One of technological marvels behind modern languages is the easiness of installing new libraries, packages and modules. Thanks to having a central repository (PyPI, RubyGems, Hackage, …) and a suitable installer (pip/easy_install, gem, cabal, …), any library is usually just one command away. For one, this makes it very easy to bootstrap development of a new project – or alternatively, to abandon the idea of doing so because there is already something that does what you need :)
But being generous with external libraries also means adding a lot of dependencies. After a short while, they become practically untraceable, unless we keep an up-to-date list. In Python, for example, it would be the content of requirements.txt file, or a value for requires
parameter of the setuptools.setup
/distutils.setup
function call inside setup.py
module. Other languages have their own means of specifying dependencies but the principles are generally the same.
How to ensure this list is correct, though?… The best way is to create a dedicated virtual environment specifically for our project. An environment is simply a sandboxed interpreter/compiler, along with all the packages that it can use for executing/compiling) programs.
Normally, there is just one, global environment for a system as a whole: all external libraries or packages for a particular language are being installed there. This makes it easy to accidentally introduce extraneous dependencies to our project. More importantly, with this setting we are sharing our required libraries with other applications installed or developed on the system. This spells trouble if we’re relying on particular version of a library: some other program could update it and suddenly break our application this way.
If we use a virtual environment instead, our program is isolated from the rest and is using its own, dedicated set of libraries and packages. Besides preventing conflicts, this also has an added benefit of keeping our dependency list up to date. If we use an API which isn’t present in our virtual environment, the program will simply blow up – hopefully with a helpful error :) Should this happen, we need to make proper amends to the list, and use it to update the environment by reinstalling our project into it. As a bonus – though in practice that’s the main treat – deploying our program to another machine is as trivial as repeating this last step, preferably also in a dedicated virtual environment created there.
So, how to use all this goodness? It heavily depends on what programming language are we actually using. The idea of virtual environments (or at least this very term) comes from Python, where it coalesced into the virtualenv package. For Ruby, there is a pretty much exact equivalent in the form of Ruby Version Manager (rvm). Haskell has somewhat less developed cabal-dev utility, which should nevertheless suffice for most purposes.
More exotic languages might have their own tools for that. In that case, searching for “language virtualenv” is almost certain way to find them.