What makes Ray difficult to use under Windows
First of all, Windows support for Ray is in alpha, and obviously not recommended for production use. Nevertheless, when getting to learn ray, some of you may still want to install it on their Windows laptop, if you don't prefer to use a Linux-based installation. When you take a look at the official installation instructions is a breeze, not only on Linux, but also on Windows: update your Visual C++ Runtime, do a simple installation with pip, and there you go.
Except that nowadays, everybody tries to keep their python environments neatly separated, which means that instead of pip, you usually use an package manager like venv/virtualenv, pipenv, pew, or conda. And that's where the fun begins. Using conda with Ray is technically a working option. For some of us, however, this option doesn't work from a legal point of view. The problem is that Anaconda Inc. changed their terms of service for the code repository that is used with conda, to require a commercial license if you're in a business with 200 or more employees.
Since this change, many in the machine learning community have switched to other package managers. Unfortunately, basic tools like venv (which is part of the Python standard library since version 3.3) and virtualenv don't work with Ray under Windows. What makes this worse is that pipenv also uses venv under the hood, so it doesn't work either. This excludes pretty much all of the most popular conda alternatives.