Python Object Oriented Programming Tutorial

Summary of steps to complete

• Fork this repository so you have your own copy to work on.
• Clone the repository on your local machine.
• Create a Jupyter Notebook in your repository.
• Watch the tutorial and execute commands.
• Push your new files to your GitHub repository.
• Submit a link to this GitHub repository in Canvas.

Fork & Clone this repository

• We did this in a previous assignment. Instructions are here: https://github.com/cmcntsh/exerGitPractice
• This can also be done directly in VSCode
  • Create a new folder on your machine where you want to put this repository if you don't already have one you want to use.
  • Copy the Clone or Download path for this repository from GitHub.
  • In VSCode from the command pallette (Ctrl-Shift-P) run Git: Clone
  • Paste the path into the path field which pops up
  • Select your new folder you created on your machine
  • A new folder for the repository with the repository files should be in the folder you selected showing in the Explorer window in VSCode on the left side.

Create a Jupyter Notebook .ipynb file

• In Jupyter Notebook or VSCode navigate to your repository folder.
  • Create a new Jupyter Notebook called OOPTutorial.ipynb

Watch Tutorial

• Follow along with Python tutorials:
  • Python OOP 1 - Classes and Instances (16 min): https://youtu.be/ZDa-Z5JzLYM
  • Python OOP 2 - Class Variables (12 min): https://youtu.be/BJ-VvGyQxho
  • Python OOP 3 - Classmethods and Staticmethods (16 min): https://youtu.be/rq8cL2XMM5M
  • Python OOP 4 - Inheritance (20 min): https://youtu.be/RSl87lqOXDE
  • Python OOP 5 - Special (Magic/Dunder) Methods (14 min): https://youtu.be/3ohzBxoFHAY
  • Python OOP 6 - Property Decorators (10 min): https://youtu.be/jCzT9XFZ5bw
• 2022 update:
  • I have created separate Jupyter Notebooks for each video. They're included in the repository.
  • Please use those to complete the assignment.
• Execute code examples in separate cells.
  • Students have found it easiest to do all the tutorials on a single Jupyter notebook so the code from previous videos is easy to see.
  • Add a comment in your code when you start code from a new video. (i.e. #video 1, #video 2, etc.)
• When you're done make sure you save your file.
• 2024 update:
  • You should be able to open the notebooks in Google Collaboratory.
  • Instructions for working with notebooks in Google Colab can be found at https://github.com/cmcntsh/exerPyth_PackageManagerPip .