. If an expert could check/correct the statements and then remove this message, that would be most helpful. If this message is still present, beware of errors.


Python3 versus Python2

You should use Python 3 going forward. As of January 2020 Python 2 will be in EOL (End Of Life) status and receive no further official support. After that date, there will be no further updates nor bugfixes. Since this end-of-life date has been planned for nearly a decade (the first end-of-life date was slated to happen in 2014, and was pushed back to 2020), and nearly all popular libraries have already ported their code, Python 2.x is well on its way to obsolescence. As such, we can only recommend learning and using Python 3.

Package installation

Multiple isolated Python environments

By default, packages are installed into the local Python installation. They become a part of it and will be available to any Python program on that computer. This can become inconvenient: Sometimes you need different versions of a package for different applications or a certain package must not be available for some.

One could avoid this by installing packages elsewhere and manipulating the PYTHONPATH environment variable appropriately, but this is inconvenient as well, because packages often depend on many other packages and so this approach can produce immense confustion and giant PYTHONPATH lists.

A virtual environment behaves like a copy of the Python installation's directory tree (with or without the site-packages subtree). One can have a separate virtual environment for each project or application to isolate them from each other and install only the required packages into each.

You should use a virtual environment for any team project and for any package you intend to distribute.

Creating a package installer or application installer

Since Python 2.0, there is a convention that any reusable package or distributable application should have a top level file setup.py that implements a command line tool for installation and configuration. This file will

See the documentation of distutils from the standard library. Distutils will not only make setup.py easy to write, it will also provide it with functionality for creating the distributable package file in the first place.

In contrast to some other platforms it is common in Python that neither a reusable package nor a distributable application come packaged with all the additional reusable packages they depend on. Rather, the dependencies are only declared in setup.py and an installer program such as pip will download and install additional packages (that are yet missing or the version of which is inappropriate) automatically.

Confusingly, there are multiple frameworks that are used to support setup.py:

So what should you use? First, be aware that many packages on PyPI will import setuptools}, so you need to have {{{setuptools or distribute installed in any case. Second, for an up-to-date answer for your own development, see the summary on stackoverflow and the Python Packaging User Guide recommendation.

GUI programming

There is a surprising range of toolkits for building desktop GUIs with Python. One of them, tkinter, is a core package consisting of Python bindings for TCL/TK's tk plus additional widgets (in tkinter.ttk and tkinter.tix). tkinter is platform-independent and easy to program for simple GUIs.

For larger applications, you might prefer a more extensive GUI toolkit.

Web development

There is a surprising range of frameworks for building web applications with Python. Several of them are quite good. They follow fairly different objectives (such as being slim vs. extensive or regarding the development style they imply). Among these, Django has the largest and most active community by far.

Object-relational mapping

There are at least two mature, powerful, and widely used solutions for O/R mapping:

Although Django is a web development framework, some people also use it for non-web software in order to make use of its persistence framework.

IntermediatesGuide (last edited 2019-10-27 00:31:30 by JennyRyan)

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