Or perhaps you just don’t want to containerize your application. Still, there are many cases when we’re just creating small projects or one-off scripts. These can be very powerful and are a good alternative.

Next in line is containerization, with the likes of Docker and Kubernetes.

A virtual machine is a much cheaper option but still requires installing a complete operating system-a bit of a waste as well for most use cases.Problem fixed! It was a bit expensive, though! In the most extreme case, you could buy a second PC and run your code there.There are other options to isolate your project: In these places, a virtual environment allows you to install anything you want locally in your project. If you’re working on a shared host, like those at a university or a web hosting provider, you won’t be able to install system-wide packages since you don’t have the administrator rights to do so. Works everywhere, even when not administrator (root) This also helps other users of your software since a virtual environment helps others reproduce the exact environment for which your software was built. Using a requirements.txt file, you can define exact version numbers for the required packages to ensure your project will always work with a version tested with your code. Virtual environments make it easy to define and install the packages specific to your project. You install packages inside this virtual environment specifically for the project you are working on. After all, APIs can change significantly on major version upgrades.Ī virtual environment fixes this problem by isolating your project from other projects and system-wide packages. Great! But once you did this, it turns out your Project A code broke badly. You upgrade library X to the latest version, and project B works fine. Say, for example, you need the latest version for another project you started, called Project B. In the future, you might need to upgrade library X. Suppose your project, Project A, is written against a specific version of library X. There’s a problem with this approach that may start to unfold weeks or months later, however. After all, you only need to install it once and can use the package from multiple Python projects, saving you precious time and disk space. You could argue that installing third-party packages system-wide is very efficient.

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