Analysts obviously need a place to learn how to code Python. For that, we've set up Codespaces, particularly for those who can't code locally. Analysts who can't code locally are welcome to learn and practice Python coding by storing code in this Repo. Ideally, however, please make a folder in the repo for your own work, I have done this for myself, so copy my example. To do this, from the home directory of LA-Analys-Tinkering, click Add File, and select New File from the dropdown. When the new file opens, when asked to enter a file name, enter your name (dashes between words '-', GitHub doesn't like spaces) then follow it with a forward slash ('/'), this tells GitHub to make a new folder with that name, then giver your file whatever name you want. Following this, click the green Code button, select the Codespaces tab, and click Create Codespace on Main.
From here, once your Codespace is set up and running, you will need to install Python, as you will have done in the codespaces tutorial. You can then make a new file, it's probably best to name it your name, then ensure it's followed by .py so that codespaces knows it's a Pthon file and knows how to run it. You can run this file as you would locally. This is probably also a good way to practice coding, making changes to your code, and commiting it back to your main code when you're happy with the changes, helping you learn the CIN Validator workflow in your own environment.