How to Use Both Python 2.x and Python 3.x in Jupyter Notebook

Working with multiple Python versions can be crucial when maintaining legacy systems while exploring the latest Python features. Jupyter (formerly IPython Notebook) supports this need by allowing users to switch between different Python versions within the same notebook environment. Below, I will guide you through the steps to set up both Python 2.x and Python 3.x kernels, without relying on Anaconda, using virtual environments.

Why Multiple Kernels?

In many projects, you may encounter libraries or code written specifically for either Python 2.x or Python 3.x. It’s often inconvenient to switch the Python version globally, especially if you’re juggling multiple projects that depend on different versions. Jupyter offers a way to install and use both Python 2.x and Python 3.x kernels side-by-side, so you can work in both environments seamlessly.

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