The latest versions of Ubuntu and Fedora come with Python 2.7 out of the box.
The latest versions of Redhat Enterprise (RHEL) and CentOS come with Python 2.6. Some older versions of RHEL and CentOS come with Python 2.4 which is unacceptable for modern Python development. Fortunately, there are Extra Packages for Enterprise Linux which include high quality additional packages based on their Fedora counterparts. This repository contains a Python 2.6 package specifically designed to install side-by-side with the system’s Python 2.4 installation.
You do not need to install or configure anything else to use Python. Having said that, I would strongly recommend that you install the tools and libraries described in the next section before you start building Python applications for real-world use. In particular, you should always install Setuptools, as it makes it much easier for you to use other third-party Python libraries.
The most crucial third-party Python software of all is Setuptools, which extends the packaging and installation facilities provided by the distutils in the standard library. Once you add Setuptools to your Python system you can download and install any compliant Python software product with a single command. It also enables you to add this network installation capability to your own Python software with very little work.
To obtain the latest version of Setuptools for Linux, refer to the documentation available here: unix-setuptools
The new easy_install command you have available is considered by many to be deprecated, so we will install its replacement: pip. Pip allows for uninstallation of packages, and is actively maintained, unlike easy_install.
To install pip, simply open a command prompt and run
$ easy_install pip
A Virtual Environment is a tool to keep the dependencies required by different projects in separate places, by creating virtual Python environments for them. It solves the “Project X depends on version 1.x but, Project Y needs 4.x” dilemma, and keeps your global site-packages directory clean and manageable.
For example, you can work on a project which requires Django 1.3 while also maintaining a project which requires Django 1.0.
To start using and see more information: Virtual Environments docs.
This page is a remixed version of another guide, which is available under the same license.