Einstein Python | Installation instructions

Back to Home

Installation instructions - All you need for this course

To be able to fully participate, you should have Python 3.x installed and you need some additional packages. All you need is included in the free Anaconda installation, which is available for all major operating systems (Windows, MacOS, Linux).

Installation instructions can be found in the Anaconda documentation and I strongly recommend following them: https://docs.anaconda.com/anaconda/install/

In short:

  1. Go to: https://www.anaconda.com/products/individual#Downloads
  2. Download the current version (should be "Python 3.11") for your operating system (Windows, Linux, or Mac)
  3. Execute the installer and follow the instructions

You don't need to sign up for an Anaconda account.

Additional remarks:

You will want to chose the 64-bit version of Anaconda on most modern computers (bought within the last ~10 years).

If you already have Anaconda installed with any Python 3.x version, you don't need to upgrade to 3.9. However, the built-in Python 2.7 in many Mac/Linux systems is usually not sufficient.

If you don't have administrator rights on your computer, it's safe to install Anaconda as a normal user (Select "Just me" when you're asked). In fact, if you're the only user using Anaconda on your computer, this is the preferred option because it makes updates later much easier.

You do not need to install PyCharm, but you may give it a try. It's a popular Editor/IDE for Python which I haven't used myself, yet.

If your computer has limited main memory (hard drive) the full Anaconda package might be too much. It takes about 2GB with the full installation. You can instead install a smaller subset of package, following this article: https://medium.com/dunder-data/b48e1ac11646

If you already have Python 3.x installed without Anaconda, you might still be able to use it for this course. However, you should make sure to have at least the following packages installed (including their dependencies): numpy, matplotlib, jupyter. How this is done in a "normal" installation, is beyond the scope of this course, but there is plenty of help available online.

Last updated: 2024-01-02