virtualenv is a tool to create isolated Python environments.
The basic problem being addressed is one of dependencies and versions, and indirectly permissions. 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/python2.7/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, virtualenv can help you. It creates an environment that has its own installation directories, that doesn’t share libraries with other virtualenv environments (and optionally doesn’t access the globally installed libraries either).
- User Guide
- Reference Guide
- Release History
Python bugfix releases 2.6.8, 2.7.3, 3.1.5 and 3.2.3 include a change that will cause “import random” to fail with “cannot import name urandom” on any virtualenv created on a Unix host with an earlier release of Python 2.6/2.7/3.1/3.2, if the underlying system Python is upgraded. This is due to the fact that a virtualenv uses the system Python’s standard library but contains its own copy of the Python interpreter, so an upgrade to the system Python results in a mismatch between the version of the Python interpreter and the version of the standard library. It can be fixed by removing $ENV/bin/python and re-running virtualenv on the same target directory with the upgraded Python.
Compare & Contrast with Alternatives¶
There are several alternatives that create isolated environments:
workingenv (which I do not suggest you use anymore) is the predecessor to this library. It used the main Python interpreter, but relied on setting $PYTHONPATH to activate the environment. This causes problems when running Python scripts that aren’t part of the environment (e.g., a globally installed hg or bzr). It also conflicted a lot with Setuptools.
virtual-python is also a predecessor to this library. It uses only symlinks, so it couldn’t work on Windows. It also symlinks over the entire standard library and global site-packages. As a result, it won’t see new additions to the global site-packages.
This script only symlinks a small portion of the standard library into the environment, and so on Windows it is feasible to simply copy these files over. Also, it creates a new/empty site-packages and also adds the global site-packages to the path, so updates are tracked separately. This script also installs Setuptools automatically, saving a step and avoiding the need for network access.
zc.buildout doesn’t create an isolated Python environment in the same style, but achieves similar results through a declarative config file that sets up scripts with very particular packages. As a declarative system, it is somewhat easier to repeat and manage, but more difficult to experiment with. zc.buildout includes the ability to setup non-Python systems (e.g., a database server or an Apache instance).
I strongly recommend anyone doing application development or deployment use one of these tools.