One of the hurdles that new Python developers have to get over is understanding the Python packaging ecosystem. This blog post is based on material covered in our Python for Programmers training course, which attempts to explain pip and virtualenv for new Python users.
PrerequisitesPython for Programmers is aimed at developers who are already familiar with one or more programming languages, and so we assume a certain amount of technical knowledge. It will help if you’re reasonably comfortable with a command line. The examples below use bash, which is the default shell on Macs and most Linux systems. But the commands are simple enough that the concepts should be transferrable to any terminal, such as PowerShell for Windows.
Let’s dive in. pip is a tool for installing Python packages from the Python Package Index.
PyPI (which you’ll occasionally see referred to as The Cheeseshop) is a repository for open-source third-party Python packages. It’s similar to RubyGems in the Ruby world, PHP’s Packagist, CPAN for Perl, and NPM for Node.js.
Python actually has another, more primitive, package manager called easy_install, which is installed automatically when you install Python itself. pip is vastly superior to easy_install for lots of reasons, and so should generally be used instead. You can use easy_install to install pip as follows:
Everything seems fine, but we’ve unknowingly created a disaster!
Next time we try to run it, we discover that our original program (the one that made us loads of money) has completely stopped working and is raising errors when we try to run it. Why? Because something in the API of the requests library has changed between the previous version and the one we just upgraded to. It might only be a small change, but it means our code no longer uses the library correctly. Everything is broken!
Sure, we could fix the code in our first program to use the new version of the requests API, but that takes time and distracts us from our new project. And, of course, a seasoned Python programmer won’t just have two projects but dozens – and each project might have dozens of dependencies! Keeping them all up-to-date and working with the same versions of every library would be a complete nightmare.
virtualenv solves this problem by creating a completely isolated virtual environment for each of your programs. An environment is simply a directory that contains a complete copy of everything needed to run a Python program, including a copy of the python binary itself, a copy of the entire Python standard library, a copy of the pip installer, and (crucially) a copy of the site-packages directory mentioned above. When you install a package from PyPI using the copy of pip that’s created by the virtualenv tool, it will install the package into the site-packages directory inside the virtualenv directory. You can then use it in your program just as before.
If you already have pip, the easiest way is to install it globally sudo pip install virtualenv. Usually pip and virtualenv are the only two packages you ever need to install globally, because once you’ve got both of these you can do all your work inside virtual environments.
In fact, virtualenv comes with a copy of pip which gets copied into every new environment you create, so virtualenv is really all you need. You can even install it as a separate standalone package (rather than from PyPI). This might be easier for Windows users. See virtualenv.org for instructions.
You only need the virtualenv tool itself when you want to create a new environment. This is really simple. Start by changing directory into the root of your project directory, and then use the virtualenv command-line tool to create a new environment:
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