The How and Why of Object-oriented Programming in Python
summary
Starts from a working procedural script that reads CSVs and produces the same travel‑time chart, then refactors that code into classes and small, testable pieces; uses Jupyter notebooks and matplotlib-style plotting, moves charging logic into a new battery class, demonstrates operator overloading and classmethod factory patterns, and shows inheritance to add connect/disconnect overhead. The examples reproduce identical numeric results, the plots render, and small exercises (height/person objects) let the code be rebuilt and verified.
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chapters (16)
- 0:00Introduction
- 0:22Speaker background
- 2:30Audience experience
- 3:11Course objectives
- 4:38Code walkthrough setup
- 14:10Switching to Jupyter
- 18:31Procedural electric car solution
- 32:33Procedural to OOP conversion
- 57:24Inheritance introduction
- 1:08:59Operator overloading
- 1:29:22Coffee break
- 1:30:04Addressing questions from the break
- 1:48:55OOP conversion exercise
- 2:09:50OOP design analysis
- 2:35:05Advantages and disadvantages of object-oriented programming
- 2:44:26Final exercise and closing
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