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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.
How to install ipython module in virtual environment code#
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. It might only be a small change, but it means our code no longer uses the library correctly. Why? Because something in the API of the requests library has changed between the previous version and the one we just upgraded to. 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.
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You can use easy_install to install pip as follows:Įverything seems fine, but we've unknowingly created a disaster! pip is vastly superior to easy_install for lots of reasons, and so should generally be used instead. Python actually has another, more primitive, package manager called easy_install, which is installed automatically when you install Python itself. It's similar to RubyGems in the Ruby world, PHP's Packagist, CPAN for Perl, and NPM for Node.js. PyPI (which you'll occasionally see referred to as The Cheeseshop) is a repository for open-source third-party Python packages. pip is a tool for installing Python packages from the Python Package Index. But the commands are simple enough that the concepts should be transferrable to any terminal, such as PowerShell for Windows. The examples below use bash, which is the default shell on Macs and most Linux systems. It will help if you're reasonably comfortable with a command line. Python 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. 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. One of the hurdles that new Python developers have to get over is understanding the Python packaging ecosystem.